With her blog post about toxic bro-culture at Uber, Susan Fowler proved that one person can make a difference
|| Diversity Equity and Inclusion || Media Article || Short (5 min or less)
|| Diversity Equity and Inclusion || Media Article || Short (5 min or less)
|| Diversity Equity and Inclusion || Media Article || Short (5 min or less)
James Damore, the man fired by Google last year after he wrote a memo arguing that there may be biological reasons why women are underrepresented at Google and other tech companies, has sued his former employer.
|| Diversity Equity and Inclusion || Media Article || Short (5 min or less)
The science in Damore’s memo is still very much in play, and his analysis of its implications is at best politically naive and at worst dangerous.
|| Diversity Equity and Inclusion || Media Article || Short (5 min or less)
Tech companies are spending hundreds of millions of dollars to improve conditions for female employees. Here’s why not much has changed—and what might actually work.
|| Diversity Equity and Inclusion || Media Article || Short (5 min or less)
An analysis of premiums and payouts in California, Illinois, Texas and Missouri shows that some major insurers charge minority neighborhoods as much as 30 percent more than other areas with similar accident costs.
|| Diversity Equity and Inclusion || Media Article || Short (5 min or less)
Amazon, Verizon, UPS and Facebook among others were found to be limiting job ads to limited age groups.
|| Diversity Equity and Inclusion || Media Article || Short (5 min or less)
Facebook’s system allows advertisers to exclude black, Hispanic, and other “ethnic affinities” from seeing ads.
|| Algorithmic Bias || Report || Short (5 min or less)
This paper seeks to study how computerized decision-making techniques compare to one another, and what accounts for the differences.
|| Algorithmic Bias || Media Article || Short (5 min or less)
There’s software used across the country to predict future criminals. And it’s biased against blacks.
|| Algorithmic Bias || Media Article || Short (5 min or less)
U of Texas at Austin has stopped using a machine-learning system to evaluate applicants for its Ph.D. in computer science. Critics say the system exacerbates existing inequality in the field.