By Angela Harvey, Senior Director, Strategic Ecosystem Marketing at SAP

The power of AI to solve large-scale problems perhaps met no greater test than COVID-19. Around the world, medical experts have leveraged AI to drastically reduce the time scale of finding and developing a new vaccine to treat the pandemic.

“One of the time-consuming pieces is really around the analysis of billions of different molecules and how those might be used to do chemical binding to the target protein that we’re looking at,” Dan Drapeau, an artificial intelligence (AI) expert and head of technology at Blue Fountain Media, told TechRepublic in August 2020. “Humans can’t possibly do that. It could take forever.”

With the help of AI, it didn’t take forever. By November, two vaccines in the U.S. with 95% or greater efficacy were making their way through emergency approval processes. If the approval moves forward, the finding and development of a vaccine for COVID-19 will beat average vaccine development timelines by years.

“The development of vaccines can take years,” explains the Mayo Clinic website. “This is especially true when the vaccines involve new technologies that haven’t been tested for safety or adapted to allow for mass production.”

AI is the new, quickly maturing tool at our disposal allowing for such a monumental achievement. So monumental, in fact, that many believe the awakening of AI is the next great human revolution. Like the invention of the printing press or the rise of the Renaissance, AI has the power to open the doors to an incredible proliferation of knowledge and creativity.

And this time around, we have the chance to do it right. Recently, I was joined on a (notable) all-woman panel by leaders from Intel, Microsoft, and SAP. We met to discuss how AI can be used for good. What are the pitfalls? Where could it go wrong? But ultimately, like with the COVID-19 vaccines, how could it help address some of the biggest challenges humankind has ever faced? We met to discuss the future but first we had to look at lessons from the past.

What the Engine Can Teach Us About Artificial Intelligence

Groundbreaking and world-changing technologies have been invented before. Take the engine, as Genevieve Bell a Senior Fellow, New Technology Group, at Intel explained. It took a century of innovation on the engine (first steam, and then combustion) to make it small and portable enough for widespread use in trains. It took longer still for us to build railway systems to fully utilize the benefit of trains (not to mention in-station ticketing systems to monetize trains and keep track of passengers).

And when we did, our very idea of time shifted.

This is because trains needed to have a single time zone to function effectively. Timeliness was important for the reliability of the new transportation method, but also its safety. Two trains running in different time zones were much more likely to collide.

At first, train stations required clocks in the stations and on trains –– all of which ran within the same time zone. Outside the train station, local British townships still ran by their own local time. It took 40 years for the British government to intervene, and mandate that train time had to become standard time, or Greenwich Mean Time (GMT) as we call it today. Soon, the entire world had to shore up their local time zones to one of the 41 in use in 2020.

AI will have a similar effect. Our understanding of the world will change as AI matures, and grows an entire market around it. It isn’t a question of if, but a question of when AI will shift something as profound as our understanding of time.

The Importance of Innovating 100 Years into the Future

Yet, our invention of the engine wasn’t perfect. No technology is.

The engine allowed us to build incredible transportation systems that resulted in the creation of historic buildings, more productive cities, and the easier sharing of food, water, and other necessities to those not in the vicinity.

It shaped our modern economy and our modern comforts. It also contributed to global warming, a looming existential risk for humanity.

If we were able to go back and re-design the engine to be more fuel-efficient and less polluting, would we not? Does the invention of the engine not look different through the lens of more than 100 years of use?

We can learn from inventions like the combustion engine and apply our learnings to our current philosophies and models for AI. We need to think “not one or two or even 10 years down the line, but really think hundreds of years ahead,” says Lila Tretikov, Corporate Vice President and Deputy CTO at Microsoft.

It’s a sentiment about AI that has been echoed by the likes of Stephen Hawking and Microsoft researcher Eric Horvitz. The topic even earned its own episode in the podcast “The End of the World” with Josh Clark, ending with the need for humans to code “friendliness” into our AI creations. In the episode, Clark states:

“We’re at a point in history, where we could create the greatest invention that humankind has ever [made], which is a super-intelligent AI that can take care of humans’ every need for eternity. The other fork in the road goes towards accidentally inventing a super-intelligent AI that takes over the world, and we become the chimpanzees of the 21st century."

**The Upside of AI and How to Integrate Ethics **

Norbert Wiener, one of the grandfathers of AI, said in 1950, "Either the engineers must become poets or the poets must become engineers.” He foresaw the need for the philosophical and the moral to intertwine more purposefully with this technology and innovation.

Indeed, AI and its implications require us to be more thoughtful, to aim not just at solving a particular problem, but to first make sure the problem we’re aiming at is the right one. AI needs to solve problems for all of the human equation, not just the privileged, and not at the expense of those without access.

“What is the solution we’re trying to aim for? Who is privileged by that solution? Who is left out? How do you make sure you have a wider range of voices in the room or a wider range of experiences? How do you make room for all of that right now so that you don’t end up having to fix the problem long after it’s been built,” asks Genevieve Bell, a Senior Fellow, New Technology Group, at Intel.

Identifying the right problems to solve with AI will require a diverse group of people and experiences shaping its future. To do that, technologists need to think outside of a technology box, and start asking better questions: How am I thinking about AI ethics? How am I thinking about inclusivity? How am I thinking about devising my system?

Perhaps most important, however, is making AI accessible and understandable by all. Creating AI in a silo only generates fear, misunderstanding, and higher possibilities of misuse. If we’ve learned anything from our major inventions of the past, it is that technology is not magic, and its implications are too far-reaching to leave anyone behind.

“As a scientist, I think it’s our responsibility to use technologies to open the black box and let people understand what we’re doing,” says Dr. Feiyu Xu, Global Head of Artificial Intelligence for SAP. “People are understandably scared of what they don’t understand, but AI isn’t magic.”

I left the panel feeling inspired by these leaders about the opportunity for AI to help the groups who need it most and free up human’s time for more creative endeavors. But they were the 1st to acknowledge a good dose of skepticism is healthy; we know we only get one chance at getting it right. Let’s learn from the past and use AI to focus on building a better version of ourselves and put it to good use.

*Watch the highlights of our Panel discussion “How AI Can Serve the World” or watch the full webcast. *