Two months after the jarring departure of a well known synthetic intelligence researcher at Google, a second A.I. researcher at the company stated she was fired after criticizing the approach it has handled workers who have been engaged on methods to handle bias and toxicity in its synthetic intelligence methods.
Margaret Mitchell, often known as Meg, who was considered one of the leaders of Google’s Ethical A.I. crew, despatched a tweet on Friday afternoon saying merely: “I’m fired.”
Google confirmed that her employment had been terminated. “After conducting a review of this manager’s conduct, we confirmed that there were multiple violations of our code of conduct,” learn a press release from the company.
The assertion went on to say that Dr. Mitchell had violated the company’s safety insurance policies by lifting confidential paperwork and personal worker information from the Google community. The company stated beforehand that Dr. Mitchell had tried to take away such recordsdata, the information website Axios reported final month.
Dr. Mitchell stated on Friday night that she would quickly have a public remark.
Dr. Mitchell’s put up on Twitter comes lower than two months after Timnit Gebru, the different chief of the Ethical A.I. crew at Google, said that she had been fired by the company after criticizing its approach to minority hiring as well as its approach to bias in A.I. In the wake of Dr. Gebru’s departure from the company, Dr. Mitchell strongly and publicly criticized Google’s stance on the matter.
More than a month ago, Dr. Mitchell said that she had been locked out of her work accounts. On Wednesday, she tweeted that she remained locked out after she tried to defend Dr. Gebru, who is Black.
“Exhausted by the endless degradation to save face for the Upper Crust in tech at the expense of minorities’ lifelong careers,” she wrote.
Dr. Mitchell’s departure from the company was another example of the rising tension between Google’s senior management and its work force, which is more outspoken than workers at other big companies. The news also highlighted a growing conflict in the tech industry over bias in A.I., which is entwined with questions involving hiring from underrepresented communities.
Today’s A.I. systems can carry human biases because they learn their skills by analyzing vast amounts of digital data. Because the researchers and engineers building these systems are often white men, many worry that researchers are not giving this issue the attention it needs.