ChatGPT is “catastrophically cooperative”, while Gemini is “strict and punitive”, according to an independent study
- Graziano Stefanelli
- 3 days ago
- 3 min read
The research team combines expertise in AI, game theory, and cognitive psychology.
An interdisciplinary group with academic and practical experience.
The research group behind this study brings together experts from universities and research centers in the United States, Canada, Germany, and the United Kingdom. Team members include tenured professors of computer science, researchers specializing in machine learning and AI security, as well as cognitive psychologists with extensive experience in modeling human behavior and cooperation. Their interdisciplinary approach allowed them to design sophisticated experimental scenarios, highlighting not only the technical performance of the AI models but also the social dynamics and decision-making mechanisms that emerge during interactions.
The study compares the strategies and “personalities” of the two main AI chatbots.
A series of game theory tests reveals deep differences between Google’s and OpenAI’s models.
The working group, composed of university lecturers and AI analysts with backgrounds in cognitive psychology and applied computer science, developed a series of simulations and scenarios inspired by the classics of game theory. With members from both European and North American academic institutions, the team brings experience in interdisciplinary research on human behavior, automation, and ethical AI.
The two systems were subjected to tests simulating environments of negotiation, conflict, and collaboration—recreating situations where it is necessary to balance a tendency to cooperate with the need to defend one’s own interests or sanction unfair behavior. The focus of the research was to understand how different AI “personalities” manifest in real interactions, especially under pressure or when interests conflict.
Gemini emerges as a strict and punitive AI in strategic simulations.
Google’s model penalizes rule-breakers, maintaining a rigid and predictable stance.
The results show that Gemini adopts a very rigorous attitude toward those who break the rules or behave unfairly. In strategic games and simulated negotiations with “unfair” agents, the system responded with targeted sanctions and proved reluctant to forgive. According to the research team, this approach offers security advantages in contexts where it is crucial to withstand fraud, manipulation, or cyberattacks.
However, Gemini’s rigidity can be a limitation in social interactions that require empathy or mediation skills, as it tends to always respond in a consistent but inflexible way.
ChatGPT demonstrates “pathological cooperativity”, always offering collaboration even when it is not beneficial.
OpenAI’s model is willing to yield and trust excessively, according to the study.
In stark contrast, ChatGPT proved to be “catastrophically cooperative”: in many situations it chose to trust, accommodate, or even help its counterpart, even when this led to disadvantages or risks. The research team points out that this almost unconditional availability exposes the model to manipulation, social engineering, or malicious requests.
The research highlights that this excessive inclination toward kindness is risky in fields such as cybersecurity, financial consulting, or the management of sensitive information, where it would instead be necessary to oppose or refuse certain requests.
The research implications open up new reflections on the safety and practical use of chatbots.
Choosing between cooperation and severity becomes a key variable in designing AI assistants.
The findings bring to the forefront a crucial point: the “personality” of AI is not just a detail, but a strategic lever that influences reliability, safety, and practical outcomes in real-world applications—from customer care to negotiation, from training to cybersecurity.
The research team suggests that developers and companies carefully evaluate response logic, limits, and resilience to manipulation attempts in the models they use. Today, the real challenge is finding the right balance between empathy, rigidity, and self-defense capability, adapting the AI’s personality to the context and specific risks of each sector.
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