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這家科技公司85%的員工是女性

Jennifer Alsever 2019年08月28日

在美國,人工智能領域基本上被白人和男性占據,但這家公司是個例外。

ThirdLove是舊金山的一家互聯網零售商。在這家公司,有一支數據科學家團隊,專門負責利用人工智能技術構建算法,用來篩選、分析數據和網購顧客的消費模式。不過這家初創公司在多元化方面,卻面臨著一個在硅谷很罕見的問題——招不到足夠的男性。

在ThirdLove的355名員工中,有將近85%是女性。在它的數據科學家團隊中,女性的比例更是占到了90%。這家公司的數據總監和聯合CEO也是女性。

當然,ThridLove“陰盛陽衰”的員工構成也是可以理解的。這家公司的“黑科技”,是利用人工智能、數據和算法,幫助網購顧客確定她們最合適的文胸尺碼。多數男性對這樣一家賣女性內衣的公司是不感興趣的,即便它有著高科技的元素——或者,他們至少對女性的文胸合不合身這檔子事并不感冒。ThirdLove的聯合CEO海蒂·扎克表示:“為了引入多元化的背景和技能,我們必須努力尋找男性員工。但是有了比較多的女性,自然而然地就會吸引更多的女性。”

ThirdLove的情況在科技行業顯然是個另類。根據美國婦女和信息技術中心(National Center for women and Information technology)的數據,科技行業女性就業比例最高的年份是1991年,占全行業的36%,此后便逐年穩步下降。而在數據科學和人工智能方面,ThridLove更像是異端中的異端。要知道,所有的人工智能從業者中有88%是男性,所有教人工智能的教授中有80%是男性。

AI4All是一家致力于讓更多女性和少數族裔進入人工智能行業的機構,該機構的負責人泰絲·波斯納指出:“目前,人工智能領域存在一場嚴重的多元化危機,比科技行業的其他領域都要嚴重。現在人工智能變得越來越普及,承擔的決策職能越來越多,但塑造它和給它編程的人,仍然是一個單一的、同質化的群體。”

人工智能領域基本上被白人和男性占據。這種情況是很危險的,歷史的偏見和權力的失衡很可能會因為這種“技術壟斷”而更加根深蒂固地延續下去。我們已經發現了一些人工智能表現出刻板偏見的案例,比如一些聊天機器人采用仇恨言論,亞馬遜的人工智能技術無法識別深色皮膚的人,等等。

Salesforce公司的數據科學總監薩拉·阿爾尼一直倡導數據科學領域的人員多元化。她表示,多元化的觀點對于人工智能和數據科學的未來發展至關重要。人工智能和數據科學雖然是一項科學工作,但你也需要以你個人的視角來解讀這些數據。“我對數據和模型的解讀,可能跟另一位數據科學家不一樣。如果我想更加全面地探索和理解這些數據,就需要多元化的視角。”

數據策略師莉莉安·皮爾森表示,人員構成的多元化,不僅有助于解決“算法偏見”的問題,同時也有助于為女性營造更舒適的工作環境。皮爾森曾經公開談論過她所在領域的性別差異。她在科技行業看到過很多這方面的問題,比如男女同工不同酬、性騷擾、女性在技術領域不受重視等等,這些現象在其他國家表現得更為嚴重。“你必須揮起你的拳頭去爭取,才可以獲得升職加薪。”

泛偉律師事務所(Fenwick & West)的合伙人、泛偉年度性別多元化調查報告的主筆人之一道恩·貝爾特表示,隨著更多女性進入企業領導層和董事會,這也會給其他女性帶來激勵。目前我們正在緩慢而穩定地朝著這個方向進步。“看到有女性擔任了領導職務,就會使女性更傾向于從事一份工作。”

去年也被一些人稱為“女性之年”。確實,這一年,性別多元化的問題有所改善——至少在那些硅谷公司的董事會和高層領導里是這樣的。加利福尼亞州率先要求所有上市公司的董事會中必須包括女性成員。在標普500企業中,女性董事會成員的數量也創下歷史新高。目前,女性在《財富》美國500強企業的董事會中已經占了25.5%的席位,而15年前這一比例僅有15.7%。

ThirdLove是扎克與她的丈夫大衛·斯佩克特共同創辦的。扎克表示,ThirdLove雖然仍是一家小公司,但她希望她能夠成為一個培養科技行業女性工作者的溫床。該公司已經從投資者手中獲得了6800萬美元的融資。這家公司有很強的導師文化,鼓勵大家互相幫助,也鼓勵員工踏上領導崗位。

