Workshop on

Insurance, algorithmic decision-making, and discrimination

(INSURANCE 2021)

Part of ACM UMAP 2021

June 25, 2021
Utrecht, the Netherlands & Online
29th Conference on User Modeling, Adaptation and Personalization

Scope

Insurance companies could use algorithmic systems to set premiums for individual consumers, or deny them insurance. More and more data become available for insurers for risk differentiation. For example, some insurers monitor people’s driving behaviour to estimate risks. To some extent, risk differentiation is necessary for insurance. And it could be considered fair when, e.g., high-risk drivers pay more.

But there are drawbacks. Algorithmic decision-making could lead, unintentionally, to discrimination on the basis of, for instance, ethnicity or gender. Too much personalised risk differentiation could also make insurance unaffordable for some people. Furthermore, risk differentiation might result in the poor paying more, thereby worsening economic inequality.

We will address these issues with a half-day workshop at ACM UMAP 2021. To this workshop, we invite participants from different disciplines (for instance, computer science, law, human- computer interaction, data justice, ethics, economy).

Peliminary programme

June 25, 2021

13:00-14:30 (CEST)

90 min

Panel

14:30-14:45 (CEST)

15 min

Coffee Break

14:45-16.00 (CEST)

75 min

Groups discussion

15 min: Introduction round
15 min: Identifying discrimination-related risks (Miro board session)
15 min: Break-out groups focusing on (ways to mitigate) one of the risks
15 min: Break-out groups focusing on (ways to mitigate) another one of the risks
15 min: Recap round

16:00-16:15 (CEST)

15 min

Coffee Break

16.15-17.00 (CEST)

45 min

Global discussion

Topics

The panel discussion is guided by questions such as:

How should discrimination on the basis of ethnicity and other grounds be avoided?
Can non-discrimination norms be built in the computer systems of insurers, and if so, which norms?
How can discrimination by algorithmic systems be identified by those affected?
Are current laws sufficient to protect fairness and the right to non- discrimination in the insurance area?
Should poor people be protected against paying extra?
Is it always reasonable when high-risk insurance consumers pay extra?
Should health insurance be regulated and approached separately?

In the working groups, participants discuss questions triggered by the panel and focus, e.g., on:

norms for digital information gathering in the insurance sector
possible unjust effects of digital information gathering in the insurance sector
means to identify these unjust effects
means to prevent unjust effects
open questions that need to be addressed to ensure responsible, fair and transparent digital information gathering in the insurance sector
aspects where different disciplines can inform each other

Panellists

Marvin van Bekkum

PhD candidate, Radboud University

Moderator

Frederik Zuiderveen Borgesius

Professor of ICT and private law, Radboud University