Research articles on GOVERNANCE

Black box algorithms and the rights of individuals: no easy solution to the “explainability” problem

Jarek Gryz, York University
Marcin Rojszczak, Warsaw University of Technology
PUBLISHED ON: 30 Jun 2021 DOI: 10.14763/2021.2.1564

The design of modern machine learning systems should take into account not only their effectiveness in solving a given problem, but also their impact on the rights of individuals. Implementing this goal may involve applying technical solutions proven in the IT industry, such as event logs or certification frameworks.

This research investigates EU member states’ preferences and coalitions in recent negotiations of the Council of the EU related to the digital single market.

Recommender systems and the amplification of extremist content

Joe Whittaker, Swansea University
Seán Looney, Swansea University
Alastair Reed, Swansea University
Fabio Votta, University of Amsterdam
PUBLISHED ON: 30 Jun 2021 DOI: 10.14763/2021.2.1565

Recommendation algorithms potentially amplifying extremist content has become a policy concern in recent years. We conduct a novel empirical experiment on three platforms (YouTube, Reddit, and Gab) to test this phenomenon. We find that YouTube’s “Recommended for you” system does promote extreme content. We synthesise the findings into the policy debate and argue that co-regulation may provide some solutions.

Once again platform liability: on the edge of the ‘Uber’ and ‘Airbnb’ cases

Nataliia Filatova-Bilous, Yaroslav Mudryi National Law University
PUBLISHED ON: 12 May 2021 DOI: 10.14763/2021.2.1559

The CJEU judgements in the ‘Uber’ and ‘Airbnb’ cases may help to determine whether platform operators bear liability towards platform customers and on what grounds.