The future of AI is in human hands.

by Cynthia Rando
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ai human centered design

If you haven’t noticed, artificial intelligence (AI) has been all over the news recently. In fact, just this morning the headlines couldn’t stop talking about it:

Amazon scraps secret AI recruiting tool that ‘didn’t like women’

Will AI replace fertility doctors? Why computers are the only ones that can end the agony of failed IVF cycles, miscarriages, and risky multiple births

Swarms of robot bees can pollinate plants if climate change and pesticides kill off insects, Dutch scientists say (but could they one day turn on their creators?)

And the list goes on.

It’s no secret that AI is changing how we live our lives and do business. For many of us, cutting-edge technology is quickly transitioning from a luxury to a need. We’re busy people, and we need AI to make our lives easier. Why drive cars when we can sit back, relax, and let them drive us? Why waste time going to the bank when we can deposit checks with an app on our phones? Why bother going to the store when Amazon can suggest exactly what we need? They’ll even deliver it within an hour or two, so we can spend time being productive instead.

So many businesses today are built around this technology, and those that aren’t are transitioning to it. In the next 7 years, this market is expected to be worth $190 billion. And that’s just the commercial sector alone. But if you’re reading the AI articles in the news, you’ll see that it’s not all rainbows and unicorns.

The purpose of technology is to improve our lives, not make them more difficult. As human beings, most of our decisions are influenced by our feelings. Even if we try to “think with our heads and not our hearts,” it’s often impossible to separate the two completely. After all, most of us strive to be fair and ethical. Can computers be fair and ethical? At the moment – no. In the future – probably not. AI is not human, and we need to realize that. Amazon learned this the hard way when they had to scrap a biased recruiting tool.

Back in 2014, the company decided that they wanted to make recruiters’ jobs much easier. So, they built technology to help. That’s what tech is supposed to do right, help us. This new technology came in the form of a searchable database that could provide recruiters with the top 5 candidates for any given job at Amazon. They trained their system to vet applicants by observing patterns in resumes that were submitted to Amazon over the course of a decade. It wasn’t until a year later that they realized the system was not suggesting any women for software developer and tech jobs.

Looking back, it’s easy to see why: Men have dominated the tech industry for the last decade. Keep in mind that AI learns by seeing examples. So, Amazon’s AI taught itself that males should be the only candidates. It even went so far as to penalize resumes that contained the word “women”! This project was scrapped. It was no help to recruiters and fueled discrimination. This is just one example in a sea of many that demonstrates why AI will always need people.

future of AI

No matter how high-tech it is, AI is limited. Humans will always need to take the lead. Yes, we want a future filled with technology that will solve our biggest challenges. This will most likely happen at some point, but it won’t be because of magic. There’s no snapping your fingers and having a solution. Technology is only as advanced as the people who create it, and it can’t succeed without us.

Last year, MIT did a study in which they compared teams of humans and robots. Some groups were human-only teams, others were robot-only teams, and still others were human-robot teams. Their findings indicated that the most efficient teams were the human-robot teams. In fact, these were 85 percent more efficient than the others.

Working together, humans and robots will change the world for the better. When we’re able to design AI products with user experience as the focus, AI will be a success. When we truly understand users’ capabilities and whether or not they fit into AI’s design and its environment, AI will be a success. When we master error rate, performance, satisfaction and learnability, AI will be a success. It’s just a matter of time.

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