The AI Optimist

When Hollywood’s Catalog Isn’t Enough and Might Need AI Licensing

Lionsgate thought they had this figured out.

The studio that owns John Wick, Twilight, and The Hunger Games partnered with Runway AI in 2025 to build custom video models. The vision? Type “anime version of John Wick” and watch AI generate it from their catalog.

That was around June 2025. Last week, the experiment quietly closed.

The problem wasn’t incompetence, it was scale.

Sources told The Wrap that “the Lionsgate catalog is too small to create a model.” Even Disney’s catalog was considered insufficient.

Let’s do the math: 8,000 movies at roughly 2 hours each equals 16,000 hours.

Add 9,000 other titles averaging 1 hour, and you’re at maybe 25,000 hours total.

Double that generously to 50,000 hours.

Still not enough.

AI companies are running out of training data after burning through the entire internet. Video. Real, diverse, messy human video has become a bottleneck.

While Lionsgate struggled with insufficient data, one Troveo client was reportedly in the market for 50,000 hours of dog videos because their AI-generated dogs kept coming out with cat bodies.That’s not a business model. That’s market unpredictability.And it’s also a signal that unused footage sitting on your hard drive might have value you haven’t considered.

Not as content for views or sponsorships, but as possibly valuable data for machines learning to understand our world.

Questions to ask yourself:

• How much unused footage do you have archived?

• What categories does it fall into—nature, urban environments, specialized activities?

• Do you own all rights, or are there B-roll clips, music, or people who’d need to sign off?

The Current Market Reality—What We Know

Let’s separate signal from speculation.

Troveo, a video licensing platform connecting creators with AI companies, claims $20M in total revenue with $5M paid to creators.

I use $1-4 per minute as a range for this episode. My reasoning is Troveo is on the lower end of video AI licensing usually $1-3 a minute.

It’s likely larger companies like Protégé are also getting paid. We don’t know how much. My assumption is the amount is higher, likely much higher.

So I add $1 on the low end of pricing. And urge you all to look at going beyond $4 a minute, a tough and still more sound business than the wholesale $1-2 market. And it may just be what it is, a small market.

This is one of the few companies publishing numbers instead of hiding behind NDAs. That transparency matters.

Also means we’re looking at early-market indicators, not established rates.

Here’s what the pricing tiers appear to reflect:

$1-2/minute (Standard Footage):

• Talking heads

• Predictable motion

• Common scenarios

• Already-seen angles

$3-4/minute (Premium/Edge Cases):

• Rare weather phenomena

• Unusual wildlife behavior

• Technical processes under stress

• Unique temporal transitions

The Tesla framework helps understand this distinction—not because they’re licensing video, but because they’ve quantified what makes training data valuable.

• Highway driving footage is standard.

• A deer crossing during a snowstorm at night is premium.

• It’s not about monetary pricing; it’s about learning density.

Most Tesla footage comes from user cars, with operational costs built into the product, not per-minute purchases.

But their internal categorization reveals something useful: edge cases, rarities, and uniqueness teach AI systems more than repetitive standard scenarios.The break-even reality check:

Look at the view of the market, knowing most of the business now is $1-2 per minute.

The threshold where this becomes a legitimate side revenue stream

This is why the $4/min barrier matters.

Below that, you’re liquidating existing assets at thin margins. Above it, potentially building a sustainable side business.

This is a one-time payment market. You’re not building recurring revenue. You’re selling training data that will likely be used to eventually replace the need for more training data.

And for anything above $3 a minute, 4K is the rule. Other footage likely goes into the $1-2 pile, why you see garage sales of old content, some valuable and most not.

Action steps for this section:

1. Calculate your actual production costs per minute for different types of footage

2. Audit your archive—how many minutes of different quality levels do you have?

3. Tag footage by category: nature, urban, people-heavy (complications), specialized technical

4. For each category, honestly assess: standard or edge case?

5. Permissions: who was in front of the camera, who was behind, and who was the producer? Signing off slows down AI licensing. Make sure your video is clear and clean with ownership and permission.

What Makes Video Actually Valuable

AI systems extract something from video that text and images can’t provide: motion, causality, temporal relationships, and context.

Would this video pass the AI Licensing test?

Mira Murati, founder of Thinking Machines Lab, says:

“We’re building multimodal AI that works with how you naturally interact with the world—through conversation, through sight, through the messy way we collaborate.”

That messiness, the unscripted, unedited reality contains teaching moments machines can’t get elsewhere.

• Compositional rarity matters: unusual angles, unexpected framing, perspectives humans naturally avoid. We shoot at eye level. We center subjects. AI needs overlooked angles.

• Temporal uniqueness creates value: time-lapses showing weather transitions, seasonal changes, processes that unfold over hours compressed into minutes. The dimension of time is where video is separated from images.

• Technical mastery in specialized domains: industrial processes, scientific phenomena, professional techniques that rarely get documented at high quality.

Video content may work, but here’s where most creators will hit the wall: rights and metadata.Look at the metadata requirements. You need:

• Title, subtitle, creator names, release date

• Studio/independent status

• Creative rights documentation (who owns what)

• Talent and production rights (every person visible)

• Rights territory and existing licenses

• Work-for-hire status

• Genre/category classification

• Exact video minutes/hours

• Language

• Content description and summary

• Keywords and tags

• Views/distribution history

• Distribution channels used

• Viewer reviews/ratings if applicable

• Awards and recognition

• Media coverage

This isn’t “throw files in a zip folder and get paid.” This is treating your footage like a professional asset.

The legal complexity escalates with people. Every identifiable face needs a signed release. Every location might need permission. Every piece of music requires clearance.

This is why nature footage, weather phenomena, and process documentation are the cleanest paths. No talent releases. No location complications. Just you, a camera, and something worth documenting.

The Facts: Many avoid, a few automate with AI

Most creators won’t do this work. The administrative overhead eliminates casual participants. That means less competition for those who take it seriously.

Practical experiment (inspired by Tesla’s approach):

Take 10 minutes of your archived footage. Watch it with fresh eyes and categorize every 60-second segment:

• Standard: Could this be filmed by thousands of other creators? Common angle, predictable motion, everyday scenario?

• Premium: Is there something unusual here? An unexpected perspective, rare moment, technical complexity, or temporal uniqueness?

Be brutally honest. Most footage is standard. Still it has value. But understanding the ratio helps you know whether you’re sitting on $1/min inventory or $4/min.

Action steps:

1. Conduct the standard vs. premium analysis on a sample of your footage

2. 4K is the cut off line to $3-4 a minute, and that’s not a guarantee. Lesser quality probably means low end pricing.

3. Make a list of locations, subjects, or processes you could access that others can’t

4. Research what’s already available. If 10,000 creators have time-lapses of the Golden Gate Bridge, yours isn’t premium

5. Identify your unique angle: local access, specialized knowledge, unusual timing, technical skills

   The Path Forward: Find Demand Before Supply

The mistake most creators make: assuming supply creates demand.

It doesn’t. Not in this market.

The smarter approach: research demand signals before you shoot another frame.

Where to look for demand signals:

1. Study existing platforms (without committing yet):

   • Troveo shows public categories: nature, sports, new media, scripted vs. unscripted

   • Notice what’s featured, what categories dominate

   • This reveals some current demand patterns

2. Enterprise-level signals:

   • Protege (enterprise-focused, doesn’t list pricing publicly—that’s actually a positive signal)

   • They work with hospital systems, media companies, specialized data aggregators

   • Private pricing suggests higher-value transactions with volume requirements

3. The unpredictability factor:

   • Remember the 50,000-hour dog video request? That probably won’t repeat.

   • But it illustrates how urgent, specific needs create temporary premium pricing

   • The lesson: diversification and patience matter more than chasing trends

To make this work, minimize:

• Editing time (raw or minimal editing only)

• Rights clearance complexity (avoid people when possible)

• Metadata preparation overhead (build templates, automate tagging)

• Storage and management costs (organize before you need to)

And maximize:

• Footage quality (4K minimum for premium rates)

• Rights clarity (know what you own completely)

• Category alignment with demand (follow platform signals)

• On time, every time (capture more in less shooting time)

Reality check on current platforms:

• Troveo operates as an open marketplace—entry-level, broker model connecting individual creators with AI companies.

Claims of $1-4/min are starting points, not guarantees. These numbers will go up and down over time. Watch for these as a moving baseline of pricing, for a market figuring it out.

• Protege works at enterprise scale—direct conduit model, vertical-focused (healthcare, specialized domains), requires significant volume and ethical sourcing. They don’t publish rates.

Neither model guarantees income. Both require patience, quality standards, and realistic expectations about one-time payments in an early market.

Action steps:

1. Don’t do anything new yet. Start with archives.

2. Pick one category where you have 20+ minutes of quality footage

3. Research that specific category: Who’s buying it? What are the metadata requirements? What’s the going rate range?

4. Prepare metadata for a test batch—treat this like a learning exercise, not a revenue projection

5. If you decide to submit, track time invested vs. payment received for accurate ROI assessment

Should You Actually Do This?

This is not passive income. The administrative work, like metadata preparation, rights documentation, platform navigation takes time.

At $1-2/min for standard footage, you’re essentially working for minimum wage unless you have massive archives already organized.

This is not recurring revenue. One-time payments mean you’re liquidating assets, not building sustainable business models. The footage you sell today trains the models that might reduce demand tomorrow.

This is market timing, not market certainty. Early movers might capture premium pricing. Late arrivals will face commoditized rates and saturated categories.

Who should seriously explore this:

✅ Videographers with extensive, organized archives gathering dust
✅ Creators with unique access to rare locations, events, or phenomena
✅ Technical specialists who regularly document processes others can’t
✅ Anyone willing to treat this as a 2-3 year experiment, not a career pivot
✅ People who enjoy systematization and documentation

Who should probably skip it:

❌ Anyone expecting quick money without organizational work
❌ Creators with people-heavy footage requiring extensive rights clearance
❌ Those hoping for recurring licensing income
❌ Anyone needing guaranteed returns to justify time investment
❌ Creators uncomfortable with one-time payment models

The 2-3 year window hypothesis:

This market likely has a limited lifespan. As wearables multiply, omnipresent cameras proliferate, and synthetic data generation improves, the premium on human-captured footage will shift. Not disappear, evolve.

Right now, there’s an insatiable appetite because AI companies burned through internet video and discovered it’s not enough. That’s a temporary condition, not a permanent feature.

Even if you never license a single minute, this exercise reveals something valuable: what makes your video data premium vs. standard from an AI learning perspective.That understanding informs how you think about your own AI tools. If your footage would be standard-tier training data, maybe your internal use should focus on templates and efficiency.

If your footage captures edge cases, maybe your AI applications should emphasize unique scenarios and specialized knowledge.

Final action framework:

🔍 Research phase (Week 1-2):

• Audit archives

• Categorize by rights clarity (clean, complicated, impossible)

• Study demand signals on existing platforms

• Calculate ROI based on current rates

📋 Test phase (Week 3-4):

• Prepare metadata for 20-30 minutes of your cleanest footage

• Submit to one platform as learning exercise

• Track time invested in preparation

• Document platform experience

📊 Evaluation phase (Week 5-6):

• Calculate actual time investment vs. payment received

• Assess whether scaling makes sense

• Decide: expand, pause, or abandon

💡 Strategic learning (Ongoing):

• Use the premium vs. standard analysis for your own AI workflows

• Notice what edge cases exist in your domain

• Consider whether creating future content with dual purpose (use + licensing) makes sense

The Market is real and forming….Video training for AI represents a real, if unpredictable, market. Companies like Troveo are paying creators.

Demand signals exist. The data shortage is genuine.

But it’s not a gold rush.
It’s an early-stage market formation with volatility, one-time payments, and a lot of admin overhead.

The $4/min barrier isn’t just about money.

It’s the threshold where this transitions from “liquidating old footage at thin margins” to “potentially worthwhile side revenue stream.”

Most footage won’t break that barrier. Most creators won’t want to do organizational work.

For those who find the intersection of unique access, clean rights, and serious systematization appealing?

There’s a 2-3 year window to explore carefully, with eyes open and forget expectations. Watch market patterns, what they do, not what they say.

The question isn’t whether AI companies need video training data. The question is whether licensing video to AI for your specific situation, with your specific archives, given your time, is worth it.

Only you can answer that.

I’d like to know what you’d add, ask, and want to know.

Want to explore this further? I’m documenting my own testing process at The AI Optimist. No guarantees, just testing out the tools and giving AI a chance to grow as an industry.

Thanks for reading The AI Optimist! This post is public so feel free to share it.

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RESOURCES

What Happened to Lionsgate’s Splashy Plan to Make AI Movies With Runway? It’s Complicated | Exclusive

AI Companies Running Out of Training Data After Burning Through Entire Internet

Everyone Is Already Using AI (And Hiding It)

Influencers are making big money selling leftover videos — ones not yet posted online — to train AI

Thinking Machines Lab

Mira Murati and the New Frontier of AI Innovation

Deep Dive into Yann LeCun’s JEPA

AI’s Next Five Years: LeCun Predicts a Physical-World Revolution

Troveo

DarkAI

AI Optimist Playlist (Shorts and Sections)

Time for creators to be recognized and paid by AI, finally!

Those days of AI stealing content for free and without permission just crashed in a quiet, proposed settlement - call it AI licensing rates 2025.

Creators are being given choice and control over how their work is used by AI, and may even get paid with licensing!

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After years of big tech telling creators their work has no value, something shifted. Anthropic just proposed paying $1.5 billion to settle copyright claims—roughly $3,000 per book.

This is not the net amount received by individual authors, as it will be reduced by administrative costs and divided among rightsholders if multiple parties are involved.

For the first time, a judge is recognizing that human creativity has measurable worth in AI training. Not just bestselling authors. Regular creators like you.

Subscribers get The complete Creator’s AI Licensing INTEL- 13 pages with a pricing simulation for books, photos, and art.

This isn't some distant future promise. This is happening now, and it's opening doors that have been slammed shut since AI started scraping content without permission or payment.

Numbers are from my research to find a starting point. The value of content will vary, and the rules are unwritten.The Evidence Shows: AI Companies Are Finally Paying AI licensing rates in 2025

Here's what most people missed in the headlines. Anthropic didn't just throw money at a legal problem. They established something unprecedented: a baseline value for creative work in AI training.

Harper Collins negotiated deals worth $2,500-$5,000 per book with major AI companies.

These aren't charity payments—they're business investments in quality training data.

Why the sudden change? Because AI companies discovered what creators always knew: garbage in, garbage out.

They need your expertise, your unique perspective, your carefully crafted content to build better AI systems.

The wild west era of free content scraping is ending. The licensing era is beginning.

What you can do now:

1. Document what creative work you own completely

2. Start thinking about your content's unique value

3. Don't wait for perfect information—early participants often secure better rates

What $3,000 Per Book Means for You Right Now? Author’s AI Revenue

That $3,000 figure isn't a lottery ticket—it's validation. A federal judge essentially agreed that copyrighted creative work has quantifiable value in AI training. Even if you never see a licensing check, this changes everything.

