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An attendee takes a photograph of Hanson Robotics Inc. humanoid robot "Sophia" during the Rise conference in Hong Kong, China. Photographer: Anthony Kwan/Bloomberg

Top AI Conference Swaps Acronym After Sexism, Misconduct Protest

The conference on Neural Information Processing Systems, which takes place annually in early December, had been commonly known by the acronym NIPS. The foundation that runs the conference said it will now use the acronym NeurIPS instead.

(Bloomberg) --One of the world’s most important conferences for researchers working on artificial intelligence has changed the acronym used for the event following complaints the former one contributed to a sexist atmosphere.

The conference on Neural Information Processing Systems, which takes place annually in early December, had been commonly known by the acronym NIPS. The foundation that runs the conference said it will now use the acronym NeurIPS instead.

The former acronym inspired off-color jokes and innuendo-laced banter on Twitter and in conversations at the event.

The conference began about 30 years ago as a sleepy academic event and as recently as 2013 was attended by fewer than 2,000 machine-learning researchers and statisticians. It has grown into one of the most important annual confabs and recruiting grounds for university labs and technology companies working on one of today’s most hyped technologies: artificial intelligence. Last year’s conference was attended by 8,000 people and the first 2,000 tickets for this year’s conference sold out in about 10 minutes when they were released in September.

While some AI researchers had long thought the acronym sexist, the issue took on increased prominence after last year’s conference in Long Beach, California. Some attendees at the event expressed discomfort with a performance by a female contortionist at a private party held by a conference sponsor and others complained about an inappropriate joke related to sexual harassment that a researcher made while his amateur band performed during the official closing night party.

The events inspired a blog post by data scientist Kristian Lum, posted shortly after the conference, alleging a culture of sexual harassment at NIPS and other AI-related conferences, and within the AI research field generally. Lum’s blog was widely shared among AI experts. Eventually, two men whose conduct Lum singled out in her blog lost their jobs.

The board of the foundation that runs the conference expressed regret in a statement that events had failed to create “an inclusive and welcoming environment for everyone in the fields of AI and machine learning.” It recruited two people to oversee diversity and inclusion efforts. And it strengthened its code of conduct, which is now displayed prominently on the conference’s registration page. It also surveyed conference attendees about whether the event should change its name to avoid the problematic acronym.

No clear consensus emerged from the survey, the board said, and in October it released a statement that it was sticking with NIPS and focusing instead “on more tangible steps to promote inclusion and diversity.”

In response, the hashtag #protestNIPS began trending on Twitter and an online petition asking the board to reconsider its decision and rename the conference garnered more than 2,000 signatures.

Two weeks later, the foundation’s board said it would reverse course. It said in a statement Nov. 16 that while the name would remain the same, the acronym NeurIPS had “sprung up organically” and the board would now officially embrace it, including the new acronym on conference signs and materials and hiring a designer to create a new logo.

The move at least partly satisfied Anima Anandkumar, a professor at the California Institute of Technology and director of research at chipmaker Nvidia Corp., who had helped promulgate the #protestNIPS hashtag and the petition. “I wish we could have started with a clean slate and done away with the problematic legacy, but this is a compromise,” she wrote on Twitter. “I hope we can all continue to work toward better inclusion” in machine learning.

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