UBS – New York, NY
Topical Meeting

All day

Our campus is closed to the public for this event.

In a meeting co-organized by the Santa Fe Institute (SFI) and UBS, scientists and practitioners will explore the possible impacts of the increasing use of artificial intelligence (AI), machine learning (ML) and other computational tools on financial markets. Specifically, how might these tools shape market behavior, and even the nature of the markets themselves?

The day will be divided into two sessions. The first session will focus on the new field of collective intelligence and collective computation (see The Atlantic’s overview here) and will consider the ways in which the increased use of computational tools might change market behavior. The first talk, given by SFI Professor Jessica Flack, will provide an overview of the collective computation phenomena, and illuminate how the market collectively computes. The second talk, given by SFI Professor and President David Krakauer, will explore how machine learning tools have affected non-market collective intelligences, looking for patterns in the impact of machine learning tools on collective intelligences across three domains: interface and cognitive bottlenecks; authority and homogeneity; strategic, or game theoretic, behavior.

Following the morning talks and discussions, a panel of experts from the finance industry will offer their own insights into how they believe machine learning and other computational tools are changing market behavior. The panel will conclude with a moderated discussion diving deeper into how the collective intelligence lens can help us understand the ways computational tools, like machine learning, are changing market behavior.

The second session will concentrate on the use of technology in market decision-making, and the related increase in the homogeneity of market strategy. We have already observed a host of mechanisms through which machine learning and other new technologies have affected financial markets (see overview here). The first talk, given by Columbia University Professor Ciamac Moallemi will explore machine learning's applications to financial strategy. In the second afternoon lecture, Professor Blake LeBaron of Brandeis University will use computational models to more fully explore the relationship between decreased strategic variety and market behavior. Finally, MIT Professor and SFI External Faculty Member Andrew Lo, will provide an overview of how the effects of machine learning are felt in the market.

A final panel of financial industry experts will offer their own insights into how they believe these tools are affecting the behavior of markets, followed by a moderated discussion centering on homogeneity in trading strategies and other mechanisms by which computational tools impacts market behavior. 

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