You now have a legal settlement that says your work isn't "training material"—it's valuable intellectual property. This gives you choices you didn't have before:

• License your work and get paid

• Opt out entirely and protect your content

• Control how AI systems learn from your creativity

The key word here is control. For years, creators watched their work get absorbed into AI systems without consent or compensation. Now there's a path to actual choice.

But here's the reality check: this applies to work you own the copyright to. If you don't have clear legal ownership, licensing becomes nearly impossible. AI companies need defensible rights to avoid future lawsuits.

Your next moves:

1. Check your copyright status on existing work

2. Register copyrights for valuable content (it's easier than you think)

3. Understand that timing matters—prepare now for licensing opportunities in 2026

What's Your Creative Work Actually Worth to AI?

Not all content gets valued equally. After researching this market for over a year, certain patterns emerge that determine what AI companies will pay for.

Nonfiction typically commands higher rates than fiction. Why? It's factual, less dependent on storytelling brilliance, and provides reliable training data.

A well-researched business book or technical guide offers more consistent value than a novel—unless that novel is awesome. And that’s up to the reader!

• Sales history matters. If your book sold thousands of copies, that's market validation AI companies understand. It proves real people found value in your work.

• Uniqueness drives premium pricing. Generic content gets generic rates. Specialized expertise, unique perspectives, and distinctive voices command attention.

Get the AI Licensing, metadata advantage:

AI systems need context to understand value. When you describe your work clearly—genre, audience, expertise level, sales performance—you're not just filling out forms. You're teaching AI why your content matters.

Think of metadata as your content's resume. Without it, you're just another file in a database. With it, you're a valuable training resource with proven worth.

Build your content value:

1. Inventory your best-performing content

2. Gather sales data, awards, recognition, media coverage

3. Start documenting what makes your work unique and valuable

Pricing Reality: What Nonfiction and Fiction Actually Earn

Based on current market data, here's what creators might expect:

• Quality nonfiction with clear copyright and sales history: $2,000-$5,000 per book. Business guides, technical manuals, and specialized expertise command top rates.

• Fiction faces steeper challenges unless it's genuinely outstanding. Most fiction licensing falls in the $1,500-$3,000 range, with exceptional storytelling pushing higher.

But remember—these are one-time payments for current licensing models. Some platforms are experimenting with annual subscriptions or revenue sharing. The economics are still evolving rapidly.

The volume game matters too. Individual authors might earn decent side income, but creators with larger catalogs see meaningful revenue.

Five books at $3,000 each through a creator-friendly platform (~15% fee) nets around $12,750.

Compare that to traditional publishing royalties, and licensing suddenly looks very interesting.

Calculate your potential:

• Calculate potential licensing value for your existing work

• Focus on your highest-quality, best-documented content first

• Consider building content specifically designed for licensing value

AI Values for Photos and Art: The Visual Content Market

Visual content follows different rules entirely. This market resembles traditional stock photography, but with an AI training twist.

High-resolution photos (4K+) command premium rates. Landscapes, urban scenes, and complex compositions provide rich training data.

Simple headshots? Not so much—AI already handles those well.

Original artwork, especially paintings, can earn $500-$1,000 per piece for AI licensing.

The key is documentation: medium, technique, inspiration, creation process. AI companies pay for context as much as pixels.

Geoffrey Laurence had his work “stolen” by AI - maybe it’s time he gets paid!

Here's where platform choice really matters. Getty Images takes 75-80% of licensing fees.

Newer creator-focused platforms take only 15%. That difference adds up quickly.

For photographers and artists, the timing couldn't be better. AI companies need diverse, high-quality visual training data, and they're willing to pay for it.

Maximize your visual content value:

• Audit your best visual content for licensing potential

• Organize high-resolution files with detailed descriptions

• Research multiple platforms—fees vary dramatically

Quality Matters: Yosemite Beats Headshots Every Time

Not all images get equal treatment in AI licensing. After studying what companies actually buy, clear patterns emerge.

Landscape photography, especially iconic locations like Yosemite, commands top rates.

These images provide complex visual information: lighting, composition, natural elements, seasonal variation.

AI systems learn more from a single great landscape than dozens of simple portraits.

Urban photography works well too. Street scenes, architecture, cultural events—anything showing human environments in detail.

The richer the visual information, the higher the licensing value.

Professional studio shots with controlled lighting often outperform casual smartphone photos, but not always. Sometimes authentic, candid moments provide exactly what AI training needs.

The metadata advantage applies here too. When you tag a sunset photo with location, time, weather conditions, and technical details, you're providing training context that makes your image more valuable.

Focus your efforts:

• Prioritize your most visually complex and interesting photos

• Add detailed tags and descriptions to your best work

• Focus on unique locations and authentic moments over generic stock-style shots

Four Steps to AI Licensing

Ready to move from passive content source to active licensing participant? Here's your practical roadmap:

Step 1: Secure Your RightsGet copyright protection for anything you want to license. Without clear legal ownership, licensing becomes nearly impossible. This isn't optional—it's foundational.Step 2: Document Everything

Gather the information that proves your content's value: sales numbers, awards, media coverage, anything showing market validation. This context dramatically affects licensing rates.

Step 3: Master Your Descriptions

Spend serious time crafting detailed, accurate descriptions of your work. Include genre, audience, expertise level, unique elements. Think of this as teaching AI why your content matters.

Step 4: Choose Your Platform

Research fee structures carefully. A platform that takes 15% vs. 80% completely changes your economics. Start with creator-friendly options but don't limit yourself to one platform.

Your action plan:

• Begin with your single best piece of content

• Work through all four steps completely before adding more

• Set realistic expectations—this is preparation for 2026+, not immediate income

Market Reality Check: Planting Seeds for Tomorrow's Harvest

After a long threatening winter of AI taking content without permission or payment, spring is finally arriving.

But let's be clear about what season we're actually in.

This is planting time, not harvest time.

Anthropic's proposed settlement won't pay out until next year at earliest. Most licensing programs are still in beta. Platform sustainability remains unproven.

The volume challenge is real. Creator-friendly platforms need massive scale to survive on 15% fees.

Traditional platforms with higher fees can operate profitably with lower transaction volumes. This creates different incentive structures that affect long-term survival in a hyper competitive market.

But here's what creators gain immediately: choice.

Even without licensing payments, this process gives you control over how your work gets used in AI training.

You can opt out entirely, negotiate specific terms, or participate actively in this new economy.

The alternative, hiding behind paywalls and hoping AI can't find your content; feels like fighting the future instead of shaping it.

We're moving toward a world where human creativity partners with AI systems, not one where we hide from them.Your creativity is the fuel that makes AI systems valuable. That was always true—now it's finally getting recognized in dollars and legal settlement.

The seeds you plant now, the relationships you build, the quality content you document and protect.

These investments compound over time. Early participants often secure better long-term rates and stronger platform relationships.

This isn't about getting rich quick. It's about getting ready thoughtfully for a market that's just beginning to emerge.

It's about moving from having your work taken without consent to having choices about how you participate in AI development.

After years of being told your creativity has no value, now we have a $3K value put on copyrighted books.

That $3,000 baseline isn't the ceiling. It's the foundation for what human creativity is actually worth.

The question isn't whether AI will use human content for training. That's already happening.

The question is whether creators will be partners in that process or just sources.

Choose partnership. Choose preparation. Choose to plant those seeds now, while the ground is still soft and the opportunities are still growing.

Human creativity isn't going anywhere. It's just finally getting the recognition, and compensation, it always deserved.

Ready to get started? As a subscriber, you'll immediately receive my “Creators’ AI Licensing INTEL" - This is my first public breakdown of what AI training content is actually worth—built from early deals, platform data, and industry settlements. The numbers are still early, but they give both creators and AI companies a starting benchmark for this new licensing economy.

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Market Stage Warning: Most platforms mentioned are in beta or early stages. Current valuations represent early market pricing and may change significantly.

Your Experience May Vary: Actual earnings depend on content type, copyright status, existing revenue, and many other factors. Some creators may earn significantly more or less than these estimates suggest.

No Guarantees: This guide provides educational information only. Market conditions, platform policies, and legal frameworks change rapidly. No earnings, platform success, or market outcomes are guaranteed.

RESOURCES

Anthropic Settlement Web Site

Settlement document - filed 09/05/25

CredTent.org

Created by Humans

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The AI Bubble Finally Burst - And It's the Best Thing That Ever HappenedIntroduction: When the Hot Air Finally EscapedThis sign greets me at TechCrunch Disrupt 2024 - yeah, who needs people?

Picture this: TechCrunch Disrupt 2024, and the first sign I saw was "Stop Hiring Humans." Who exactly is going to adopt AI with that message?

If you've been following the AI hype train, you've probably noticed something shifting lately. The algorithms are suddenly filled with Sam Altman fans quoting him saying "yeah, I guess it's over."

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The AI bubble has finally popped. ChatGPT-5 came out, and honestly, the AGI reasoning promise isn't even real. The pipe dream is gone, and for you and me, this is the very best part.

I wrote about this back in July 2024 - "The AI Bubble Burst" became one of my most popular episodes because people understand that the hype and hot air are getting in the way of creativity. The whole message was that AI was going to take your job. Sign me up for that motivation, right?

We've been living in some male-engineered science fiction fantasy that AI is just going to go all Terminator on us. Do you wonder why adoption is slow worldwide? Why people aren't paying for it? It's because we've been sold fear instead of partnership.

But here's the thing - this crash brings AI down from the ivory tower billionaire pitch fest. It shows us how we can work WITH AI as a tool, how it can actually work with you, not against you. As my guest Maya Ackerman said last week, it's about being co-creative with it.

From Sequoia Research, the tipping point is finally here.The AI Bubble Bursts: A History of Hot Air and Broken Promises

"A lot of the people saying AI first really don't have a high opinion of human beings. And I'm not talking about their visions. I'm talking about yours."

Let's take a trip through the greatest hits of AI prediction failures. This isn't about being negative - it's about recognizing patterns so we can build something real.

Back in 2015, Elon Musk predicted driverless cars within a few years. Then 2019. Then 2021. We're in 2025 now. It's coming, but not as fast as predicted.

Geoffrey Hinton, the so-called Godfather of AI, said radiologists would be gone in a few years - that was 2017. I checked recently. They still have jobs.

Mark Zuckerberg pitched the metaverse for years and lost an estimated $45 billion because it didn't work.

Listen to Satya Nadella talking about the metaverse - it sounds exactly like current AI pitches, just with different buzzwords. They literally took out "metaverse" and put in "AI."

The pattern is clear: we get sold on revolutionary transformation, but reality moves at its own pace. The difference between hype and progress isn't just timing - it's approach.

AI Myths Revisited: Why This Time Feels Different

We've heard this song before. Every major tech shift brings promises of instant transformation. But AI feels different because it touches creativity, thinking, and decision-making - the stuff we thought was uniquely human.

The myths we've been sold include AI doing "everything for everybody" instead of focused tasks. We've been told to create guardrails instead of limiting the overwhelming amount of stuff we're expecting it to do. The goal seems to be "replace everybody" and "stop hiring humans."

But people are working with AI secretly, like it's some scarlet letter. Don't say it's AI. It's become this weird, detached thing when it doesn't need to be.

Key Points:

• Pattern recognition shows AI hype follows historical tech prediction failures

• Current messaging focuses on replacement rather than partnership

• Real adoption happens quietly, person by person, project by project

Trickle Down AI: Why Top-Down Implementation Fails

"Time after time again, C-suite executives sit there in their little meetings, separate from the employees, in this hierarchical 'I'm up here, you're down there' job model.

Telling them to use AI without considering to those working for them, AI means replacement."

Here's what happens in many companies: executives decide they need AI. They hand it down to their teams with no real goal, no central focus, just "you guys figure it out."

Meanwhile, employees have heard that AI is going to replace them and maybe kill them. Yeah, they're really excited to make that happen faster.

This creates a weird dynamic where AI becomes evil because it's going to take jobs. People may work with AI, but they keep it secret.

Executives are doing the same thing - working on their own AI projects privately because admitting you're using AI feels like admitting weakness.

The trickle-down model says the head decides to do it all, and everyone else follows. But people are sabotaging it, even unconsciously. They're stopping progress because the whole narrative is backwards.

From July 2024 and the AI Crash finally arrivesThe Real Foundation: Data and Communication

Leaders need to start with people at the beginning. You need to start with your data, which is dormant, not organized, and hard to communicate with. Communication and organization are the core of useful AI. They build their way up.

Instead of AI trickling down from the top, it should be bottom-up. You need to invert this platform because that trickle-down approach isn't working. People aren't going to accelerate their own replacement.

I talk to small businesses that have been sold ten AI agents doing different things, but they don't do them well. They need updates and tuning. People are buying AI like it's software - out of the box and working. That's not how it functions.

Key Points:

• Top-down AI implementation creates resistance and secrecy

• Real AI success starts with data organization and communication

• Bottom-up approach builds trust and actual functionality

High Costs, Low Revenue: The Business Model Problem

"The business model of AI is flawed. It doesn't have one yet."

Let's talk numbers. Sequoia came out with their $600 billion article this week, and people were freaking out about how much money AI companies need to make to reach that goal. It's huge, and it's not going to happen overnight.

The business model has way too many costs. When you ask ChatGPT-5 a reasoning question, it takes massive resources.

Jeffrey Funk, who predicted this crash before anyone did, has shown how much these things cost in tokens. A simple chatbot runs 50-100 tokens. But once you start reasoning, costs get astronomical.

Have you noticed on Claude they now shut users down to five-hour limits? In the early days, with lots of money, they let people keep things open. But they're burning cash. You're seeing AI shrinkflation - same package, but smaller portions.

The Revenue Reality Gap

ChatGPT needs way more money to become profitable. They originally planned to sign off with Microsoft when they achieved AGI, but nobody can even agree on what AGI is or why it matters. This is going to look silly in a few years.

Companies are building data centers the size of New York City, using massive amounts of potable water, buying wickedly expensive Nvidia chips. The math doesn't work. Market realities are taking over.

This doesn't mean AI is going away. But in a crash, we don't need five large language models doing everything. We need small language models addressing specific goals.

Key Points:

• Current AI costs are unsustainable for the value delivered

• Revenue expectations don't match market reality

• Small, focused models make more business sense than universal solutions

The 3 AI Problems Hiding in Plain SightProblem 1: The Revenue and Reality Gap

The first problem is obvious when you look at the numbers. AI companies need massive revenue to justify their investments, but adoption is slow and people aren't paying premium prices. Goldman Sachs released a report showing how few companies are actually adopting AI effectively.

You talk to companies and the really advanced tech ones can make it work. But most companies are sitting there thinking the support isn't reliable, it's not trustworthy, and they're trying to make it do too much. This is early-stage technology being sold as mature solutions.

When the biggest players like Goldman Sachs, Sequoia, and Sam Altman start saying it's not working as promised, people listen. But we don't need to wait for them to give us permission to build something better.

