In this episode...

Tim and Tally sit down to tackle one of the most requested topics on The Boring AI Show: AI governance. While governance may sound like a dry policy conversation, the episode quickly turns into a practical discussion about trust, risk, responsibility, and what it really takes to bring AI into an organization without creating avoidable surprises.

The episode starts with AI news stories that set up the broader theme. From AI literacy efforts in education to a brand mishap involving AI-generated marketing, Tim and Tally explore why organizations need more than enthusiasm when adopting AI. They need shared rules, clear expectations, and a thoughtful understanding of where AI fits into their culture, values, and daily work.

The conversation covers what AI governance actually means, why it should not be treated as only an IT or legal issue, and how companies can begin building guardrails that are realistic for where they are today. Tim and Tally also discuss the risks of moving too fast, from reputational damage and workforce mistrust to shadow AI, data exposure, and tools evolving faster than policies can keep up.

Throughout the episode, one theme keeps resurfacing: good AI governance is not about slowing innovation down. It is about helping people use AI with more confidence, more clarity, and more accountability, so organizations can move forward without losing sight of quality, trust, and human judgment.

Topics Covered

What AI governance means in practical terms
Why governance is more than policy
AI guardrails and avoiding bad surprises
AI literacy for students, teachers, parents, and communities
Human review for AI-generated marketing and public content
Reputational risk, legal risk, financial risk, and workforce trust
Shadow AI and tools already being used inside organizations
Building an AI-forward team or steering committee
Starting small with governance instead of overbuilding too early
Model inventories and approved AI tool lists
Data classification and acceptable use
Policies, procedures, standards, and guidelines
Use case intake and review workflows
AI wearables, recording, consent, and workplace expectations
Using AI for creative work, slide generation, and brainstorming

Resources

Articles and News Mentioned

AI Literacy Framework for Primary and Secondary Education
REI got roasted for a nonsensical Instagram ad featuring a bike with 2 sets of handlebars and blamed a Meta AI tool
EU AI Act
Gamestorming: 7Ps Framework
TechCrunch: Humane’s AI Pin is dead, as HP buys startup’s assets for $116M

Organizations Mentioned

Mind Over Machines
OECD
European Commission
Code.org
REI Co-op
Meta
Microsoft
Anthropic
OpenAI
Google
Adobe
ElevenLabs
Higgsfield AI
Humane
HP

Tools and Technologies Mentioned

Meta AI
Microsoft Copilot
Copilot in PowerPoint
PowerPoint Agents in Microsoft 365 Copilot
ChatGPT
Claude
Adobe Firefly
Higgsfield AI
ElevenLabs
Ray-Ban Meta AI Glasses
Google Maps
Google Street View

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In this mini episode...

Tim and Tally wrap up The Boring AI Show’s AI for Good Global Summit mini-series with one final recap from the week.

The conversation gives listeners a taste of the summit’s closing themes, from education and human connection to global governance, authenticity, and the long-term choices organizations face as AI continues to evolve.

Rather than covering every session, Tim and Tally reflect on the ideas that felt most useful for business leaders, teams, and everyday AI users trying to make sense of where this technology is heading.

Throughout the episode, one theme comes through clearly: the future of AI will be shaped not only by what the tools can do, but by the values, questions, and people guiding how they are used.

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In this mini episode...

Tim and Tally return for another AI for Good Global Summit recap, this time reflecting on a day that brought a slightly different tone to the global AI conversation.

The episode gives listeners a quick look at some of the themes emerging from the summit, including creativity, trust, responsibility, and the relationship between AI and human expression.

Rather than trying to cover every session, Tim and Tally focus on the ideas that felt most relevant for organizations, creators, and everyday AI users trying to understand where this technology is headed.

Throughout the episode, one theme keeps resurfacing: AI is not just changing what people can make. It is also pushing us to think more carefully about ownership, consent, creativity, and the human role behind the work.

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In this mini episode...

Tim and Tally kick off The Boring AI Show’s AI for Good Global Summit mini-series with a quick first recap from the event.

The conversation gives listeners a taste of the major themes emerging from the summit, from responsible AI and global collaboration to trust, values, and the role people play in shaping what comes next.

