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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8 years ago
Blatantly Discriminatory Machines: When Algorithms Explicitly Penalize

 Originally published in The San Francisco Chronicle (the cover article of Sunday’s “Insight” section) What if the data tells you to be racist? Without the right precautions, machine learning — the technology that drives risk-assessment in law enforcement, as well as hiring and loan decisions — explicitly penalizes underprivileged groups. Left to its own devices, the algorithm will count a black defendant’s race as a strike against them. Yet some data scientists are calling to turn off the safeguards and unleash computerized prejudice, signaling an emerging threat that supersedes the well-known concerns about inadvertent machine bias. Imagine sitting

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