ai diversity report lack industry field systems

‘Disastrous’ lack of diversity in AI industry perpetuates bias, study findsLack of diversity in the artificial intelligence field has reached “a momentof reckoning”, according to new findings published by a New York Universityresearch center. A “diversity disaster” has contributed to flawed systems thatperpetuate gender and racial biases found the survey, published by the AI NowInstitute, of more than 150 studies and reports.The AI field, which is overwhelmingly white and male, is at risk ofreplicating or perpetuating historical biases and power imbalances, the reportsaid. Examples cited include image recognition services making offensiveclassifications of minorities, chatbots adopting hate speech, and Amazontechnology failing to recognize users with darker skin colors. The biases ofsystems built by the AI industry can be largely attributed to the lack ofdiversity within the field itself, the report said.“The industry has to acknowledge the gravity of the situation and admit thatits existing methods have failed to address these problems,” Kate Crawford, anauthor on the report said. “The use of AI systems for the classification,detection, and prediction of race and gender is in urgent need of re-evaluation.”More than 80% of AI professors are men, and only 15% of AI researchers atFacebook and 10% of AI researchers at Google are women, the report said. Themakeup of the AI field is reflective of “a larger problem across computerscience, Stem fields, and even more broadly, society as a whole”, said DanaëMetaxa, a PhD candidate and researcher at Stanford focused on issues ofinternet and democracy. Women comprised only 24% of the field of computer andinformation sciences in 2015, according to the National Science Board. Only2.5% of Google’s workforce is black, while Facebook and Microsoft are each at4%, and little data exists on trans workers or other gender minorities in theAI field.“The urgency behind this issue is increasing as AI becomes increasinglyintegrated into society,” Metaxa said. “Essentially, the lack of diversity inAI is concentrating an increasingly large amount of power and capital in thehands of a select subset of people.”> The use of AI systems for the classification, detection, and prediction of> race and gender is in urgent need of re-evaluationKate Crawford, report authorVenture capital funding for AI startups reached record levels in 2018,increasing 72% compared to 2017 to $9.33bn in funding. Active AI startups inthe US increased 113% from 2015 to 2018. As more money and resources areinvested into AI, companies have the opportunity to address the crisis as itunfolds, said Tess Posner, the chief executive officer of AI4ALL, a not-for-profit that works to increase diversity in the AI field. This lack ofdiversity must be addressed before AI reaches a “tipping point”, she said.“Every day that goes by it gets more difficult to solve the problem,” shesaid. “Right now we are in an exciting moment where we can make a differencebefore we see how much more complicated it can get later.”The report released on Tuesday cautioned against addressing diversity in thetech industry by fixing the “pipeline” problem, or the makeup of who is hired,alone. Men currently make up 71% of the applicant pool for AI jobs in the US,according to the 2018 AI Index, an independent report on the industry releasedannually. The AI institute suggested additional measures, including publishingcompensation levels for workers publicly, sharing harassment anddiscrimination transparency reports, and changing hiring practices to increasethe number of underrepresented groups at all levels.Google disbanded an artificial intelligence ethics council meant to overseesuch issues just one week after announcing it in March. The AdvancedTechnology External Advisory Council (ATEAC) was attracted backlash inside andoutside the company after it appointed the anti-LGBT advocate Kay Coles James.Posner noted that additional efforts to increase transparency around howalgorithms are built and how they work may be necessary to fix the diversityproblems in AI. This month, the US senators Cory Booker and Ron Wydenintroduced the Algorithmic Accountability Act, a bill that would requirealgorithms used by companies that make more than $50m per year or holdinformation on at least 1 million users to be evaluated for biases.“The core of the problem is whether market forces are going to be sufficientfor this to be fixed,” Posner said. “It’s going to take effort at all stagesof AI and take change at cultural and procedural levels to solve this.”