Rather than trying to cover everything, Tim and Tally highlight the ideas that stood out most and connect them back to the practical questions organizations should be asking as AI continues to evolve.

Throughout the episode, one theme comes through clearly: the future of AI is not just about better technology. It is about the choices people, communities, and organizations make together.

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In this special announcement...

The Boring AI Show is interrupting its regularly scheduled programming for something a little different: a mini-series covering the AI for Good Global Summit.

Next week, Tim and Tally will be following the summit virtually each day and bringing listeners quick, practical recaps of the biggest themes, takeaways, and conversations. The summit brings together global voices around one big question: how can AI be developed and used responsibly to help solve real-world challenges?

This mini-series will break down the major ideas coming out of the event, from responsible AI and sustainable development to policy, governance, and what organizations should be paying attention to next.

Tune in next week as The Boring AI Show does what it does best: taking a huge, important AI topic and making it useful, approachable, and a little less boring.

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In this episode...

Tally is joined by Nicholas Detorie and Jared Jones from Mind Over Machines to explore what it means to start a software development career in the age of AI. With Tim out for this episode, the conversation focuses on the next generation of workers: AI can make learning, building, and experimenting more accessible, but it does not replace fundamentals, judgment, or accountability.

The episode starts with a few AI news stories that set up a broader discussion about trust, risk, and real-world adoption. From there, Nicholas and Jared join Tally to talk about how AI is changing the way developers learn, work, and think through problems, especially for people entering technical fields today.

The conversation covers the benefits and risks of AI-assisted learning, why strong fundamentals still matter, and how managers can support newer workers who are already used to having AI in the workflow. Along the way, the group shares practical examples of AI as a coding partner, learning tool, coach, and reviewer.

Throughout the episode, one theme keeps resurfacing: AI can help people move faster and try things they might not have attempted before, but the strongest results still come from pairing AI with human judgment, clear quality standards, and the willingness to learn what is happening underneath the output.

Topics Covered

• Starting a software development career in the age of AI
• How AI changes the learning curve for new developers
• Why AI can lower barriers to entry for technical work
• The difference between using AI to learn and using AI as a crutch
• Why programming fundamentals still matter
• Stack Overflow, GeeksforGeeks, and how developers learned before AI
• Developer trust and distrust in AI coding tools
• Why AI-generated code still needs human review
• Human-in-the-loop workflows for developers and AI tools
• Vibe coding and the risk of hidden technical debt
• Inflated confidence when AI helps with unfamiliar skills
• Knowing when to involve an expert
• AI safety, jailbreaks, and model governance
• Export controls and dependency on frontier AI models
• Business continuity risks when an AI model is suddenly unavailable
• AI in agriculture, including robotic milking and laser weeding
• Using AI as a coach, thought partner, and reviewer
• How managers can support AI-native junior workers
• Balancing speed, quality, mentorship, and accountability
• Using AI to maintain consistency across client-facing project materials
• Building an e-ink AI news dashboard with RSS feeds and LLM ranking
• Using ChatGPT for soccer tactics and formation planning

Resources

Articles and News Mentioned

• Anthropic pulls Claude Mythos 5 and Claude Fable 5 following US government directive
• Inside the whirlwind 24 hours that led the White House to slap export controls on Anthropic
• Forbes: Anthropic Pulls Fable, Mythos After Government Issues Emergency Export Control Order
• New York Times: From Cow-Milking Robots to Weed-Zapping Lasers, Farmers Are Embracing A.I.
• Stack Overflow 2025 Developer Survey: AI
• Stack Overflow Blog: Developers remain willing but reluctant to use AI
• MDN: RSS
• FIFA World Cup 2026

Organizations Mentioned

• Mind Over Machines
• Anthropic
• Amazon
• Stack Overflow
• The New York Times
• Seeed Studio
• GeeksforGeeks
• FIFA

Tools and Technologies Mentioned

• Claude
• Claude Fable 5
• Claude Mythos 5
• ChatGPT
• Stack Overflow
• GeeksforGeeks
• Seeed Studio reTerminal E1001

Thanks for listening! Visit us at @mindovermachines.com to learn more about us!
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In this episode...

