Summit Overview: Artificial Intelligence (AI) is the hot buzz of today. While AI promises the potential to improve business processes and operational efficiency, simplify user interactions, as well as help companies identify new revenue stream, much challenges are still ahead. Adam Lashinsky wrote, in his article, Cast a Critical Eye Over the A.I. Hype Merchants, published in the Fortune magazine, the Feb. 2019 edition, “artificial intelligence has the potential to transform business. But the key to utilizing it will be realizing its limitation, otherwise, it would become another extremely expensive and elusive money pit”
IEEE WIE AI Summit Chicago would like to provide a forum to women students, researchers, teachers, engineers and leaders as well as disruptors to share their unique point of views on AI through real life projects and experiences, discuss lessons learned, identify its challenges and limitations, collaborate on critical skills needed to accelerate the industry movement.
Event: IEEE Women in Engineering AI Leadership Summit, Friday, September 20, 2019, Nokia Auditorium, 2000 W. Lucent Lane, Naperville, IL 60563.
Title: When machines become “know it alls”: The ethics of defining “at risk”
There is something about the human quality of spontaneity that makes life worth living. If humans had all the answers to every question, knew the results of all their choices before embarking on a particular way forward, living as we know it would be different, some might even say boring. The fact that we must learn to struggle through things ourselves, make mistakes and learn from them, provides a certain level of freedom that none of us should take for granted. It was not that long ago, that we would get into our car with a street directory on our laps, excited to explore a new route for the first time, instead of just relying on a shortest path algorithm to get us to our destination. While we are all grateful for the ease with which we can now navigate, there is an opportunity cost.
The very ease with which we can now transact, propels responses back and forth, that we simply cannot keep up with. The cutting out of physical acts in preparation to send or receive a message, has meant that our reflection and consumption time of that information has been reduced. But if that is not enough, we have now also cut out the human interaction in favor of machine responses in the name of “self-service”. As part of the conditioning we call digital transformation, people have given up on call center human operators in favor of online chatbots. Interpersonal skills that we once depended on for work and play, are now morphing into predictive online interactions. Expressive language once admired, has now given way to no more than a few words. While this may be considered a new level of efficiency to some, few would disagree that we have lost something, despite all the perceived gains.
We are each training our machines connected to the Cloud to act like us; respond like us, use our phraseology and wording, all with the push of a button. Where things might well get even more interesting is when algorithms, and big data engines use automated data collection machines, to watch and listen to us unobtrusively, and even covertly. Together, with additional parameters, like location and condition information, being able to view someone’s facial expressions and even hear what they are saying may be enough to drive an analytics engine to determine that someone is happy or sad, genuinely not excitable at all, or even “at risk” of particular situations.
Preemptive actions can be presupposed on individuals that may well intervene with a natural inclination to act in some way. What we do with the data we collect is one thing, and how we apply it as evidence and a call to action is another. We could declare a system as having implemented “ethical AI”, but the outcomes of that process will undeniably interfere with human decision-making. At what point does it become acceptable to act retrospectively on evidence gathered, say through social media voice, image and video data, about an individual’s circumstances? This presentation will consider current and future possibilities.
Panel Discussion (4-5pm): Leadership in AI
Dr. Katina Michael, School for the Future of Innovation in Society, Arizona State University
Dr. Bimba Rao, Director of Engineering Ultrasound Division, Siemens Healthineers
Maria Rios, Founder and CEO, Nation Waste Inc.
Sara Taylor-Demos, Founder and CEO, Cora Home
Susanne Tedrick, Client Technical Specialist, IBM Cloud Platform
Questions I wanted to discuss:
How can we use Artificial Intelligence for good without the commensurate consequences?
What are the biggest concerns you have about the future of Artificial Intelligence?
What is the role of women in the development of systems that are reliant upon artificial intelligence?
If you had one message to industry about the future of the AI industry what would it be?
Biography: Katina Michael is Director of the Center for Engineering, Policy and Society at Arizona State University. She holds a joint appointment in the School for the Future of Innovation in Society and the School of Computing, Informatics and Decision Systems Engineering. She is the IEEE Transactions on Technology and Society founding editor-in-chief which will officially launch in 2020. In 2017, Katina was the recipient of the Brian O’Connell Distinguished Service Award. Recently she co-edited a special issue of Proceedings of the IEEE on machine ethics.