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At the main forum of the 2024 Inclusion Bund Conference, Michael Jordan emphasized three key points missing from the current discussions on artificial intelligence: collectivity, uncertainty, and incentive mechanisms. He pointed out that AI systems need to form collaborative collectives and introduce an economic perspective on incentives to build collaborative systems. He noted that AI performs inadequately when facing uncertainty and that humanity's ability to cope with uncertainty through collective collaboration is worth emulating. To enhance the collective collaboration capability of AI systems, Michael Jordan suggested constructing a 'three-layer data market' model.

Former Trump lawyer Michael Cohen admitted to citing fake AI-generated cases in court documents. He used Google's Bard for legal research, mistakenly regarding it as a 'super search engine' rather than an AI chatbot. The three cases cited in the court documents do not actually exist. Cohen stated there was no intention to mislead the court and acknowledged his lack of understanding of AI legal technology. Previously, two lawyers in New York faced sanctions and fines for including fake cases generated by ChatGPT in legal documents.

Michael Jordan believes that current large models still need to improve in quantifying uncertainty and providing measures of certainty in predictions. Large models also lack a healthy economic incentive structure to trace and reward those who provide answers. Michael Jordan had two epiphanies in his career, one in statistics and the other in microeconomics, which influenced his expectations for large models. He believes that solving social problems requires considering issues from a systemic and collective perspective, not just enhancing individual models. Governments and foundations should not only support large corporations.