We invite researchers and practitioners to join us in examining how scientific reasoning and imagination are being reconfigured as AI systems become a part of the everyday practice of science. Learn m...

The idea that machines will be as smart as—or smarter than—humans has hijacked an entire industry. But look closely and you’ll see it’s a myth that persists for many of the same reasons conspiracies d...

Companies often fail to refund money to victims and aggressively fight police to claw back scam money seized from machines.

Date and time Wednesday 15 October 2025, 9:00am to 2:00pm Location In-person, the Cabot, 25 Cabot Square, London. Registration for this event closes at 12pm on Thursday 9 October 2025. About this even...

Build trust, shape a culture and kick start conversations. Physical games for in person threat modelling, training and fun.

CAISI and NIST hosted an AISIC workshop with approximately 140 experts in January

Whenever we speak to public servants who are keen to involve the public more on decisions about data and AI, an early subject to be raised is always: who’s already done it, and how did they do it? People are understandably keen to learn from what has already been tried. This blog/case study is part of a series exploring how public sector organisations involve the public, workers and civil society in decisions about data and AI, and some of the consequences when they do not. Read more about our work on public involvement in public sector data and AI.

Innovation agencies in the EU are no longer fit for purpose. A major overhaul of both the concept of innovation and of institutional structures is urgent.

In a new communications landscape that feasts on polarization, the science community needs to rethink how it engages society in scientific discovery, controversy and policy.

Policy@Manchester’s publication On Critical Technologies offers sharp insights, robust evidence, and forward-thinking policy recommendations from leading experts at The University of Manchester.

The Guardian has obtained surveillance images taken by hired spies whose goal is said to have been identifying sources and gaining ‘leverage’

Patrick Hodge, supreme court’s deputy president, wants judges to improve their scientific and technical literacy

Join our Future Leaders workshop in collaboration with the RBOC Network+

The malfunctioning xAI chatbot provides some insights into how large language models work.

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models.

These guidelines focus on the scope of the obligations for providers of general-purpose AI models laid down in the AI Act, in light of their imminent entry into application on 2 August 2025.

Confronting the production-progress paradox

The AIs are designed to teach people about atrocities in Sudan.