JPM Distinguished Lecture Series in AI, Tuesday, October 29, 2020

Abstract

Data-driven approaches have led to powerful prediction, optimization and automation techniques.  Powered by large-scale, networked computer systems and machine learning algorithms, these have been very impactful to-date and hold great promise in many disciplines, in finance, but even the humanities.  However, no new technology arrives without complications, and we have recently seen the press and various political circles illustrating real, potential, and fictional implications of Big Data.

This presentation aims to balance the opportunities provided by Data Science and its associated artificial intelligence techniques with a discussion of the various challenges that have ensued. I review eleven types of challenges, including those which are technical (resilience and complexity), societal (difficulties in setting objective functions or understanding causation), and humanist (issues relating to free will or privacy). I build on my experiences in finance and big technology, show example problems, and suggest ways to address some of the unanticipated consequences of Big Data. 

PDF Slides of Holistic View of Data Science

I wrote a quick thought piece on the opportunities and perils of using cell-phone location tracing to both understand and limit the spread the Novel Coronavirus.  See the Recent Material, under the Material menu, to find it.

This is the September 2019, University of Pittsburgh update of a talk I first gave in November 2014.  The files contain both Google slides and a PDF, but no transcript.   See the Recent Material, under the Material menu, to find it.

I’ve finished editing a version of this recent talk that I’ve been giving on some university campuses, and it’s now posted.  The files contain both the slides and a transcript.   See the Recent Material, under the Material menu, to find it.

I am inaugurating my self-publishing website, www.azs-services.com today, January 1, 2017.