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1. Recognize bias → Create better algorithmsCan we humans better recognize our biases before we turn the machines loose, fully automating them? Here’s a sample of recent caveats about decision-making fails: While improving some lives, we’re making others worse. Yikes. From HBR, Hiring algorithms are not neutral. If you set up your resume-screening algorithm to...
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1. It’s tempting to think there’s a hierarchy for data: That evidence from high-quality experiments is on top at Level 1, and other research findings follow thereafter. But even in healthcare – the gold standard for the “gold standard” – it’s not that simple, says NICE in The NICE Way: Lessons for Social Policy and...
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Museum musings.

Pondering the places where people interact with artificial intelligence: Collaboration on evidence-based decision-making, automation of data-driven processes, machine learning, things like that.

Recent Articles

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20 June 2023
Stolen cars and AI ‘moral self-correction’
person in silhouette with orange background, pondering AI input for an evidence based decision
9 May 2023
Can you trust AI with your next decision? Part 3 in a series on fact-checking/citation
image generated by bing image creator bottle on apothecary shelf
25 April 2023
How is generative AI referencing sources? Part 2 in our series
22 April 2023
Sneaky STEM: Inspire learning with immersive experiences
15 March 2023
Can AI replace your CEO?