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.
Who's Who of AI
Alexandra Olteanu
Why they matter
Researcher with public evidence across Responsible AI, AI research.
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Ethical/Responsible AI. Rigor in AI. Grumpy eastern european in north america. Lovingly nitpicky.
What they're sharing
Back-to-basics: on poor conceptualizations in AI work - (Un)rigorous AI rigor-in-ai.leaflet.pub
Back-to-basics: unobservable constructs and their ‘surplus meaning’ - (Un)rigorous AI rigor-in-ai.leaflet.pub
Articles & links
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.
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