Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Constantinos Daskalakis, MIT + David Eisenbud, MSRI - Reducing AI Bias Using Truncated Statistics - H2O World 2019 NYC


Published on

This session was recorded in NYC on October 22nd, 2019 and can be viewed here:

Reducing AI Bias Using Truncated Statistics
An emergent threat to the practical use of machine learning is the presence of bias in the data used to train models. Biased training data can result in models which make incorrect or disproportionately correct decisions, or that reinforce the injustices reflected in their training data. For example, recent works have shown that semantics derived automatically from text corpora contain human biases, and found that the accuracy of face and gender recognition systems are systematically lower for people of color and women. While the root causes of AI bias are difficult to pin down, a common cause of bias is the violation of the pervasive assumption that the data used to train models are unbiased samples of an underlying “test distribution,” which represents the conditions that the trained model will encounter in the future.  Overcoming the bias introduced by the discrepancy between train and test distributions has been the focus of a long line of research in truncated Statistics. We provide computationally and statistically efficient algorithms for truncated density estimation and truncated linear, logistic and probit regression in high dimensions, through a general, practical framework based on Stochastic Gradient Descent.  We illustrate the efficacy of our framework through several experiments.

Bio: David Eisenbud served as Director of MSRI from 1997 to 2007, and began a new term in 2013. He received his PhD in mathematics in 1970 at the University of Chicago under Saunders MacLane and Chris Robson, and was on the faculty at Brandeis University before coming to Berkeley, where he became Professor of Mathematics in 1997. He served from 2009 to 2011 as Director for Mathematics and the Physical Sciences at the Simons Foundation, and is currently on the Board of Directors of the Foundation. He has been a visiting professor at Harvard, Bonn, and Paris. Eisenbud’s mathematical interests range widely over commutative and non-commutative algebra, algebraic geometry, topology, and computer methods.
Eisenbud is Chair of the Editorial Board of the Algebra and Number Theory journal, which he helped found in 2006, and serves on the Board of the Journal of Software for Algebra and Geometry, as well as Springer-Verlag’s book series Algorithms and Computation in Mathematics.
Eisenbud was President of the American Mathematical Society from 2003 to 2005. He is a Director of Math for America, a foundation devoted to improving mathematics teaching. He has been a member of the Board of Mathematical Sciences and their Applications of the National Research Council, and is a member of the U.S. National Committee of the International Mathematical Union. In 2006, Eisenbud was elected a Fellow of the American Academy of Arts and Sciences.

Published in: Technology
  • Be the first to comment

  • Be the first to like this

Constantinos Daskalakis, MIT + David Eisenbud, MSRI - Reducing AI Bias Using Truncated Statistics - H2O World 2019 NYC

