Related papers: Operationalising AI governance through ethics-base…

As artificial intelligence (AI) reshapes industries and societies, ensuring its trustworthiness-through mitigating ethical risks like bias, opacity, and accountability deficits-remains a global challenge. International Organization for…

The deployment of AI systems faces three critical governance challenges that current frameworks fail to adequately address. First, organizations struggle with inadequate risk assessment at the use case level, exemplified by the Humana class…

Whether and how data scientists, statisticians and modellers should be accountable for the AI systems they develop remains a controversial and highly debated topic, especially given the complexity of AI systems and the difficulties in…

Risk-based approaches to governance bear an ambiguous stance regarding the Research and Development stages of AI, for they the possibility of explicit risks before they are posed by a given finalised product. In this context, Institutional…

Documentation plays a crucial role in both external accountability and internal governance of AI systems. Although there are many proposals for documenting AI data, models, systems, and methods, the ways these practices enhance governance…

The growing integration of Artificial Intelligence (AI) into Human Resources (HR) processes has transformed the way organizations manage recruitment, performance evaluation, and employee engagement. While AI offers numerous advantages, such…

In this paper we, an epistemologist and a machine learning scientist, argue that we need to pursue a novel area of philosophical research in AI - the ethics of belief for AI. Here we take the ethics of belief to refer to a field at the…

The rapid integration of Artificial Intelligence (AI) in Higher Education (HE) is transforming personalized learning, administrative automation, and decision-making. However, this progress presents a duality, as AI adoption also introduces…

Complying with the EU AI Act (AIA) guidelines while developing and implementing AI systems will soon be mandatory within the EU. However, practitioners lack actionable instructions to operationalise ethics during AI systems development. A…

Despite its successes, to date Artificial Intelligence (AI) is still characterized by a number of shortcomings with regards to different application domains and goals. These limitations are arguably both conceptual (e.g., related to…

Several high-profile events, such as the mass testing of emotion recognition systems on vulnerable sub-populations and using question answering systems to make moral judgments, have highlighted how technology will often lead to more adverse…

Artificial Intelligence (AI) has the potential to revolutionize various sectors, yet its adoption is often hindered by concerns about data privacy, security, and the understanding of AI capabilities. This paper synthesizes AI governance…

Many enterprises are increasingly adopting Artificial Intelligence (AI) to make internal processes more competitive and efficient. In response to public concern and new regulations for the ethical and responsible use of AI, implementing AI…

This policy report draws on country studies from China, South Korea, Singapore, and the United Kingdom to identify effective tools and key barriers to interoperability in AI safety governance. It offers practical recommendations to support…

Artificial intelligence is gaining momentum, ongoing pandemic is fuel to that with more opportunities in every sector specially in health and education sector. But with the growth in technology, challenges associated with ethics also grow…

Trusted AI literature to date has focused on the trust needs of users who knowingly interact with discrete AIs. Conspicuously absent from the literature is a rigorous treatment of public trust in AI. We argue that public distrust of AI…

Human oversight requirements are a core component of the European AI Act and in AI governance. In this paper, we highlight key challenges in testing for compliance with these requirements. A central difficulty lies in balancing simple, but…

Existing AI disclosure mandates in scholarship require that AI assistance be reported but leave transparency philosophically unspecified: they fix the duty without explaining what the duty serves. We argue that ethical inquiry is…

As artificial intelligence continues its unprecedented global expansion, accompanied by a proliferation of benefits, an increasing apprehension about the privacy and security implications of AI-enabled systems emerges. The pivotal question…

Alignment of artificial intelligence (AI) encompasses the normative problem of specifying how AI systems should act and the technical problem of ensuring AI systems comply with those specifications. To date, AI alignment has generally…