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How to blame a robot for mistakes: Do your finger pointing properly.

19 August 2021By
People and artificial intelligence work together, sometimes quite nicely, on insurance underwriting, medical diagnosis, customer experience. (Plus autonomous vehicles, until some dude crashes his Tesla.) This is the Human+AI hybrid we often talk about at Museum of AI. Humans have varying levels of awareness, input, or control over an AI system. Evidence suggests these factors...
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How fun & games can make us better at deciding.

20 May 2019By
What is a fun experience really about? I’ve gained new perspective from Fun, Taste, & Games: An Aesthetics of the Idle, Unproductive, and Otherwise Playful (MIT Press). I have first-hand knowledge that the authors, John Sharp (Parsons/New School) and David Thomas, are in fact, fun: They would probably join you at Casa Bonita*. John and...
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silver corded microphone in shallow focus photography

Our #1 fear: Withering under scrutiny.

6 February 2019By
Jerry Seinfeld was wrong when he claimed public speaking is our #1 fear. I’m pretty sure we’re more afraid of having our decisions scrutinized. Adding to the fun, now algorithmic decisions are under pressure too. It is rather painful to have decisions second-guessed before the numbers come in, and even worse if things go pear-shaped....
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Papers We Love: Judgment Under Uncertainty / Cognitive Bias

17 January 2018By
Our founder, Tracy Allison Altman, will talk about cognitive bias and behavioral economics for software design @ Papers We Love – Denver. Tversky and Kahneman’s classic “Judgment under Uncertainty: Heuristics and Biases” challenged conventional thinking about bias in decision making, inspiring new approaches to cognitive science, choice architecture, public policy, and the underlying technology. Join...
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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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laptop covered with sticky notes

Analytics teams need to be insight integrators.

5 July 2017By
1. Lori C. Bieda of SAS is spot on, describing how analytics professionals can grow into roles as trusted advisors for senior executives. In The Translation Layer: The Role of Analytic Talent, she explains that “Analytics teams… need to evolve from data providers into insight integrators.” Lots of detailed observations and recommendations in this white...
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monitor showing code

The Cardinal Sin of data science, and cognitive bias in 5 easy steps.

20 July 2016By
1. Confusing correlation with causation is not the Cardinal Sin of data science, say Gregory Piatetsky (@kdnuggets) and Anmol Rajpurohit (@hey_anmol): It’s overfitting. Oftentimes, researchers “test numerous hypotheses without proper statistical control, until they happen to find something interesting and report it. Not surprisingly, next time the effect, which was (at least partly) due to...
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Bad logic=bad decisions, evidence-based youth programs, and a fresh hell of confusing numbers.

11 June 2016By
1. Bad logic → Bad arguments → Bad decisions The Book of Bad Arguments is a simple explanation of common logical flaws / barriers to successful, evidence-based decisions. This beautifully illustrated work by Ali Almossawi (@AliAlmossawi) should be on everyone’s bookshelf. Now available in several languages. 2. Home visits for children → Lifelong benefits →...
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Mistakes we make, Evidence Index, and Lebron vs Steph.

8 June 2016By
1. Mistakes we make when sharing insights. We’ve all done this: Hurried to share valuable, new information and neglected to frame it meaningfully, thus slowing the impact and possibly alienating our audience. Michael Shrage describes a perfect example, taken from The Only Rule Is It Has to Work, a fantastic book about analytics innovation. The...
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photo of stadium seats

Masters of self-deception, rapid systematic reviews, and Gauss v. Legendre.

24 April 2016By
1. Human fallibility → Debiasing techniques → Better science Don’t miss Regina Nuzzo’s fantastic analysis in Nature: How scientists trick themselves, and how they can stop. @ReginaNuzzo explains why people are masters of self-deception, and how cognitive biases interfere with rigorous findings. Making things worse are a flawed science publishing process and “performance enhancing” statistical...
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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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