#Adversarial Robustness in Machine Learning

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions

Artificial intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the …

The Selective Labels Problem

Evaluating whether machines improve on human performance is one of the central questions of machine learning. However, there are many domains where the data is …

Copyright Protection and Accountability of Generative AI: Attack, Watermarking and Attribution

Generative AI (e.g., Generative Adversarial Networks - GANs) has become increasingly popular in recent years. However, Generative AI introduces significant concerns regarding the protection of …

Protecting Intellectual Property of Deep Neural Networks with Watermarking

Deep learning technologies, which are the key components of state-of-the-art Artificial Intelligence (AI) services, have shown great success in providing human-level capabilities for a variety …

Protecting Intellectual Property With Reliable Availability of Learning Models in AI-Based Cybersecurity Services

Artificial intelligence (AI)-based cybersecurity services offer significant promise in many scenarios, including malware detection, content supervision, and so on. Meanwhile, many commercial and government applications …

Worldwide AI ethics: A review of 200 guidelines and recommendations for AI governance

The utilization of artificial intelligence (AI) applications has experienced tremendous growth in recent years, bringing forth numerous benefits and conveniences. However, this expansion has also …

AI Governance by Human Rights-Centred Design, Deliberation and Oversight: An End to Ethics Washing

In Defence of Principlism in AI Ethics and Governance

A ‘biased’ emerging governance regime for artificial intelligence? How AI ethics get skewed moving from …

Overcoming Barriers to Cross-cultural Cooperation in AI Ethics and Governance

Abstract Achieving the global benefits of artificial intelligence (AI) will require international cooperation on many areas of governance and ethical standards, while allowing for diverse …

Conversational Explanations of Machine Learning Predictions Through Class-contrastive Counterfactual Statements

Machine learning models have become pervasive in our everyday life; they decide on important matters influencing our education, employment and judicial system. Many of these …