  1. 1. Collaborative Research at the Frontiers David Eisenbud Director MSRI
  2. 2. 17 GAUSS WAY, BERKELEY, CALIFORNIA WWW.MSRI.ORG Collaborative research at the frontiers
  3. 3. What Distinguishes MSRI? Exceptional Breadth of Scientific Activity • MSRI programs span every aspect of fundamental mathematics and many applications resulting from the latest discoveries of advanced research • MSRI is a center where new fields are born (MSRI was among the first to recognize Random Matrix Theory as a significant field), and where classical topics such as symplectic geometry can have a major revival. • We connect mathematicians and math educators through workshops on “Critical Issues in K-12 Education” 3
  4. 4. What Distinguishes MSRI? A place where young talent flourishes • MSRI is a place where young talent is mentored, where careers are developed, and where underrepresented groups are empowered • Summer Graduate Schools include strong contact between students and leaders • Groundbreaking, sustained programs empowering women and minorities (MSRI- UP, SWiM, ADJOINT, Connections workshops...) 4
  5. 5. What Distinguishes MSRI? MSRI is supported by the whole Math Community • A network of 110 “Academic Sponsor” institutions – from the US and abroad share in governance • Impeccable advisors such as Dusa MacDuff, Fields Medalists Charlie Fefferman, Andrei Okounkov, Terry Tao (Board members and program organizers) and a rotating Scientific Advisory Committee (SAC) help us reach into all parts of fundamental mathematics 5
  6. 6. What Distinguishes MSRI? MSRI is a pioneer in international engagement • Increases connections between US researchers and the international community • In 2020, MSRI partnered with universities in Australia, Canada, China, England, Greece, and Switzerland on Summer Graduate Schools in emerging areas, using non-NSF funds and international support. • Co-founders of the Banff International Research Station (BIRS) and Casa Matemática Oaxaca (CMO), where MSRI remains a full partner in governance and in scientific interactions 6
  7. 7. What Distinguishes MSRI? Public Understanding of Mathematics • Congressional Briefings 2x/year • Numberphile—most popular informal math channel on YouTube: over 3M subscribers, 450M ”views” ( • Films, such as Navajo Math Circles, and Secrets of the Surface, the Mathematical Vision of Maryam Mirzakhani • National Math Festival • Mathical Books—a prize for children’s literature related to mathematics 7
  8. 8. • To formalize and facilitate the flow of information between the corporate world and MSRI we have developed a corporate partnership program. • Corporate members may choose from three tiers depending on the level of interaction and sponsorship desired. • Custom sponsorship and individualized packages are also available. 8 Corporate Partners Program
  9. 9. Corporate Partners Program Investing in new mathematics and in people
  10. 10. Tier 1 $150,000/year • MSRI-UP nonacademic employment opportunities information session (lunch or dinner) • Two at large nonacademic employment opportunities information sessions at MSRI • Invitation to the Academic Sponsors and MSRI Board of Trustees evening (Spring) • Invitations to Museion (distinguished donor) events • Recognition on MSRI website • Desk available for corporate research use at MSRI 10 Corporate Partners Program
  11. 11. Tier 2 $300,000/year • All of the Tier 1 benefits plus: – Named postdoc – Principal program sponsor recognition and participation opportunities for one semester-long program – Prominent sponsor recognition for all workshops 11 Corporate Partners Program
  12. 12. Tier 3 $500,000/year • All of the Tier 2 benefits plus: – Named research professor or 2 named postdocs – Prominent sponsor recognition for MSRI summer schools 12 Corporate Partners Program
  13. 13. Mathematical themes for current and future Programs • Analysis and Mathematical Physics: Programs 1, 2, 3, 4, 7, 9 • Number Theory: Programs 5,6,10 • Dynamical Systems and Fluid Mechanics: Programs 7,8,9 • Probability: Programs 5,8,11 • Economics: Program 11 • Quantum Mechanics: Programs 1 and 3 • What Mathematics will be useful next?? 13 Corporate Partners Program
  14. 14. For Reference: Current and future MSRI Programs: 1. Holomorphic Differentials in Mathematics and Physics (Fall 2019) 2. Microlocal Analysis (Fall 2019) 3. Quantum Symmetries (Spring 2020) 4. Higher Categories and Categorification (Spring 2020) 5. Random and Arithmetic Structures in Topology (Fall 2020) 6. Decidability, Definability and Computability in Number Theory (Fall 2020) 7. Mathematical Problems in Fluid Dynamics (Spring 2021) 8. Universality and Integrability in Random Matrix Theory and Interacting Particle Systems (Fall 2021) 9. Complex Dynamics: from Special Families to Natural Generalizations in one and Several Variables (Spring 2022) 10. Algebraic Cycles, L-Values, and Euler Systems (Spring 2023) 11. Mathematics and Computer Science of Market and Mechanism Design (Fall 2023) 14 Corporate Partners Program
  15. 15. 17 GAUSS WAY, BERKELEY, CALIFORNIA WWW.MSRI.ORG From MSRI… The view is global!