The best bit? The regulations cover the complete system’s life cycle by mandating assessment to be continuous, not check-once-and-forget checkbox lists. Interestingly, assessment results *need* to be made public! 5/5

High-risk systems get explicit requirements not only for explainability but also contestability! It is good to see a distinction between the two processes/ values (see our work with Aler Tubella, Michael, and @vdignum.bsky.social: arxiv.org/abs/2006.05133 ) 4/5

Regardless of the risk level, a great deal of emphasis is placed on 4 core rights: the right to information; the right to data privacy and protection; the right to human choice and participation; and the right to non-discrimination and bias correction. 3/5

...including ones "that employ subliminal techniques that have the purpose or effect of inducing a natural person to behave in a manner that is harmful or dangerous to their health or safety " This is IMO vague as we often anthropomorphise AI systems. Courts may have to decide what is 'harmful.' 2/5

And yes, this applies to continental Europe universities too as they are, increasingly, follow the British trend of going after metrics while also reducing education spending.

Probably because it provides an incentive to produce data that are 'publication worthy.' A financial or some other form of payout at the end of the study is guaranteed regardless of the study results. Moreover, keeping private data associated with the research data would create a nightmare for DPOs.

I just got a TiaGO robot —meant to be more robust and powerful than Pepper, but also costs 5x as much— where I plan to port the code!

A shoutout to my PhD supervisor @j2bryson.bsky.social whose social media policy (joanna-bryson.blogspot.com/2024/10/guid...) inspired me to join. 2/2