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Stolen cars and AI ‘moral self-correction’

20 June 2023By
Is AI getting closer to human values? It’s no secret that algorithms can produce systemically biased recommendations, such as in lending decisions. Some good news: A team at Anthropic tested the hypothesis that “language models trained with reinforcement learning from human feedback (RLHF) have the capability to ‘morally self-correct’ — to avoid producing harmful outputs...
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Can AI replace your CEO?

15 March 2023By
The Hustle recently asked Should we automate the CEO? And the question isn’t facetious: Instead Zachary Crockett walks us through data showing many CEOs earn ~300X the pay of an average worker, and more than a few run underperforming companies. ” Tasks ripe for automation include reviewing forecasts and sending emails; some experts believe 40%...
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woman exiting revolving door

Struggling to explain AI? Try this before|after strategy.

30 January 2020By
To cut through AI complexity, focus on decisions. Never has it been more important to effectively explain complex concepts. Technology is influencing most decision processes, not always transparently so. On the bumpy road toward explainable AI (XAI), we find great communication options, from printed materials to state-of-the-art experiences. But where do you start, or know...
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The skill set for explaining, XAI, and why they both matter.

1 December 2018By
As data complexity grows, so does the importance of explaining. The philosophy of science can teach us about the role of explaining in high-quality, evidence-based decisions. It’s not just navel-gazing: An explanation is a statement that makes something clear, or a reason or justification given for an action or belief. It describes “a set of...
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PitchLab shows how to present complex technology.

13 September 2018By
Present everything better! As co-organizer of the meetups Papers We Love – Denver and Domain-Driven Design – Denver, I was delighted to co-host PitchLab for a talk on presentation skills. Jay Mays and Keefer Caid-Loos did an excellent job explaining how to connect with your audience. Participants were engaged, and appreciated PitchLab’s approachable, ask-me-anything attitude. The...
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Building trust in the decision process

Evaluate your decision process separately from your outcomes.

12 August 2018By
How we decide is no less important than the data we use to decide. People are recognizing this and creating innovative ways to blend what, why, and how into decision processes. 1. Apply behavioral science → Less cognitive bias McKinsey experts offer excellent insight into Behavioral science in business: Nudging, debiasing, and managing the irrational...
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fox

What makes us trust analytics, and how to argue.

7 June 2018By
1. Prior experience → More trust In Trustworthy Data Analysis, Roger Peng gives an elegant description of how he evaluates analytics presentations, and what factors influence his trust level. First, he imagines analytical work in three buckets: A (the material presented), B (work done but not presented), and C (analytical work not done). “We can...
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Weaponizing KPIs and debiasing decision algorithms.

31 May 2018By
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

What cancer decision trees can teach us.

22 May 2018By
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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Debiasing is painful, why analytics fail, and health app evidence.

15 May 2018By
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

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?
reference to Google's Bard AI and Microsoft's Bing AI compared to conflict at Sopranos Bada Bing
28 February 2023
What’s state-of-the-art when an AI cites sources of evidence? Part 1 in our series