Related papers: We Are AI: Taking Control of Technology
Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system's entire life cycle: it should be (1) lawful, (2) ethical, and (3) robust, both…
With the upcoming enforcement of the EU AI Act, documentation of high-risk AI systems and their risk management information will become a legal requirement playing a pivotal role in demonstration of compliance. Despite its importance, there…
Rapid advancements in artificial intelligence (AI) have sparked growing concerns among experts, policymakers, and world leaders regarding the potential for increasingly advanced AI systems to pose catastrophic risks. Although numerous risks…
The discourse on responsible artificial intelligence (AI) regulation is understandably dominated by risk-focused assessments and analyses. This approach reflects the fundamental uncertainty policymakers face when determining appropriate…
The availability and abundance of GenAI tools to administer tasks traditionally managed by people have raised concerns, particularly within the education and academic sectors, as some students may highly rely on these tools to complete the…
Artificial intelligence (AI) is a technology which is increasingly being utilised in society and the economy worldwide, and its implementation is planned to become more prevalent in coming years. AI is increasingly being embedded in our…
Artifical Intelligence (AI) in Education has great potential for building more personalised curricula, as well as democratising education worldwide and creating a Renaissance of new ways of teaching and learning. We believe this is a…
The rise of conversational AI (CAI), powered by large language models, is transforming how individuals access and interact with digital information. However, these tools may inadvertently amplify existing digital inequalities. This study…
AI technologies, including deep learning, large-language models have gone from one breakthrough to the other. As a result, we are witnessing growing excitement in robotics at the prospect of leveraging the potential of AI to tackle some of…
Generative AI is reshaping education, yet most university AI policies are written without students and focus on penalizing misuse. This top-down approach sidelines those most affected from decisions that shape their everyday learning,…
This paper reviews Trustworthy Artificial Intelligence (TAI) and its various definitions. Considering the principles respected in any society, TAI is often characterized by a few attributes, some of which have led to confusion in regulatory…
As AI technologies increase in capability and ubiquity, AI accidents are becoming more common. Based on normal accident theory, high reliability theory, and open systems theory, we create a framework for understanding the risks associated…
Artificial Intelligence (AI) governance is the practice of establishing frameworks, policies, and procedures to ensure the responsible, ethical, and safe development and deployment of AI systems. Although AI governance is a core pillar of…
Cooperation between the United States and China, the world's leading artificial intelligence (AI) powers, is crucial for effective global AI governance and responsible AI development. Although geopolitical tensions have emphasized areas of…
This chapter addresses the citizenship challenges related to AI in education, particularly concerning students, teachers, and other educational stakeholders in the context of AI integration. We first explore how to foster AI awareness and…
After the release of several widely adopted artificial intelligence (AI) literacy guidelines by 2021, the unprecedented rise of generative AI since 2023 has transformed the way we work and acquire information worldwide. Unlike traditional…
With the rapid development of artificial intelligence (AI) community, education in AI is receiving more and more attentions. There have been many AI related courses in the respects of algorithms and applications, while not many courses in…
Auditability is defined as the capacity of AI systems to be independently assessed for compliance with ethical, legal, and technical standards throughout their lifecycle. The chapter explores how auditability is being formalized through…
AI auditing is a rapidly growing field of research and practice. This review article, which doubles as an editorial to Digital Societys topical collection on Auditing of AI, provides an overview of previous work in the field. Three key…
Artificial Intelligence (AI) and its associated applications are ubiquitous in today's world, making it imperative that students and their teachers understand how it works and the ramifications arising from its usage. In this study, we…