GoKawiilSotheby's uses algorithms built by MIT alum to predict art auction prices
Kelly Shen, an MIT graduate from the class of 2017, works in Sotheby's art intelligence division, where she designs algorithms that forecast auction prices based on buyer trends and artist popularity. Her work also includes cataloguing art pieces and building real-time systems capable of handling thousands of simultaneous bidders on the auction house's website.
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This reflects a broader shift in the traditionally relationship-driven art market toward data-driven decision-making, as auction houses seek competitive advantages through predictive analytics. It also highlights how technical talent from institutions like MIT is increasingly finding roles in industries not traditionally associated with computer science, blending quantitative rigor with creative markets.
- Sotheby's employs data science to forecast art auction prices using buying trends and artist popularity metrics.
- MIT alum Kelly Shen's role spans algorithm development, cataloguing, and scaling systems for high-traffic bidding events.
- The art market is increasingly incorporating technology and predictive analytics traditionally used in other financial sectors.
Sotheby's: The Art of the Deal (book) — If the intersection of algorithms and the auction block fascinates you, a book on the inner workings of Sotheby's is a great companion read. It gives context on how the art market prices masterpieces "the old way" — the very trends data scientists like Kelly Shen now model.
See Sotheby's: The Art of the Deal (book) on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.Source: technologyreview.com — Kara Baskin, 2026-08-25
Published there as: “Art and algorithms at Sotheby’s”
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