The Philosophy of Data Science: Data Science Governance

Conference: The Philosophy of Data Science: Data Science Governance

This conference, hosted by the Centre for Human & Machine Intelligence (HMI) at the Frankfurt School of Finance & Management and part of the project group Regulatory Theories of Artificial Intelligence of the Centre for Responsible Digitality (ZEVEDI), aims to bring together researchers from ethics, political philosophy, and philosophy of science to discuss questions surrounding the governance of data science. The conference’s guiding question is how to conduct, design and regulate data science for the public good. The proper guidance of data science requires the formulation of both moral and legal norms and frameworks, which may guide individuals, private corporations, as well as public and political institutions. The conference will approach this topic by looking at a range of different domains, exploring the specific challenges they raise and how they might call for different, custom-made solutions. These domains include, but are not limited to, healthcare, scientific research, transportation, surveillance, social media, and law and law enforcement. In these domains, good data science governance is a matter of understanding and balancing a variety of often competing values and ideals, among which are responsibility, trust, fairness, accountability, privacy, cost-efficiency, as well as epistemic goods such as knowledge, understanding and predictive power.

Location
Frankfurt School of Finance & Management
Adickesallee 32-34
60322 Frankfurt/Main, Germany
Room: S3.02, 3rd floor

Date
10 & 11 June 2022

 Program

Friday, June 10, 2022

10.00 – 10.30              Welcome

10.30 – 12.00              Boris Babic (University of Toronto): The Explainability Bait and Switch

12:00 – 13:30              Lunch break

13.30 – 15.00              Cassandra Grützner (University of Halle-Wittenberg), Maximilian Goldmann (unaffiliated), Moritz Appels (Mannheim University), Rebecca C. Rühle (VU Amsterdam): Behavioural data governance - the feasibility of data leak prevention through nudging

15:00 – 15:15              Oliver Buchholz (Tübingen University): Building Effective Guidelines for Machine Learning: Lessons from Means-End Epistemology

16:45 – 17:00              Coffee break

17:00 – 18.30              Sabina Leonelli (University of Exeter): Governing Data Circulation: An Underrated Concern for Scientific Inquiry

Saturday, June 11, 2022

9.00 – 10.30                Kate Vredenburgh (London School of Economics): Justified Algorithmic Decisions: Thresholds and Randomness

10:30 – 10:45              Coffee Break

10.45 – 12.15              Michael Da Silva (University of Ottawa/University of Southampton): Explainability, Public Reason, and Medical Artificial Intelligence

12.15 – 13.45              Lunch break

13.45 – 15.15              Mahdi Khalili (VU Amsterdam): Understandable Artificial Intelligence and Virtuous Characters

15:15 – 15:30              Coffee break

15.30 – 17.00              David Danks (University of California, San Diego): Governing Ethical Bias, not Statistical Bias

The conference will be a hybrid event. To register for in-person or online attendance, please visit our website: https://www.frankfurt-school.de/home/research/conferences-workshops/ds-2022. Information on how to attend online will be shared with registered participants in due course. There is no registration or conference fee. Registration closes on 3 June. On the website, you will also find further information regarding travel directions. If you have any further questions, please direct any enquiries to [email protected].

Organisers:
Gregory Wheeler, Peter Königs, and Sebastian Köhler

This is an event sponsored by the Centre for Human & Machine Intelligence (HMI), Frankfurt School of Finance & Management and part of the project group Regulatory Theories of Artificial Intelligence of the Centre for Responsible Digitality (ZEVEDI).