Machines do not 'think fast and slow'in the sense that humans do in dual-process models of
cognition. However, the people who create the machines may attempt to emulate or simulate …

This paper proposes a research direction to advance AI which draws inspiration from
cognitive theories of human decision making. The premise is that if we gain insights about …

In the field of AI ethics, after the introduction of ethical frameworks and the evaluation
thereof, we seem to have arrived at a third wave in which the operationalisation of ethics is …

An important step in the development of value alignment (VA) systems in artificial
intelligence (AI) is understanding how VA can reflect valid ethical principles. We propose …

As automated machine learning (AutoML) systems continue to progress in both
sophistication and performance, it becomes important to understand the 'how'and 'why'of …

Artificial intelligence (AI) still lacks human capabilities, like adaptability, generalizability, self-
control, consistency, common sense, and causal reasoning. Humans achieve some of these …

Constraining the actions of AI systems is one promising way to ensure that these systems
behave in a way that is morally acceptable to humans. But constraints alone come with …

Goal recognition is a crucial aspect of understanding the intentions and objectives of agents
by observing some of their actions. The most prominent approaches to goal recognition can …

In many machine learning scenarios, looking for the best classifier that fits a particular
dataset can be very costly in terms of time and resources. Moreover, it can require deep …

In human-agent collectives, humans and agents need to work collaboratively and agree on
collective decisions. However, ensuring that agents responsibly make decisions is a …