How fun & games can make us better at deciding.
Our #1 fear: Withering under scrutiny.
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 […]
Papers We Love: Judgment Under Uncertainty / Cognitive Bias
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. […]
Algorithm reluctance, home-visit showdown, and the problem with wearables.
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 […]
Analytics teams need to be insight integrators.
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 […]
The Cardinal Sin of data science, and cognitive bias in 5 easy steps.
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 […]
Masters of self-deception, rapid systematic reviews, and Gauss v. Legendre.
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 […]
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 […]