Six ways machine learning threatens social justice

Machine learning is a powerful and imperfect tool that should not go unmonitored.

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  • When you harness the power and potential of machine learning, there are also some drastic downsides that you've got to manage.
  • Deploying machine learning, you face the risk that it be discriminatory, biased, inequitable, exploitative, or opaque.
  • In this article, I cover six ways that machine learning threatens social justice and reach an incisive conclusion: The remedy is to take on machine learning standardization as a form of social activism.
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The one book you need to understand alt-right trolls

Antisocial is a deep dive into the extremist views.

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  • The New Yorker's Adam Marantz spent three years embedded with leading alt-right voices.
  • His book, Antisocial, carries you deep inside the mindset and motivation behind online trolling.
  • To get back on track, Marantz believes we need a "new moral vocabulary."
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Scientists can now predict at birth who will have academic success

Study identifies predictors of which students are likely to do well in education.

  • Researchers looked at data from 5,000 students and found 2 factors that were strongly linked to academic success.
  • Students with genetic predisposition towards academics were much more likely to go to University.
  • Equally important was having well-educated parents with wealth.
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Big companies can be a force for good—if they ask the right questions

Transformation of big companies is really important if we want to create a system that is fairer, more sustainable and less unequal.

  • Large companies can and should ask themselves "Where can we collaborate? Where can we pre-compete?"
  • Both collaboration and competition can help big business be the force for good.
  • B Corp certifications can lead to companies being more purposeful and transparent.
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