As the globally increasing population drives rapid urbanization in various parts of the world,
there is a great need to deliberate on the future of the cities worth living. In particular, as …

Deep learning has rapidly advanced artificial intelligence (AI) and algorithmic decision-
making (ADM) paradigms, impacting many traditional fields of medicine. Pathology is a …

Accountability is a cornerstone of the governance of artificial intelligence (AI). However, it is
often defined too imprecisely because its multifaceted nature and the sociotechnical …

Academic and policy proposals on algorithmic accountability often seek to understand
algorithmic systems in their socio-technical context, recognising that they are produced by …

Ethics-based auditing (EBA) is a structured process whereby an entity's past or present
behaviour is assessed for consistency with moral principles or norms. Recently, EBA has …

Over the years, companies have adopted hiring algorithms because they promise wider job
candidate pools, lower recruitment costs and less human bias. Despite these promises, they …

Accountability is widely understood as a goal for well governed computer systems, and is a
sought-after value in many governance contexts. But how can it be achieved? Recent work …

This article explores the cooperation of government and the private sector to tackle the
ethical dimension of artificial intelligence (AI). The argument draws on the institutionalist …

Artificial intelligence (AI) has the potential to benefit humans and society by its employment
in important sectors. However, the risks of negative consequences have underscored the …

The growing use of automated decision-making (ADM) systems in the public sector and the
need to control these has raised many legal questions in academic research and in …