Zach Lipton, Assistant Professor, Machine Learning Department at Carnegie Mellon University
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Zach Lipton

Assistant Professor, Machine Learning Department
Carnegie Mellon University

Conference Day Two: March 20 2019

Tuesday, March 19th, 2019

4:15 PM Panel discussion: Understanding, managing and effectively mitigating the hidden risks associated with AI

  • The risks of the person behind the AI/model: how to remove bias?
  • Coping with tail risks
  • Can you ever model all circumstances in an undefinable and constantly moving market?
  • How can AI measure a risk it hasn’t seen yet?
  • Balancing the compliance and risk demands of creating human understanding of complex models 
  • Overfitting: Have you applied diversification in your quant strategies? A variety of asset classes? Appropriate algorithm choices?
  • Would a failure of model or liquidity mean you have inappropriate risk management in place?

4:55 PM The critical issues of interpretability: understanding what it really means?

  • Underspecified and unclear: have you appropriately defined your model and the properties it satisfies?
  • Understanding causal structure: validating the decisions your machine made
  • Resilience and robustness: The importance of factoring in domain adaptation and distribution shift
  • Anomaly detection: quantifying and actively compensating by modifying your beliefs and constraints

Check out the incredible speaker line-up to see who will be joining Zach.

Download The Latest Agenda