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March 10, 2021

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Diversity in AI May Help the Future of Robots Look Less Creepy

Quick – think of your favorite cautionary tale about robots. Is it the Matrix? Blade Runner? Ex Machina? Why are there so many?! The answer is pretty simple: we fear what we don’t know. And we don’t really know what the future of AI holds…yet.

It seems like every time we hear about new AI capabilities, the internet lights up with sensationalist speculation. People fear that if robots keep getting smarter, they’re going to render our jobs obsolete. Or that if we’re mean to them, they’ll start a revolution and enslave us all. And while these fears are mostly far-fetched, there is a *tiny* bit of truth to them.

Robots Make People Feel Weird

Artificial intelligence has come a long way over the past several years, but it’s still nowhere near being as intelligent as the war-mongering robots we all know and love. Computers may be able to target ads and learn from data, but they aren’t smart enough to form new ideas. They aren’t truly self-aware. They have trouble understanding context. And they certainly aren’t smart enough to band together and overthrow humanity.

In our hearts, we know this. But it doesn’t matter because robots still freak us out on a visceral level. For example, look at Sophia, Hanson Robotics’ latest and greatest humanoid robot. She’s done quite a few remarkable things, like posing on the cover of Elle, gaining Saudi citizenship, and cracking a few genuinely funny jokes. Most recently, she shared this unsettling holiday greeting with the world.

Despite being a heartwarming message, it still has an element of eeriness to it. Sophia’s not-quite-human vibe is a tad off-putting. This is known as the uncanny valley effect, and it’s something that engineers have been trying to overcome for a long time. As robots get closer to looking and acting like us, the creep factor multiplies. It’s not until AI is nearly indistinguishable from humans that it will be commercially and universally accepted. Overcoming the uncanny valley is one thing on a long laundry list of goals – and it’s just one of the reasons the AI industry needs more diversity.

Tech Needs Lots of People - Lots of Different People

The AI industry is in desperate need of talent, as most people know. But what many of these news clips and think pieces forget to mention is that what the AI industry really needs is diverse talent. AI is only as open-minded and inclusive as the data we feed it. Without diverse perspectives and data sets, it will continue to be just as homogenous as the industry that created it. The Hill covered a recent hearing about AI, in which Hawaii Democratic Senator Brian Schatz, outlined some of the biggest concerns:

“You have software engineers and decision makers both at the line level writing the code, but all the way up to project management and all the way up to people dealing with these moral questions are mostly white men. Is it fair, is it rational to have predominately white men in charge of setting up these algorithms that most of the rest of society can’t even access because it’s all proprietary?”

When the inputted data isn’t diverse, the output isn’t either. It’s then that we run into problems like racial and gender bias in machines. And when those machines are used for things like, say, law enforcement or predicting creditworthiness, the consequences could be dire. So, perhaps the real threat we should be trying to resolve isn’t robot domination - it’s robot discrimination.

What Can We Do to Diversify the Industry?

The industry suffers from both a lack of workforce diversity and a lack of talent. So, the obvious answer is to get more people. In this article from The Verge, Chinese tech investment company Tencent reports that there are only an estimated 300,000 AI engineers in the world, while the actual need numbers in the millions. Tech companies across the globe are in an arms race to hire the best engineers, and salaries are skyrocketing to nearly half a million dollars per year. The biggest players have their own unique advantages; China has the numbers, Japan has the best robotics teams, and the UK excels in ethics and legal development. What does the US have? Opportunity, and lots of it.

According to the Verge article, America currently tops the charts for education in AI and related fields. There are more AI education programs here than anywhere else on the planet, and many of them are considered the best in terms of quality. What’s more, America is home to about 1,000 AI startup companies - nearly 40% of all the AI startups in the world. And while we may not be #1 for the most diverse country on earth (Canada is), we do fall somewhere in the middle of the list. We’re still a melting pot for modern civilizations. And if you combine our moderate diversity with high-quality education programs and ample startup opportunities, it sets the scene for some really special stuff. Maybe eliminating machine bias and overcoming the uncanny valley are a lot closer than we think.

Diversification is the Answer to Literally Everything

This AI race will continue as the bottleneck of education evens out. Currently, many AI engineers are still in school. But does it really matter who becomes the AI race winner and the global superpower? I don’t think so. What matters is that we – all of us - strive for diversity across all industries, especially in tech. We’ve said this before and we’ll say it again: If AI is truly to become a part of everyday life, and robots will one day walk amongst humans, it’s essential that the data input is just as diverse as humanity itself. Then, we can look forward to a future where robots are intelligent, unbiased, and maybe not so damn creepy.





Sunil Bagai
Sunil Bagai
Sunil is a Silicon Valley thought leader, speaker, motivator, and the visionary behind the groundbreaking Crowdstaffing ecosystem. Blending vision, technology, and business skills, he is transforming the talent acquisition landscape and the very nature of work. Prior to launching Crowdstaffing, Sunil honed his skills and experience as a business leader for companies such as IBM, EMC, and Symantec. "We need to think exponentially to mindfully architect the future of humanity, civilization, and work. When we collaborate and work together, everyone prospers."
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