Dr Michel Loi, AI ETHICS EXPERT BUSINESS CONSULTANT RESEARCH LEADER Logo
Dr Michel Loi, AI ETHICS EXPERT BUSINESS CONSULTANT RESEARCH LEADER Logo
Dr Michel Loi, AI ETHICS EXPERT BUSINESS CONSULTANT RESEARCH LEADER Logo

SWISS NATIONAL SCIENCE FOUNDATION

In close collaboration with higher education institutions and other partners, the SNSF strives to create the best possible conditions for the development and global interconnectedness of Swiss research. It pays particular attention to the promotion of early-career researchers. In addition, it accepts evaluation mandates to help ensure that large third-party-funded research initiatives deliver the highest scientific quality.

Swiss National Science Foundation. Academic collaboration. Michele Loi AI Expert, Business Consultant and Research Leader

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ELSI Task Force
Socially Acceptable and Fair Algorithms
ethical, legal and societal aspects of using Big Data in private insurance

project 1: ELSI TASK FORCE

Project Focus

I developed a plan for the integration of different disciplinary perspectives across the social science, humanities and law pillars of the National Research Programme on Big Data of the Swiss National Science Foundation. The work of the task force was completed the subsequent year (I had to resign in order to lead a SNF-funded project as PI) with a different coordinator.

Institution

University of Zurich, Digital Society Initiative

Funder

Swiss National Science Foundation

Project duration

October 2020 - December 2020

project 2: Socially Acceptable and Fair Algorithms

Project Focus

This project develops a methodology to reason about the selection of statistical fairness definitions for machine-learning-led applications in human resources. It consists of three mutually influencing research pillars:
1. philosophical research into the relationship between theories of justice and discrimination and definitions of fairness in machine learning;
2. empirical research (social psychology and experimental economy) in fairness perceptions;
3. development of fairness-constrained optimization algorithms and data-driven visualizations to enable the analysis of moral trade-offs by stakeholders (fairness lab).

Institution

Biomedical Ethics and the History of Medicine. University of Zurich

Funder

Swiss National Science Foundation

Project duration

June 2020 - June 2024

project 3: Between Solidarity and Personalisation – Dealing with Ethical and Legal Big Data Challenges in the Insurance Industry

Project Focus

Within 30 months, an interdisciplinary team of researchers from the University of Zurich and the University of Applied Sciences of the Grisons – in collaboration with experts from Swiss Re – investigated the ethical, legal and societal aspects of using Big Data in private insurance. I reseached the ethics of big data and interacted with experts of law, management science, psychology and sociology to create recommendations that directly emerge from the team’s research. 

 

View Project output.

Institution

Biomedical Ethics and the History of Medicine. University of Zurich

Funder

Swiss National Science Foundation

Project duration

April 2017 - January 2019