How to Be Algorithmically Governed Like That
Data- And Algorithmic Agency From User Perspective
Bibliographic Data
| ID | 22008945 |
|---|---|
| Authors | Ana Pop Stefanija (0000-0002-5700-602X, Vrije Universiteit Brussel), Jo Pierson (0000-0002-9077-6229, Vrije Universiteit Brussel) |
| Year | 2021 |
| Publication date | 2021-09-15 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | AoIR Selected Papers of Internet Research (JOURNAL) |
| Journal identifiers | ISSN: 2162-3317 • E-ISSN: 2162-3317 |
| Publisher | University of Illinois Libraries (PUBLISHER) |
| DOI | 10.5210/spir.v2021i0.12227 |
| OpenAlex | W3199641784 |
| Language | EN |
| References cited | 5 |
If users are being $2 algorithms, and companies and regulators are proposing ways for $2 algorithms, with this paper we would like to discuss and propose a third type of governance — one where users have agency, control and governing power(s) over algorithmic systems and their outputs. Our main research question is how do we enable users to actively govern algorithms, instead of passively being governed by them? And what do the users need in order to be algorithmically governed in such a way that will enable more agency, autonomy and control when interacting with AI systems and their outputs. Instead of getting insights in an abstract way, to answer this question, we opted for a guided and supportive process where participants were able to reflect on the process, formulate and elaborate their insights, thoughts, needs and requirements based on their lived experience, i.e., after a real interaction with these algorithmic systems. We conducted a participatory technographic research with 47 participants, through a multi-stage process consisting of a survey, Subject Access Requests (Article 15 of the General Data Protection Regulation), purposeful interaction with the transparency tools of seven chosen platforms and extensive structured research diaries. A quali-quantitative analysis of the insights enabled us to formulate the participants’ requirements of $2 and $2 in a way that will enable their agency, control and autonomy. These requirements are translatable and implementable at a user-interaction level, via technology design and through regulatory mechanisms
Autonomy · Business · Computer security · Corporate governance · Data science · Knowledge management · Sociology · Computer Science · Ethics and Social Impacts of AI · Technology, Environment, Urban Planning · Artificial Intelligence
| Highly cited | No |
|---|