May 2018

Month

1. Vigilance → Better algorithms “Eliminating bias… requires constant vigilance on the part of not only data scientists but up and down the corporate ranks.” In an insightful Information Week commentary, James Kobielus (@jameskobielus) considers the importance of Debiasing Our Statistical Algorithms Down to Their Roots. “Rest assured that AI, machine learning, and other statistical...
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prostatecancerdecision.org
Suppose you’ve gotten a cancer diagnosis. Would your business experience help you navigate the care pathway? Larry Neal describes how he applied his Decision Analysis skills to prostate treatment in Eight Lessons from a Decision Professional’s Cancer Decision. When a physician said Neal had a 30% chance of having cancer, but his analysis suggested 95-99%,...
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1. Debiasing → Better decisions Debiasing is hard work, requiring honest communication and occasional stomach upset. But it gets easier and can become a habit, especially if people have a systematic way of checking their decisions for bias. In this podcast and interview transcript, Nobel-winning Richard Thaler explains several practical ways to debias decisions. First,...
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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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Stolen cars and AI ‘moral self-correction’
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Can you trust AI with your next decision? Part 3 in a series on fact-checking/citation
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25 April 2023
How is generative AI referencing sources? Part 2 in our series
15 March 2023
Can AI replace your CEO?
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28 February 2023
What’s state-of-the-art when an AI cites sources of evidence? Part 1 in our series