Tim and Tally sit down with Brent Paugh, Business Intelligence Manager at Mind Over Machines, to dig into the data layer behind AI. The conversation centers on a practical truth that shows up again and again across healthcare, business intelligence, automation, and everyday AI use: AI is only as useful as the context, data, governance, and human judgment surrounding it.

The episode starts with a pair of AI news stories that set up a broader discussion about the relationship between AI, data, and human expertise. From there, Brent joins Tim and Tally to explore what it takes to make AI useful inside organizations, including data quality, business context, governance, and trust.

The conversation covers why AI struggles without shared definitions and structured information, how organizations can think about security and access when deploying AI tools, and where human judgment still plays a critical role. Along the way, the group shares practical examples of AI in action, from analytics and synthetic data to knowledge management and content creation.

Throughout the episode, one theme keeps resurfacing: successful AI initiatives depend on more than the technology itself. The strongest results come when AI is paired with well-managed data, clear business context, and thoughtful human oversight.

Topics Covered

• What “clean data” means in practice
• Why AI needs business context, not just access to data
• Structured versus unstructured data
• Why humans still need to define terms like customer, revenue, region, and inventory
• The importance of semantic models for BI and AI
• Using AI with dashboards and trusted business metrics
• Why AI outputs need expert validation
• Cognitive laziness and the risk of over-trusting AI
• Data classification, restricted data, sensitive data, PII, PHI, and HIPAA considerations
• AI connectors and the danger of unfettered system access
• Using synthetic data to protect private information
• Predictive analytics, machine learning, and early cancer detection
• The baseball statistics example: clean domain data plus human expertise
• AI-readable communication, including headings and structured documents
• AI slide generation across Copilot, NotebookLM, and Miro
• Claude agent swarms and Dynamic Workflows for large knowledge-graph updates
• Using AI as a thought partner and role-based reviewer

Resources

Articles and News Mentioned

• AI for Good: AI and the Future of Inclusive Mental Health Care
• AI for Good Global Summit 2025
• Mayo Clinic: AI Detects Pancreatic Cancer Up to 3 Years Before Diagnosis in Landmark Validation Study
• Forbes: Samsung Bans ChatGPT and Other Chatbots for Employees After Sensitive Code Leak
• CIO Dive: Samsung Employees Leaked Corporate Data in ChatGPT

Organizations Mentioned

• AI for Good
• International Health Charity Association
• Mayo Clinic

Tools Mentioned

• GameChanger
• Claude Opus 4.8
• Claude
• ChatGPT
• Microsoft Copilot
• Copilot in PowerPoint
• Google Gemini
• NotebookLM
• Miro Sidekicks
• Perplexity
• Redgate SQL Data Generator

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In this episode...

Tim and Tally sit down with Jessy Jordan, professor of philosophy at Mount St. Mary's University in Emmitsburg, Maryland, to dig into what AI is doing to critical thinking. The conversation starts with discussion around the Pope's first encyclical, Magnifica Humanitas. Jessy pulls out the three things that matter most: a moral vision centered on human dignity, a pointed warning about AI monopolies and the danger of leaving transformative technology in the hands of a very few.

Then Jessy takes the conversation into the trenches of university education. He describes the university as an intellectual gym and explains why students who outsource their cognitive work to AI aren't just cutting corners on a paper, they're skipping the reps that build judgment, structure, and confidence in their own competence. Tim connects that to what he's seeing in the workforce too, where experienced professionals are accepting AI outputs without validation and people who have been doing their jobs for years are hitting the easy button without ever checking what came out the other side.

Topics Covered

• The Pope's encyclical Magnifica Humanitas and what it says about AI
• AI monopolies and who controls transformative technology
• The IKEA chatbot example: automation paired with reskilling
• What a university education is actually for
• The university as an intellectual gym
• Cognitive offloading and what students lose when AI does the thinking
• Why generalists are going to be in high demand
• Using AI as a thinking partner without losing slow reflection
• Practical AI use cases: summarization, audio tools, and slide creation

Resources

Articles and News Mentioned

• Pope Leo XIV's Encyclical: Magnifica Humanitas
• Time: Pope Leo Uses First Major Papal Text to Warn About Dangers of AI
• PBS NewsHour: Pope Calls for Robust Regulation of AI
• Fortune: Barnes & Noble CEO Clarifies Stance on AI-Generated Books
• PYMNTS: IKEA Turned 8,500 Call Agents Into Design Consultants
• Mississippi Statewide AI Framework

People and Organizations Mentioned

• Jessy Jordan, Ph.D. — Mount St. Mary's University
• Algorithmic Justice League
• Mind Over Machines Resources

Tools Mentioned

• ElevenReader by ElevenLabs
• Miro

Thanks for listening! Visit us at @mindovermachines.com to learn more about us!
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In this episode...

