The future is female: How women are redefining A.I.

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The future is female: How women are redefining A.I.

There’s no shortage of new stories about artificial intelligence (also known as A.I.) these days. The cutting-edge technology is driving billion-dollar investments, turning founders into millionaires overnight and increasing competition amongst the biggest businesses around the world.  

As the industry matures, A.I. will revolutionize how humans interact with the world. Interestingly, some of today’s new breakthroughs are fueled by women. It’s hopefully a telling sign of what’s to come when women are making important moves behind the scenes.  

The drivers of change

 
Despite significant gains made in the last decades, women still remain underrepresented in STEM, and the A.I. field is no different. Given the preponderance of men working in the industry, the achievements made by just a few women end up making their success all that more impressive.

“AI is a technology that gets so close to everything we care about. It’s going to carry the values that matter to our lives, be it the ethics, the bias, the justice, or the access…” @drfeifei

Megan Anderson, business development director at Integrate.ai, is one of a growing number of female leaders working in the industry. Her role, which focuses on driving and implementing new growth opportunities, has helped grow the company (more than $9 million raised in 2017 so far). That accomplishment, including being named to the Top 25 Women of Influence, has put her in the spotlight. It’s also highlighted the impact women like Anderson are having in A.I.

“I would love for more women to make the leap into careers in tech, even if they don’t have STEM backgrounds,” she says. My background is in management consulting, but I am an analytical person with intense curiosity so I took the leap into tech.”

While more women are needed, Anderson points to industry leaders —  like McGill University professor Joelle Pineau and Fast Forward Labs CEO Hilary Mason — who are showing a new path forward.

“AI companies need lots of skills and talents in addition to engineering, like sales, customer success, operations, etc. As long as you learn quickly, stay curious and leverage skills that you have built in other sectors, it is never too late to jump into tech.”

Education is key

 
Dr. Inmar Givoni, Autonomy Engineering Manager at Uber ATG (the company’s self-driving division), is also blazing a new trail. Her company is on the frontline of driverless car technology. Last year, the company famously launched a fleet of self-driving cars in San Francisco.

These days the technologist is used to being the only woman in the room. While she’s not surprised that women are now being recognized, more needs to be done. The key, she says, is to focus on introducing tech to the next generation as soon as possible.

“There’s no point in trying to get more women into A.I. specifically. I think the effort should be towards getting women into STEM,” she explains. “From my perspective, it basically starts as soon as the baby’s born. When a girl is given a shirt that reads ‘I’m a princess’ and the boy gets one that reads ‘I’m a hero’ it already sets a mindset of expectations for [the child] from society.”

Other leaders in the industry agree. Stanford professor and A.I. researcher Fei-Fei Li’s organization, AI4All, is partnering with universities to inject much-needed diversity into the field. “We need to get them young,” she shared with Wired magazine earlier this year.

Making a difference

 
Even though men right now outnumber women, there is hope at the end of the tunnel.

Influencers and stakeholders are now making a dedicated effort to improve those numbers. The Women in Machine Learning Conference, launched in 2006, is doing its part. Through it, entrepreneurs can network, find connections to mentors and learn more about the field.

A little closer to home, the Canadian Institute for Advanced Research (CIFAR) is helping in as well. The organization, probably best known these days for its role leading the $125 million Pan-Canadian A.I. strategy, is championing women at all levels.

Dr. Alan Bernstein, president and CEO of CIFAR, is keen to see change since diversity is crucial for innovation.

“Diversity is our strength. At CIFAR, we’ve known that since we started. We have a strong view that for the advancement of knowledge you need diversity,” Dr. Alan Bernstein, president of @CIFAR_News

As part of their efforts to increase opportunities for women, CIFAR is putting in place ways to increase diversity. “You don’t make as much progress having 10 of the same person in the same room. When you have people with different perspectives sitting around the table, you end up with different questions being asked, and better results.” While change takes time, Bernstein is optimistic. “We’re going to see a big difference in the coming future,” he explains.

 

Is artificial intelligence dangerous?

Elon Musk. Stephen Hawking. Bill Gates.

Some of the richest (and best known) names in science and technology are worried about the future survival of mankind. These innovators are sounding the alarm, not about North Korea, nuclear war or even global warming, but something much more sinister: artificial intelligence.

Hollywood has spent decades showcasing how dangerous artificially intelligent computers (think: Terminator, Ex Machina and more) can be. However some experts believe the bigger (and arguably more immediate) threat A.I. poses isn’t from killer robots, but something far less sexy: computer-generated bias. When computers make decisions based on data skewed by humans it can topple economies and disrupt communities.

Helpful or harmful?

 
One of the most pivotal moments in A.I. history took place in 1996 when IBM’s supercomputer, Deep Blue, beat chess champion, Garry Kasparov. For some, it signalled how far technology had come and how powerful the technology could soon become.

Since then, newspapers have produced countless stories about what an artificially intelligent future could look like. However, the reality is that A.I.is already here. In fact, machines lurk behind the millions of decisions that impact our every move, like what stories pop up in online newsfeeds and how much money banks lend its customers.

In a way, this makes the A.I. infinitely more dangerous. These algorithms shape public perception in ways that were once considered unimaginable.

“The idea of robots becoming smarter than humans and us losing our place in the totem pole is misplaced,” @HumeKathryn.

What people should worry about instead is how machines are making big decisions based on little information. “What I found the greatest hurdle has to do with machine learning systems. They make inferences based on data that carries with it traces of bias in society. The algorithms are picking up on that bias and perpetuating it,” explained Kathryn Hume, vice president of product and strategy for integrate.ai.

