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January 2018

Month

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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data visualization of crime statistics using Tableau

But where is the decision? Data visualizations don’t show the why and how.

29 January 2018By
Technology helps us discover meaningful patterns: Buying behavior, criminal activity, health effects. But when we succumb to pretty pictures and mindless measurement, shiny data fails to help answer important questions. Source: Tableau. This data visualization tool would be great for someone seeking crime stats – say, for law enforcement or house buying. But it doesn’t...
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Long-term thinking, systems of intelligence, and the dangers of sloppy evidence.

24 January 2018By
1. Long view → Better financial performance.A McKinsey Global Institute team sought hard evidence supporting their observation that “Companies deliver superior results when executives manage for long-term value creation,” resisting pressure to focus on quarterly earnings (think Amazon or Unilever). So MGI developed the corporate horizon index, or CHI, to compare performance by firms exhibiting...
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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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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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