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Ken Perry, Consultant in Risk and Quantamental Investing, CRO, formerly of Och Ziff - "Challenge for Finance: AI Interpretability."

 

 

 

 

 

 

 

Ken Perry’s Summary:

-          Artificial Intelligence (Deep Learning specifically) has transformed diverse areas such as computer vision, machine translation and health care. But these advances have come at a cost.

-          A defining feature of Deep Learning is that models are trained, not programmed imperatively. Fitting an unknown function using a large number of examples results in high accuracy (surpassing humans at some tasks) and low interpretability. Insight into how the inference was obtained is neither offered nor expected: deep learning model as black-box is the accepted norm. 

-          We sacrifice interpretability in the pursuit of accuracy at our own peril.  Our lack of understanding exposes us to risks such as AI Safety (harm caused by AI) and AI Security (deliberate efforts to “trick” AI).

-          How do we learn to trust that which we can’t explain ?

-          In this talk, we show that Deep Learning models don’t have to be opaque. We show steps toward interpretable Deep Learning that have been made in other domains (e.g., computer vision).   With this as inspiration, we challenge the Finance community to make their AI models interpretable.

 

Ken Perry’s Bio

-          Ken created the Risk department at Och Ziff and served as Chief Risk Officer for nearly 14 years. He defined the Risk Manager’s objective as being a proactive provider of insight into the portfolio, the markets and trader behavior,  not  as someone who measures and monitors in retrospect.  He pioneered the integration of quantitative techniques into the fundamental investing style, anticipating the “quantamental” revolution.  He now assists clients who are seeking to gently evolve along the quantamental path.

-          More recently, Ken has been actively involved in deepening the understanding of the proper role of Artificial Intelligence in Finance.

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