Machine Learning Times
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AGI Is Infeasible. Instead, Pursue Superhuman Adaptable Intelligence
  Originally published in Forbes On a recent episode of the...
Artifact-Driven Development: Making It Possible to Query Large Analytics and AI Projects
 A practical introduction to making complex project structure explicit...
Incoherent AGI Hype Spurs An Industrywide Pivot To Hybrid AI
  Originally published in Forbes Recently on The Dr. Data Show,...
The AI Paradox: More Humanlike Means Less Autonomous
  Originally published in Forbes The AI executives are at...
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11 years ago
Trust in Analytics Work: Why it’s Needed and How to Build It

 Much has been written about data-driven decision making. Someone new to analytics in business might reasonably think that the days of gut instinct and experience driving decisions are over, replaced by statistical models, machine learning methods, and optimization techniques. This is not wholly inaccurate but it grossly overstates reality, at least in my experience. The reality is, data and analytics are not enough. To get emotional animals, often working in politically charged environments, to actually change decisions requires a lot of trust and consulting between colleagues. In what follows I’ll discuss an overlooked aspect of building trust in

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