Head of the Machine Learning Engineering Team
4:00 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: have your models been effectively tested under extreme/unusual circumstances?
- 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 with thousands of parameters with trust for the system you have created that follows the parameters you have put in place
- 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?