What comes next?

 

In theory, machines should offer up bias-free and objective decisions, but that’s often not the case. Computers learn by reviewing examples fed to it and then use that information as a basis for future decisions. In layman terms, it means if you train a computer using biased information, it will end up replicating it.

dmzthereview-ai

One doesn’t have to look too far to find examples of this phenomenon. In 2016, Pro Publica found learning software COMPAS was more likely to rate black convicts higher for future recidivism than their white counterparts. Last year Google’s algorithm was likelier to show high-paying jobs to men than women, and online searches for CEOs regularly showed more white men than another other race or gender.

Breaking down bias in A.I.

 
Breaking down bias is possible. However, it takes work and a lot of it. Relying on more inclusive data can go a long way to fixing the problem.

“It’s important that we be transparent about the training data that we are using, and are looking for hidden biases in it, otherwise we are building biased systems,” said John Giannandrea, Google’s chief A.I. expert, earlier this year.

Education is also a crucial part of the equation. Organizations like the Algorithmic Justice League are helping on that front. Among many things, they’re educating the public about A.I. limitations and working to improve algorithmic bias.

“We in the data community need to get better at educating the public,” adds Hume. “The superficial level sounds really scary and they will stymie the use of it. The tech community can help people who aren’t technical community know what the stuff is and feel empowered to use it.”

Meet the future Einsteins: The kids taking over A.I.

It’s Saturday morning and Toronto-born Tommy Moffat is hunched over his computer. The award-winning programmer is fixated on getting the algorithm behind his A.I.-fuelled robot up and running.

Despite an impressive Rolodex that includes contact details for influencers at some of today’s hottest tech companies, Moffat isn’t an entrepreneur at some high-flying startup or engineer at a high-profile tech company. In fact, he’s just a teenager living in Burlington, Ontario. Although, you would be hardpressed to believe it by just looking at his resume.

At 16 years old, he’s accomplished what it takes some professionals a lifetime to achieve. Earlier this month he spoke at the 2017 Toronto Machine Learning conference, alongside industry heavyweights, like Ozge Yeloglu, chief data scientist at Microsoft Canada, and Google Brain’s Aidan Gomez.

He also recently placed in the top one percent for his age group at an international conference and is slated to join a new startup, called Gradient Ascent, where he’ll be the youngest member of staff.

But all that doesn’t really matter to him. “What I really want to do is change the world,” he says. His motivation isn’t fame or fortune but altruism, he confesses. “I want to use what I’ve learned to help other people. Using augmented reality and computer vision could help a lot of people with disabilities in the real world.”

Teen prodigies making a difference using A.I.

Artificial intelligence has transformed how people around the world access data. It’s  created a new way for everyday engineers to change lives by helping machines do what humans can’t: analyze data at lightning-fast speeds.

While it might be easy to view Moffat as an outlier, he’s quick to point out that he’s not. Other Generation Z-ers — those born mid-to-late nineties — feel the same way he does. “You can see the difference you can make in the world with [artificial intelligence]. It’s not only me.”

Moffat’s right. He’s not the only teenager focused on making the world a better place.

Meet Generation Z


Kavya Kopparapu, also 16, has created an application that A.I. app that can cheaply and quickly diagnose diabetic retinopathy. The eye disease, associated with diabetes, and can lead to blindness if not treated early.

“One of the most important applications of artificial intelligence is in medicine, in saving lives,” she explains in a recent TED Talk. “I envision … a future where a diagnosis is available to anyone, regardless of where they live, money or even electricity. I envision a future where we can save lives”.

Meanwhile, Canadian prodigy Tanmay Bakshi, 13, is working with IBM on a project designed to help a quadriplegic woman walk again. “We’re trying to give her artificial communication ability … through the power of artificial intelligence and systems like IBM Watson that allow you to essentially implement artificial intelligence.”

While he’s somewhat of a celebrity in the tech world — his YouTube channel has more than 20,000 subscribers  — he remains humble. “[I’m interested] in generally sharing my knowledge about these sorts of technologies with the rest of the community and of course through things like open-source technology and so much more.”

The kids are alright



Vik Pant isn’t surprised by today’s tech-leaning youth. Especially teens choosing to specialize in A.I.; a burgeoning new area in tech that’s expected to grow in the future.

“A.I. is the future. It’s not a trend. It’s on the ramp up, not down,” @vikpant, who works for Oracle’s competitive intelligence team. “Youth see that and want to harness that potential.”

The only challenge he can see is a discrepancy between those, like Moffat, who posses new-age tech skills and those that don’t. Primarily, youth from lower-income brackets who might have access to tools they require.

“Definitely in terms of artificial intelligence it’s a discipline and domain that doesn’t discriminate, he explains. “It’s socioeconomic factors that constrain or allow youth to be more involved. I’m encouraged, though. I’ve noticed that many private sector and corporations are helping underprivileged helping youth.”

Moffat agrees. Thankfully, the learning opportunities that exist today have grown beyond what was available as little as 10 years ago. Now people, at any age, can start learning online. It’s this type of thinking that drives Moffat’s to one day become an industry expert in A.I.

“Before I broke out of my old way of thinking, I never thought about becoming an ‘expert’ in anything. It takes years to go through school to get a degree. With the help of modern education programs like The Knowledge Society, it’s possible to go way deeper into a topic at a significantly earlier age than ever before.”