ThirdLove公司的數據科學總監梅根·卡特賴特表示,在加入ThirdLove之前,那些公司的數據科學團隊經常只有她一位女性,自己作為一名職業母親,下班后也沒有辦法跟同事們去喝酒聊天,也就無法同大家建立更緊密的關系。而ThirdLove的大部分員工都已經為人父母了,所以他們下班后很少一起喝酒,而是會一起吃午餐或者喝咖啡。

卡特賴特最后說道:“大家在公司的表現才是最重要的。在這里,我們研究的是前沿的數據科學,而這些女性將利用這些技能來創辦企業、組建團隊。”(財富中文網)

譯者:樸成奎

Inside the offices of ThirdLove, an Internet retailer in San Francisco, a team of data scientists build algorithms using artificial intelligence to sort and dissect data and patterns among online shoppers. Yet the startup faces an unusual diversity problem for Silicon Valley: It can’t seem to hire enough men.

Nearly 85% of ThirdLove’s 355 employees are female, and women make up nine out of 10 members on its data science team. The startup’s head of data and its co-CEO are also female.

Granted, ThirdLove’s female-oriented workforce makes good sense. The company uses AI, data, and algorithms to help shoppers determine the best fit for a bra. And most men aren’t interested in working for an undergarment retailer even if it has a high-tech bent — or at least they’re not passionate about better fitting bras, ThirdLove’s criteria in hiring. Says co-CEO Heidi Zak: “We have to look hard for men in order to bring in diverse backgrounds and skillsets. But having more women attracts more women.”

Still, ThirdLove is an anomaly in the technology industry, where women’s employment has steadily declined since 1991, after it peaked at 36%, according to the National Center for Women and Information Technology. And when it comes to data science and artificial intelligence employment, ThirdLove is even more unusual. Men make up 88% of all AI workers and 80% of all AI professors.

“Right now, there’s a major crisis in diversity in AI— worse than the rest of tech,” says Tess Posner, director of AI4All, an organization working to get more women and minorities into the industry. “As AI becomes more ubiquitous, taking on a lot more decision making, it’s being shaped and programmed by a single homogenous group.”

The AI field, which is overwhelmingly white and male, is at risk of replicating or perpetuating historical biases and power imbalances through technology. We’ve already seen cases of AI bias, including chatbots adopting hate speech and Amazon’s tech failing to recognize people with dark skin.

Diverse views in AI and in data science is vital going forward, says Sarah Aerni, Salesforce’s director of data science who has championed diversity in data science. It’s a scientific job, but it also involves interpreting information through your own personal lens. “The way I interpret and investigate data and models is different from another data scientist. If I want fuller exploration and understanding, I need diverse perspectives.”

It’s not just bias in algorithms at stake, diversity in tech lends to a more comfortable work environment for women, says data strategist Lillian Pierson, who has spoken out about the gender gap in her field. In her own career, she has witnessed unequal pay, sexual harassment, and problems of women not being taken seriously in a technical field— especially overseas. “You have to put your dukes up to advance and get a raise,” she says.

Having more women in leadership and on corporate boards helps, and we’re making slow but steady progress in that arena, says Dawn Belt, a partner at law firm Fenwick & West and coauthor of the annual Fenwick & West Gender Diversity Survey, which reviews leadership and board diversity in Silicon Valley. “Seeing women in leadership makes women more inclined to take a job.”

Last year—dubbed by some as “the year of the woman” overall— did, in fact, show improvements in terms of gender diversity— at least in board and leadership roles in Silicon Valley. California became the first state to require public companies to include women on their corporate boards, and indeed a record number of them were appointed to boards on S&P 500 companies. Today, women hold 25.5% of board seats at Fortune 500 companies compared to just 15.7% 15 years ago.

Zak, who started ThirdLove with her husband, David Spector, says she hopes that ThirdLove, though still small, will become a breeding ground for women in technology. The firm, which has raised $68 million from investors, has a strong culture of mentorship that encourages helping each other and encouraging leadership opportunities for employees.

ThirdLove data science director Megan Cartwright said that prior to joining ThirdLove she was often the lone woman on all-male data science teams and often felt that she was missing out on the relationships built during after-hour drinks that she couldn’t attend because she was a working mother. A good chunk of ThirdLove’s workforce are parents, so instead of drinks after work, they meet for lunch or coffee.

“Performance in the office is what matters,” Cartwright says. “We’re working on cutting edge data science here, and these women are going to take these skills and go on to start companies and build teams.”

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