Michele Loi

University of Zurich

Rämistrasse 71

Zürich, CH-8006

Switzerland

SCHOLARLY PAPERS

5

DOWNLOADS

494

SSRN CITATIONS

0

CROSSREF CITATIONS

0

Scholarly Papers (5)

1.

Canvas White Paper 1 – Cybersecurity and Ethics

Number of pages: 69 Posted: 28 Dec 2017
Delft University of Technology, Delft University of Technology, University of Zurich, Dublin City University, OTH Regensburg, Institute for Social Research and Technology Assessment (IST), University of Zurich, Dublin City University and OTH Regensburg, Institute for Social Research and Technology Assessment (IST)
Downloads 301 (104,374)

Abstract:

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Cybersecurity, Ethics, Health, Finance, National Security

2.

Insurance Discrimination and Fairness in Machine Learning: An Ethical Analysis

Number of pages: 30 Posted: 28 Aug 2019 Last Revised: 14 Sep 2019
Michele Loi and Markus Christen
University of Zurich and University of Zurich
Downloads 54 (388,838)

Abstract:

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insurance, discrimination, big data, fairness in machine learning, ethics

3.

Big Data and the Morality of Inclusion

Definitive (and shortened) version published in Italian as a book chapter in "Per cosa lottare. Le frontiere del progressismo", edited by Enrico Biale and Corrado Fumagalli, Fondazione Giangiacomo Feltrinelli, Milano, 2019 ISBN: 9788868353476
Number of pages: 26 Posted: 12 Feb 2019 Last Revised: 22 Oct 2019
Michele Loi and Markus Christen
University of Zurich and University of Zurich
Downloads 51 (398,859)

Abstract:

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big data, ethics, insurance, people analytics, human resources, solidarity

4.

Transparency As Design Publicity: Explaining and Justifying Inscrutable Algorithms

Number of pages: 20 Posted: 20 Jun 2019
University of Zurich, Dep. Management, Technology, and Economics ETH Zurich and University of Zurich - Institute for Biomedical Ethics and the History of Medicine
Downloads 49 (405,724)

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algorithms, transparency, interpretability, explanation, justification, AI

5.

A Philosophical Theory of Fairness for Prediction-Based Decisions

Number of pages: 10 Posted: 18 Sep 2019 Last Revised: 04 Nov 2019
Michele Loi, Anders Herlitz and Hoda Heidari
University of Zurich, The Institute for Future Studies and ETH Zürich
Downloads 39 (444,140)

Abstract:

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fairness, machine learning, algorithmic fairness, theories of justice, John Rawls, equality of opportunity, fairness dilemma