Contribution: Contributions Program
Université du Québec à Montréal (UQAM)
$49,900.00
Privacy and Ethics: Understanding the convergences and tensions for the responsible development of machine learning
EF 2020-21 · 2020-05-25
Résumé
Machine learning models are now ubiquitous in our society. However, their widespread use also raises serious privacy and ethical issues, especially if their predictions are applied in domains where they can significantly affect individuals. To understand how to best address privacy and ethics responsibly when developing machine learning models, we need to first have a clear view of how these concepts interact with each other. The objective of this project is to investigate this question by following an interdisciplinary approach at the crossroads of computer science, law and ethics.
Programme
Contributions Program
Bénéficiaire
Emplacement
Montreal|Montréal, Quebec, Canada
Type de bénéficiaire
Academia
Type
Contribution
Source
Proactive Disclosure - Grants and Contributions
Tel que publié
Agreement Start Date
2020-05-25
Agreement Title
Privacy and Ethics: Understanding the convergences and tensions for the responsible development of machine learning
Agreement Title (French)
Vie privée et éthique : comprendre les convergences et les tensions en vue de l’évolution responsable de l’apprentissage machine
Agreement Type
Contribution
Agreement Value
$49,900.00
Amendment Number
0
Description
Machine learning models are now ubiquitous in our society. However, their widespread use also raises serious privacy and ethical issues, especially if their predictions are applied in domains where they can significantly affect individuals. To understand how to best address privacy and ethics responsibly when developing machine learning models, we need to first have a clear view of how these concepts interact with each other. The objective of this project is to investigate this question by following an interdisciplinary approach at the crossroads of computer science, law and ethics.
Description (French)
Les modèles d’apprentissage machine sont désormais omniprésents au sein de notre société. Toutefois, leur utilisation répandue soulève d’importants enjeux touchant la vie privée et l’éthique, surtout si leurs prédictions sont appliquées dans des domaines où elles peuvent avoir une grande incidence sur les personnes. Pour comprendre la meilleure façon d’intégrer de manière responsable la protection de la vie privée et l’éthique à l’élaboration des modèles d’apprentissage machine, nous devons d’abord avoir une vision claire de la manière dont ces concepts interagissent. Ce projet a pour objectif d’étudier cette question en suivant une approche interdisciplinaire qui se trouve au carrefour de l’informatique, du droit et de l’éthique.
Organization Code
opc-cpvp
Organization
Office of the Privacy Commissioner of Canada | Commissariat à la protection de la vie privée du Canada
Program Name
Contributions Program
Program Name (French)
Programme des contributions
Recipient City
Montreal|Montréal
Recipient Country
CA
Recipient Legal Name
Université du Québec à Montréal (UQAM)
Recipient Operating Name
Université du Québec à Montréal (UQAM)
Recipient Province or Territory
QC
Reference Number
CP-000001-F