“Humans, Data and Machines” was the 2018 theme of the annual public lecture series put on by the University of Arizona College of Science. As in past years, the ASA is sponsoring encore presentations of the talks for those who missed the original lectures.

Machine learning (ML) is becoming pervasive in society, powering many applications from recommending music, movies and merchandise to driving our cars to assisting in medical diagnoses. Our daily interactions, behavior, and choices, whether we are aware of them or not, are the sources of data for training these systems.

But how are these ML-based platforms built and utilized? While ML-based platforms create amazing opportunities, especially when coupled with advances in cloud computing, reliance on these platforms comes with ethical, security, and technical concerns.

In this third encore presentation of “Humans, Data and Machines,” the 2018 University of Arizona College of Science public lecture series, Nirav Merchant will discuss these concerns in a live lecture set to begin at 3:30 p.m. Wednesday (May 9) in the ASA Great Room.

Merchant’s talk, “Working Alongside Thinking Machines,” will describe how we can strike a balance for enabling pragmatic and productive use of the capabilities made possible by machine learning. ML-powered platforms are gaining proficiency and becoming deeply integrated into existing and emerging automation across many domains of science and society, Merchant notes, causing a shift in opportunities impacting many professions. Merchant will discuss some of the new learning and training opportunities that allow us to stay relevant and lead the way for future innovations.

Nirav Merchant

Merchant is director of the UA Data Science Institute (Data7). He received his undergraduate degree in industrial engineering from the University of Pune, India, and a graduate degree in systems and industrial engineering from the University of Arizona in 1994.

 Over the last two decades his research has been directed towards developing scalable platforms for supporting open science and open innovation. His interests include large-scale data management platforms, data delivery technologies, managed sensor and mobile platforms for health interventions, workforce development, and project based learning.

Written by Mike Maharry, Academy Village Volunteer

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Working Alongside Thinking Machines: May 2018