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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Building trust in the decision process
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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1. Biased instructor response → Students shut out Definitely not awesome. Stanford’s Center for Education Policy Analysis reports Bias in Online Classes: Evidence from a Field Experiment. “We find that instructors are 94% more likely to respond to forum posts by white male students. In contrast, we do not find general evidence of biases in...
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Translators at IFLA 2010
1. Hire analytics translators → Keep data scientists happy An emerging role – what some call the Analytics Translator – is offloading burden from data scientists, while helping business executives get better value from their technology investments. A recent HBR piece explains You Don’t Have to Be a Data Scientist to Fill This Must-Have Analytics...
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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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