Alexandra Olteanu

I'm in Europe, and next week I'll be in Malmö (for #AIES until Weds) & Copenhagen speaking at the Pioneer Center for AI on Thurs www.aicentre.dk/events/20261... Thank you @gretawarren.bsky.social & @iaugenstein.bsky.social for hosting me! If you are around and want to chat/cat…

P1 guest talk by Responsible AI researcher Alexandra Olteanu | Event | Pioneer Centre for Artificial Intelligence aicentre.dk

Wrote a brief reflection on poor conceptualizations in AI work and why they matter, something I believe is so startlingly neglected. TL;DR - Poor conceptual foundations can severely undermine the credibility and reliability of knowledge claims.

Back-to-basics: on poor conceptualizations in AI work - (Un)rigorous AI rigor-in-ai.leaflet.pub

So what do AI evaluations do or should do? Wrote a brief reflection about prototypical questions evaluations often try to answer and why it is useful to have clarity about what exactly one is trying to learn about some phenomenon of interest. rigor-in-ai.leaflet.pub/3ms4ax4sojs2j

Back-to-basics: so what do evaluations do - (Un)rigorous AI rigor-in-ai.leaflet.pub

Wrote another brief post motivated by a reflection on how in AI research folks might not fully appreciate the care that working with unobservable constructs requires. TL;DR -- Because unobservable constructs hold ‘surplus meaning,’ your metric is not your construct.

Back-to-basics: unobservable constructs and their ‘surplus meaning’ - (Un)rigorous AI rigor-in-ai.leaflet.pub

AI alignment is at the centre of the growing debates about AI systems and their failures. The impulses of AI alignment work are however *not* new. Making sure computational systems do what we want them to do has long been a core goal of computing research.