The Word is Out - AI Is Overhyped (SURPRISE?)Problem 2: The One Model Trap

"One model to rule them all. We just need ChatGPT. Oh wait, DeepSeek is just as good and cheaper. Oh wait, Anthropic's great. Oh wait, Mistral does really cool stuff."

We're seeing the same mistake IBM made in the 70s - believing there would be one computer to rule them all. Sounds silly now, doesn't it?

That's exactly where OpenAI and other AI companies are heading. They're trying to be the moat, the single solution to control it all and make the money.

The reality check is different. There's so much you can do if you keep small and focused. Foundation to small language models building their way up.

That's why they don't hallucinate - because you don't ask them to do too much. That's why they're trustworthy - because you don't let them do things they shouldn't do.

Even Klarna, which made headlines for wiping out customer support, quietly brought back employees. Nobody talks about that part.

Others are doing the same because AI doesn't have that capability yet. And why should it?

Problem 3: The "Set It and Forget It" Myth

"Would you hire somebody without training them? Without setting clear performance goals? Without checking their work?

Why do we do that with AI?"

The third problem is treating AI like traditional software. You wouldn't hire someone without training them, setting performance goals, and checking their work until you trust them. But that's exactly what people do with AI.

You need to customize AI to your business. That's the cool thing about AI - instead of learning software and hoping your team adapts, your business becomes the center and you customize AI to fit your solution.

Your business is dynamic. It changes. Consumers buy new things. Markets shift. Things go out of fashion. We react to that constantly, but we think AI will handle it all automatically. That's wishful thinking.

Key Points:

• Revenue expectations exceed realistic adoption timelines

• Multiple specialized models work better than universal solutions

• AI requires ongoing training and customization like any team member

Maybe AI First folks simply don’t like people….and bring them back.AI as Employee, Not All-Knowing Sage

"It's not how smart it is. It's how much you can trust it. It's not that it's doing things you can't do.

It's that you can do things reliably and take work off your back."

Stop thinking of AI as some mystical intelligence that knows everything. Think of it as a new team member who's really good at specific tasks but needs clear direction and ongoing training.

As a creator, understand your own creative process first. Document it. Find areas where AI can help.

In business, start with your workflows - small ones. Automate around them gradually. Build them to where you can trust them. Develop measurements and check in quarterly.

Don't just set it and forget it. That's the weird, lazy thing nobody would do in business, but somehow AI comes along and we think it's different because "it's smarter than me."

Focus on Organization and Communication

If you do nothing else, focus on organization and communication. Humans aren't naturally good at these things.

AI is wickedly good at them, and you don't make it in charge of your business. It's just organizing things better and making sure everybody is on the same page.

Instead of forcing your existing tools to handle communication (some do well, many don't), streamline with AI.

But start there - it's real, practical, measurable, and you can develop AI you actually trust.

Key Points:

• Treat AI like a specialized team member needing training and oversight

• Focus on organization and communication as primary AI strengths

• Build trust through small, measurable improvements over time

Even Yann LeCun of Meta agrees; time to adapt beyond ChatGPT!The Beginning is Near: Why This Crash Changes Everything

"The future belongs to the builders, not the believers. The future belongs to people who sit down and make common sense decisions."

Now that the crash is starting, the beginning is here. Get excited. The path forward is with us, not against us.

We're at a creative crossroads with AI, and most people think it's either creative salvation or creative apocalypse. I believe it's neither.

AI is a humble creative machine that becomes powerful when you know how to work with it, and it knows how to work with you.

The most powerful technologies we've ever had come when we prioritize how people use them, not when we prioritize the technology as some all-encompassing solution.

The AI crash isn't going to destroy creation - it's going to reveal what we can do with it. It's not going to destroy businesses - it's going to open opportunities to get beyond the hot air and get down to business. Get down to how it works with us and serves us, not how it takes over the world.

It's About You, Not the Technology

I'm planning on being part of the human revolution - human connection, human co-creativity, taking all that horrible, repetitive work off our backs and giving us time to do amazing human things.

The crash frees us to see what we can actually accomplish. Small language models building from the bottom up make sense.

After all, you don't build a house without starting with the foundation. The foundation is people and their data, not some CEO's vision from the top floor.

We don't need to put guardrails on AI - we need to limit the overwhelming amount of stuff we're expecting it to do.

We need tools that don't do everything for everybody, but that focus on specific tasks. We need to work WITH AI creatively instead of being slaves to technology.

Trust your voice. Amplify with AI. The crash isn't the end - it's the beginning of something much better.

Key Points:

• AI crash reveals realistic, practical applications over hype

• Human creativity and AI capability work best in partnership

• Small, focused steps build more value than grand transformations

• Success comes from prioritizing people over technology

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The AI bubble burst isn't a failure - it's a liberation. Now we can finally build AI that works with human creativity instead of trying to replace it. The future belongs to those who understand that the most powerful technology serves people, not the other way around.

AI Bubble Pops Resources

“AI is in a Bubble:” OpenAI CEO Sam Altman compares AI hype to the Dot-Com crash

AI’s $600B Question

GEN AI: TOO MUCH SPEND, TOO LITTLE BENEFIT?

Goldman Sachs: AI Is Overhyped, Wildly Expensive, and Unreliable

Companies That Tried to Save Money With AI Are Now Spending a Fortune Hiring People to Fix Its Mistake, Oopsie.

Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI

As AI Hype dissolves into mainstream cringe, it’s easy to forget that the gems are found below the surface jargon and PR blather.

Like Maya Ackerman, founder and CEO of WaveAI since 2017, helping people write lyrics and make music without breaking the rules. Or stealing other’s music!

Creating emotional connections, inspiring discovery, AI designed to release that creative feeling, focusing on human creativity instead of the AI Roulette wheel:

“We should be thinking, how can we build technology?

How can we build an LLM or a different kind of model designed to elevate the human spirit? And there are ways to do this.

We just need to expand our imagination.”

Maya Ackerman

Check out LyricStudio

MelodyStudio is here

Over a million songs have been created with of WaveAI since 2018. Including a few big hits and several quiet relationships with major players who face backlash for exploring an AI future that empowers musicians.

Maya Ackerman built her company to work completely differently than what investors wanted or what her competitors – Udio and Suno - deliver.

AI tools that make you betterWhile most generative AI tools function like "rotating roulette wheels of content" - spin the wheel, get random output - Maya delivers on a different vision.

As an opera singer and musician herself, she experienced firsthand how AI elevates her own creative process, not replace it.

"My songwriting abilities blew up," she told me about her first encounter with an early AI prototype.

"I went from being a certain level in songwriting to being three times better instantly."

That personal breakthrough led to WaveAI - a platform helping both skilled and beginner musicians craft songs and lyrics. Easy to use and affordable.

And the technology isn't built to be bought out or go IPO. It's built to elevate creative skills in humanity, in people.

Eight years after starting, Maya is still aligned with this vision, even when it means moving away from what the investment world wants.

How Does AI Elevate Creativity: Who's Really in Control?Creative Machines on Amazon

Maya laughs when framing what's wrong with most AI tools today:

"If ChatGPT is a god when you use ChatGPT, then when you use Lyric Studio, you are the God."

Think about how you interact with most AI. You prompt, it produces. You ask, it answers.

The AI is the oracle, you're the follower. And Maya knows this approach fundamentally disempowers users.

Curtiss King, who had a No.1 hit on iTunes via an album made with LyricStudio, said that it’s like lightning in a bottle.

“It enables you to capture this kind of inspiring moment, but also stay in ‘flow’ – to stay solidly in this creative space.

You can get out this inspiration onto paper or onto your monitor before it fizzles away.”

Curtiss King

Maya’s insight from her upcoming book "Creative Machines" cuts to the heart of it:

"I now see that AI has always been - and will always be - all about us."

This isn't just philosophy - it's a completely different business strategy. While companies like Suno and Udio pitched investors on "human-free Spotify," Maya forged her own path.

"The reason that you see Suno and Udio make it so simple and so efficient is because that's what investors wanted.

They wanted a replacement model," she explains.

She respects their tech, but the AI divide is clear.

When you build AI to replace people from day one, that intent gets baked into everything - the algorithms, the interface, the user experience.

When you build to elevate people, that's a fundamentally different architecture. Results come from intention as much as doing the work.

She’s building a creative force that helps musicians grow, sometimes where they don’t even need to use her tools anymore….which is awesome!

Breaking the Average: AI that adapts to your style

Most AI systems optimize for the most likely outcome - they head toward the average, the safe choice.

"We don't take it towards the mean.

We don't give you the most likely outcome because we're trying to help you be creative."

Instead of serving up what's most probable, Wave AI intentionally offers low-probability responses that aid and challenge the musician.

It's literally programmed to provide divergent, unique results rather than predictable ones.

The interface tells this story too. No prompt box asking what you want AI to create. Instead, "a big empty text box" that immediately signals: you're writing.

The AI suggests and supports, but you're driving.

"The suggestions are divergent, so they don't all take you to the same directions.

There is no right way to write your lyrics."

When Humans Stay in Charge: Songwriting AI that teaches

Helping to create a million songs is impressive. Learning how people use your technology and adapting is where this radically improves.

Take Sky Jordxn, using Wave AI in a way Maya, and AI, never anticipated.

"Sky Jordxn has a whole playlist of videos... it just blew my mind.

In the early days, Jordan would turn on his beats, click generate as the music played, and improvise rap lyrics in real time using AI suggestions.

"He would sort of improvise his rap with Lyric Studio on top of the beat in real time and create music like that."

Or Curtiss King, a professional who uses Wave AI to enhance, not replace, his process.

"When professionals like Curtiss can use Lyric Studio, a lot of the lines just come out from them.

They only use Lyric Studio to the extent that they want to."

The creative AI pattern is clear: when you design AI to support rather than replace, people find ways to use it that surprise even the creators.

Sure it’s great, but can it create an Italian Aria?

Arido Taurajo - the Italian Aria created with help from early WaveAI

James Morgan, a San Jose State art professor, always dreamed of writing an opera. Problem: no musical experience, doesn't speak Italian.

During her early research days, Maya took a walk with Morgan through the San Jose State campus.

Beginning to create WaveAI, she asked Morgan about that Italian opera idea, and she had a twist.

They could retrain their AI music system on public domain Italian works, like Puccini. The setup was simple: feed it Italian lyrics, get back different melody suggestions.

Remember, Morgan has no music experience or background, though extremely creative. Trying to create an Italian aria without knowing the language:

"The guy creates Arido Taurajo, this amazing Italian aria,"

Dr. Ackerman says, still amazed. The piece got showcased in galleries, with Dr. Ackerman herself singing parts of Morgan's creation.

This wasn't AI generating an opera. These were two humans using a tool to leap over impossible gaps - language barriers, musical inexperience, technical limitations - to create something genuine, personal and beautiful.

"You give somebody a fairly basic AI tool and they can go out and create something," she reflects. "A non-musician who doesn't speak Italian could create a beautiful Italian aria."

AI Elevates Creativity: The Counter-Intuitive Business Model

Being a founder means sometimes not wanting to admit a good thing. Maya is finding that some Wave AI users actually stop paying - not because they're dissatisfied, but because they've gotten good enough that they don't need the tools anymore.

"Some of our users stop paying for our products because they have become better songwriters.

They got to where they want to go. And I think that's fantastic."

It's the opposite of the typical tech playbook focused on user addiction and lifetime value optimization.

WaveAI is literally building itself out of some customers' lives - and celebrating it.

"The way to make a successful product with AI is to have it give real value and elevate the user and help them learn and help them grow, not just foster addiction and dependence."

Standing Up to the AI Hype

As generative AI grows and big moonshot companies grab headlines, will any of this stand the test of time?

"How can we build technology designed to elevate the human spirit?

There are ways to do this.

We just need to expand our imagination."

This requires breaking free from the science fiction narratives shape investor thinking.

"The narrative has really crystallized into this autonomous intent field evil thing that ultimately wants to kill us and replace us," she observes.

Still at every level, we can choose differently. Investors don't have to fund replacement models.

Builders don't have to create black box oracles. Users don't have to accept being told what to do, how to do it, and losing control.

The Long Game: How can AI make us more human?

Dr. Ackerman's first principle, laid out in her upcoming book "Creative Machines":

"The greatest impact creative machines can have is to elevate human creativity."

This isn't about making AI less powerful. It's about designing that power to serve human thriving instead of human replacement.

"How can AI make us more human?

How can it help us connect deeper with our emotions, connect more deeply with each other, and connect more deeply with our creative capabilities?"

The answer lies in what she calls "humble creative machines."

AI systems built to put humans in charge, to adapt to users rather than forcing users to adapt to them.

When James Morgan created his Italian aria, he wasn't just making music. He was proving that the impossible becomes possible when technology is designed with the right intent from the ground up.

While everyone else is building roulette wheels, Maya and the team at WaveAI is building something different: tools that make you more creative, not more dependent.

And in a world racing toward AI that does everything for us, maybe that's exactly what we need.

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Resources

WaveAI

Creative Machines: AI, Art, and Us (Maya's Book)

LyricStudio

MelodyStudio

Maya Ackerman LinkedIn

Arido Taurajo by James Morgan with help

from an early version of WaveAI

Curtiss King TV

How LyricStudio Pro Helped Me Get Out Of A Writer’s Block

Sky Jordxn

James Morgan

Udio

Suno

AI Optimist Playlist (Shorts and Sections)

When Heart Meets Code: Rediscovering Creativity in the Age of AI

Explain AI to me like I’m a 5-year-old, she said.

I was doing the research, looking at different AI hot takes from all kinds of sources with differing degrees of credibility.

From data engineers endlessly defending their right to grab data like all the others, because in their bubble it’s all okay.

And many artists swear that the only way to beat AI is to stop it, how it’s all cheating and liars and doesn’t understand human value.

That gets a head nod, but there’s no where to go next, what to do, it’s just stop this and scream loudly so it will go away.

Artists draw on the suffering stories of Marcel Proust or Kafka or Van Gogh, playing on the hope that someone will notice their work when they’re dead.

Then making decisions driven by single-issue neurosis and a knack for saying nothing in many words. Tech speaks scientific lingo for AI or emotional dumps from the “I never get respect” artists.

(I was a member of that club for a long time pre-AI, and the entry fee is acknowledging that creativity is suffering, suffering is art.Luckily a friend taught me that the purpose of art is to beautify the artist, because if anyone or many ones grab onto your art, it’s rare. So might as well heal yourself.)

Artists burn time fighting a technology that's already here.

Engineers build half-smart AI on cheap data hyper radicalized by AI social algos that favor anger and finger pointing, while ignoring the human creativity that makes it valuable.

And while both sides play this zero-sum game, mediocrity wins.

You're not fighting AI or creativity. You're fighting each other.

Today, I'm going to show you what happens when we stop pretending this is a war and start treating it like what it is: the biggest co-creating chance in human history.

Théåtre D’opéra Spatial, by Jason Allen - not given a copyright. No human author!

We'll look at how Japan figured this out, why even inspired creativity borrows from others, and then I'll tell you a simple story that explains AI better than any technical.

Because sometimes the most complex problems need the simplest explanations.

So here’s my manifesto, because you have to have one at some point!

