What happens when artificial intelligence goes head-to-head with real lawyers?
In this mind-bending episode, we explore the legal battle of the century: AI vs Human Lawyer. From courtroom showdowns to drafting complex contracts in seconds, we unpack the real potential — and real risks — of AI in the legal world.

Some topics we explored are:

• Whether AI can out-argue a human in court
• How AI is reshaping law firms, legal media, and ethics
• What legal jobs might disappear (and what new ones will rise)
• Real-world legal tasks: Should AI or a human do them?

If you're a lawyer, law student, tech enthusiast, or just curious about how AI is shaking up one of the oldest professions on earth, this episode is for you.

🔔 Follow for bold conversations at the intersection of law, tech, and the future of work.

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📖 Pre-order my book "AI, Machine Learning, Deep Learning: From Novice to Pro" here: https://a.co/d/dmZ7FXJ.

In Part I, we explored how a simple neural network could tell a Bulldog from a German Shepherd just by analyzing images.

In Part II, we go deeper into the mechanics of deep learning.

You'll learn how cost functions, the chain rule, gradient descent, backpropagation, and forward passes help artificial neural networks learn and improve accuracy.

We break it down step-by-step with real-world examples, making it simple to understand how machines "think" and "learn" through constant adjustment.

Topics in this episode:

• How neural networks start with random weights and biases
• What the cost function measures
• How the chain rule helps identify errors
• How gradient descent improves predictions
• What happens during backpropagation and forward passes

Perfect for visual learners and curious minds interested in AI, machine learning, and deep learning.

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📖 Pre-order my book "AI, Machine Learning, Deep Learning: From Novice to Pro" here: https://a.co/d/igaehTZ

In this video, I break down how deep learning works in a simple, beginner-friendly way. You’ll learn the basics of neural networks, how they process data through layers, the role of weights, bias, and the popular ReLU activation function.

Perfect if you're new to AI, machine learning, or just want a visual, no-fluff explanation of how these systems learn and make decisions.

Please follow for more easy-to-digest AI concepts.

📱 Connect with me on LinkedIn: https://www.linkedin.com/in/tolulope-awoyomi/

📱 Follow me on X: https://x.com/TolulopeAwoyomi

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You can pre-order my book "AI, Machine Learning, Deep learning: From Novice to Pro" here - https://a.co/d/igaehTZ.

In this video, I break down how AI and machine learning actually work — especially in response to a surprising claim I reacted to in a previous video: that AI is a “demon” or “fallen angel.”

This is a simplified overview meant to help you understand the real process behind AI — no fear-mongering, no mysticism, just real talk on algorithms, data, and learning systems.

If you’ve ever been confused about how AI or machine learning functions, this video is for you.

Preorder my new book:

"AI, Machine Learning, Deep Learning: From Novice to Pro"

Available now on Amazon → https://a.co/d/6vLYEIH

In this episode of Everything AI and Law, Tolulope sits down with Monica D. Higgins to talk about something that's becoming more and more urgent: when AI messes up—who’s to blame?

From biased algorithms to deepfakes, from legal personhood to job loss fears—this conversation goes deep. Monica shares honest, practical insights from her work at Future Proof, where she helps companies and individuals make AI useful and actually make sense in the real world. It’s smart, eye-opening, and packed with gems—whether you’re into tech, law, or just trying to figure out where you fit in the AI age.

🧭 Timestamps & Topics:

00:00 – The biggest ethical blind spot in AI adoption
02:00 – OpenAI’s Sora & systemic bias in AI-generated content
04:56 – Should AI be granted legal personhood?
07:58 – Rights vs. responsibilities: Who is truly accountable?
09:09 – Agentic AI: Excitement, fear & future implications
10:05 – Upskilling: The antidote to AI-induced job displacement
12:30 – How Future Proof designs role-specific AI training
14:37 – Deepfakes: Real concerns in a synthetic world
17:03 – A universal code of ethics for AI?
18:33 – Transparency, bias & the ethics checklist
19:13 – AI companionship: Support or silent danger?
21:02 – Negligence & product liability in AI deployment
23:00 – Should AI liability be a new legal category?
23:53 – AI in hiring: The case for algorithmic bias audits
24:49 – Should agency be granted to AI?
25:09 – What’s next for Future Proof & AI innovation
27:35 – Final thoughts: Upskilling, value, and the future of work
28:50 – Monica’s vision: “Let technology live up to its hype”

Connect with Monica D. Higgins & FuturProof:
🔗 LinkedIn
🌐 FuturProof Website

Connect with Tolulope Awoyomi (Host):
🔗 LinkedIn

🔗 Twitter

Like what you heard? Hit subscribe, leave a rating/review, and share it with someone who needs to hear this.

Tag us with your thoughts using #EverythingAIAndLaw

AI isn't just replacing jobs — it's creating entirely new ones.
In this video, we explore 24 exciting jobs emerging from the rise of artificial intelligence — split into technical and non-technical roles.

Whether you're a coder, a creative, or just curious about where the world is headed, this video will open your eyes to the career opportunities of tomorrow.

Now is the time to adapt, learn, and thrive in the AI era.

🎙️ Hit follow to stay updated on tech, AI, and the future of work.

It's well known that AI cannot exist without data. However, we need to balance this as sensitive information shouldn't be exposed.

In this video, I show you two simple ways to protect your data from being used to retrain AI models like ChatGPT.

As a technologist, I understand that AI depends on data and that these models need continuous improvement. At the same time, as a lawyer, I recognize the privacy risks AI presents—especially when it comes to personal and confidential data that must be protected.

While this video focuses on ChatGPT, the same concerns apply to other AI tools. Even if you don’t use ChatGPT or have a paid plan, it’s important to understand the risks of sharing sensitive data with AI models—it could be used to retrain them.

Think of it this way: 

Entering sensitive data into an AI tool is like posting your private information on the open internet. Once it’s out there, you have little control over where it might end up.

So what can you do?

• Opt out of AI training when possible.
• De-identify your data before sharing.
• Read the privacy policies—yes, they’re long, but they matter.

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Follow for more AI insights. 

Want the latest AI news, breakthroughs, and policy updates in one place? Tune in every Monday for a quick yet deep dive into the biggest AI developments from the past week.

What’s Inside?

• AI Innovations – The latest models, tools, and research shaping the future.
• AI Laws & Regulations – Key government policies and legal shifts.
• Industry Updates – Startups, acquisitions, and big tech strategies.
• Ethical Debates & AI Controversies – The impact of AI on jobs, privacy, and society.

New Episodes Every Monday! Hit Follow so you never miss an update!

Join the Conversation:
💬 What’s your take on this week’s AI news? Share your thoughts!
⭐ Follow & Rate to stay ahead of the AI curve!

Thinking about using AI but don’t know where to start? In this episode, I’ll walk you through five easy ways to access AI models and begin leveraging artificial intelligence in your projects, business, or everyday life.

Follow the podcast for more AI insights!

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📌 Pre-order AI, Machine Learning, Deep Learning: From Novice to Pro

Pre-order AI, Machine Learning, Deep Learning: From Novice to Pro.