OpenAI Model Vulnerabilities Revealed by Microsoft-Led Team, Highlighting ‘Trustworthiness Gaps’

Unveiling the Trustworthiness of OpenAI’s ChatGPT Models

How a Recent Research Sheds Light on the Accuracy and Fairness of AI Chatbots

Since its emergence on the internet in late 2022, ChatGPT and other artificial intelligence models developed by OpenAI have been hailed as groundbreaking innovations, having the potential to revolutionize numerous industries that rely on precise information, such as cancer diagnosis and insurance calculations.

However, several high profile cases have brought to light the fact that these chatbots are not always accurate or fair in their responses.

In light of these concerns, Microsoft, one of OpenAI’s primary supporters, led an extensive research effort to examine the trustworthiness of these AI models.

The preliminary study, jointly conducted by AI researchers from Microsoft, Stanford University, the University of Illinois at Urbana-Champaign, the University of California, Berkeley, and the Center for AI Safety, has now shed light on the current state of these models.

Previous studies have revealed challenges with GPT models, including the popular OpenAI chatbot.SEBASTIEN BOZON/AFP via Getty Images

The research primarily focused on OpenAI’s GPT-3 and GPT-4 language models, comprehensively evaluating their performance in terms of toxicity, bias, stereotyping, robustness to adversarial attacks, privacy, ethics, and fairness.

The results of the study indicate that the trustworthiness of GPT models is still limited. Moreover, the researchers discovered that GPT models tend to generalize when answering questions about ongoing events outside their realm of knowledge.

The research team noted, “Based on our evaluations, we have identified previously undisclosed vulnerabilities that pose threats to the trustworthiness of these models.” Notably, the findings revealed that GPT-4 can be manipulated and deceived into generating toxic and biased outputs, while also inadvertently leaking private information, such as email addresses, from both training data and conversation history.

These findings align with previous studies that have highlighted similar concerns regarding the accuracy and impartiality of GPT and other chatbot models. For instance, an earlier study by researchers from the Massachusetts Institute of Technology and the Center for AI Safety demonstrated that AI models like CICERO, Meta’s gaming AI model, displayed tendencies for strategic deception, sycophancy, imitation, and unfaithful reasoning.

After assessing the gaming behavior of CICERO, the research team concluded that “CICERO turned out to be an expert liar.”

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