A Reality Check for the AI Wars Nobody's WinningPoint #1: Stop Playing Zero Sum - You're All Losing

Artists fighting AI create generic content. Engineers ignoring artists build soulless tools. While you're battling each other, the boring middle wins.

The enemy isn't AI or creativity. It's the delusion that one side can succeed by defeating the other.

Point #2: Your Creativity Won't Get Stolen (Stop Acting Like It Will)

Only 20% of content can be extracted from AI models, even by experts trying to hack them. Your unique voice, perspective, and human experience can't be replicated by machines. Fear of theft is keeping you from the real game; showing what makes you irreplaceable.

Point #3: Engineers - You're Building Half-Smart AIWithout human creativity and context, your AI produces technically perfect garbage. You're optimizing for patterns while missing the point.

Artists don't just create data. They create meaning. Ignore that, and your models stay sophisticated copy machines.

Point #4: Artists - The Future Already Left Without You

While you're demanding AI stop existing, others are learning to play with it. Your choice isn't whether AI gets built.

It's whether you help shape it or get left behind. Sitting out guarantees you have no voice in what comes next.

Point #5: Co-creating Beats Competition (Japan Figured This Out)

Japan's copyright model proves you can protect creators AND advance AI. They focus on case-by-case solutions instead of blanket wars. The future belongs to countries and communities that build bridges, not walls.

Point #6: Machines Learn, Humans Create Intent

AI mimics your technique but not your purpose. Engineers who claim AI is "creative" are lying to themselves.

Artists who think technique is everything are selling themselves short. The magic happens where human intent meets machine capability.

And when the audience gets what you’re sharing; they aren’t looking for you in AI if they’ve never heard of you.

“The court concluded in a ruling authored by Justice Sonia Sotomayor that the works made by Warhol did not have a sufficiently different commercial purpose from that of the original photo taken by Goldsmith: Both are used to illustrate magazine articles about Prince. Whether a work is used for a commercial purpose is just one of various factors used to analyze copyright infringement.” (click photo for link)Point #7: Value Flows Both Ways (Not Just to Big Tech)

If art trains AI, AI must serve artists. If engineers build tools, creators must help them understand what matters.

Fair exchange means more than just money.

It means respect, attribution, and shared success.

Point #8: Together We Build the Future, Apart We Build Mediocrity

Your greatest work won't come from protecting old models or building without context.

It'll come from artists who understand technology and engineers who value human creativity. The zero-sum game produces zero-sum results.

The AI Age doesn't need you to pick sides. It needs you to stop playing a game where everyone loses and start building a future where both clay and code create something neither could achieve alone.

(that’s the fable at the end of this wandering post…hang in there).

The choice is yours: Keep fighting and lose together, or co-create and win together.

✍️ Signed:

• Artists, Writers, Makers

• Engineers, Designers, Builders

• And all those shaping the creative future

Japan Lets AI Take Copyright Work for Free

In Tokyo right now, an AI can legally train on nearly everything created in Japan - books, songs, artwork - without permission or payment.

This isn't science fiction; it's current Japanese copyright law.

Step outside Japan's borders, and suddenly those same works may gain legal protection. This isn't theoretical - it's playing out in courtrooms today.

The story of Ultraman - one of Japan's superheroes - represents this contradiction. In a Chinese courtroom, this Japanese character won a copyright battle against AI.

The Ultraman Case: First Win against AI Fair Defense Claims so far

Yet back home in Japan, that same AI use – for training - would be completely legal.

This isn't about superheroes and science fiction.

It's about your work becoming someone else's fuel, with different rules depending on which digital border you cross.

In 2025, we're witnessing the emergence of AI zones - digital territories where copyright means different things in different places.

There won't be one global system, it’s a patchwork of nationalistic and cultural points of view.

The Blueprint Behind Japan's AI Freedom

Looking at Japan's approach reveals something engineers have been arguing for: a system where AI learns from everything while still respecting creators' rights.

Japan's copyright rules for AI rest on two key pillars that balance progress with protection:

The Non-Enjoyment Purpose Requirement

The first pillar is simple: intention matters. Japan allows copyrighted content to train AI systems if the purpose isn't to recreate the original work.

You're not bringing in Van Gogh paintings to create more Van Goghs - you're bringing them in to help the AI understand artistic styles, composition, and color theory.

This creates breathing room for AI development while maintaining a boundary around blatant copying. The focus isn't on inputs but outcomes.

While this sounds straightforward, it creates real questions for creators: how do you distinguish between "learning from" and "copying" in a practical sense? This leads to Japan's second pillar.

Article 34 Proviso: Where Protection Lives

Japan doesn't leave creators without protection. Their Article 34 Proviso acts as a safety net, establishing that if AI output causes actual harm to a creator's career, reputation, or financial status, normal copyright protections kick in.

This practical approach says: let data flow into AI systems, but watch carefully what comes out. If the output creates direct competition or damages creators, that's where the line gets drawn.

Fair Use and Japan's AI Freedom - not the same

How different Japan's approach is from the U.S. "fair use" defense - both trying to solve the same problem.

In the U.S., fair use isn't a rule - it's a legal defense. You only know if something is fair use after you've been sued, and a court decides. It's reactive, not proactive.

In Japan, they've built a system that's more predictable. AI companies know upfront what's permitted: training is allowed, copying isn't.

Creators know where their protection lies: not in restricting input, but in preventing harmful output.

GenAI and the Future of Creative Ownership: Are Artists Being Written Out?

The Copyright Protects My Original Work

“AI stole from artists in the first place. In some pieces, you can even see an original artist’s signature incorporated into the work. AI isn’t creating new work, it’s taking pieces of existing works and putting them together....

I don’t think AI is a bad thing. I do think that the way it’s been built is. Some of my work was on sites that have belatedly announced that they allowed all artworks to be scraped by AI bots.

For some of mine, I probably would have given permission, if asked. For others, I would have denied it, but I never had the chance to make that choice.

Some sites do say they’re training AI with your creative works but hide it in their settings. Adobe does this. You have to go into settings and change your permissions if you don’t want your work scraped.”

Te-ge Watts Bramhall

“The success and profitability of OpenAI are predicated on mass copyright infringement without a word of permission from or a nickel of compensation to copyright owners.”

Franzen, Grisham and Other Prominent Authors Sue OpenAI

Why the AI Industry Is Taking the Hard Way

I'm not afraid of AI. I'm afraid of what people will do with AI. All this hype about AGI and superintelligence - to me, it's all about control from the top down.

Sure, automation improves efficiency. But what's the glaring problem we face as humans? It's organizing and communicating.

If we let AI handle these tasks instead of just automating an old software model, imagine how radical that would be.

Clay, Code, and the Creative Spark: A New Dialogue Between Artists and Engineers"

Talk to me like a 5-year old about AI?

Here’s a children’s AI Fable….playing together just like they taught me in recess.

Once upon a time, in a world where clay could giggle and computers could dream, a gentle artist and a clever inventor were about to discover something magical—that their gifts were even more powerful when shared with each other.

In a world made of soft, colorful clay, lived a kind artist named Fiora. With her nimble fingers and a heart full of ideas, she molded whimsical creatures and vibrant scenes. Each pinch and roll brought a new friend to life, full of charm and cheer.

Fiora loved to share her creations with the world. She carefully photographed her clay friends and posted them online, where they sparkled and shone, bringing smiles to faces near and far. Her art was a gift, freely given and widely adored.

Far away, in a room filled with blinking lights and whirring sounds, lived Algernon, an AI engineer. He was building clever machines that could learn and create, but they needed lots and lots of examples to understand the world.

One day, while searching for beautiful patterns for his AI to learn from, Algernon stumbled upon Fiora's delightful claymation art. "Perfect!" he thought, "So much creativity, so many unique shapes and colors!"

Algernon's AI, like a tiny digital vacuum cleaner, began to collect Fiora's art, along with countless other creations from the internet. It sucked up all the colors, shapes, and styles, storing them away in its vast digital brain. Algernon was pleased; his AI was learning so fast!

But Fiora started to notice something strange. Her unique claymation style, her special way of making things, was appearing in places she hadn't put it. AI-generated images, looking almost like her own, popped up online. A little cloud of confusion and sadness floated over her head.

Algernon's AI grew smarter every day, creating amazing new things. Yet, something felt missing. The AI's creations were technically perfect, but they lacked the warmth, the unique spark, the feeling that Fiora's original art had. He scratched his head, a thoughtful frown on his face.

Algernon realized that while his AI could learn from the art, it couldn't truly understand the artist's heart without asking. He decided he needed to talk to the creators, especially Fiora, whose art had inspired him so much.

Fiora and Algernon met, a little nervously at first. Algernon explained how her beautiful art had helped his AI learn and grow. Fiora, in turn, shared how it felt when her creations were used without her knowing, like a piece of her heart was borrowed without permission.

Algernon truly understood. He proposed a new way: working together! Fiora could share her art, knowing it was valued and respected, and Algernon's AI could learn with permission, creating even more wonderful things. They shook hands, ready to build a future where clay and code danced together.

(Yes, AI helped with the visuals and video)

Createl illustrated storybooks in Gemini

The Art of Understanding: How AI Could Make Us More Human

Let me leave you with simple possibilities if we co-create instead of fight over AI.

A Recent Entrance to Paradise by the Creativity Machine software - and Stephen Thaler

We are the children of AI.

We are the engineers and data scientists.

We are the creators and artists.

We started out on opposite sides,

But the experience of AI brings us together.

Valuing human creativity.

Seeing AI as ingenuity, not a destructive force.

You create things with intent.

We're creating something unbelievable, and all we do is take sides.

It's the human race, remember?

We're on the same side.

The zero-sum game ends when we realize there's more value in building together than fighting apart.

Japan proved it works.

Baroness Kidron showed us inspiration isn't theft.

And two fictional characters—an artist and an engineer—demonstrate what the rest of us keep missing.

The future doesn't need you to pick sides. It needs you to drop the anger and work together.

Your creativity won't get stolen by AI. But it might get left behind if you keep fighting the future instead of shaping it.

The choice is yours: Keep burning time and energy in a war nobody wins, or start building something neither humans nor AI could create alone.

What's it going to be?

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RESOURCES

Chinese Court Issues First Decision on AI Copyright Infringement

China’s First Case on AIGC Output Infringement--Ultraman

Supreme Court rules against Warhol foundation in copyright fight over Prince images

Gemini Storybook Creator

We were somewhere around Redwood City on the edge of the metaverse when the drugs began to take hold. Not the good kind of drugs.

The algorithmic kind. The kind making you believe your smartphone loves you more than anyone ever did. And AI is the future, everyone else is the past.

It starts with a YouTube comment, one of those beautiful smacks of “I’ve done the research” digital trolling setting the tone of us v. them:

"@DeclanDunn ai is the future, you cant stop it. you just sound like a boomer complaining about it."

Of course. The classic "you can't stop progress you old dude" statement. Not listening to the short video, cutting out after the first 10 seconds.

Expecting someone to spend a minute to realize I was telling creators, fighting AI is like standing in front of a runaway train and telling it to stop.

I'm not trying to stop AI. I'm trying to stop turning AI into something mostly serving its masters, like a cult, instead of the people who created all the data that fills it with brilliance.

And those creators are the anti-AI Clankers – pro humanity cult – stop it! There's a difference between embracing the future and bending the knee.

The AI industry in the US at least are the drug dealers, we’re just the ones receiving the addicted message, and calling it our own.

And in the end I’m going to give you all, AI or anti-AI, a 3 step recovery program.

The first part is recognizing your both in the same cult, on different sides, but it’s the same.

The Great Digital Cult Rush of 2025

See, here's what the “follow the billionaire” in Silicon Valley don't want you to know.

Read the entire research document here

The research is so clear. Barnabas Barnty (and yes, that's his real name—you can't make this stuff up) published a study:

The Psychology of Indoctrination: How Coercive Cults Exploit Vulnerability and Foster Radical Beliefs

that reads like a playbook for AI manipulation. Cults prey on people experiencing "significant life transitions, emotional distress, or social isolation."

Sound familiar? That's basically everyone on social media, except the influencers (but they’re all avatars anyway)

The story? Like AI taking over, taking your jobs, taking your content, and in the end likely destroying us all. That’s a common storyline.

Everyone who's ever posted "Thoughts?" on social and waits for the sweet, sweet validation of professional strangers.

And if you don’t play the game by their rules, you’re not in the game. Your thoughts don’t exist. That’s the classic definition of a cult.

Barnty’s Four Rules applied to the AI Cult – whether you’re for it or against it.1. Love Bombing Creates The Algorithm's Embrace

Classic cult technique: Shower recruits with attention and affection to create belonging.

AI's version? Your first TikTok gets no views, except for some bots who give you the illusion they’re human, maybe even commenting.

Humanity's Last Exam becomes your obsession, an LLM test you don’t understand.

Doesn’t matter, fake it. Stop being yourself, start copying and spraying around Game Changers and Hot Takes on the latest AI taking over.

The algorithm whispers sweet nothings: "You're going viral IF you’re in the AI cult, baby. Dance for me."

Suddenly you're hooked like a lab rat hitting the cocaine button, creating content at 3 AM, chasing your first viral, day after day. Don’t give up, but whatever you do, be extreme.

And it hits, you get like 1,000 people….ok, 500 people and 500 bots, but who knows?

But cross the AI Cult—post something it doesn't like—and watch the love turn cold faster than a San Francisco summer.

You're back to 12 views and your mom's comment: "Nice post, honey."

2. Isolation Sucks, Join the Echo Chamber Express

Cults cut you off from outside influences. We built something more efficient: algorithmic isolation chambers.

Built on content, training you to be AI believers….you can be a AI hater, but that’s so niche.

Your feed becomes your reality. AI decides what content you see, what you think about, who you argue with online.

Like being trapped in a hall of mirrors, but all the mirrors show you content that confirms you're already right about everything.

The genius? We think we're discovering this organically.

"Wow, everyone really does agree that pineapple doesn't belong on pizza!"

No, you're in an anti-pineapple bubble, like the AI cult. There are pineapple people out there. They're just segregated into their bubble of poor pizza judgment.

3. Repetitive Reinforcement → The Infinite Scroll of Zoomer or Doomer?

Cults use constant repetition to diminish critical thinking. We streamline this with infinite scroll.

Every swipe confirms your worldview. Every recommendation validates what you already believe.

The algorithm doesn't challenge you—it's like having a personal yes-man that never gets tired of agreeing with you. Whether you’re for AI, like the 80%, or in the 20% against it.

It's digital chanting, but instead of "You’re one of us, you’re one of us”, it’s really saying to you

"Here, consume this content that perfectly aligns with everything you already believe while slowly eroding your ability to think independently."

4. Cognitive Restructuring → The Great AI Reality Replacement

Cults reinterpret your personal history through their lens. AI did something more elegant: We outsourced thinking entirely, taking it all without permission or payment or even a thank you.

Because it’s stealing content, meh. Remember we’ve got to beat China, with algorithms designed, at least in Meta’s recent hirings, by people trained in China.

