Machine Learning Times
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The Data Disconnect: A Key Challenge for Machine Learning Deployment
  EDITOR’S NOTE: This article is excerpted from The...
A Brief History of Why Machine Learning Projects Stall
  EDITOR’S NOTE: This is the preface to The...
Hybrid AI Emerges To Tame LLMs – And Not A Moment Too Soon
 Originally published in Forbes The great potential of LLMs is...
AGI Is Infeasible. Instead, Pursue Superhuman Adaptable Intelligence
  Originally published in Forbes On a recent episode of the...
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12 years ago
It is a Mistake to…. Answer Every Inquiry

 (Part 9 (of 11) of the Top 10 Data Mining Mistakes, drawn from the Handbook of Statistical Analysis and Data Mining Applications) I’m tempted to start with a kind of query that experience teaches some of us not to answer, like “Does this data make me look fat?” But that actually misleads about the point I’m trying to make. Data Scientists (and their models) should answer all queries as truthfully as the evidence allows, regardless of how happy or unhappy that makes the questioner. What I am arguing here is we shouldn’t answer when our opinion is unqualified;

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