Machine Learning Times
Machine Learning Times
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Diversity and Collaborative Problem Solving to Address Wicked Data Ethics Problems
 The complexity of the ethical issues facing professionals who...
Climate Tech Needs Machine Learning, Says PAW Climate Conference Chair
  Straight from the horse’s mouth – the founding...
Predictive Policing: Six Ethical Predicaments
  Originally published in KDNuggets. This article is based...
Measuring Invisible Treatment Effects with Uplift Analysis
  Models make predictions by identifying consistent correlations in...

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 Originally published in MIT Technology Review, Nov 18, 2020. The process used to build...

 Originally published in Forbes, Nov 23, 2020. The most obvious way that artificial intelligence...

 Originally published in Reuters, Nov 9, 2020. TBILISI (Thomson Reuters Foundation) – When Anna...

  • 5 days ago
    Diversity and Collaborative Problem Solving to Address Wicked Data Ethics Problems

     

     The complexity of the ethical issues facing professionals who work in machine learning, data science, analytics, and related professions have all the hallmarks of a “wicked problem”.  Rittel and Weber, the researchers responsible for coining the term “wicked problems”, believed a more inclusive approach to problem-solving was especially important in diverse and pluralistic societies where […]

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      Straight from the horse’s mouth – the founding chair of the all-new Predictive Analytics World for Climate, Eugene Kirpichov, along with his colleague, Cassandra Xia – read this article for the central role machine learning has to play for climate tech and access the viral “Goodbye, Google” posts that marked their departure from big […]

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      Originally published in KDNuggets. This article is based on a transcript from Eric Siegel’s Machine Learning for Everyone. View the video version of this specific article Nowhere could the application of machine learning prove more important — nor more risky — than in law enforcement and national security. In this article, I’ll review this […]

  • 2 weeks ago
    Measuring Invisible Treatment Effects with Uplift Analysis

     

      Models make predictions by identifying consistent correlations in what has been observed, but we usually require more than predictions to know what action we should take. For example, knowing that older people are more likely to have heart disease is a good first step, but knowing behaviors or treatments that will reduce the risk […]

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      In this article, I identify unmet learner needs that are addressed by my business-oriented machine learning course series, Machine Learning for Everyone. Machine learning runs the world. It drives millions of business-critical decisions more effectively, guided by concrete evidence in the form of data – determining whom to call, mail, approve, test, diagnose, warn, […]

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      It’s the age of machine learning. Companies are seizing upon the power of this technology to combat risk, boost sales, cut costs, block fraud, streamline manufacturing, conquer spam, toughen crime fighting, and win elections. But while there are so many how-to training programs for hands-on techies, there are practically none that also serve business […]

  • 1 month ago
    Ethical Machine Learning as a Wicked Problem

     

     In the 1950 and 1960s, social and behavioral sciences were at the cutting edge of innovation. Scientific techniques and quantitative analyses were being applied to some of the most pressing social problems. The thinking was “If NASA can put men in space, why can’t we use these techniques to solve the problems of housing discrimination […]

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