Aggregating value systems for decision support

We adopt an emerging and prominent vision of human-centred Artificial Intelligence that requires building trustworthy intelligent systems. Such systems should be capable of dealing with the challenges of an interconnected, globalised world by handling plurality and by abiding by human values. Within this vision, pluralistic value alignment is...

Ethics of generative AI and manipulation: a design-oriented research agenda

Generative AI enables automated, effective manipulation at scale. Despite the growing general ethical discussion around generative AI, the specific manipulation risks remain inadequately investigated. This article outlines essential inquiries encompassing conceptual, empirical, and design dimensions of manipulation, pivotal for comprehending...

Transparency for AI systems: A value-based approach

With the widespread use of artificial intelligence, it becomes crucial to provide information about these systems and how they are used. Governments aim to disclose their use of algorithms to establish legitimacy and the EU AI Act mandates forms of transparency for all high-risk and limited-risk systems. Yet, what should the standards for...

Personality and acceptance as predictors of ChatGPT use

Within a year of its launch, ChatGPT has seen a surge in popularity. While many are drawn to its effectiveness and user-friendly interface, ChatGPT also introduces moral concerns, such as the temptation to present generated text as one’s own. This led us to theorize that personality traits such as Machiavellianism and sensation-seeking may be...

Why we should not mistake accuracy of medical AI for efficiency

In the medical literature, promising results regarding accuracy of medical AI are presented as claims for its potential to increase efficiency. This elision of concepts is misleading and incorrect. First, the promise that AI will reduce human workload rests on a too narrow assessment of what constitutes workload in the first place. Human...

Why and How Should We Explain AI?

Why should we explain opaque algorithms? Here four papers are discussed that argue that, in fact, we don’t have to. Explainability, according to them, isn’t needed for trust in algorithms, nor is it needed for other goals we might have. I give a critical overview of these arguments, showing that there is still room to think that explainability...

Meaningful human control: actionable properties for AI system development

How can humans remain in control of artificial intelligence (AI)-based systems designed to perform tasks autonomously? Such systems are increasingly ubiquitous, creating benefits - but also undesirable situations where moral responsibility for their actions cannot be properly attributed to any particular person or group. The concept of...

Individual Fairness Guarantees for Neural Networks

We consider the problem of certifying the individual fairness (IF) of feed-forward neural networks (NNs). In particular, we work with the ϵ-δ-IF formulation, which, given a NN and a similarity metric learnt from data, requires that the output difference between any pair of ϵ-similar individuals is bounded by a maximum decision tolerance δ ≥ 0...

Federated data as a commons: a third way to subject-centric and collective-centric approaches to data epistemology and politics

Purpose: This study advances a reconceptualization of data and information which overcomes normative understandings often contained in data policies at national and international levels. This study aims to propose a conceptual framework that moves beyond subject- and collective-centric normative understandings. Design/methodology/approach: To...

The Human in Command: An exploratory study into human moral autonomy of Behavioural Artificial Intelligence Technology

The accelerating development of algorithms causes a disruptive effect in many domains, including the complex decision-making of knowledge workers. Experts can manage difficult but repetitive decisions with software technologies like a Decision Support System (DSS). A DSS is used to monitor decisions, get additional insights and improve decisions...

Design approaches to tackle ethical issues for proficiency estimation in AI-enabled recruitment

Companies have been looking for automation in their hiring practices and Artificial Intelligence offers a solution. A popular opinion on the topic is that AI-enabled hiring will enhance talent acquisition overall, eliminating bias and bettering results. However, deployed AI hiring tools often do not offer a solution but worsen the problem by...

Ethics by design and research ethics for artificial intelligence

Four Responsibility Gaps with Artificial Intelligence: Why they Matter and How to Address them

The notion of “responsibility gap” with artificial intelligence (AI) was originally introduced in the philosophical debate to indicate the concern that “learning automata” may make more difficult or impossible to attribute moral culpability to persons for untoward events. Building on literature in moral and legal philosophy, and ethics of...

Hard choices in artificial intelligence

As AI systems are integrated into high stakes social domains, researchers now examine how to design and operate them in a safe and ethical manner. However, the criteria for identifying and diagnosing safety risks in complex social contexts remain unclear and contested. In this paper, we examine the vagueness in debates about the safety and...

Towards Engineering AI Software for Fairness: A framework to help design fair, accountable and transparent algorithmic decision-making systems

Algorithmic decision-making (ADM) is becoming increasingly prevalent in society, due to the rapid technological developments in Artificial Intelligence. ADM make substantially impactful decisions about people: diagnosing whether we have a disease, what news and which ads we get to see, whether we<br/>are eligible for a job, benefits, a college...

AI and the path to envelopment: knowledge as a first step towards the responsible regulation and use of AI-powered machines

With Artificial Intelligence (AI) entering our lives in novel ways—both known and unknown to us—there is both the enhancement of existing ethical issues associated with AI as well as the rise of new ethical issues. There is much focus on opening up the ‘black box’ of modern machine-learning algorithms to understand the reasoning behind their...

Meaningful Human Control Over Autonomous Systems: A Philosophical Account

Debates on lethal autonomous weapon systems have proliferated in the past 5 years. Ethical concerns have been voiced about a possible raise in the number of wrongs and crimes in military operations and about the creation of a “responsibility gap” for harms caused by these systems. To address these concerns, the principle of “meaningful human...