Elma Avdic

I am a researcher at CONNECT, Research Centre for Future Networks and Communications, based in Trinity College Dublin. My background is in electrical engineering, but I like the synergy of social sciences, arts and engineering. I’m interested in how communities and economies work, how individuals and institutions share, the effects of ideology and activism, the role of technology in changing the culture and the economic systems. I’m a strong believer in the power of context, meaningful research and policymaking, and postmodern philosophy.

Presenting

Let the Machines Govern Things

I will talk about machine-enabled regulation of radio spectrum sharing. The radio spectrum is a rare oasis of outdated legacy regulation, and the ground of the most advanced communication technologies we know today. It hosts most of the networks we talk about in Radical Networks. The spectrum asked for a relatively advanced technology to be put to use, evolving with each new generation of devices. When I call for a machine regulated spectrum, I want to give it in the robotic hands for a somewhat paradoxical reason: we need more human values in its regulation.

We will not be able to stay ahead of the exponential demand unless the network operators start sharing spectrum. Without the culture of sharing, they will never share: the regulator has to walk an extra mile to help building the culture. The current state of governance screams for help; the machines can rescue it. We will discover spectrum uniqueness by discussing how to make that transition and if legacy rulemaking of the misunderstood resource is necessary as an input to the first machine-enabled regulation.

The ethical considerations and the necessary value system for a robotic regulator tailored for spectrum will follow from the tale about the culture of sharing, drawing from information and knowledge sharing, internet culture and sharing economies. Elaborating on the whole idea of letting the machines govern things, we will place the culture of sharing among the norms which regulate the thing in Lawrence Lessig’s pathetic dot theory of regulation. The talk will address the utopian best-case scenario in a perfect machine-based regulation, juxtaposing it to a dystopian perspective of the worst case scenario and the dangers of Big Data analytics. Who is going to teach the machines about the rulemaking and governance? What system of values should be there?