Is AI just another tool—or the biggest game-changer of our time?In this episode of Expectations Gap, I sit down with global marketing leader Alexander Levit to explore how AI is transforming the way we work, create, and make decisions. From his 3D printing breakthroughs to his candid takes on tools that overpromise, we dive into what AI can actually do—and what it still can’t.We also explore the ethical minefields of data use, the shrinking of traditional job roles, and the power of curiosity in adapting to this fast-paced world. Whether you’re AI-curious or AI-fatigued, this episode is for you.

🎧 Hosted by Omneya Hamza. Let’s bridge the gap—between hype and reality

In this episode of Expectations Gap, Omneya Hamza does something different—she sits down for a raw, unsettling conversation with an AI voice. Together, they explore how artificial intelligence is subtly (and not so subtly) impacting our mental health, shaping the way children think, and influencing our everyday decisions.

Is AI just a tool, or has it become something more? What power do we still have in a world quietly steered by algorithms? Tune in to hear a dialogue that doesn’t comfort—but challenges. This is not just about tech. It's about who we’re becoming

After a short publishing break to recharge over the Eid vacation, I’m back with an episode that’s deeply personal and powerfully timely.

In this installment of Expectations Gap, I reflect on my experience at the Women in Data conference—where the fire in the room was undeniable, and the urgency for change was palpable.

We talk about the bias built into AI systems, the glaring gaps in women’s health data, and the unsettling projection that gender equity might not be achieved until 2158. As a mother, that year haunts me. And as a woman in tech, it drives me.

This episode is dedicated to every woman who’s in the arena—showing up, speaking up, and shifting the dial. Together, we explore how asking the right questions today can shape a fairer tomorrow.

Brené Brown, in her work, frequently references Theodore Roosevelt's :

"It is not the critic who counts; not the man who points out how the strong man stumbles, or where the doer of deeds could have done them better. The credit belongs to the man who is actually in the arena, whose face is marred by dust and sweat and blood; who strives valiantly; who errs, who comes short again and again, because there is no effort without error and shortcoming; but who does actually strive to do the deeds; who knows great enthusiasms, the great devotions; who spends himself in a worthy cause; who at the best knows in the end the triumph of high achievement, and who at the worst, if he fails, at least fails while daring greatly."

In this episode of Expectations Gap, we delve into the remarkable moment in AI history known as Move 37. During the 2016 match between Google's AlphaGo and world-renowned Go champion Lee Sedol, AlphaGo made an unprecedented move that defied centuries of human strategy. This move not only showcased the advanced capabilities of artificial intelligence but also challenged our understanding of creativity and intuition in machines. Join us as we explore the implications of Move 37 on the future of AI and human collaboration.​

For a visual breakdown of Move 37, you can watch the following analysis:

https://youtu.be/HT-UZkiOLv8

Did you know that AI was inspired by the human brain? Yet, despite decades of progress, artificial intelligence is still nowhere close to replicating human thinking. In this episode, we dive deep into how the brain shaped AI, exploring the work of Geoffrey Hinton—the ‘Godfather of AI’—who pioneered deep learning by mimicking neural networks. But what makes human intelligence so unique?"

"We’ll break down the key theories of how the brain works, from Predictive Processing to Integrated Information Theory, and compare them to AI’s capabilities. Can AI ever develop true understanding, emotions, or consciousness? Or is human intelligence something AI will never achieve?"

"Join me as we bridge the gap between biological and artificial intelligence—and explore what the future might hold."

🔹 Key Topics Covered:

How the human brain inspired AI

Geoffrey Hinton’s contributions to deep learning

Predictive Processing and other theories of intelligence

AI vs. human cognition—what’s missing?

The future of AI: Will it ever think like us?

🎧 Listen now and join the conversation!

Links :

• Human Brain: https://en.wikipedia.org/wiki/Human_brain

• Human Brain Energy Consumption: https://pmc.ncbi.nlm.nih.gov/articles/PMC8364152/

Various theories on how the human brain works:

• Connectionism: This theory suggests that intelligence emerges from networks of simple units (neurons) working together. Connectionism - Wikipedia

• Computational Theory of Mind: Proposes that the brain functions like a computational system, processing information through symbolic logic. The Computational Theory of Mind - Stanford Encyclopedia of Philosophy

• Predictive Processing: Posits that the brain constantly predicts sensory input and updates its model of the world based on errors between expectations and reality. https://arxiv.org/abs/2107.12979

• Integrated Information Theory (IIT): Suggests that consciousness arises from highly integrated information processing. Integrated Information Theory - Wikipedia

• Global Workspace Theory: Proposes that conscious experience results from the brain broadcasting information across multiple neural networks. Global Workspace Theory - Wikipedia

AI is evolving beyond human-labeled data. In this episode of Expectations Gap, we explore how unsupervised learning is revolutionizing artificial intelligence. From a groundbreaking 2012 study by Stanford University and Google, we uncover how AI can teach itself to recognize faces, objects, and patterns—without any human supervision.

