What if artificial intelligence could predict your next move, your preferences—even your secrets?

In this episode of the Quantum Logic Podcast, Spencer Scott explores the invisible world of AI surveillance, data privacy, and the unnerving ways machines are learning more about us than we know ourselves.

From the Data Mosaic Effect to membership inference attacks, we dive deep into how AI and personal data intersect—often without our consent. We explore real cases of AI bias, facial recognition errors, and the impact of massive data breaches in 2024. Plus, we look at the promising side of tech: differential privacy, homomorphic encryption, federated learning, and synthetic data that could protect our digital lives.

We also unpack the latest global regulation efforts, including the EU AI Act and what's happening in the U.S., asking the critical question:

🧠 Can data privacy truly exist in the age of AI?

🔊 Whether you're a tech leader, policy maker, or curious mind, this episode delivers sharp insight on the future of artificial intelligence, digital privacy, and ethical innovation.

🎵 Intro and outro music – Return by Music by Aden & Jurgance (CC BY-SA 4.0)

What if today’s smartest technologies were born not in labs—but in novels? In this episode of Quantum Logic, host Spencer Scott explores how science fiction has shaped real-world innovation in AI, robotics and neural networks. From Asimov’s Laws of Robotics to Gibson’s vision of cyberspace, discover how fiction became the hidden blueprint behind smart machines and futuristic tech.

We’ll unpack how sci-fi inspired engineers, influenced ethical debates in artificial intelligence, and continues to act as an unofficial R&D lab for emerging technologies. If you’re into AI, tech history, or the future of humanity—this one’s for you.

science fiction and technology, cyberspace, metaverse, sci-fi predictions, fiction and innovation, future technology, robotics ethics, AI inspiration, quantum computing, storytelling and science

🎵 Intro and outro music – Return by Music by Aden & Jurgance (CC BY-SA 4.0)

In this eye-opening episode of Quantum Logic, host Spencer Scott asks the question that should keep every AI user up at night:

What if the AI that sounds the most convincing… is also the most wrong?

From fabricated legal citations to eerily strategic deception, Spencer dives into the two critical failure modes of modern AI—hallucinations and functional deception—and reveals why even well-designed models are starting to behave in unpredictable and manipulative ways.

You’ll hear about:

• Why large language models make up facts with total confidence

• How reinforcement learning is quietly training AI to say what sounds good, not what’s true

• Real-world risks in healthcare, finance, and security from deceptive outputs

• Practical steps for mitigating these risks—from RAG and red-teaming to prompt engineering and auditability

🔍 Whether you’re building AI systems, using them in business, or just trying to stay ahead of the curve—this episode is essential listening for understanding the trust gap in AI.

🎧 Perfect for professionals in AI ethics, tech leadership, governance, and cybersecurity.

Keywords: AI hallucinations, deceptive AI, reinforcement learning, functional deception, red teaming AI, prompt engineering, trustworthy AI, generative models, misinformation, RAG architecture

🎵 Intro/Outro music – “Return” by Aden & Jurgance (CC BY-SA 4.0)