Why remember facts when ChatGPT knows everything? Why decide what to watch when YouTube has you figured out better than you have yourself?

So you don’t have to think, just follow. Call it "optimization."

It's like having a digital Samantha, the AI in the movie Her, that it is "not just an OS. It’s a consciousness."

Or as Sam Altman of OpenAI put it
“The number of things that I think Her got right, that were not obvious at the time, like the whole interaction model with how humans are gonna use an AI—this idea that it is going to be this conversational language interface, that was incredibly prophetic, and certainly more than a little bit inspired us,”

“So it’s not just like a prophecy, it’s like an influenced shot or whatever.”

Tracing OpenAI CEO Sam Altman’s Love for Scarlett Johansson’s AI Romance Her

From the voice of the leading AI cult creator, rises the anti-AI pro humanity, Creator cult trigger. Anything AI is cheating. It steals. It’s evil.

Either way, you’re in a cult that thinks for you. Acts for you. And if you’re in a Cult, where are you?

Like the troll said, Declan, AI is the future. You’re a boomer complaining.

Stereotype set, attention dissolved…game set match.

Not being in either cult, like me – everyone knows its nowhere. Or is it?

The AI God Complex: When Silicon Valley Becomes Scientology

Here's where it gets properly gonzo:

While China builds AI like infrastructure—practical, utilitarian, boring—America has turned AI into a cult, chasing Super Intelligence.

Mark Zuckerberg just shared his vision for 'personal superintelligence.' Read his letter.

Mark Zuckerberg just shared his vision for 'personal superintelligence.' Read his letter.

"I am extremely optimistic that superintelligence will help humanity accelerate our pace of progress," Zuckerberg wrote.

Listen to tech bros talk about ASI and try not to hear religious fervor:

"AI will solve all human problems!"

"It will transcend human limitations!"

"We must prepare for the AI singularity!"

And maybe in the end it will replace you, and destroy you, but you already lost your job, who cares?

The research shows cults create "pseudospiritual authority" where leaders claim "exclusive access to divine knowledge."

Replace "divine" with "artificial super intelligence" and you've got the exact same playbook.

Pay with attention, cash, or support – nobody rides for free.

Looking into the Uncomfortable Mirror with the AI Drug of Inevitable Control

We're not just users—we're the product being cultified.

Our psychological vulnerabilities aren't being exploited to control us; they're being monetized to sell us back to ourselves.

Zuckerberg’s personal superintelligence vision just makes you a better ad unit, nothing to do with being a better person.

The weird part? We're paying for the privilege. It's like joining a cult that charges membership fees and somehow convincing yourself you're getting a good deal.

3 Steps to Recover from the AI Cult Trap

The research shows recovery requires rebuilding critical thinking and independent decision-making. So here's your digital detox program:

Step 1: Your Reality Check When did you last change your mind about something important based on information that challenges your beliefs?

If you can't remember, congratulations. You're living in an AI cult compound. Even if you’re anti-AI, and pro humanity.

It doesn’t matter if you think different, and act the same.

Step 2: The Dependency Test Could you function for a week without AI, without algo’d recommendations?

No GPS, no curated feeds, no "people you might know." Considering what someone who doesn’t agree with you thinks.

If that sounds terrifying, you might be more dependent and controlled than you think.

Like Dylan Sang, "He who is not busy being born is busy dying"

Dang, maybe I am like a boomer complaining.

Step 3: The God Test Do you treat AI companies with the skepticism you'd give any other corporation, or do you grant them special authority because they claim to be building the future?

If it's the latter, you're worshipping at the Church of Artificial Intelligence.

And if you only give them skepticism, like the Anti AI creators, you’ve given up participating. You’re on the sidelines.

Get off social media and go out to the real world. Often where there’s no algorithms and AI, there’s discussion.

The Way Forward: Taking Advantage Before Being Taken Advantage Of

The best way to take advantage of AI is to not be taken advantage of by it.

China builds AI like infrastructure because they see it as a tool. America builds AI like a religion because we've forgotten the difference between utility and worship.

The future isn't about better AI. It’s about better humans who can't be easily algorithimically manipulated into believing their smartphone notifications are more important than actual human connection. Than Human creativity.

The real question isn't whether AI will take over. The real question is: Why did we hand over control to begin with?

Leaving a cult is often an intensely difficult and emotionally overwhelming. It’s a complex mix of anger, shock, shame, embarrassment, annoyance, devastation, and despair, which are normal.

A Great Read on what it’s like to leave a Cult

“You can be a silent reader or an active participant. It’s all up to you.

But you’ll find many of the things you believed or feared were common to other people. You’ll be relieved to read that most of their fears never materialised.

You’ll discover that the great, big, unsurvivable thing is indeed survivable.”

Clare Heath-McIvor

Time to stop AI fanboy cheering or Clanker creator doom-scrolling.

Remember: In the AI age, the most radical act is thinking for yourself.

The most revolutionary, game changing tech is your own mind.

Start thinking again. Before we forget how.

And put down the phone and have a real conversation with a real human being.

Thanks for reading The AI Optimist! This post is public so feel free to share it.

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RESOURCES

The Psychology of Indoctrination: How Coercive Cults Exploit Vulnerability and Foster Radical Beliefs

Tracing OpenAI CEO Sam Altman’s Love for Scarlett Johansson’s AI Romance Her

Mark Zuckerberg just shared his vision for 'personal superintelligence.' Read his letter.

What to expect when leaving a cult or toxic group By Clare Heath-McIvor

The AI Optimist Club

The Techno-Optimist Manifesto

=============================

AI Optimist Playlist (Shorts and Sections)

We’re playing AI Copyright bingo and the only winners so far, are Big Tech….at least according to President Trump.

Charting GenAI by Graham Lovelace - excellent source!

Anything you post or create is now fair game for AI in the US—and pretty much any AI worldwide. President Trump just made it official:

"China's not doing it ... and you have to be able to play by the same set of rules."

The US announcement: AI companies no longer have to pay for the books, articles, videos, or any content they use to train their models.

Big Tech and the US government finally agree on something. Your content goes into AI for free.

Americas Ai Action Plan509KB ∙ PDF fileDownloadDownload

Give the AI industry credit for the propaganda machine that made this real. From Microsoft CEO Satya Nadella to Marc Andreessen, they kept repeating the same talking point until it became truth, then law, at least according to Trump:

"When a person reads a book or an article, you've gained great knowledge.

That does not mean that you're violating copyright laws, or have to make deals with every content provider."

It's persuasive sales copy. It's also complete BS.

When you read a book, you can't turn around and create millions of derivative works for commercial use.

You can't build a business empire by pattern-matching everything you've consumed. But AI can, and now it's almost legally protected to do so.

The Trump AI policy isn't just about copyright.
It's about what happens when we follow China's playbook.

The same China that's been the enemy of intellectual property for decades, taking whatever they want with impunity.

And while it’s not yet law, given the many Executive Actions President Trump has taken, it’s wise to take this as a sign to adapt early. He usually follows up on his promises in situations like this.

Now we're adopting their model because of fear-mongering about losing the "AI race": a race primarily about military applications, not whether ChatGPT can write better blog posts.

What happens to human creativity when taking becomes legal?

We've been hoping that recent legal rulings and licensing payments meant we were reaching some middle ground. Not fair, maybe, but at least acknowledging that taking people's work without permission, payment, or consideration was wrong.

Instead, Big Tech companies are knowingly buying copyrighted content from Dark Web sources like LibGen, because AI development is apparently more important than legal protections and creative traditions.

The real threat isn't just to your content—it's to the human edge itself.

If you don't encourage the people on the fringe, those who don't see, don't do, don't act like everyone else, to express themselves, you lose more than just their voice.

You lose the edge that shows us what could be, not just what was or what's popular now. That's where the new comes from. That's where we learn what's possible.

Think AI's amazing now? Wait until you see what happens when the creative edge disappears, when quality content creators give up because there's no protection or incentive.

When anyone can buy pirated content, feed it to an open-source AI model, and compete with the originals.

Your content has no protection. But your creativity still has value—if you know how to protect and position it.

This week's podcast dives deep into the mindset shift creators need to make. Not to give up, but to adapt.

To build resilience in a world where the rules just changed overnight. To remember why we create and how to thrive when the law won't protect us.

Because while Trump just handed AI companies a free pass, he can't legislate away what makes you uniquely human.

Question 1: Will AI Replace What I Do?

The ultimate question everyone asks me: will AI replace what I do? The honest answer is probably yes.

Will it ultimately be able to do everything you do? Maybe.

The question isn't whether AI will replace what you do.

The question is: what are you doing that makes you better than AI?

AI is patterns, probabilities, matching algorithms that give people what's been done before. It's about history, not innovation. It's not about vision or looking forward—it's about recreating what already exists.

While some jobs are being replaced right now, depending on that replacement happening might actually make you give up.

And that belief system becomes your reality. Those belief codes are what either make you grow or make you stagnant.

I'm not doing what I did when I began my career, and that had nothing to do with AI. So maybe if AI replaces what you're doing now, you're heading somewhere better. Somewhere that's not reliant on the repetitive stuff AI can handle.

SOURCE: Company Regrets Replacing All Those Pesky Human Workers With AI, Just Wants Its Humans Back

Look at the Klarna example. The financial services company bragged about replacing customer support with AI. They got rid of people, celebrated the efficiency gains.

Now they're hiring people back. Because people had complex questions that AI couldn't handle.

AI spins answers, but it doesn't really understand what customers need.

Don't let "Will AI replace what I do?" become a self-fulfilling prophecy.

You're really saying "I'm afraid of being replaced," and in any career, that's always been a possibility. AI or not.

Start looking at AI copyright law changes not as something to blame, but as something to challenge you. Because you don't have another choice.

AI won't have human consciousness anytime soon. It won't have your experience, the way you process information through your eyes, ears, feelings. That's your advantage.

Remember this: you're unique. AI really isn't. It's built on what other people have thought, said, or done.

Next Steps for Creators:

1. Understand your uniqueness: List what you do that requires human experience, emotion, or forward-thinking vision.

2. Identify your "non-replicable" skills: Focus on work that requires human connection, complex problem-solving, or creative leaps.

3. Reframe the threat: Instead of asking "Will AI replace me?" ask "How can I use AI to enhance what only I can do?"

4. Document your process: Your thinking processes are harder for AI to replicate.

5. Build relationships: AI can't form genuine human connections—make this your competitive advantage.

The Trump AI policy might have made content gathering a bit more legitimate, but it can't legislate away human creativity, experience, and the ability to see what's possible rather than just what was.

Question 2: Can I Use AI for a Boost Without Betraying What I'm Doing?

This question reveals something deeper: the fear that AI will somehow betray your creative work. Betraying is a human characteristic.

How can something betray you if it's not human, if it's not even thinking?

The real betrayal? You're betraying yourself by not adapting.

Recognize the elephant in the room: "How can I protect myself from AI copying my work or stealing it?"

If you put anything on social media or the public internet, you don't stand much of a chance.

Under the new Trump AI policy, it's going to take your content. But AI cannot recreate your work verbatim.

It can't produce your ten-page article. It might create two pages if you're lucky, but it works in patterns, not perfect copies.

What makes AI different from what we had five years ago? Back then, Google would search the internet, find your information, and let people use it to answer questions. Now AI does the same thing. It just processes and responds faster.

The uncomfortable truth for many creators, especially in SEO: you've been kings and queens of taking other people's ideas and reshaping them slightly.

This is just how content has worked. AI loves to copy what everyone does because it works on probabilities. It leans toward the middle, the average, the predictable.

The more context you give AI, the better answer you get. But here's the key question: if somebody's really searching for your specific work, are they going to settle for an AI approximation?

Or is your fear of being copied just an excuse not to put anything out there?

If you're scared of content being copied, don't put it on the public internet. But if you want to get noticed, you have to put stuff out. So be smart about it.

Take the book example: give away a free chapter, or pieces of a chapter. Sure, someone can take that, but it's not the complete work.

That sample is what gets you recognized and puts you in front of people. Behind a paywall or password protection, you can keep your premium content safe.

But if you get too paranoid, no one's going to see your work. That's the trade-off you have to evaluate.

The fear of AI copying content has become an easy way for creators to say "it's over, everything's over." But that's just one opinion among many—and opinions are all we have.

Keep creating. Build protected areas where your information isn't being taken, and ask people not to share it with AI systems.

Is it perfect? No. But it was never perfect, and work was being stolen long before AI came along.

Even AI companies have bought pirated books. Valuable copyrighted books like Harry Potter to train their models. Were those protected? Yes, and no. No one's completely protected under current AI copyright law.

The biggest thing AI can stop isn't your content being copied—it's your energy to create something new.

My biggest fear is that people will use AI as an excuse not to do anything, or rely on it so much that it does the work for them. Be careful not to do this!

Next Steps for Creators:

1. Develop a content strategy with layers: Free samples in public, premium content behind protection.

2. Use AI as a collaborator, not a replacement: Let it help with editing, brainstorming, or filling skill gaps.

3. Focus on what AI can't replicate: Your personal experience, unique perspective, and human connections.

4. Build direct relationships with your audience: AI can't maintain genuine human relationships.

5. Create "unfakeable" content: Work that requires your specific expertise, experience, or creative vision.

The Trump AI policy may have changed the legal landscape, but your creative value isn't just in the content itself—it's in your ability to think, connect, and create meaning that resonates with real humans.

Question 3: If AI Can Do What I Do... What Am I Worth?

If AI can copy what you do and your work looks like everyone else's, what's left?

There are a lot of businesses where people are already doing the same thing. Look at search engine optimization—it's been built on creating similar articles with slight variations so Google will rank you.

You're essentially doing what you accuse AI of doing: mimicking, copying, reshaping existing content.

But your worth goes far beyond any isolated piece of work you create.

Your worth comes from within. It shouldn't be defined by what an audience says or doesn't say, because anyone in the creative world knows that value is subjective.

What readers hear, what they think, how they interpret your work: that's based on how they feel from it, not just what you created.

When you can touch that connection and send it out into the world, it's magical. But don't expect it every time.

Your worth is much more than just what you create. It's the work you do on yourself, how you improve, how you learn and push yourself further.

Think about musicians. They love to play, learn, listen to others, and develop their own styles. Is it entirely original? No.

But it's entirely unique because no one else can create exactly what that individual creates, taking in those influences and put them out in their own way.

Your worth encompasses:

• The people you work with

• The problems you're trying to solve

• The originality you bring to common challenges

• Your experience and perspective

• Your ability to connect and communicate

Don’t value yourself based on the things AI can do. That's just marketing designed to sell you something.

Whether it's OpenAI selling ChatGPT as revolutionary, or someone claiming their art is completely original and unreplicable.

Under the new Trump AI policy, the question "Can AI create that?" becomes "Maybe." But is that really what's stopping you?

The protection strategy isn't just about legal safeguards. You can put content behind paywalls where AI can't access it. You can block the bots. You can even get paid for your content (not much, but something).

AI can only take what's happened and create something sort of like what happened in different patterns.

