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James Damore: The Case for Diversity
A 2015 meta-analysis published in PLOS One showed that all-else-being-equal, “the mere representation of females on corporate boards is not related to firm financial performance”. Another 2015 meta-analysis published in the Academy of Management Journal also found that across 140 studies, the relationship between gender parity on boards and market performance was near zero. What seems to matter most is not the gender of executives on a board, but their individual talents and team cohesiveness.

What about other kinds of diversity? Scott Page argues in The Diversity Bonus: How Good Teams Pay Off in the Knowledge Economy that cognitively diverse teams can lead to more innovation and better decision making. Indeed, this has been demonstrated by a recent study titled The Wisdom of Polarized Crowds (ªªhttps://arxiv.org/abs/1712.06414) whichºº found that polarization among Wikipedia editors leads to articles of higher quality.
JamesDamore  Feminism  Diversity  DasGeileNeueInternet  ncpin  nct 
4 hours ago by walt74
Close the digital skills gap and gain the talent edge – lessons from diginomica’s diversity coverage - by @jonerp
"It's easy for workplace diversity to become a useless, feel good cliché. But there are field lessons and data that should be reckoned with. Here's my review of diginomica's recent diversity coverage."
digital  skills  and  training  diversity  hcm  the  future  of  work  new  professional  it  as  a  service 
19 hours ago by jonerp
Algorithms are making American inequality worse - MIT Technology Review
In Automating Inequality, author Virginia Eubanks argues that the poor are the testing ground for new technology that increases inequality. The book, out this week, starts with a history of American poorhouses, which dotted the landscape starting in the 1660s and were around into the 20th century. From there, Eubanks catalogues how the poor have been treated over the last hundred years, before coming to today’s system of social services that increasingly relies on algorithms.

Eubanks leaves no uncertainty as to her position on whether such automation is a good thing. Her thesis is that the punitive and moralistic view of poverty that built the poorhouses never left us, and has been wrapped into today’s automated and predictive decision-making tools. These algorithms can make it harder for people to get services while forcing them to deal with an invasive process of personal data collection. As examples, she profiles three different programs: a Medicaid application process in Indiana, homeless services in Los Angeles, and child protective services in Pittsburgh.
technology  diversity  economics  fail  future  algorithms  ai  casestudies 
2 days ago by dancall

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