Bias & Trust in AI

AI & Data Science in Trading

Seth Adler

The bulk of the AI  & Data Science in Trading program focuses on maximizing margins and discovering competitive edge. But there are two sessions of note, which highlight key hurdles to accomplishing any goal through artificial intelligence:

Artificial Intelligence Bias

The Bias in AI panel brings together leaders from IBM, Bloomberg, the University of Oxford and others to uncover that which you’re doing wrong of which you cannot conceive.

Artificial Intelligence Trust

The Trust in AI sessions opens up the conversation around interpretability. It will be interesting to discover if the session covers the veracity of artificial intelligence technology as opposed to the delineation of information about the asset.

As the event says:

"The world of Capital Markets is changing. Soon there will be no room for traditional players without digital capabilities – markets will become increasingly efficient and the margin pool will shrink.  Being the first to deploy a winning strategy from a particular data set (or group of data sets) requires asset managers to learn, build and master the latest computing techniques."

Register for AI & Data Science in Trading

Agenda Highlights:

Bias in AI

Pavan Arora Former Chief Data Officer & Director IBM Watson 
Peter Jackson Director, Group Data Science Legal & General 
Gary Kazantsev Head of Quant Technology Strategy, Office of the CTO Bloomberg 
Mariarosaria Taddeo Deputy Director, Digital Ethics Lab University of Oxford 
Anthony Ledford Chief Scientist Man AHL 


Trust in AI

Afsheen Afshar Former Chief Artificial Intelligence Officer and Senior Managing Director Cerberus Capital Management 

Trust and interpretability are vital in allowing asset allocators to increase investment in AI driven funds.  What are the latest developments, and how can you separate the claims from the facts.