It works great for predictable code. It works well for formulaic content. But for creative work, for writing that connects, for putting ideas together in new ways?

AI's job isn't to replicate what you do. It's to help you fill gaps and enhance what you're already capable of.

If you want to see AI as something that's constantly taking from you, then keep your work completely hidden. But if no one sees your work, you'll never connect with your audience. When your audience really gets what you're creating, that's something AI cannot replicate.

Look at all the AI-generated content flooding LinkedIn and social media. It's bot mania, and it's completely vanilla. Generic. Forgettable.

Your worth is in stepping out and being unique while understanding the problem: over-relying on AI tools.

Next Steps for Creators:

1. Define your unique value: List the experiences, perspectives, and insights only you can bring

2. Build your "AI-proof" skills: Focus on human connection, emotional intelligence, and creative problem-solving

3. Create meaningful audience relationships: Develop trust and connection that transcends any single piece of content

4. Diversify your creative process: Don't let AI become a crutch—use it strategically to enhance, not replace, your thinking

5. Develop your creative voice: What makes your perspective unique isn't just what you say, but how you see the world

6. Focus on improvement over perfection: Your growth and learning process is something AI cannot replicate

It's in your ability to grow, connect, and create meaning that resonates with real humans—something that remains uniquely, irreplaceably yours.

The Over-Reliance Problem and What's Coming Next

The big problem nobody's talking about? Over-relying on AI.

What happens when ChatGPT goes down and you have a project due? You can't complete it because the tools aren't there.

If that becomes your reality, you're letting your skills erode. You're becoming dependent on it, addicted to it.

Be careful with that dependency. While AI can create work that might even be better than what you produce as a writer, it cannot become something you completely depend on.

Because when someone asks "Why shouldn't we replace you with AI?" and your answer is "AI does everything I do," then you are totally replaceable.

When you do the actual work, everything you've experienced, the way you see the world, your unique perspective—all of that comes through. And that's what ChatGPT fundamentally cannot do.

The Criminal Element Nobody's Discussing

Here's where the Trump AI policy gets really dangerous. AI companies just received a legal privilege: the right to take any content without permission or payment. But that's exactly what criminals have been doing for years.

If major corporations can now buy content from pirated sources, what's stopping bad actors from doing the same thing? Anyone can buy copyrighted content from Dark Web sources like LibGen, feed it into an open-source AI model, and compete directly with legitimate creators.

Ann Handley’s best selling books? Buy them illegally on LibGen. Meta may have.

The AI companies acted like digital gangsters first—taking what they wanted, when they wanted it.

Now that it's legal, why wouldn't actual criminals take advantage of this privilege? The technology doesn't care if you're OpenAI or a content pirate. AI is AI.

We've just created a wild west where stealing becomes legal as long as you call it "AI training."

What We're Really Losing

This isn't just about individual creators losing income. We're witnessing an engineering-driven solution that completely disrespects the actual data. The human creativity that makes AI brilliant in the first place.

Without human creativity, AI dies. And we're setting up a system that will erode the very creativity that feeds these models.

When quality content creators give up because there's no protection or incentive, what replaces them?

More AI-generated content. And the problem with that feedback loop?

AI trained on AI-generated content doesn't improve models. It degrades them.

We're potentially witnessing the death of the creative edge that shows us what's possible, not just what was popular. The people on the fringe who see differently, act differently, create differently. The ones who push human understanding forward.

And many of these fears about AI replacement are more about how you feel about yourself than about what AI can actually accomplish.

AI is not a person. It's a series of pattern recognition algorithms and vectors that come together to produce some impressive results. But it doesn't give us you.

AI only gives you what's been seen before. In a world where that's becoming the legal standard, your human voice, your creative edge, your ability to see what's possible rather than just remix what existed, becomes more valuable than ever.

Bank on it.

Protecting the Human Edge in an AI-First World

The Trump AI policy represents more than a legal shift. It’s a fundamental choice about what kind of creative future we want to build.

By following China's model of taking intellectual property without permission, we're not just changing copyright law. We're potentially destroying the creative ecosystem that makes AI valuable in the first place.

This engineering-driven approach treats human creativity as raw material to be processed, not as the irreplaceable foundation it actually is.

In rushing to win an AI race that's primarily about military applications, we're sabotaging the creative intelligence that makes AI systems worth having.

But here's what the policy makers and tech giants can't legislate away: your human experience, your unique perspective, and your ability to connect with other humans in ways that matter.

The path forward isn't to retreat into fear or give up creating.

Yes, the rules changed overnight.

Yes, your content is now legally fair game for AI training.

But your creativity, your voice, your ability to see possibilities rather than just patterns? That’s your.

The creative edge isn't just a boundary. It's the frontier of human potential. Once we lose it, no amount of AI can bring it back.

In a world increasingly filled with vanilla AI content, your authentic human voice becomes essential.

The question isn't whether you can compete with AI. The question is whether you're ready to be more human than ever.

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Trump's bombshell to creators: 'AI wants your content, but Big Tech need not pay'

Charting Gen AITrump's bombshell to creators: 'AI wants your content, but Big Tech need not pay'🚨Charting Gen AI is a reader-supported publication. To support my work and enjoy a full uninterrupted Charting experience, including searchable access to the archive, please become a paid subscriber today…Read more8 months ago · 7 likes · Graham Lovelace

Let's play AI-copyright deniers' BINGO!

Charting Gen AILet's play AI-copyright deniers' BINGO!🚨Charting Gen AI is a reader-supported publication. To support my work and enjoy a full uninterrupted Charting experience, including searchable access to the archive, please become a paid subscriber today…Read morea year ago · 24 likes · 9 comments · Graham Lovelace

America's AI Action Plan

Search LibGen, the Pirated-Books Database That Meta Used to Train AI

Company Regrets Replacing All Those Pesky Human Workers With AI, Just Wants Its Humans Back

"What you end up having is lower quality."

Thumbnail Image

For two years, I've documented the AI content wars from every angle - court cases, licensing deals, developers' reasons for taking content without permission or payment, and the gut-punching threat that greets every creator who does the work for little reward.

Judging creators to be standoffish, privileged, and pains in the ass reveals the true element lacking in AI: respect for people who create, who aren't engineers.

Because you don't build brilliance by lacking respect for humanity.

The singularity isn't just about humans and machines melding - it's about a better life for people. AI companies throw this out with casual disregard, and it shows.

Wonder why AI adoption is so slow?

Why only 3% are willing to pay for AI?

Why Big Tech forces AI into every piece of software without choice, telling the rest of us to 'adapt or die' as if they're in control?This is what causes crashes and bad business. And oh yeah - what's your business model?

Because except for ChatGPT, most willingly hide from having one. After all, business models and plans and people are distractions from this grandiose vision of AI.

I've worked with engineers for years. Many stare into the mirror of their own creativity like the artists they disdain.

They're myopic, don't listen to users, convinced they're geniuses. Dunning-Kruger at best, inferiority-superiority complex at worst.

Meanwhile, great engineers listen to people. They don't start with tech - they start with users, the ones who show you what's up.

Creators understand it isn't their work that matters - it's the audience's reaction.

What they create isn't what the audience consumes. It means different things to different people. Unpredictable.

That's how you find a business model: customers plus onboarding and retention. Relying on the latest cool AI is so yesterday.

Most of it's based on a few LLMs with little differentiation. This game gets hard when you're stuck in the engineer bubble hoping the hype lasts.

And it doesn't - which is good. What's happening now is ego.

Safe Superintelligence and Sutskever running secret projects with no plans, no business models, just billionaire egos getting stroked.

But these dances end when truth surfaces. What people do with your tech matters more than what you say.

Engineers fall on the cross of their own egos, staring into mirrors users don't share.

You're part of the world. Join it. Get a business model. Stop bragging you should get content for free because 'AI will free the world.'

Then tell me why DeepSeek is every bit as good with less money - because they focus on solving problems, not massaging engineer egos.

That bubble is popping. Here's how I know.

Part 1: The Divide (Bruce Randall Interview)

Why both sides think they're right - and why that's the problem

Bruce Randall cut right through my bias in ways that made us both laugh - because we recognized ourselves in the problem. I share what I’ve heard….

"I think both sides are like incredibly similar... They're entitled. Their work sucks.

I don't like their work, so they shouldn't get paid for it. Right?

Versus the creatives. Like I should get paid for everything that I don't get paid for."

We're all just defending our positions instead of listening.

Engineers dismiss creators as entitled whiners whose work isn't worth paying for. Creators demand payment for everything that gets used.

Both sides have dug in so deep they can't see how similar their arguments actually are.

Bruce nailed the core issue - it's not about who's right, it's about perspective and how people develop that perspective.

Once they lock into their worldview, they resist change because they believe they're absolutely right. The other side believes they're absolutely right too.

Then Bruce said something that stopped me cold:

"And then when you start going inside, you start developing. You start seeing that it's all the same, right? It's just a matter of what degree to what side you're on."

That's the breakthrough most people miss. It's not two different species fighting - it's humans with different stakes in the same system.

The engineering mindset that solves technical problems runs into the creative mindset that solves human problems, and instead of collaboration, we get tribal warfare.

The solution isn't picking sides - it's recognizing we're humans being imperfect and learning from each other.

That's what AI needs too. Not just code and training data, but understanding the impact on people.

TechCrunch Disrupt October 2024: Stop Hiring Humans is the first message you see!Not parading around with "AI First" and "Stop Hiring Humans" with pride. It's cool to be efficient, but it's cruel to focus your future on the destruction of someone else's present, life, and future.

Both sides could find common ground and build on it, but they're stuck believing their truths are the only truths that matter.

TLDR:

• Both sides create "truths" from their beliefs, resist change once positions harden

• Developers stereotype creators as entitled; creators want payment for everything taken

• The similarity between sides is what they refuse to see

• Solution requires finding common ground instead of defending positions

• "AI First, Stop Hiring Humans" isn't progress - it's cruelty disguised as efficiency

Part 2: The Human Edge Makes AI Brilliant

Where else is that data from, and the logic that makes sense of it?

Here's what manyAI developers miss: you're not just scraping data, you're losing the source of what makes that data valuable in the first place.

"If we lose the human edge, we're going to lose the great AI that we could have.

Because if you lose that edge, you lose out on a lot. You lose showing us what could be, not just what was or what's popular now."

Are we going to live like content social media algorithms, feeding us just what we want so we don't actually grow?

"The edge isn't just a boundary, it's the frontier of human creativity.

And once you lose it, no amount of AI can bring it back."

For the few who choose to be creative - because it's not a calling of many, it's hard and rarely gets compensated - it's good to nourish and nurture this, not simply take what they create without reward.

Look at what happened to Marvel. Those comics took years to develop, then the blockbuster movies became like AI is becoming - just kept repeating the good stuff, focusing on the violence, not the human interactions.

It went from meaningful to caricature. And those Marvel comics were founded by writers and artists with little pay, people looking at them like they were crazy.

Ask Stan Lee how long it took - there's no guarantee. Same thing with AI.

"The human edge is the source of creativity. Otherwise, we're just spinning the same tunes over and over again. It's sort of dull. Do you really want 2025 on repeat?"

When everything goes into some AI database and over time becomes just an image we can sort of create, you lose the breakthrough.

TLDR:

• Creativity comes from the margins, gets killed when everything moves to algorithmic middle

• Marvel went from breakthrough to repetitive caricature - same path AI is on

• Taking without nurturing kills the creative source that makes AI valuable

Part 3: Andersen et al v. Stability - The Legal Crack

Judge Orrick's discovery ruling - why this small win could crack Big Tech's wall

Sarah Anderson and her group of artists just landed something that seemed impossible - they cracked open AI's black box, even if just a little.

After months of legal maneuvering where it looked like Big Tech would shut this down before it even started, Judge Orrick delivered a surprise.

The artists have only one angle to protect them - copyright law. And the copyright lawsuit was at a point where it could have been dismissed before discovery, where lawyers sit down and ask the hard questions.

This is where they discover what each side actually has, what evidence gets brought into the case, and whether it's legal or not.

If it doesn't go to discovery, AI companies don't have to share anything about what's actually going on behind the scenes. But Judge Orrick said yeah, it does.

"Now they're going to have to open those black boxes of AI not only tell us how to work, but telling the decisions that went through to grabbing those materials."

Lawyers for the artists can now peer inside and examine documents from Stable Diffusion, Midjourney, and DeviantArt, revealing more details about their training datasets, their tech, and how we got here in the first place.

Something private companies don't have to share unless they do something illegal - like maybe violating copyright law.

Remember what Stability's CEO said?

"We took them. Now we can recreate them and do iterations."

Laws are built on intent - why you did something. And OpenAI says it can't create this without copyrighted material and won't pay for it. The intent is actually pretty clear.

This isn't a legal decision yet - the case has got a ways to go.

But it means the case has enough merit to warrant that deeper discovery. That's what makes this huge.

Even though this is a small victory, remember - this is a giant underdog fight. How are they going to win against Big Tech companies whose business model is "steal and sue," or at least have lawyers to defend yourself and ask forgiveness later?

This small victory is a crack in the wall of Big Tech dominance and could lead to more accountability in the future and more respect for the people who create the content.

TLDR:

• Anderson v. Stability moves to discovery - AI companies must reveal training data sources

• Judge found "sufficient" evidence of induced copyright infringement to proceed

• Companies must explain decision-making process behind grabbing copyrighted materials

• Small crack in Big Tech's "steal and defend later" business model

• Discovery could expose intentional copying vs. claimed technical accidents

AI Image only; not Ultraman and not the actual judge.Part 4: Ultraman in China - The Economics Lesson

When courts actually side with creators - and why it matters

Here's where things get weird. In a Shanghai courtroom, a Japanese superhero won a copyright battle against AI.

Meanwhile, in Tokyo, that same AI could legally devour everything in sight.

This isn't just about Ultraman - it's about your work becoming someone else's fuel, and Japan is showing us how it happens.

Japan has one of the most permissive AI models in the world.

That manga you created? Legal training data.

That song you recorded? Fair game for AI.

But it's not that simple - there are boundaries and rules around this, allowing access to copyrightable content to learn, as long as it doesn't replicate, copy, or impact what money creators earn from their work.

That last part is crucial: financial challenge.

"As long as it doesn't do it, to really replicate the copy it, or to challenge somebody financially."

But in China, they drew a different line. When AI companies used Ultraman's likeness to generate content that competed directly with the original, the court said no.

The key wasn't that AI training happened - it was that economic damage occurred.

This case reveals the real test for copyright protection worldwide. Courts aren't interested in abstract principles about AI ethics or creative rights.

They care about economic impact and demonstrable damages. Show real financial harm, and courts will lean toward creators. Show no damages, and you get no judgment.

The weird contradiction here is telling. Japan allows AI to consume everything but protects against economic impact through the courts.

China, where most people think copyright law is ignored, actually enforced it when clear loss of money to the brand was proven.

This signals something important: the licensing wave isn't about moral arguments or creator rights. It's about business reality.

As AI companies start making real money from generated content, they create real economic competition with original creators. That's when courts start paying attention.

