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analytics & machine learning

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Cognitive bias in algorithms, baseball analytics denied, and soft skills ROI.

31 January 2018By
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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Value your gut, plus the perils of decision fatigue.

7 November 2017By
1. “A gut is a personal, nontransferable attribute, which increases the value of a good one.” This classic from Harvard Business Review recaps how policy makers have historically made big decisions. It’s never just about the data. A Brief History of Decision Making. 2. A reminder to look for the nonobvious. This analysis examines differences...
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man and woman about to feed each other

“Big E” vs. “little e” evidence, and probabilistic thinking.

5 November 2017By
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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Underwriters + algorithms, avoiding bad choices, and evidence for rare illness.

3 August 2017By
1. Underwriters + algorithms = Best of both worlds. We hear so much about machine automation replacing humans. But several promising applications are designed to supplement complex human knowledge and guide decisions, not replace them: Think primary care physicians, policy makers, or underwriters. Leslie Scism writes in the Wall Street Journal that AIG “pairs its...
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kitten on keyboard awww!

Algorithm reluctance, home-visit showdown, and the problem with wearables.

28 July 2017By
Yikes, evidence-based decisions are taking on water. Decision makers still resist handing the car keys to others, even when machines make better predictions. And government agencies continue to, ahem, struggle with making evidence-based policy.  — Tracy Altman, editor 1. Evidence-based home visit program loses funding.The evidence base has developed over 30+ years. Advocates for home visit programs –...
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photo of people grouped together

False dichotomy: Data-driven vs. gut-feel

21 July 2017By
Smart decision-making is more complicated than becoming ‘data-driven’, whatever that means exactly. We know people can make better decisions if they consider relevant evidence, and that process is getting easier. But too often tech enthusiasts dismiss people’s decisions as based on gut feel, as if data will save us from ourselves. Let’s put an end to...
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Equity crowdfunding algorithms, decision-making competitions, and statistical wild geese.

16 March 2017By
1. CircleUp uses algorithm to evaluate consumer startups. Recently we wrote about #fintech startups who are challenging traditional consumer lending models. CircleUp is doing something similar to connect investors with non-tech consumer startups (food, cosmetics, recreation). It’s not yet a robo adviser for automated investing, but they do use machine learning to remove drudgery from...
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ROI from evidence-based government, milking data for cows, and flu shot benefits diminishing.

17 February 2017By
1. Evidence standards → Knowing what works → Pay for success Susan Urahn says we’ve reached a Tipping Point on Evidence-Based Policymaking. She explains in @Governing that 24 US governments have directed $152M to programs with an estimated $521M ROI: “an innovative and rigorous approach to policymaking: Create an inventory of currently funded programs; review...
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patient value

Valuing patient perspective, moneyball for tenure, visualizing education impacts.

28 December 2016By
1. Formalized decision process → Conflict about criteria It’s usually a good idea to establish a methodology for making repeatable, complex decisions. But inevitably you’ll have to allow wiggle room for the unquantifiable or the unexpected; leaving this gray area exposes you to criticism that it’s not a rigorous methodology after all. Other sources of...
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Everyone’s decision process, C-Suite judgment, and the Golden Gut.

28 December 2016By
1. SPOTLIGHT: MCDA, a decision process for everyone. ‘Multiple criteria decision analysis’ is a crummy name for a great concept (aren’t all big decisions analyzed using multiple criteria?). MCDA means assessing alternatives while simultaneously considering several objectives. It’s a useful way to look at difficult choices in healthcare, oil production, or real estate. But oftentimes,...
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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.

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