Keyword: machine learning

Toward a Critique of Algorithmic Violence external link

Bellanova, R., Irion, K., Lindskov Jacobsen, K., Ragazzi, F., Saugmann, R. & Suchman, L.
International Political Sociology, vol. 15, num: 1, pp: 121–150, 2021

Abstract

Questions about how algorithms contribute to (in)security are under discussion across international political sociology. Building upon and adding to these debates, our collective discussion foregrounds questions about algorithmic violence. We argue that it is important to examine how algorithmic systems feed (into) specific forms of violence, and how they justify violent actions or redefine what forms of violence are deemed legitimate. Bringing together different disciplinary and conceptual vantage points, this collective discussion opens a conversation about algorithmic violence focusing both on its specific instances and on the challenges that arise in conceptualizing and studying it. Overall, the discussion converges on three areas of concern—the violence undergirding the creation and feeding of data infrastructures; the translation processes at play in the use of computer/machine vision across diverse security practices; and the institutional governing of algorithmic violence, especially its organization, limitation, and legitimation.

affordences, algorithmic violence, Artificial intelligence, cloud computing, frontpage, governance, harm, interdisciplinary, machine learning

Bibtex

Article{Bellanova2021, title = {Toward a Critique of Algorithmic Violence}, author = {Bellanova, R. and Irion, K. and Lindskov Jacobsen, K. and Ragazzi, F. and Saugmann, R. and Suchman, L.}, doi = {https://doi.org/https://doi.org/10.1093/ips/olab003}, year = {0329}, date = {2021-03-29}, journal = {International Political Sociology}, volume = {15}, number = {1}, pages = {121–150}, abstract = {Questions about how algorithms contribute to (in)security are under discussion across international political sociology. Building upon and adding to these debates, our collective discussion foregrounds questions about algorithmic violence. We argue that it is important to examine how algorithmic systems feed (into) specific forms of violence, and how they justify violent actions or redefine what forms of violence are deemed legitimate. Bringing together different disciplinary and conceptual vantage points, this collective discussion opens a conversation about algorithmic violence focusing both on its specific instances and on the challenges that arise in conceptualizing and studying it. Overall, the discussion converges on three areas of concern—the violence undergirding the creation and feeding of data infrastructures; the translation processes at play in the use of computer/machine vision across diverse security practices; and the institutional governing of algorithmic violence, especially its organization, limitation, and legitimation.}, keywords = {affordences, algorithmic violence, Artificial intelligence, cloud computing, frontpage, governance, harm, interdisciplinary, machine learning}, }

Implementing User Rights for Research in the Field of Artificial Intelligence: A Call for International Action external link

Flynn, S., Geiger, C., Quintais, J., Margoni, T., Sag, M., Guibault, L. & Carroll, M.
European Intellectual Property Review, vol. 2020, num: 7, 2020

Abstract

Last year, before the onset of a global pandemic highlighted the critical and urgent need for technology-enabled scientific research, the World Intellectual Property Organization (WIPO) launched an inquiry into issues at the intersection of intellectual property (IP) and artificial intelligence (AI). We contributed comments to that inquiry, with a focus on the application of copyright to the use of text and data mining (TDM) technology. This article describes some of the most salient points of our submission and concludes by stressing the need for international leadership on this important topic. WIPO could help fill the current gap on international leadership, including by providing guidance on the diverse mechanisms that countries may use to authorize TDM research and serving as a forum for the adoption of rules permitting cross-border TDM projects.

Artificial intelligence, Auteursrecht, frontpage, machine learning, tdm, text and data mining

Bibtex

Article{Flynn2020b, title = {Implementing User Rights for Research in the Field of Artificial Intelligence: A Call for International Action}, author = {Flynn, S. and Geiger, C. and Quintais, J. and Margoni, T. and Sag, M. and Guibault, L. and Carroll, M.}, url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3578819}, year = {0421}, date = {2020-04-21}, journal = {European Intellectual Property Review}, volume = {2020}, number = {7}, pages = {}, abstract = {Last year, before the onset of a global pandemic highlighted the critical and urgent need for technology-enabled scientific research, the World Intellectual Property Organization (WIPO) launched an inquiry into issues at the intersection of intellectual property (IP) and artificial intelligence (AI). We contributed comments to that inquiry, with a focus on the application of copyright to the use of text and data mining (TDM) technology. This article describes some of the most salient points of our submission and concludes by stressing the need for international leadership on this important topic. WIPO could help fill the current gap on international leadership, including by providing guidance on the diverse mechanisms that countries may use to authorize TDM research and serving as a forum for the adoption of rules permitting cross-border TDM projects.}, keywords = {Artificial intelligence, Auteursrecht, frontpage, machine learning, tdm, text and data mining}, }