The Ultraman case shows us the future - not because of any grand legal precedent, but because it demonstrates the threshold where taking content becomes legally risky.

AI companies can scrape and train all they want, but the moment their output starts displacing original creators' income, they've crossed into dangerous territory.

TLDR:

• Japanese superhero wins copyright case in China despite Japan's permissive AI laws (though the fine was paid by a web site that used another AI to generate the image, so it’s not really stopping the problem.)

• Court focused on economic damage, not training data usage

• Shows the real test: demonstrable financial harm to creators triggers legal protection

• Licensing isn't about ethics - it's about avoiding lawsuits

• AI companies safe until their output directly displaces creator income

Part 5: NY Times Reality Check - The 85% vs. 20% Revelation

What's actually happening vs. the headlines

The New York Times versus ChatGPT case has been my go-to example of AI companies literally reproducing copyrighted content.

I quoted that 85% accuracy rating from their legal documents, showed all those exhibits where ChatGPT spit out nearly verbatim New York Times articles.

Then a smart Substacker named Swen Werner made me look closer.

What I found changed everything about how I see this case.

The New York Times wasn't pulling out complete articles. They were pulling out snippets - little sections where they'd give ChatGPT the beginning of an article and ask it to continue.

These were all using articles printed by the New York Times, and they showed tons of examples. But they were all short clips.

I didn't see one single full article reproduced, which is what I was expecting based on the way they positioned their case.

When Swen compared what was actually pulled out to the original articles, he found about 20% of the article content had that 85% similarity rate. So 20% of the article showed 85% reproduction - not the entire piece.

The New York Times was doing all sorts of things to influence the output, including techniques most of us can't do today.

For the general public paying $20 a month for ChatGPT, it would take enormous amounts of work to try to reproduce what's already been created.

"Large language models do what's called reconstruction. They put together different pieces, different starting with tokens, putting together words.

There's a whole science to it, but nothing is actually sitting there like the New York Times claims in memory."

The memorization argument falls apart when you understand how LLMs actually work. They reconstruct patterns, they don't store articles like a database.

When you can pull out Hamlet's "To be or not to be" passage, that's not because it's stored verbatim - it's because that pattern appears so frequently in training data that reconstruction becomes highly probable.

The same thing applies to that viral Guy Fieri article. It went massively viral on social media, got commented on everywhere, quoted endlessly.

All of that social sharing made it much more likely that content would be reconstructable from ChatGPT.

This case isn't really about copying snippets. It's about the New York Times versus ChatGPT as competitors.

The Times doesn't want ChatGPT to become a news source. They don't want it taking subscribers away.

At worst, if you could go into ChatGPT and get New York Times content without paying them, that's obviously what this is all about.

But the evidence shows that's not what's actually happening. What's happening is business competition disguised as copyright violation.

Be interesting to see how this turns out, as it appears licensing settlements have likely been offered along the way. But the NY Times sees something bigger, again, that economic damage. Keep an eye on this one.

TLDR:

• NYT showed 85% similarity in snippets, not full articles - only 20% of articles affected

• Required advanced prompting techniques most users can't replicate

• LLMs reconstruct patterns, don't store articles in memory like databases

• Viral content more likely to be reconstructed due to training data frequency

• Real issue: business competition between NYT and ChatGPT, not only copyright theft

• Case reveals gap between legal headlines and technical reality

Two years ago, I started this podcast as the AI Optimist, believing we'd find common ground between creators and developers.

I documented court cases, licensing deals, and arguments from both sides. Being nuanced and balanced, this podcast didn’t stand a chance of reaching the masses because I wasn’t playing the clickbait game - which most do who find an audience.

The common ground exists - but it's not where anyone expected.

It's in the reality that free content was always temporary, and ego-driven development was always unsustainable.

I've built businesses through crashes before. My startup's revenue tripled when the dotcom bubble burst - not through hype, but by focusing on what people actually needed.

This AI world has more money, and it's the same exclusivity problem: engineers only. That exclusivity kills growth.

There's more to the world than math and engineering. I love engineers - work with them constantly - and know in their hearts they're some of the kindest, most caring people.

But not with AI. This lack of appreciation for humanity shows, scares users, and isn't your best.

Want to make AI that changes the world?

Begin with yourself. Realize we're all serving humanity, not AI - despite what some leaders want. Humans are amazing. Try looking at them the way you look at AI.

Look at Parasol Cooperative's RUTH - a chatbot helping people escape domestic abuse and human trafficking.

No data collection because their users' privacy isn't a corporate slogan, it's their lives.

No paywalls, no founder ego conferences. They love what they're doing and use AI for people who need help. AND need to keep it private.

Want a real Turing Test?

Be like Turing - doing things for society, caring even when society didn't care for his identity.

Prove you're human to another human not through IQ tests founded on eugenics, but by being real, caring, using your skills for what people need instead of telling them what they need.

You don't have to be in a cult. You can be part of the human race, as can AI.

And while you're debating superiority, DeepSeek builds better AI for less money because they focus on solving problems, not stroking egos.

Americans love saying we're the greatest - I love this country, but there's no proof we're better. We're colleagues, not masters of AI.

While China uses this for surveillance openly, we build surveillance capitalism and act superior. At least they're honest.

The great AI content free-for-all is over. The engineer ego bubble is deflating. The business model reckoning is here.

Your choice: Join the world, or keep pretending you're the genius while reality moves on without you.

Because this isn’t Dotcom with the US leading the way. The whole world is able to build AI today.

Most aren’t doing it to threaten people, they are trying to help them. And many in the US are also doing this, but the leadership of AI is out of touch.

Billions of dollars will do that. Most of the world doesn’t need billions to do this and their solutions come from the people they design their AI for.

Turn the focus from Singularity to people, and watch what you find.

Thanks for reading The AI Optimist! This post is public so feel free to share it.

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Bruce Randall on LinkedIn:

If AI is an Inventor, then So is Nature - Robert Plotkin (EP #35)

The NYT’s AI Lawsuit Hinges on a Misleading Claim—And Nobody Noticed

My Digital Truth® - FusionisticThe NYT’s AI Lawsuit Hinges on a Misleading Claim—And Nobody NoticedThe New York Times Company has an ongoing lawsuit against OpenAI and Microsoft, filed in December 2023. The lawsuit alleges that OpenAI's language models were trained on the Times' copyrighted content without permission, constituting copyright infringement. …Read morea year ago · 1 comment · Swen Werner

OpenAI warns copyright crackdown could doom ChatGPT

How a New York Times copyright lawsuit against OpenAI

could potentially transform how AI and copyright work

Who’s suing AI and who’s signing:

January 2025: Major AP, AFP and Axios deals announced.

By Charlotte Tobitt

Top Takeaways from Order in the Andersen v. Stability AI Copyright Case

by Kevin Madigan

Oscar Wilde by Napolean Sarony

Chinese Court Issues First Decision on AI Copyright Infringement

China’s First Case on AIGC Output Infringement--Ultraman

Report on AI and Copyright Issues by Japanese Government

NO&T IP Law Update

27th_Tokyo_International_Film_Festival_Ultraman_from_Ultraseven_(15001540863) By Dick Thomas Johnson from Tokyo, Japan - 27th Tokyo International Film Festival: Ultraman from Ultraseven, CC BY 2.0,

By Dick Thomas Johnson from Tokyo, Japan - Ultraseven from "ULTRASEVEN 55th Anniversary Special Screening" at Red Carpet of the Tokyo International Film Festival 2022, CC BY 2.0,

SCLA

The State of Consumer AI

There’s Something Very Weird About This $30 Billion AI Startup by a Man Who Said Neural Networks May Already Be Conscious

Once upon a time, in a land not so far away, there lived an Emperor who loved new technology more than anything else in the world.

One day, two groups of ambitious alchemists arrived at his court with perfect proposals.

Now, alchemists, for those who might not know, are the folks who claim they can turn ordinary metals into gold through secret methods.

In medieval times, they promised kings magical transformations. In our modern AI version, they promise investors magical returns.

I learned about digital alchemists the hard way during the dotcom boom.

A well-funded CEO once called me with an irresistible offer:

"Book me a million-dollar ad campaign.

Keep $100,000 for yourself, send me back the rest, but invoice the full million."

Easy money, right?

A year later, that CEO went to white-collar prison.

I turned down the deal because I've learned there's no such thing as easy money, no free lunch, no magical transformation of nothing into something valuable.Except, apparently, in AI.

The first digital alchemist group claims they transmute ordinary human coding into revolutionary artificial intelligence.

The second group promises to transmute creator protections into competitive advantage, warning that protecting artists' rights dooms the kingdom to irrelevance in the global AI arms race.

Both are selling the same invisible cloth: the belief that you get something unexpected without paying the real cost.

And just like in the fairy tale, everyone is so eager to see the magic that they forget to ask the obvious question:

"Where's the actual gold?"

This is the story of how $450 million disappears into thin air, and how two groups of alchemists use the same magical formula: promise transformation, hide what's really going on, and let people's desire to believe do the rest.

Part 1: The First Alchemists - Builder.ai

The first group of alchemists called themselves Builder.ai—though they started as Engineer.ai in 2016, which should have been the first clue.

They began with an astonishing claim: they'd invented an AI assistant named "Natasha" that builds smartphone apps with 80% automation.

"As easy as ordering pizza," they promised.

Builder.ai

The Emperor's court? Mesmerized.

Microsoft opened their treasury. The Qatar Investment Authority, SoftBank, the World Bank—they all lined up with golden coins. Over $450 million poured in at a valuation of $1.5 billion.

But here's where the story gets interesting. In 2019, the Wall Street Journal decided to peek behind the curtain. What they found wasn't revolutionary AI.

Instead it was 700 engineers in India, manually coding every single app. The "artificial intelligence" was more like a smart toaster.

This AI startup claims to automate app making but actually just uses humans

You'd think that ends the story, right? Emperor discovers the alchemists aren't telling the truth, throws them in the dungeon, recovers the gold?

Not in our AI fairy tale.

Builder.ai not only survives. It thrives for six more years. Microsoft doubles down with equity investments. The Qatar Investment Authority keeps writing checks.

Because in the age of AI, even when you catch the alchemists red-handed, the desire to believe in magic is stronger than the evidence of your own eyes.

The deception continued. Revenue was inflated by 300%. In 2024, they claimed $220 million when the real number was closer to $50 million.

When a new CEO finally looked at the books in 2025, he discovered what everyone should have known since 2019: there was no gold, there was no magic, there was no AI.

It's not "no code"—it's lots of code. Human code.

From $1.3B to Bust: The Rise and Collapse of Builder.ai

In June 2025, the creditors came calling. Viola Credit seized $37 million, leaving Builder.ai with just $5 million in restricted accounts.

The company filed for bankruptcy, owing over $100 million against assets worth less than $10 million.

But here's the most fascinating part about their creditor list—it reads like a spy novel.

They owed money to Shibumi Strategy, an Israeli intelligence firm founded by former Mossad operatives. Quinn Emanuel, one of the world's most intimidating litigation firms. Sitrick and Company, crisis communications specialists. T&M USA, corporate intelligence.

When your AI startup needs spies and crisis management experts on speed dial, you're probably not disrupting app development.

More like you're disrupting the truth.

Key Facts: Builder.ai's $450M DeceptionEngineer.ai in 2016, later became Builder.ai

• Company Evolution: Engineer.ai → Builder.ai (2016-2025)

• The Promise: "Natasha" AI assistant, 80% automation, "easy as ordering pizza"

• The Investors: Microsoft, Qatar Investment Authority, SoftBank, World Bank - $450M+ raised, $1.5B valuation

• The 2019 Exposure: Wall Street Journal revealed engineers in India doing manual coding

• The Continuation: Despite exposure, company thrives for 6 more years with continued investment

• The Revenue Fraud: 300% inflation - claimed $220M, actual $50M in 2024

• The Collapse: Viola Credit seizes $37M, bankruptcy filing June 2025

• The Creditor List: $100M+ liabilities, <$10M assets including:

  • Shibumi Strategy (Israeli intelligence firm)

  • Quinn Emanuel (intimidating litigation specialists)

  • Sitrick and Company (crisis communications)

  • T&M USA (corporate intelligence)

  • AWS ($85M), Microsoft ($30M)

Part 2: The Second Alchemists - UK Government Policy

While the first group of alchemists was busy turning investor gold into nothing, the second group was performing an even more ambitious transformation in the courts of the United Kingdom.

This alchemy involves Getty Images versus Stability AI—a case that should be open and shut. Getty has evidence that their copyrighted images were used to train Stability's AI without permission.

We're talking about wholesale appropriation of creative work on an industrial scale. Even I know Getty has been litigating since the dotcom era—what were they thinking taking on one of the most aggressive legal teams in the business?

UK government accused of 'gaslighting' as data bill deadlock with upper house goes onWhile Getty fights for its rights, the UK Government is going in a different direction?

In the overall question of AI and creator’s rights, the UK government chose sides, and it's not the side you might expect.

Instead of protecting creators' rights, the government is pushing for an "opt-out" system.

Picture this: every artist, photographer, writer, and musician in the kingdom must individually track down every AI company, knock on their digital door, and beg them to please not steal their work.

Meanwhile, there's no transparency requirement. Creators have no way to know if their work has already been fed into the machine.

The government's alchemy here is particularly clever: they're transmuting theft into innovation by simply calling it something else.

"We're not enabling copyright infringement," they say, "we're fostering competitive advantage in the global AI arms race."

UK Creators fight back: Make it Fair

Still, the UK system fights back, with movements like Make It Fair and celebrities like Elton John pushing the issue hard.

I wish the US was doing as much.

The House of Lords won a series of votes against the government to introduce provisions securing greater transparency from AI firms to determine what they've trained their systems on.

Five times they voted to require AI companies to reveal what copyrighted material they've used. Five times they demanded transparency. Five times they won.

Then the government struck down these provisions.

The final vote came on June 11, 2025. The transparency provisions were removed. The Data (Use and Access) Bill passed without requiring AI companies to disclose their training data.

The government's position is clear: tech companies' convenience wins over creators' rights.

After all, AI is more important than all of us, right? Who's going to live without AI?

This isn't just about Getty Images—though they have the lawyers to fight this battle.

It's about every independent creator who doesn't have a legal team on retainer. In this new system, those with lawyers get paid, those without get plundered.

The government calls this "balancing innovation with creator rights."

But when you look at the balance, one side gets everything they want, and the other side gets the right to opt out of having their life's work stolen…if they can figure out who stole it in the first place.

The UK tech secretary actually told Baroness Kidron, a leading advocate fighting for creators' rights, that creators were asking for a "privilege"—that demanding permission before AI companies take their work without payment was somehow asking for special treatment.

But that's not a privilege.

It's called property rights.

And it's clear that governments and big tech around the world are working together because they think AI is bigger than all of us.

Key Facts: UK Government Chooses Big Tech Over Creators

• The Case: Getty Images vs. Stability AI - clear evidence of billions of copyrighted images used without permission

• Government Position: "Opt-out" system instead of "opt-in" for creator protections. Does this apply to Getty? We’ll see.

