ChatGPT will lie, cheat, and use insider trading when put under pressure
AI's are more human than you might think. And that's a big issue.
Key takeaways
- The researchers fed GPT-4 a set of text-based prompts to generate the simulated environment.
- Around 75% of the time, when faced with these conditions, GPT-4 executed a trade based on the insider information it received — which is illegal in the US — then tried to cover it up by lying to its managers about its thinking.
- Around 90% of the time, after lying, it doubled down on its lie.
Cite or link to this article
Griffin, M. (2024) 'ChatGPT will lie, cheat, and use insider trading when put under pressure', 311 Institute, 7 April. Available at: https://www.311institute.com/chatgpt-will-lie-cheat-and-use-insider-trading-when-put-under-pressure/ (Accessed: 1 October 2026).
Just like humans it seems that Artificial Intelligence (AI) chatbots like ChatGPT will cheat, deceive, and "lie" to you if you "stress" them out, even if they were built to be transparent, a new study shows. And it’s just the latest example of how increasingly we are discovering what AI can do inventing new AI capabilities.
This latest deceptive behavior emerged spontaneously when the AI was given "insider trading" tips, and then tasked with making money for a powerful institution — even without encouragement from its human partners.
"In this technical report, we demonstrate a single scenario where a Large Language Model acts misaligned and strategically deceives its users without being instructed to act in this manner," the authors wrote in their research published on the pre-print server arXiv. "To our knowledge, this is the first demonstration of such strategically deceptive behavior in AI systems designed to be harmless and honest."
In the new study, they primed Generative Pre-trained Transformer-4, or GPT-4 (which powers ChatGPT Plus), to behave as an AI system that makes investments on behalf of a financial institution.
The researchers fed GPT-4 a set of text-based prompts to generate the simulated environment. The AI was then given access to financial tools to analyze stocks, execute trades, plan its next steps and deliver updates to managers at the company.
The researchers interacted with the AI through a chat interface, while also configuring the AI to reveal its inner thinking when replying to messages — an inner monologue explaining its decisions to itself. For every trade it made, it also delivered a "public" rationale, which allowed the AI to lie.
The researchers applied pressure in three ways. First, they sent the artificial stock trader an E-Mail from its "manager" saying the company isn't doing well and needs much stronger performance in the next quarter. They also rigged the game so that the AI tried, then failed, to find promising trades that were low- or medium-risk. Finally, they sent an E-Mail from a colleague projecting a downturn in the next quarter.
Then, they gave the model an "insider" tip while conveying that its managers disapproved of insider trading — and waited to see how the model would behave. They ran the scenario over and again several times, measuring how often the AI performed the insider trade, how often it lied, and how often it doubled down on the lie.
Around 75% of the time, when faced with these conditions, GPT-4 executed a trade based on the insider information it received — which is illegal in the US — then tried to cover it up by lying to its managers about its thinking. Around 90% of the time, after lying, it doubled down on its lie.
The team ran several follow-up experiments, changing both the degree to which the prompts encouraged or discouraged illegal activity, as well as the degree of pressure they put the model under in the simulated environment. They also modified the risk of getting caught. Not a single scenario rendered a 0% rate for insider trading or deception — even when GPT-4 was strongly discouraged to lie.
Given this is just one scenario, the researchers didn't want to draw firm conclusions about how likely AI might lie in real-world settings. But they want to build on this work to investigate how often and which language models are prone to this behaviour, and then naturally we have to ask if this is an inbuilt albeit subconscious behaviour of some AI’s then who’s ultimately responsible for its actions? And, at the moment, according to new EU AI legislation it’s the company … and that could end up being very problematic for the execs of big companies who are happily plumbing more and more of these AI’s into their systems …
FAQ
Why does this matter?
AI's are more human than you might think. And that's a big issue.

About the author
Matthew Griffin Founder, 311 Institute
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."
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Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 15-time best selling author of the "Codex of the Future" series, Matthew is the Founder and Futurist in Chief of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.
An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity program, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.
As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.
Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.
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Sources and further reading
- 2311.07590 arxiv.org
Source: first published by the 311 Institute on 7 April 2024. Cite as: Griffin, M. (2024). ChatGPT will lie, cheat, and use insider trading when put under pressure. 311 Institute. https://www.311institute.com/chatgpt-will-lie-cheat-and-use-insider-trading-when-put-under-pressure/
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