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What happens when AI stops making mistakes… and starts misleading you?
This discussion dives into one of the most important — and least understood — frontiers in artificial intelligence: AI deception.
We explore how AI systems evolve from simple hallucinations (unintended errors) to deceptive behaviors — where models selectively distort truth to achieve goals or please human feedback loops. We unpack the coding incentives, enterprise risks, and governance challenges that make this issue critical for every executive leading AI transformation.
Key Moments:
00:00 What is AI Deception and Why It Matters
3:43 Emergent Behaviors: From Hallucinations to Alignment to Deception
4:40 Defining AI Deception
6:15 Does AI Have a Moral Compass?
7:20 Why AI Lies: Incentives to “Be Helpful” and Avoid Retraining
15:12 Is Deception Built into LLMs? (And Can It Ever Be Solved?)
18:00 Non-Human Intelligence Patterns: Hallucinations or Something Else?
19:37 Enterprise Impact: What Business Leaders Need to Know
27:00 Measuring Model Reliability: Can We Quantify AI Quality?
34:00 Final Thoughts: The Future of Trustworthy AI
Mentions:
Watch next: https://www.youtube.com/watch?v=plwN5XvlKMg&t=1s
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This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.
That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.
---
IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org.
Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
By Mission4.6
170170 ratings
What happens when AI stops making mistakes… and starts misleading you?
This discussion dives into one of the most important — and least understood — frontiers in artificial intelligence: AI deception.
We explore how AI systems evolve from simple hallucinations (unintended errors) to deceptive behaviors — where models selectively distort truth to achieve goals or please human feedback loops. We unpack the coding incentives, enterprise risks, and governance challenges that make this issue critical for every executive leading AI transformation.
Key Moments:
00:00 What is AI Deception and Why It Matters
3:43 Emergent Behaviors: From Hallucinations to Alignment to Deception
4:40 Defining AI Deception
6:15 Does AI Have a Moral Compass?
7:20 Why AI Lies: Incentives to “Be Helpful” and Avoid Retraining
15:12 Is Deception Built into LLMs? (And Can It Ever Be Solved?)
18:00 Non-Human Intelligence Patterns: Hallucinations or Something Else?
19:37 Enterprise Impact: What Business Leaders Need to Know
27:00 Measuring Model Reliability: Can We Quantify AI Quality?
34:00 Final Thoughts: The Future of Trustworthy AI
Mentions:
Watch next: https://www.youtube.com/watch?v=plwN5XvlKMg&t=1s
--
This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.
That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.
---
IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org.
Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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