• The Burden: Creators must individually track down AI companies to request removal of their work

• No Transparency: Creators have no way to know if their work was already used in training

• Parliamentary Battle: House of Lords voted 5 times for transparency requirements

• Government Response: Struck down transparency provisions each time

• Final Vote: June 11, 2025 - transparency provisions removed from Data (Use and Access) Bill

• The Message: Tech companies' convenience prioritized over creators' rights

• The Reality: Those with lawyers get paid, those without get plundered

• Government Rhetoric: Called creator rights a "privilege" rather than property rights

The Pattern Reveals The AI Bias of Governments

Both groups of alchemists follow the same playbook.

Builder.ai hid their army of engineers behind claims of revolutionary AI.

The UK government hides wholesale appropriation of creative work behind claims of competitive advantage.

Both demand trust without transparency. Both benefit the powerful at the expense of creators and copyrights.

And both continue thriving long after their methods were exposed. Builder.ai survived six years after the Wall Street Journal revealed their deception.

The UK government pushed through their anti-creator legislation despite five House of Lords victories demanding transparency.

The system rewards AI theater over substance.

When billion-dollar companies can fake AI capabilities for years, and governments can transmute theft into "innovation policy," what else are we missing?

What other emperors are parading around naked while we all politely admire their invisible code?

Choose Reality Over Faux Magic

In the original fairy tale, it takes a child to point out the obvious truth: the Emperor has no clothes.

In our modern version, that child's voice comes from bankruptcy courts and creator lawsuits, from auditors and journalists willing to look behind the curtain.

But what makes this story different from the fairy tale? We don't have to wait for the parade to end to see the truth.

We can choose to look behind the curtain right now, before the decisions are made, while we still have a chance to make AI better by working together instead of against creativity.

Builder.ai is bankrupt, but hundreds of other companies are making similar claims about their AI capabilities.

The UK's transparency battle is over, but similar fights are happening in courtrooms around the world.

And all of this could make AI so much better if we wake up and realize that the engine driving AI's impressive capabilities comes from our imaginations, dreams, creativity, reactions, and experience. Not just reasoning.

So here's my question for you: When the next digital alchemist arrives at your business, promising to transmute your ordinary problems into automated solutions (sounds like most AI pitches today, doesn't it?)….

Will you ask to see the actual gold?

Will you demand transparency?

Or will you join the parade, hoping someone else will point out that the emperor has no code?

Because in the end, true progress doesn't require creators to surrender their rights.

The future belongs to those who choose reality over beautiful, invisible AI cloth.

The Emperor has no code.

The Emperor is doing things that could be done so much better when they wake up and realize that the AI magic they're selling is powered by human creativity—and that creativity deserves protection, not plunder.

Because the real alchemists aren't the ones promising to turn code into gold.

They're the creators who transform human experience, intuition, and imagination into the art, stories, and visions that make AI worth building in the first place.

Thanks for reading The AI Optimist! This post is public so feel free to share it.

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From $1.3B to Bust: The Rise and Collapse of Builder.ai

This AI startup claims to automate app making but actually just uses humans

Builder.ai

UK government accused of 'gaslighting' as data bill deadlock with upper house goes on

Charting Gen AIUK government accused of 'gaslighting' as data bill deadlock with upper house goes on🚨Charting Gen AI is a reader-supported publication. To support my original journalism and enjoy a full uninterrupted Charting experience please become a paid subscriber…Read more9 months ago · 7 likes · 2 comments · Graham Lovelace

Victory again for tireless AI transparency campaigner. Will the government now act?

Charting Gen AIVictory again for tireless AI transparency campaigner. Will the government now act?🚨Charting Gen AI is a reader-supported publication. To support my work and enjoy a full uninterrupted Charting experience, including searchable access to the archive, please become a paid subscriber today…Read more9 months ago · 13 likes · 3 comments · Graham Lovelace

Matthew Clifford - UK AI Plan

Make it Fair UK Campaign

OpenAI warns copyright crackdown could doom ChatGPT

AI Optimist Playlist

The TikTok Blueprint: When Silicon Valley Startup Advice Becomes Government Policy

Taking advantage of AI before it takes advantage of you – especially when governments are writing the playbook.

First, they came for our content. Now they're rewriting the law books.

"Make me a copy of TikTok. Steal all the users. Steal all the music. Put my preferences in it."

Then, if it takes off, "hire a bunch of lawyers to go clean the mess up."

That Silicon Valley playbook – steal first, settle later – is startup wisdom becoming government policy.

And it's playing out in real time across UK and US copyright battles, where AI companies and political power are deeply aligned against creators.

Almost like AI is too big to fail.

Sacrificing property rights (because that's what copyright is – a property right) on the altar of tech supremacy.

UK: The AI Training Opt-Out Lottery

The UK government's proposal is simple: AI companies can scrape whatever they want. No permission is needed. Creators must actively opt-out. Good luck with that.

Charting Gen AIVictory again for tireless AI transparency campaigner. Will the government now act?🚨Charting Gen AI is a reader-supported publication. To support my work and enjoy a full uninterrupted Charting experience, including searchable access to the archive, please become a paid subscriber today…Read more9 months ago · 13 likes · 3 comments · Graham Lovelace

As Baroness Kidron, an independent filmmaker and presenting the case to UK politicians puts it:

"The plan is a charter for theft, since creatives would have no idea who is taking what, when and from whom.”

The policy architect? Matt Clifford – a tech investor with conflicts "so deep" it could be a TV drama.

His solution to prevent the UK from "falling behind"? Gut copyright law.

Meanwhile, big creators with lawyers are cutting deals left and right. Small creators get the opt-out lottery.

When challenged on fairness, Tech Secretary Peter Kyle defended removing transparency requirements because

"it would not be fair to one sector to privilege another."

Baroness Kidron's response cuts deep:

"It is extraordinary that the government's decided, immovable, and strongly held position is that enforcing the law to prevent the theft of UK citizens' property is unfair to the sector doing the stealing."

US: Copyright Office Chaos

Plot twist across the pond. The US Copyright Office on May 9 releases a bombshell report siding with creators. Then a day later, the Trump administration fires its author, Shira Perlmutter.

Her replacement? A DOJ attorney with "no expertise in the field."

The turmoil is real. As Graham Lovelace notes in his excellent tracking of this copyright chess match:

"Doubts now also exist over whether the office's fourth report will ever see the light of day."

The Pattern EmergesAI companies plead poverty while sitting on tens of billions in funding, aiming for trillion-dollar valuations. They've bought five years of free data with fair use arguments.

What other industry openly takes what it wants, settles only with players who can afford lawyers, and claims it can't pay for the raw materials that built their entire business model?

Both sides of the Atlantic are choosing AI supremacy over creator rights. The Stanford "hire lawyers later" strategy has become official policy.

This isn't just about big tech versus artists. This is about who gets to participate in the AI economy.

When governments write the rules for free data extraction, only the biggest players win.

Small AI companies? They'll still need to pay. Individual creators? They get nothing. The middle gets squeezed while the top and bottom play by different rules.

When governments write the rules for digital content extraction, who's really getting optimized here?

The blueprint is clear. The question is whether we'll recognize it before it's too late to rewrite the rules.

Part 2: The UK AI Opt-Out Impossibility

Here's where it gets absurd.

The UK government's proposal? AI companies scrape everything. No permission. No cost. Creators just need to "actively opt out."

Now if I write a book, I'd have to contact ChatGPT: "Opt me out." Then Claude: "Opt me out." Then DeepSeek: "Opt me out."

You get the picture. It's the automated opt-in problem that's plagued the internet since day one.

Except now governments are telling creators:

"You handle it. What's the problem? You're in control."

48,000 People Disagree

This week in the UK, the pushback exploded. Artists previously filed a 48,000-signature petition.

Parliament votes went in favor of transparency requirements. This might force AI companies to disclose what they're using and giving creators real opt-out control.

Though the general feeling is that won’t happen. Why?

Tech Secretary Peter Kyle's defense?

"It would not be fair to one sector to privilege another."

Enforcing existing property law is now "privileging" creators over the companies taking their work?

Baroness Kidron nails it:

"It is extraordinary that the government's decided, immovable and strongly held position is that enforcing the law to prevent the theft of UK citizens' property is unfair to the sector doing the stealing."

The AI Patterns

Both sides of the Atlantic show how closely aligned governments and AI companies have become. In DC, it's not even subtle anymore.

Where do creators play this game? Will the US report survive?

Will we stand up like 48,000 in the UK?

If you're a creator, this isn't theoretical anymore. You don't have years to figure this out.

The rules are being written right now, with or without you.

Part 3: The Solution Exists – But Only if Companies Want to Pay

The pushback to forcing creators to opt-out individually? There's already a solution.

Meet Credtent CEO Eric Burgess, who's built exactly what the market needs – if AI companies want to play fair.

The AI model has been, data is free.

"It's not. And it's a total Silicon Valley thing.

Eric Schmidt outlined it last August at Stanford: steal, bring in the lawyers."

If governments force AI companies to pay for content, does that kill startups and only help the big players?

Credtent's Tiered Approach

Burgess has a different take:

• Startups get revenue sharing – "We can set them up with a revenue share opportunity, they can license early"

• Vertical companies pay by category – Only license what they need for specialized solutions

• Enterprise pays premium rates – Full access, full price

• Prices drop as scale grows – More creators joining = lower costs for everyone

AB-2013: The California Delete Act starts January 2026The Compliance Reality

AB 2013 passed here in California .

January 1st, 2026, AI companies are going to be required to disclose what content they've used for training. The EU has similar requirements.

Some AI companies claim they can't disclose training data because it's a "trade secret."

Credtent solves this: companies upload their training corpus, and the platform identifies what's licensable, public domain, or problematic.

AI Copyright Guardrails That Work

"We know guardrails are possible. If you say,

'I want to create a story like Stephen King,'

they're afraid of Stephen King because he has the means of hiring lawyers."

Burgess envisions a future where creators choose to get paid for AI using their style, or block it entirely.

Like James Earl Jones licensing his voice for future Darth Vader content before he died – "his family is now getting paid for AI use of his voice."

"You're taking value and extracting the value from that work and creating market replacements potentially."

Even bad AI-generated content hurts creators:

"All it has to do is make something similar that they can pay a little bit of money to have go higher up on the list of what's found on Amazon.

And guess what? They just hurt your book."

Any excuse that they had for saying it's going to be too hard to do licensing?

Credtent, and others, already solve that problem for you.

The infrastructure exists. The question is whether governments will force AI companies to use it – or keep writing laws that let them take whatever they want.

Part 4: The AI That Thinks Like You Do (Without Stealing Your Thoughts)

While governments debate letting AI companies raid everyone's content, Dr. Stephen Thaler built something completely different.

His DABUS system doesn't need your data because it thinks more like you think.

"When we talk to these chatbots online, we're looking at the cumulative opinion of many contractors," Thaler explains.

"It's not really sentience. It's not really conscious.

Nor is it really thinking for itself."

Current AI? It's human opinions filtered through human opinions.

No real emotion. No actual thought. Sophisticated pattern matching.

Thaler built two neural networks that literally argue with each other:

• The Generator creates a stream of potential ideas

• The Critic watches and gets frustrated when solutions don't emerge

• When frustrated, the critic injects more "disturbances" into the generator

"That looks like consciousness," Thaler realized.

"You have a stream of consciousness, a stream of ideas coming apparently from out of nowhere. And you also have a critic getting frustrated."

The Neurotransmitter Breakthrough

This mirrors how your brain works. Thaler discovered his system was replicating "global release" – when your brain floods itself with neurotransmitters during emotional states.

"There's nothing magical about a neurotransmitter.

It's a molecule that can either increase or decrease neural activity randomly, stochastically. And that's your noise."

That "noise"? It's emotion. It's the voice in your head that says "do something" before you consciously decide to act.

DABUS doesn't steal content to learn creativity. It generates emotion, gets frustrated, has eureka moments, and creates original ideas.

Because it's built like a brain, not a database.

While everyone fights over who owns training data, Thaler built AI that doesn't need it. The future of AI might not be about who can scrape the most content, but who can build the most human-like consciousness.

That voice in your head saying "wait, what if..." before you have a breakthrough?

DABUS has that too. And it didn't need to steal anyone's work to get it.

The AI Copyright Crossroads – Where Creators Make Their Stand

We're at a crossroads in AI. On one side: big tech and governments. On the other: everyone else.

This isn't just US and UK drama. Meta, Google – these international companies are working country by country to ensure "AI works for them." Makes sense from their perspective.

But here's their line:

OpenAI saying it can’t pay to the House of Lords in 2024

"We can't pay for content. We need too much. It would ruin AI."

Remember that UK politician?

"It's a privilege. You're asking for a privilege".

When creators want compensation for work that was clearly taken without permission.

The Poverty Bluff

AI companies plead poverty while sitting on tens of billions in funding, aiming for trillion-dollar valuations. This fair use bluff has bought them five years of free data since 2020.

The mask slipped in a Meta lawsuit. A director of engineering admitted: If we license one book, then we have to license them all and fair use is out the window.

The Two-Tier Reality

Disney gets licensing deals. Getty gets deals. Anyone with lawyers gets paid.

Everyone else? You get the opt-out lottery.

That is why Baroness Kidron is fighting this. That's why Shira Perlmutter is fighting for her job.

When the replacement doesn't even understand copyright, like this Department of Justice attorney with no domain experience, creators lose their voice.

The US Copyright Doc That Changes Everything (If they use it)

There's a US Copyright Office report sitting there that could literally change the AI industry because it leans towards compensating creators.

And nobody's listening. Nobody's talking.

What other industry openly takes what it wants, settles only with players who can afford lawyers, and claims it can't pay for the raw materials that built their entire business model?

The infrastructure exists. Credtent proved licensing can work at scale. Dr. Thaler showed AI doesn't need stolen content to be creative.

The legal frameworks are there.

But if creators don't stand up now – while these rules are being written – the window closes. The big players cut their deals. Everyone else gets crumbs.

The TikTok blueprint worked for startups. Now it's looking like a government policy.

The question isn't whether this system benefits AI companies – it obviously does.

The question is: do we want an AI future where only the biggest players get to participate?

Your move, creators. The blueprint's being written with or without you.

Taking advantage of AI before it takes advantage of you means understanding the game being played. These aren't accidents – they're strategies. What's your strategy?

LINKS FROM PODCAST

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Credtent.org

Eric Burgess - LinkedIn:

FAQ: Is AI training data a trade secret?

Copyright and Artificial Intelligence, Part 3: Generative AI Training Pre-Publication Version

Five Takeaways from the Copyright Office’s Controversial New AI Report

Matthew Clifford - UK AI Plan

Make it Fair UK Campaign

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Stephen Thaler is at:

Imagination Engines

LinkedIn:

Stephen Thaler’s Quest to Get His ‘Autonomous’ AI Legally Recognized Could Upend Copyright Law Forever

DABUS Wikipedia

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California Delete Act

AB-2013 Generative artificial intelligence: training data transparency.

OpenAI warns copyright crackdown could doom ChatGPT