Objective Profiling may threaten values that the law aims to protect, and undermine goals that the law aims to achieve. Profiling involves automated processing of personal or other data to develop profiles that can be used to make decisions about people. Profiling can be used in different contexts. For instance, (i) with retail price discrimination, online shops charge different consumers different prices for the same or similar products. (ii) Lenders use profiling to estimate a consumer’s creditworthiness. Lenders can adapt interest rates to certain consumers, or refuse to lend to them. (iii) Predictive policing refers to the use of profiling technology to predict criminal behaviour.However profiling has drawbacks. For instance, profiling can discriminate unintentionally, when an algorithm learns from data reflecting biased human decisions. Additionally, profiling is opaque: people may not know why they are treated differently. Making profiling transparent is difficult, among other reasons because of the complexity and the possibly ever-changing nature of algorithms. The project’s overarching research question is: considering the rationales for the rules in different sectors, is additional regulation needed, and if so: how should profiling be regulated? The project aims to develop guidelines for regulating profiling.I examine profiling in three sectors: retail price discrimination, consumer credit, and predictive policing. For each case study, I analyse current rules that apply to profiling. Next, I analyse these rules’ rationales, which are partly different for each sector. A rule may, for example, aim to protect a human right, or express a legal principle, such as equality, contractual freedom, or the right to a fair trial. Rules may also have economic rationales, which are different for each sector. Drawing from the three case studies, I develop guidelines to regulate profiling. Policymakers, NGOs, and other stakeholders expressed great interest in the results. Fields of science natural sciencescomputer and information sciencesdata sciencesocial sciencespolitical sciencespolitical policiescivil societynongovernmental organizationssocial scienceseconomics and businessbusiness and managementsocial scienceslaw Keywords Profiling discrimination human rights fundamental rights privacy data protection fairness price discrimination algorithmic decision-making machine learning predictive policing big data Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2016 - Individual Fellowships Call for proposal H2020-MSCA-IF-2016 See other projects for this call Funding Scheme MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinator VRIJE UNIVERSITEIT BRUSSEL Net EU contribution € 172 800,00 Address Pleinlaan 2 1050 Bruxelles / brussel Belgium See on map Region Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest Région de Bruxelles-Capitale/ Brussels Hoofdstedelijk Gewest Arr. de Bruxelles-Capitale/Arr. Brussel-Hoofdstad Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
