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Enough of Alexa – why AI assistants shouldn’t be female on default

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By Tara O’Sullivan, CMO at Skillsoft

Have you ever wondered why Alexa was the name chosen by Amazon?

Why not a genderless name like Alex or Ali? All four of the major AI assistants—Alexa, Apple’s Siri, Google Assistant, and Microsoft’s Cortana—speak by default with a female voice. Why, when naming the ‘server,’ did the creators give each one a female name?

Some in the industry claim it has to do consumer preference that both genders respond better to a female-sounding voice over a male one. I disagree. I can’t help wondering if that has more to do with cultural norms and that it reinforces pre-existing gender stereotyping and unconscious bias.

Historically, telephone operators, cashiers and secretaries were predominantly female. And therefore, it follows that when designing a voice for the machine that will operate these tasks in the future, we’d choose a female one; a sound that many perceive as soothing, subservient, compliant, passive and agreeable.

And there are those who’ll argue that women’s voices are easier not just listen to, but also to understand and hear. All of which is untrue. They are myths, as Sarah Zhang calls them. She talks about the reason why these myths persist:

“An oft-cited reason for Siri’s femaleness is the persistence of history. The first voice navigation systems to become widely used were in the cockpits of WWII fighter planes, where female voices supposedly stood out against the low rumble of engines. More recently, though, a 1998 study at the Wright-Patterson Air Force Base in Ohio found the opposite: It’s actually female voices that are less intelligible against the noise inside cockpits, though the difference was tiny and only statistically significant at the highest levels of noise.”

I know you can change Siri’s voice (and we did in our house to an Australian male) but people are inherently lazy and they tend not to change things. The fact that this is the default on over a billion Apple devices is a problem. And it’s worse for Amazon – you cannot even change Alexa’s gender – only her accent. It simply boils down to the fact that it has more to do with gender and perceived roles genders play in society. And it’s part of a larger problem within the tech world.

Does it matter?

The people behind the majority of today’s technological advances — the workers creating the algorithms — are predominantly white and male. And even more importantly, when white male coders assemble data for chatbots, machines are likely to perpetuate inequities found in the real world. They are prone to hard code their own subconscious bias about race, gender and class into algorithms that are designed to mirror human decision making. This has the propensity to amplify existing stereotypes and create a stronger association for male and female-oriented images, behaviors and careers.

Machines learn from masses of data. If that data has gender biases incorporated, it will become part of the algorithm. For example, researchers at Boston University and Microsoft asked the machine learning software to complete the statement “Man is to computer programmer as woman is to …” It replied, “homemaker.” Ugh!

In more depressing news, Wired reported that machines were learning to associate images of kitchens with women. The article stated that research-image collections display a “predictable gender bias in their depiction of activities such as cooking and sports. Images of shopping and washing are linked to women, for example, while coaching and shooting are tied to men.”

Ivana Bartoletti, chair of the Fabian Women’s Network, wrote an excellent article for the Guardian in which she gave more examples of this bias that you can look at right now. Search Google for “unprofessional hairstyles at work.” You are served up a slew of black women with natural hair. Now, search for “professional hairstyles for work” and, you guessed it, it is all coiffed white women! Why is natural hair on black women deemed to be unprofessional whereas natural hair on white women is considered professional?

If you want further proof, try this – search for “women” on Google – and you get three pages of images of white young women before you come to any other racial or ethnic representations!

In the excellent book The Man Who Lied to His Laptop, Clifford Nass reports how BMW was forced to recall one of its cars because male drivers in Germany didn’t trust the female voice offering directions from the car’s navigation system. In Japan, a call centre operated by Fidelity would rely on an automated female voice to give stock quotes but would transfer customers to an automated male voice for transactions.

And this reinforcement of gender clichés can result in women getting targeted unequally for financial loans, medical services, hiring and political campaigns. Such is the danger of the current gender imbalance that, as Erika Hayasaki points out in a report by the National Science and Technology Council, the shortage of women and minorities is “one of the most critical and high-priority challenges for computer science and AI.”

Women in STEM

Of course, these issues are driven and further supported by the lack of women who are working on coding the future. Andrea Keay, director of Silicon Valley Robotics, an industry group that supports the innovation and commercialization of robotics technologies, aptly sums up my concern with such imbalance:

“Inherently having only a section of the population involved in the practice of AI means that we are missing out on a range of inputs and insights. And we are also seeing that AI is, by design, susceptible to learning stereotypes, and then perpetuating them. When things happen and we don’t see a person involved, we are less likely to see that the process may be biased, or wrong. And it’s much harder for us to know how to take action against an algorithm.”