Tim and Tally talk about the AI for Humanity event, hosted at The Towson University College of Liberal Arts. The idea for the event was simple: give liberal arts students - those who normally don't get the first say in tech - the opportunity to shape the future. Tim and Tally recap the various group teams that presented their solutions to a modern AI problem in a hypothetical scenario. 

The conversation explores how AI governance spans from a technical problem to a social problem. Tim and Tally discuss the different approaches student teams took, including ethics-first frameworks, impacted-population governance, stage-gate review processes, and even a critical anti-AI perspective.

The episode also features interview clips from students, faculty, and professionals answering the question: “What advice would you give to business professionals just starting to use AI?”

Topics Covered

•  AI governance as a liberal arts challenge 
•  Towson University’s AI for Humanity event 
•  Responsible AI policies and human-in-the-loop review 
•  Ethics-first AI governance 
•  Impacted-population governance 
•  Stage-gate review processes for AI use 
•  Whether every problem actually needs AI 
•  Building AI tools with affected communities, not just for them 
•  AI as a collaborator, not a competitor 
•  Practical advice for business professionals starting to use AI 
•  Using AI carefully without treating it as an answer machine 
•  Practical AI use cases for learning, organization, dashboards, and workflow support 

Resources

Event Sponsors

• Baker Donelson
• APWU Health Plan
• The Coca-Cola Company
• Maryland Technology Council

Event Links

• Towson University: Students Develop Solutions for Responsible AI Use
• CLA AI for Humanity Competition
• Towson StarTUp at the Armory
• WMAR: Towson University Hosts AI for Humanity Challenge
• Mind Over Machines Resources

Articles and News Mentioned

• Gates Foundation: Making AI Work for More People
• Anthropic: Gates Foundation Partnership
• Reuters: Anthropic and Gates Foundation Launch $200 Million Partnership
• Reuters: Elon Musk Loses Lawsuit Against OpenAI
• Arnold’s Pump Club: This Is Your Brain on AI

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AI is getting weirder, more useful, and more consequential all at the same time and that's exactly why we wanted a clear, grounded conversation about what's coming next. Tim and Tally start with what's been grabbing our attention lately, from a looming governance event with Towson University to a reminder that AI systems can pick up odd patterns and biases (yes, "goblins" and "gremlins" included) through the data and feedback we give them. 

From there, we get practical about the future of work and enterprise AI adoption. We talk about why many organizations will feel "AI disillusionment" after big spending and scattered Copilot rollouts that never connect to a real use case. The fix is not more hype, it's better measurement and better change management: define metrics that matter, look beyond time savings, and build a culture where people can use AI without fear of being judged for "shortcutting" their work. Along the way we tie AI back to purpose and core competency, because roles and meaning don't disappear just because tasks get automated. 

Then we dig into MIT Tech Review's "AI things that matter right now," including agent orchestration (think an AI assembly line of specialized agents), artificial scientists, open source models and vendor transparency, world models that move beyond text into simulated environments, and humanoid data that raises real privacy, consent, and labor questions. We also name the cultural backlash and resistance we expect to keep growing, and why that pushback can be healthy if it leads to more responsible AI governance and ethics. If you're trying to understand AI trends in 2026 without the noise, hit subscribe, share this with a teammate, and leave a review. What's the one AI trend you're most excited or worried about right now?

Links:

2026 10 Things That Matter in AI Right Now | MIT Technology Review

Where the goblins came from | OpenAI

Mouse Heaven or Mouse Hell? (Calhoun's Universe 25) | Science History Institute

World Labs (Fei-Fei Li's spatial intelligence company)

Ghost Work by Mary L. Gray and Siddharth Suri

A Roomba recorded a woman on the toilet | MIT Technology Review

Measure What Matters by John Doerr (the OKR book)

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