TED@IBM 2017: Dare to Ask “Why Not”

TED@IBM is an annual event with talks exploring the relationship between technology and humanity. The most recent one was held in San Francisco in December 2017 with the theme “Why Not?” Alexa Youssefian shares with us her learnings and insights from her favorite talks at the event.

By Alexa Youssefian

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Photo Credit: Madeleine Matthews

 To build big, you need to think big. Where some only see obstacles, big thinkers imagine a way forward. These are the visionaries who dare to ask, “Why not?”

That was the theme of this year’s TED@IBM in San Francisco: Why not? It’s a mantra that’s inspired breakthroughs through time, and it’s the principle that continues to push progress today, especially in artificial intelligence and machine learning. These technologies have seemingly endless potential, if we’re only willing to imagine what could be.

Those who took the stage at TED are no strangers to moonshot ideas. One fourteen-year-old AI ingénue says we can leverage predictive analytics to identify depression in teenagers; a refugee advocate believes we can use artificial intelligence to predict emergency migrations. Each of these “why not” thinkers shared their bold visions for the future, and I took a lot of notes. Here are some highlights from a few of my favorite talks.

Predicting the Next Refugee Crisis with AI
Big data is changing the way we do business, but Rana Novack imagines a future where we extend its utility to humanitarian crises. Rana’s family fled Syria as refugees, and they quickly encountered the dilemmas all refugees must confront. “Stay in a familiar place, or leave? Staying meant risking their lives; leaving meant an uncertain future in an unfamiliar country. And where would they go?”

There’s no easy choice.

Rana’s vision for the future involves using artificial intelligence to predict emergency scenarios ahead of time to curve their devastating impact. With the power of predictive analytics, “We can answer questions, like, ‘What if we close a border? What if transportation is unavailable?’ We can react to refugee crises proactively.”

Artificial Intelligence with Emotional Intelligence
Our interactions with computers today are emotionally static, but Raphael Arar believes this exchange will become more dynamic once we learn to program emotional intelligence. Raphael is a technology artist, using art to close the gap between humans and computers. “Art attaches tangible experiences to intangible things.”

According to Raphael, the complex web of human emotion poses a challenge when building artificially intelligent technology, because even seemingly simple human behaviors contain layers of nuance. One example: helping computers recognize nostalgia – an emotion that’s simple on the surface, but difficult to define programmatically. Raphael asked: “How do we take a highly subjective emotion and turn it into something that’s mathematically precise?”

Ultimately, Raphael believes intuition is the quality that separates man from machine, and the bridge that might connect our worlds. “Unconscious knowing is what helps us make amazing things and come up with creative ideas. If we want computers to relate to us and amplify our creativity, we have to think about how to make computers intuitive.”

Using Neural Networks to Identify Teenage Depression
Suicide is the second-leading cause of death among teenagers today. Tanmay Bakshi believes we can curb the trend, using artificial intelligence to detect signs and symptoms of depression.

Tanmay, a fourteen-year-old neural network architect, shared that 80% of teens today display clear warning signs of suicidal intent. By tracking lifestyle changes, Tanmay believes systems can recognize these irregularities in data, helping us build early warning systems for teen depression.

In the past, these systems have been difficult to implement because of noise in data – but because of neural networks, we can remove the grain and identify important patterns that could help save lives.

Bridging Two Cultures
As new technologies change how we live and work, we hear a lot about the singular value of a STEM-dominated workforce. Eric Berridge, engineer co-founder of Bluewolf, argued that this sentiment is “tempting, but totally overblown.”

It’s not a knock on STEM, but an endorsement of a diverse workforce that melds the sciences and humanities. This becomes an important guiding principle for us today with AI – once the technology works, we need to make it work for humans. Programming that human-machine interaction will require input from philosophers, psychologists and historians – not just engineers.

Eric closed by encouraging people to “study whatever they want,” as technology becomes more accessible and easily manipulated without writing code. With this diversity of disciplines, we might be able to program technologies that are equipped with equally diverse capabilities.

 In Conclusion
AI, like any other technology, is a tool that helps us live and work more intelligently. At IBM, I’ve seen firsthand how machine learning and AI are used to solve some of the world’s most complex challenges.

The speakers at TED@IBM painted a picture of what this might look like in the future, and how we can use the potential of machine learning to affect real, human change. It’s exciting to imagine a future that’s made safer with the help of emotionally intelligent AI, systems programmed by engineers and philosophers alike.

To make that future a reality, we start with a bold first step: daring to ask, why not?

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