We all know there are very few women, and even fewer women of colour, working in STEM:

13.5 per centof women work in machine learning
18 per cent of software and 21 per cent of computer programmers identify as women
Just 20 per cent of Google tech employees are women
19 per cent of Facebook’s tech employees are female

How do we fix it?

Coders are smart people (most of them). The lack of women in STEM is not some secret plan to ensure the patriarch continues unabated into the fourth industrial revolution. It is happening because people are unaware of how their conscious and subconscious biases are influencing artificial intelligence. Eventually, we will be able to train AI to recognize and self-correct any inherent biases from the author. But we are a long way from this reality.

We need to train coders to recognize their own biases, to improve the AI experience for everyone. We need to get more women in STEM. Only 6.7 per cent of women are pursuing STEM careers and only 25 per cent hold STEM jobs. A perception remains that STEM is male-dominated and super techy. We need to get better at explaining why AI is an excellent career for women, and work hard to attract them into the industry. But that’s a whole other blog post!

Fortunately, some of the work on this has already begun.

Women in Machine Learning is on a mission to increase the number of women in machine learning, help such women succeed professionally and increase the impact of women in the machine learning community. One of the founders, Hanna Wallach is an advocate for “fairness, accountability and transparency” in machine learning. AI4ALL is a non-profit working to increase diversity and inclusion in acritical intelligence. They create pipelines for underrepresented talent through education and mentorship programmes in high schools around the US and Canada. Finally, Women in AI is a global organization of women experts in the field of artificial intelligence who run workshops, networking events and conduct research with a goal of changing the lack of diversity in AI.

About the author

Tara O’Sullivan is the Chief Creative Officer at Skillsoft


HeForShe: Steve Wainwright | Managing Director, Skillsoft

Steve Wainwright

Steve Wainwright is the Managing Director, EMEA at the eLearning company, Skillsoft.

Why do you support the HeForShe campaign? For example – do you have a daughter or have witnessed the benefits that diversity can bring to a workplace?

I have two daughters and previously worked in California which is extremely diverse in race, religion, sexual orientation etc. These experiences have helped show me how diverse teams, in terms of gender and ethnicity, are beneficial in all walks of life, including the workplace. It mirrors society today and is important to me.

I support the HeForShe campaign because bias – conscious or unconscious – exists in many organisations still today. It is a contributing factor to why there are fewer women in leadership or board level positions, and why the gender pay gap is as wide as it is. My personal and professional goal is to help eliminate this by making training tools available, so that we can play a part in establishing a workplace where everyone is afforded the same financial and leadership opportunities — regardless of gender.

Why do you think it’s important for men to support gender equality in the workplace?

As with all areas in life, the more voices that are raised, the more likely action will be taken. It’s an issue of equality and it’s important that people in a position of responsibility show leadership on this topic.

How welcome are men in the gender equality conversation currently?

That’s exactly what it is – a conversation in equality. That means everyone is welcome and should all be encouraged to take part in it.

Do you think groups/networks that include the words “women in…” or “females in…” make men feel like gender equality isn’t really their problem or something they need to help with?

If we achieved equality there would be no need to set these organisations up. That’s why I believe it is so important to foster a culture of support and inclusion for people of all genders.

What can businesses do to encourage more men to feel welcome enough to get involved in the gender debate?

In my opinion, it is all about greater understanding and better training. At Skillsoft we are lucky to have a ‘top-down’ approach that filters from the CEO and management team right down the organisation. It means that we are all encouraged to get involved in the gender debate, as it is part of our company’s culture.

Do you currently mentor any women or have you in the past?

Throughout my career I have mentored men and women alike, and continue to do so, both inside and outside my organisation.

Have you noticed any difference in mentoring women – for example, are women less likely to put themselves forward for jobs that are out of their comfort zones or are women less likely to identify senior roles that they would be suited for?

Traditionally, yes, women are more likely to settle. For instance, often when men are offered a job there will be a back and forth on pay, holiday and other benefits. Women tend to simply accept offers, because of absurd notions about being too pushy and outspoken.

That’s one of the reasons why Skillsoft has taken the pledge for parity and provides dedicated eLearning resources to help women progress in their careers and to help employees recognise and stamp out gender bias.