Welcome! Please contribute your ideas for what challenges we might aspire to solve, changes in our community that can improve machine learning impact, and examples of machine learning projects that have had tangible impact.
Lacking context for this site? Read the original paper: Machine Learning that Matters (ICML 2012). You can also review the slides.
How can we combat algorithm aversion?
  • I highly recommend this fascinating study, from the Journal of Experimental Psychology.  It investigates the reasons why people may choose to trust a human's forecasts over an algorithm's forecasts, even when the algorithm is demonstrably superior.

    "Algorithm Aversion: People Erroneously Avoid Algorithms after Seeing Them Err"

    There are a lot of interesting psychological issues wrapped up in the decisions people make about whether to trust algorithms (or models, or ML systems).  In trying to get our ML systems adopted, we may not be paying enough attention to these non-obvious barriers.  Can we find ways to overcome algorithm aversion?


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