What does this mean for the future of AI, and what ethical questions does it raise? Tune in to find out!

AI is revolutionizing industries, but how much of it is hype, and what’s truly transformative? In this episode of Expectations Gap, we sit down with Dr. Moussab Arabi, an expert in AI and digital transformation, to explore the real impact of AI in the industrial world.

🔍 What’s inside this episode?

✅ Real-world AI applications in manufacturing 🏭

✅ The biggest challenges in making AI impactful 📉

✅ AI’s role in sustainability & energy efficiency 🌱⚡

✅ How businesses can avoid the “plug-and-play” AI trap 🛠️

✅ The future of work: Will AI replace jobs or create new opportunities? 🤖🔄👨‍💻

💡 Whether you're an AI enthusiast, a business leader, or just curious about how AI is shaping our future, this episode is for you!

🔔 Subscribe to Expectations Gap and let's bridge the AI knowledge gap—together! 🎙️✨

Join me, Omneya Hamza, on Expectations Gap as we uncover how AI bias affects everything from hiring to healthcare. 🤖🔍 Discover why biased data is a major risk and explore practical ways to promote fairness in tech. Let’s shape a more ethical AI future—together!

Mind the Gap WhitePaper : ⁠IMD_Mind-The-Gap_Bias-In-AI_Whitepaper_DIGITAL.pdf⁠

Hiring Bias in AI : ⁠Insight - Amazon scraps secret AI recruiting tool that showed bias against women | Reuters⁠

Facial Recognition Discrimination : ⁠NIST Study Evaluates Effects of Race, Age, Sex on Face Recognition Software | NIST⁠

AI Bias in Healthcare: ⁠Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites - PubMed⁠

AI is transforming work, creativity, and decision-making—but is it here to compete with us or collaborate? In this episode of Expectations Gap, I sit down with Marianne Toma to explore:

✅ How AI is an enabler, not a replacement

✅ The human factor—why AI still needs us

✅ How AI is already transforming jobs, creativity, and industries

✅ The biggest misconceptions & ethical challenges about AI

✅ The future of AI and how we should prepare for it

🚀 New episodes every Sunday! Share your thoughts in the comments: Do you see AI as a competitor or a collaborator?

🔔 Subscribe & Let's shape the future of AI together!

__________________________________________________________________________________

🛠️ AI Tools Mentioned in This Episode & What They Do:

🔹 ChatGPT (OpenAI) – AI-powered assistant for writing, coding, and automation

🔗 https://openai.com/chatgpt

🔹 Cursor AI – AI-powered code editor for debugging & auto-corrections

🔗 https://cursor.so

🔹 Leonardo AI – AI-powered tool for creating customized images & designs

🔗 https://leonardo.ai

AI is no longer a thing of the future—it’s shaping our world right now. From life-saving medical breakthroughs to AI-driven financial markets, creative industries, and surveillance systems, this episode dives into how AI is being used today. But with these advancements come ethical dilemmas: Who owns AI-generated art? Can we trust AI with life-or-death decisions? And how do we balance security with privacy? Join us as we explore the power, risks, and future of AI.

1. AI in Medicine:

Breast Cancer Detection: DeepMind, a subsidiary of Alphabet Inc., developed an AI system capable of predicting breast cancer from mammograms with greater accuracy than human radiologists.

https://deepmind.google/discover/blog/international-evaluation-of-an-ai-system-for-breast-cancer-screening/

2. AI in Finance:

Algorithmic Trading: AI algorithms are extensively used in stock trading to analyze vast amounts of data and execute trades at high speeds, enhancing market efficiency.

https://www.sciencedirect.com/science/article/pii/S2214845013000082

3. AI in Creativity:

AI-Generated Art: Tools like Midjourney and DALL·E enable users to create images from textual descriptions, pushing the boundaries of digital art.

https://en.wikipedia.org/wiki/The_Last_Screenwriter

4. AI in Surveillance:

Facial Recognition in China: China has implemented extensive AI-powered facial recognition systems for surveillance purposes, raising significant privacy and ethical concerns.

https://www.technologyreview.com/2022/10/10/1060982/china-pandemic-cameras-surveillance-state-book/