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Video Surveillance

Why the AI Industry Faces a Diversity 'Crisis'

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April 17, 2019

The under-representation of women and people of color across the field of artificial intelligence is causing a “diversity crisis” that is contributing to the creation of flawed systems and technology, according to a New York University research center report.

According to the study, about 80 percent of AI professors are men, while just 15 percent of AI research staff at Facebook and 10 percent at Google are women. Just 2.5 percent of Google’s workforce is black while Facebook and Microsoft are both right around 4% each – and the under-representation of women of color is even worse, the report notes. What’s more, “there is no public data on trans workers or other gender minorities.”

The AI sector needs a profound shift in how it addresses the current diversity crisis, the study said. "The industry needs to acknowledge the gravity of its diversity problem, and admit that existing methods have failed to contend with the uneven distribution of power, and the means by which AI can reinforce such inequality. Further, many researchers have shown that bias in AI systems reflects historical patterns of discrimination. These are two manifestations of the same problem,and they must be addressed together."

In addition, the study noted that the overwhelming focus on ‘women in tech’ is too narrow and likely to privilege white women over others. "We need to acknowledge how the intersections of race, gender, and other identities and attributes shape people’s experiences with AI. The vast majority of AI studies assume gender is binary, and commonly assign people as ‘male’ or ‘female’ based on physical appearance and stereotypical assumptions, erasing all other forms of gender identity."

The study noted that fixing the ‘pipeline’ won’t fix AI’s diversity problems; that the focus on the pipeline has not addressed deeper issues with workplace cultures, power asymmetries, harassment, exclusionary hiring practices, unfair compensation, and tokenization that are causing people to leave or avoid working in the AI sector altogether.

The report offers several recommendations for improving workplace diversity, including:

  1. Publish compensation levels, including bonuses and equity, across all roles and job categories,broken down by race and gender.
  2. End pay and opportunity inequality, and set pay and benefit equity goals that include contract workers, temps, and vendors.
  3. Publish harassment and discrimination transparency reports, including the number of claims over time, the types of claims submitted, and actions taken.
  4. Change hiring practices to maximize diversity: include targeted recruitment beyond elite universities, ensure more equitable focus on under-represented groups, and create more pathways for contractors, temps, and vendors to become full-time employees.
  5. Commit to transparency around hiring practices, especially regarding how candidates are leveled, compensated, and promoted.
KEYWORDS: artificial intelligence (AI) Artificial Intelligence (AI) Security

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