• Graduate program
  • Research
  • Summer School
  • Events
    • Summer School
      • Sustainable Finance
      • Applied Public Policy Evaluation
      • Economics of Blockchain and Digital Currencies
      • Economics of Climate Change
      • Foundations of Machine Learning with Applications in Python
      • From preference to choice: The Economic Theory of Decision-Making
      • Gender in Society
      • Business Data Science Summer School Program
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • 16th Tinbergen Institute Annual Conference
    • Annual Tinbergen Institute Conference
  • News
  • Alumni
  • Magazine
Home | Events Archive | S.A.F.E. Artificial intelligence
Seminar

S.A.F.E. Artificial intelligence

  • Series
    TI Complexity in Economics Seminars
  • Speaker(s)
    Paolo Giudici (University of Pavia and European University Institute, Italy)
  • Field
    Data Science and Econometrics
  • Location
    University of Amsterdam, Roeterseilandcampus, E5.22
    Amsterdam
  • Date and time

    November 20, 2024
    12:00 - 13:00

Abstract

The growth of Artificial Intelligence applications requires to develop risk management models that can balance opportunities with risks. We contribute to the development of AI risk management models proposing a set of integrated statistical metrics that can measure the Sustainability, Accuracy, Fairness and Explainability of any Artificial Intelligence application. Our metrics are consistent with each other, as they are all derived from a common underlying statistical methodology: the Lorenz curve. Our experimental results indicates that they are are easy to interpret, and that they can be applied to any machine learning method, regardless of the underlying data and model.