As research on algorithms and their impact proliferates, so do calls for scrutiny/accountability
of algorithms. A systematic review of the work that has been done in the field of'algorithmic …

One obstacle to applying reinforcement learning algorithms to real-world problems is the
lack of suitable reward functions. Designing such reward functions is difficult in part because …

This paper looks at philosophical questions that arise in the context of AI alignment. It
defends three propositions. First, normative and technical aspects of the AI alignment …

Abstract The idea of Artificial Intelligence for Social Good (henceforth AI4SG) is gaining
traction within information societies in general and the AI community in particular. It has the …

As the range of potential uses for Artificial Intelligence (AI), in particular machine learning
(ML), has increased, so has awareness of the associated ethical issues. This increased …

Artificial intelligence (AI) is becoming part of the everyday. During this transition, people's
intention to use AI technologies is still unclear and emotions such as fear are influencing it …

With artificial intelligence (AI) becoming increasingly capable of handling highly complex
tasks, many AI-enabled products and services are granted a higher autonomy of decision …

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 …

Recommender systems are the algorithms which select, filter, and personalize content
across many of the world's largest platforms and apps. As such, their positive and negative …

Increasingly complex and autonomous systems require machine ethics to maximize the
benefits and minimize the risks to society arising from the new technology. It is challenging …