The Workflows Community Summit gathered 111 participants from 18 countries to discuss
emerging trends and challenges in scientific workflows, focusing on six key areas: time …

This paper focuses on the opportunities and the ethical and societal risks posed by
advanced AI assistants. We define advanced AI assistants as artificial agents with natural …

Large-scale GPS location datasets hold immense potential for measuring human mobility
and interpersonal contact, both of which are essential for data-driven epidemiology …

Developments in medical big data analytics may bring societal benefits but are also
challenging privacy and other ethical values. At the same time, an overly restrictive data …

Big data and artificial intelligence are key elements in the medical field as they are expected
to improve accuracy and efficiency in diagnosis and treatment, particularly in identifying …

As AI assistants become increasingly sophisticated and deeply integrated into our lives,
questions of trust rise to the forefront. In this paper, we build on philosophical studies of trust …

Given that scientific practices contribute to the climate crisis, scientists should reflect on the
planetary impact of their work. Research computing can have a substantial carbon footprint …

Digitalisation of health and the use of health data in artificial intelligence, and machine
learning (ML), including for applications that will then in turn be used in healthcare are major …

Early-stage drug discovery is highly dependent upon drug target evaluation, understanding
of disease progression and identification of patient characteristics linked to disease …

In their highly topical paper, Graham et al argued that Trusted Research Environments
(TREs) are not actually about trust because they reduce or remove '… the need for trust in …