Artificial intelligence (AI) is producing highly beneficial impacts in many domains, from
transport to healthcare, from energy distribution to marketing, but it also raises concerns …

Bias, unfairness and lack of transparency and accountability in Artificial Intelligence (AI)
systems, and the potential for the misuse of predictive models for decision-making have …

The concept of innovation ecosystems has become prominent due to its explanatory power.
It offers a convincing account of innovation, explaining how and why innovation pathways …

Algorithmic impact assessments (AIAs) are an emergent form of accountability for
organizations that build and deploy automated decision-support systems. They are modeled …

Big Data has gained much attention from the academia and the IT industry. In the digital and
computing world, information is generated and collected at a rate that rapidly exceeds the …

Following years of intensive international debate of the ethical and human rights
implications of artificial intelligence (AI)-related technologies, there are numerous proposals …

The ethics of artificial intelligence (AI) is a widely discussed topic. There are numerous
initiatives that aim to develop the principles and guidance to ensure that the development …

Over the years, companies have adopted hiring algorithms because they promise wider job
candidate pools, lower recruitment costs and less human bias. Despite these promises, they …

The concept of responsible research and innovation (RRI) is increasingly used to describe
novel ways of governing research and the relationship between key research stakeholders …

While digital health or mHealth applications (apps) have become accessible resources for
the support of personal health, the privacy and security of users' data have been the subject …