The Blackbox Within: The Social Implications of Last Mile Data Analytics

Conference: International Conference on Intelligent and Smart Computing in Data Analytics

Title: The Blackbox Within: The Social Implications of Last Mile Data Analytics

Abstract: The notion of a blackbox is not new. Blackboxes appear in all types of shapes and sizes. But all of them have one thing in common, they collect data, and lots of it. Most of them have an audit function, but increasingly blackboxes are present for real-time tracking and monitoring and are network-enabled, interfacing with smart devices, and even satellites. Blackboxes are also getting smaller in size given breakthroughs in the miniaturization of high-tech devices, and the ability to pack multiple sensors onto small motherboards. The smartphone for example, is the most pervasive black box that exists, not only because of what it can do, but because of its hidden capabilities that are not apparent to the end-user. Today, people seldom switch off their mobile devices, they are not only ubiquitous but persistent, offering service providers are 24x7 intimate user profile. And blackboxes are no longer just embodied in airplanes, trains, trucks and cars today but increasingly in Internet of Things devices in a smart city on a lamp post or in the house in a thermostat, in conversational search robots or on people in the form of smart watches.

Implantable blackboxes are particularly prevalent in the prosthesis market, where people bear biomedical devices. In the US, for example, about 10% of the population now carries some form of implantable. These devices will transform in function with time from manual to digital, as the infrastructure develops for bidirectional feedback loops in a variety of operational scenarios. Purportedly the blackbox is there to capture the “last mile”, providing a variety of time stamps to help determine identity, location and condition of the bearer. The implantable thus becomes that non-transferable token that identifies the individual with certainty bringing a level of assurance of the data being gathered. This presentation will ponder on data analytics of the future that are humancentric and the social implications of what we have described in the literature as uberveillance.

Affiliation:

Professor

School for the Future of Innovation in Society

School of Computing, Informatics and Decision Systems Engineering

Director, Society Policy Engineering Collective

Biography: Katina Michael is a professor at Arizona State University, holding a joint appointment in the School for the Future of Innovation in Society and School of Computing, Informatics and Decisions Systems Engineering. She is also the director of the Society Policy Engineering Collective (SPEC) and the Founding Editor-in-Chief of the IEEE Transactions on Technology and Society. Katina is a senior member of the IEEE and a Public Interest Technology advocate who studies the social implications of technology. She has held 13 annual workshops in the social implications of national security space and chaired 3 international symposia on technology and society (ISTAS) in Wollongong, Toronto and Phoenix. She is the Senior Editor of the socio-economic impact section in IEEE Consumer Electronics Magazine and was the editor in chief of the award-winning IEEE Technology and Society Magazine. In 2019 she took on the role of working group chair for the IEEE P2089 standard. In 2017, she received the Brian M. O'Connell SSIT Distinguished Service Award.

In the 1990s, Katina was employed as a senior network planner at Nortel Networks and systems analyst at Andersen Consulting and OTIS. In 2002 she entered academia as a lecturer at the University of Wollongong and in 2013 became a member of the executive team in the Faculty of Engineering and Information Sciences as the Associate Dean – International, overseeing 8 partner and twinning arrangements for the University in the UAE, Malaysia, Singapore, China and Hong Kong. Katina completed a Masters degree in transnational crime prevention in the Faculty of Law with a UOW postgraduate scholarship in 2007, and was later invited to teach cybercrime in the law school. Her PhD was on systems of innovation in the automatic identification industry.

Citation: Katina Michael, 3 October 2020, “The Blackbox Within: The Social Implications of Last Mile Data Analytics”, International Conference on Intelligent and Smart Computing in Data Analytics, https://icscda.com/keynote-speakers.html