Big Data without Big Brothers

Keynote: Prof. Ido Erev (Technion, Haifa): The potential of gentle rule enforcement

Panelist Barnabás Szászi (ELTE, Behavioural Science Lab)

Moderator: Csaba Johanyák

 

The potential of gentle rule enforcement

Wise use of Big Data technology can facilitate the enforcement of laws and regulations in two ways: It can reduce the necessity of severe and costly punishments, and can reduce invasion of privacy. This suggestion rests on two key observations: First, basic decision research shows that experience leads people to underweight rare events, and select the options that lead to the best payoffs in most cases. Second, most consequential violations start with less important violations that if detected can be stopped without collecting personal data. In other words, Prof. Erev propose to focus on the development of gentle rule enforcement technology that generalises the success behind the seat belt alarm system.

Prof. Ido Erev joined the Faculty of Industrial Engineering and Management in the Technion in 1990. He received his PhD in Cognitive/Quantitative Psychology from the University of North Carolina the same year.

Prof. Erev has been a visiting research associate in Economics at the University of Pittsburgh; a Michael A. Gould fellow at Columbia Business School; a Marvin Bower Fellow at Harvard Business School; a fellow in the Israel Center of Advanced Studies; a visiting professor at Erasmus School of Economics; a visiting professor at the Interdisciplinary center (IDC) in Herzliya; and a research environment professor at Warwick Business School.

He focuses on three related lines of research; observation of a large difference between decisions that are made based on a description of the incentive structure, decisions that are made based on experience and difference between anomalies and forecasts.

Registration: https://feliratkozas.mcc.hu/hu/registration-big-data-without-big-brothers

We welcome all those interested!