AI & Ethics: What Kind of Society Do We Want to Have?

With Inmar Givoni, Anna Goldenberg, Karen Bennet & Hessie Jones


AI is accelerating its pace and with it, bringing us incredible benefits… but also vulnerabilities to individuals and society, real and yet to be revealed. This panel will discuss how AI has dramatically improved convenience, access to information, communication and expectations for everyone and society at large. But are we, as humans, slowly ceding control to the machines we’ve programmed? How will AI change the way we think about how our information is used in exchange for the things we want?

In conjunction with Girl Geeks Toronto, we created a panel discussion to learn more about this topic from the perspective of people who deal with data everyday and through AI understand the opportunities, but also the dangers as AI begins to unfold.

THE PANEL:

Moderated by Hessie Jones, Co-Founder of Salsa AI and contributor for Towards Data Science and Cognitive World knowledge hubs. Salsa AI is non profit organization that is building a platform that brings Artificial Intelligence to everyone by developing an open source AI research and development platform. This is for anyone seeking to rapidly innovate by generating insights, automating manual processes, and unlocking unstructured data. Hessie's grounding has been in database marketing and has been in digital for last the two decades, launching Yahoo! Answers in Canada, and working for various startups in contextual video, social intelligence, profiling and customer journey analytics. She is a digital strategist, published author, writer for various marketing and tech publications and is also an educator in digital transformation leveraging advanced insights from big data and machine learning.

Inmar Givoni - Autonomy Engineering Manager at Uber Advanced Technologies Group

Inmar leads a team of research and software engineers at Uber Advanced Technology Group, Toronto, working on self-driving technologies. Her mission is to bring cutting-edge deep-learning based solutions from the Toronto research team into Uber's self driving fleet. Inmar led machine learning and research engineering team in various Toronto based companies (Kindred, Kobo), worked as a research scientist (Kobo, Intel, Microsoft Research) and prior to that completed her PhD at the University of Toronto, specializing in machine learning. She is a regular speaker at big data, analytics, and machine learning events, and is particularly interested in outreach activities for young women, encouraging them to choose technical career paths.

Karen Bennet - VP Engineering at new Startup (stealth)

Karen is an experienced senior engineering leader with more than 25 years in the software development business in both open and closed source solutions. She is currently focusing on AI / machine learning at a new startup company. Previously she worked as a senior engineering leader at IBM, Yahoo, Trapeze and as well with two startups: Cygnus and Red Hat which have grown into sustainable businesses.

Anna Goldenberg - Member of the Vector Institute, Assistant Professor at the University of Toronto Department of Computer Science, and Scientist at the Genetics and Genome Biology Lab at SickKids Research Institute

Anna is an Assistant Professor of Computer Science and a key scientist in the Genetics and Genome Biology Lab at Sick Kids Research Institute. Her research focuses on high-throughput experiments that facilitate data collection. In her laboratory, she works on creating machine learning methods that make such data useful for clinical diagnosis. Her goal is to use machine learning to decipher human disease heterogeneity. Anna earned both her Ph.D. in Computational and Statistical Learning and Masters in Knowledge Discovery & Data Mining at Carnegie Mellon University.

Many thanks for the Social Producers for producing this video

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