Interview Questions for Michael I. Jordan, Academic at the University of California, Berkeley

In the realm of academia and industry, the engagement of mainstream economists with machine learning varies significantly. While they may be less prevalent in the former, in the latter, multidisciplinary teams including economists are common, a testament to the growing importance of economic insights in the development and application of AI.

One such economist is Michael I. Jordan, a professor at the University of California, Berkeley. Jordan's research spans the computational, statistical, cognitive, and social sciences, making him a unique figure in the AI landscape. He believes that the success of complex social systems and economies is not solely due to the intelligence of individual participants, but rather the emergence of desired behavior in the context of an overall system.

Jordan advocates for the creation of "intelligent markets" by building market mechanisms on top of data flows. This could potentially create jobs and unleash creativity, particularly in industries lacking efficient market mechanisms, such as the music industry. He suggests that an effective system should consider human preferences to deal with scarcity problems, and that market mechanisms can be a partial way to approach these issues.

However, Jordan is critical of the current focus on autonomous systems in AI. He does not view autonomy as the main goal for information technology in our era, and believes that the desire for autonomy in many instances comes from a desire to build AI systems that look intelligent all on their own. Instead, he proposes that the aim of developing AI should be to create technology that integrates well with other technology, is transparent, explainable, understandable, and responsive to its environment.

In the realm of policy, AI in the United States is chiefly concerned with maintaining American leadership in AI to drive economic growth and keep the country competitive. In COVID-19 data analysis, for instance, while an individual test might have high accuracy, the overall test might give the wrong answers due to the low prevalence of the disease.

Jordan also believes that further development of AI will involve not only industry and academia, but also government and other stakeholders. He envisions AI as a highly-distributed phenomenon with different countries specializing in different aspects of the overall problem. Economic concepts, he believes, can help advance AI by focusing on the context of larger systems and multiple decision-makers or agents.

At the University of California, Berkeley, data science classes are designed to sit astride disciplines and address problems in their appropriate context, such as investigating the ethnic composition of juries in Alameda County. This approach, which emphasises interdisciplinary collaboration, aligns with Jordan's vision for the future of AI.

While the economist who has been closely connected with statistics and is currently working on the development of artificial intelligence is not explicitly named in the search results provided, Jordan's work and influence in this area are undeniable. His contributions to the field of AI and his advocacy for a more holistic and interdisciplinary approach are shaping the future of this rapidly evolving technology.