If you're using your phone or laptop and thinking everything feels super glitchy and janky, you're not alone. But it's not necessarily AI's fault. My latest for @inc.com pinpoints what's going on www.inc.com/chris-stokel...
This week's post is about #AI, #metaphors and magic, and, inspired by @davemurrayrust.bsky.social and @mlucel.bsky.social, how to deal with the enchantment through design makingsciencepublic.com/2026/02/27/m...
Social workers’ AI tool makes ‘gibberish’ transcripts of accounts from children www.theguardian.com/education/20...
pca.st/episode/da72... this was an interesting listen, might get the book, by José Marichal
Yes, I think so. Essentially, services offering an AI powered variant on the polygraph
Can anybody point me towards any academic research on AI lie detectors? Evaluative studies or critical STS perspectives perhaps?
The creator of Nearby Glasses made the app after reading 404 Media's coverage of how people are using Meta's Ray-Bans smartglasses to film people without their knowledge or consent. “I consider it to be a tiny part of resistance against surveillance tech.”
We wanted to draw attention to this in one of our agent scenarios: that there are likely to be privacy impacts based on people being able to easily task agents to find information on other people. The harassment part is outside our remit, but very likely.
I tried to make a "you're having me on? / Avignon?" joke here, but couldn't get it to work.
Thank you. I think an emergent, socially-grounded answer makes more sense to me than something like "around 0.005 encyclopedias".
Sure. Agree you can't be an expert on everything. If you should deepen your domain of expertise, it'd be useful to know what reasonably counts as a domain.. so history, or history of France, or history of medieval France, or...
Cat, do you have any examples of how 'big' an attainable domain of individual expertise might be?
AI mockup of the cover of a report. Titled ICO tech futures report, agentic AI. It features they stereotypical humanoid robot face made out of circuits...
We were quite careful to avoid humanoid robots as illustrations for AI agents. Then our report is publishrd and people create their own AI mockups of a cover to illustrate their linkedin takes, and the robots return...
Please consider applying for the 10th edition of CNIL-Inria Privacy Award.
The CNIL-Inria Privacy Award is intended to promote research in Computer Science and Privacy and to raise awareness among citizens and decision-makers on privacy and data protection issues.
1/2
Given my job, I have many, many opportunities to use this joke.
I apologise profusely to everybody in advance.
The UK government consultation on a proposed AI Growth Lab closed recently.
How can this regulatory sandbox contribute to governing AI in the public interest?
Elsa Donnat highlights the key design choices for building UK regulatory capacity for AI.
www.adalovelaceinstitute.org/blog/regulat...
Possible retirement hobby:
www.anthropic.com/news/claude-... little bit manifesto, little bit person spec, little bit binding spell
Just gave a presentation online Messed up the screen sharing, got flustered, now feeling awkward. Watching videos from Davos to recalibrate.
These two should do the research functions at data protection authorities for their next paper
If an AI system cannot show who authorized a decision, it should not be making it. Wrote about judgment routing, signing authority, and why invisible discretion is dangerous:
makingpublicwork.com/who-holds-th...
My latest on Substack -- a write-up of the talk I gave at NeurIPS in December.
aiguide.substack.com/p/on-evaluat...
Come and work with me! I'm so excited about the way this project is developing 😊
#PhDSky #AcademicSky #XR #VR #AR
For much more detail and particularly the impacts for regulation, and data protection of agentic AI have a look at ico.org.uk/about-the-ic...
4) Ubiquitous agents. High adoption of high capability agentic AI (but not AGI) gets closer to current marketing hype. Agentic systems mediate vast amounts of personal data and interactions between agents become highly complex.
3) Agents in waiting: low adoption despite increased capabilities and mitigations of llm risks, due to sociotechnical factors (maybe inc compliance or liability concerns). Orgs that do deploy tend to be knowledgeable and deployments are bespoke. Public use of agents is uncommon.
2) Just good enough to be everywhere: High adoption of agentic despite limited capabilities. Embedded in lots of digital infrastructure. Aggressive marketing. Lots of inappropriate or unwise use, and impacts from failures and errors.
1) Scarce, simple agents. Low adoption because of limited capability, close to current baseline. Challenges of LLMs remain. Agentic doesn't live up to hype. It's a toy, an experiment. Heavy supervision needed to get value from agents. Some orgs get burned. We see use cases that aren't feasible.
