这家科技公司85%的员工是女性

ThirdLove是旧金山的一家互联网零售商。在这家公司，有一支数据科学家团队，专门负责利用人工智能技术构建算法，用来筛选、分析数据和网购顾客的消费模式。不过这家初创公司在多元化方面，却面临着一个在硅谷很罕见的问题——招不到足够的男性。

在ThirdLove的355名员工中，有将近85%是女性。在它的数据科学家团队中，女性的比例更是占到了90%。这家公司的数据总监和联合CEO也是女性。

当然，ThridLove“阴盛阳衰”的员工构成也是可以理解的。这家公司的“黑科技”，是利用人工智能、数据和算法，帮助网购顾客确定她们最合适的文胸尺码。多数男性对这样一家卖女性内衣的公司是不感兴趣的，即便它有着高科技的元素——或者，他们至少对女性的文胸合不合身这档子事并不感冒。ThirdLove的联合CEO海蒂·扎克表示：“为了引入多元化的背景和技能，我们必须努力寻找男性员工。但是有了比较多的女性，自然而然地就会吸引更多的女性。”

ThirdLove的情况在科技行业显然是个另类。根据美国妇女和信息技术中心（National Center for women and Information technology）的数据，科技行业女性就业比例最高的年份是1991年，占全行业的36%，此后便逐年稳步下降。而在数据科学和人工智能方面，ThridLove更像是异端中的异端。要知道，所有的人工智能从业者中有88%是男性，所有教人工智能的教授中有80%是男性。

AI4All是一家致力于让更多女性和少数族裔进入人工智能行业的机构，该机构的负责人泰丝·波斯纳指出：“目前，人工智能领域存在一场严重的多元化危机，比科技行业的其他领域都要严重。现在人工智能变得越来越普及，承担的决策职能越来越多，但塑造它和给它编程的人，仍然是一个单一的、同质化的群体。”

人工智能领域基本上被白人和男性占据。这种情况是很危险的，历史的偏见和权力的失衡很可能会因为这种“技术垄断”而更加根深蒂固地延续下去。我们已经发现了一些人工智能表现出刻板偏见的案例，比如一些聊天机器人采用仇恨言论，亚马逊的人工智能技术无法识别深色皮肤的人，等等。

Salesforce公司的数据科学总监萨拉·阿尔尼一直倡导数据科学领域的人员多元化。她表示，多元化的观点对于人工智能和数据科学的未来发展至关重要。人工智能和数据科学虽然是一项科学工作，但你也需要以你个人的视角来解读这些数据。“我对数据和模型的解读，可能跟另一位数据科学家不一样。如果我想更加全面地探索和理解这些数据，就需要多元化的视角。”

数据策略师莉莉安·皮尔森表示，人员构成的多元化，不仅有助于解决“算法偏见”的问题，同时也有助于为女性营造更舒适的工作环境。皮尔森曾经公开谈论过她所在领域的性别差异。她在科技行业看到过很多这方面的问题，比如男女同工不同酬、性骚扰、女性在技术领域不受重视等等，这些现象在其他国家表现得更为严重。“你必须挥起你的拳头去争取，才可以获得升职加薪。”

泛伟律师事务所（Fenwick & West）的合伙人、泛伟年度性别多元化调查报告的主笔人之一道恩·贝尔特表示，随着更多女性进入企业领导层和董事会，这也会给其他女性带来激励。目前我们正在缓慢而稳定地朝着这个方向进步。“看到有女性担任了领导职务，就会使女性更倾向于从事一份工作。”

去年也被一些人称为“女性之年”。确实，这一年，性别多元化的问题有所改善——至少在那些硅谷公司的董事会和高层领导里是这样的。加利福尼亚州率先要求所有上市公司的董事会中必须包括女性成员。在标普500企业中，女性董事会成员的数量也创下历史新高。目前，女性在《财富》美国500强企业的董事会中已经占了25.5%的席位，而15年前这一比例仅有15.7%。

ThirdLove是扎克与她的丈夫大卫·斯佩克特共同创办的。扎克表示，ThirdLove虽然仍是一家小公司，但她希望她能够成为一个培养科技行业女性工作者的温床。该公司已经从投资者手中获得了6800万美元的融资。这家公司有很强的导师文化，鼓励大家互相帮助，也鼓励员工踏上领导岗位。

ThirdLove公司的数据科学总监梅根·卡特赖特表示，在加入ThirdLove之前，那些公司的数据科学团队经常只有她一位女性，自己作为一名职业母亲，下班后也没有办法跟同事们去喝酒聊天，也就无法同大家建立更紧密的关系。而ThirdLove的大部分员工都已经为人父母了，所以他们下班后很少一起喝酒，而是会一起吃午餐或者喝咖啡。

卡特赖特最后说道：“大家在公司的表现才是最重要的。在这里，我们研究的是前沿的数据科学，而这些女性将利用这些技能来创办企业、组建团队。”（财富中文网）

译者：朴成奎

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.”