Steven Adler

Steven Adler

San Francisco, California, United States
5K followers 500+ connections

About

I'm a researcher focused on how to make AI go better. These days, the best place to…

Experience

  • Roots of Progress Institute Graphic
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    San Francisco, California, United States

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    San Francisco, California, United States

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    San Francisco, California, United States

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    San Francisco, CA

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    New York, New York

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    Boston, MA

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    Seattle, WA

Education

  • Brown University Graphic

    Brown University

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    Activities and Societies: Phi Beta Kappa

    Awarded the Samuel C. Lamport Prize for my honors thesis, "Price Discrimination and Consumer Taste for Fairness"​

    Select coursework:
    Applied Artificial Intelligence
    Intro to Algorithms and Data Structures
    Game Theory and Applications
    Economics of Creativity, Entrepreneurship, & Innovation
    Behavioral Economics
    Human Cognition
    Making Decisions (TA)

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Publications

  • What are you optimizing for? Aligning Recommender Systems with Human Values

    We describe cases where real recommender systems were modified in the service of various human values such as diversity, fairness, well-being, time well spent, and factual accuracy. From this we identify the current practice of values engineering: the creation of classifiers from human-created data with value-based labels. This has worked in practice for a variety of issues, but problems are addressed one at a time, and users and other stakeholders have seldom been involved. Instead, we look to…

    We describe cases where real recommender systems were modified in the service of various human values such as diversity, fairness, well-being, time well spent, and factual accuracy. From this we identify the current practice of values engineering: the creation of classifiers from human-created data with value-based labels. This has worked in practice for a variety of issues, but problems are addressed one at a time, and users and other stakeholders have seldom been involved. Instead, we look to AI alignment work for approaches that could learn complex values directly from stakeholders, and identify four major directions: useful measures of alignment, participatory design and operation, interactive value learning, and informed deliberative judgments.

    See publication
  • Report on Algorithmic Risk Assessment Tools in the U.S. Criminal Justice System

    Partnership on AI

    We prepared a report highlighting the shortcomings of algorithmic risk assessment tools today in the US (often used to detail people pre-trial) and 10 recommendations for standards these tools must meet prior to high-stakes usage.

    See publication
  • When Is It Appropriate to Publish High-Stakes AI Research?

    Partnership on AI

    We wrote up a light framework of considerations when publishing high-stakes research, informed by a simulation event with our partners and a preliminary survey of their views.

    See publication
  • What AI can and can't do (yet) for your business

    McKinsey Quarterly

    Our team surveyed today's AI landscape to identify AI's current limitations; the business problems that become solvable once those limitations are addressed; and the emerging techniques driving progress within them. I conducted and synthesized 20+ expert interviews with CEOs, professors, post-doc researchers, and others in the AI community to identify said techniques, their business applications, and their limitations.

    See publication

Projects

  • Project Euler - top 10% problem-solver

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    Project Euler is a series of programming challenges in which people write code to solve complex mathematical puzzles. I rank in the top 10% of the site's all-time problem-solvers (750K people total), having completed ~50 of the site's challenges.

    See project

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