By: Zoe Hillenmeyer, Chief Commercial Officer for Decision Intelligence company, Peak.
There’s been a lot of chatter recently around the acceleration of AI. Twitter news feeds have been full of images generated by DALL-E, an AI model that converts text prompts into images. A Google engineer’s claim that the company has built a ‘sentient’ chatbot sparked debates around whether conscious AI exists. And amidst it all, there’s growing confusion around what AI is capable of today, and where it could be headed in the coming decades.
In a recent opinion piece for the New York Times, columnist Kevin Roose argued that as AI grows more sophisticated, we need to increase public influence on how this technology is put to use. I couldn’t agree more; but I think we need to start by dismantling the idea that AI is necessarily sophisticated or complex in the first place.
There’s a common misconception that only an exclusive tech elite can understand AI—and that it’s these people who will determine its future. But there are actually many different ways to learn and implement this technology. In my experience building AI teams, I’ve found that creative people who don’t come from a technical background are often just as adept at picking up the principles of AI.
Taking AI off its Pedestal
At its core, AI works by mapping math to reality. People who are great at that, it turns out, are people with great intuition. People who can pick up on patterns. Plenty of us are doing this in our jobs every day: making sense of data, and predicting the right decision. Many people could apply AI to this process—if they were empowered to do so.
I’ve been working in AI for the past decade, but I didn’t take a typical pathway into the field. I’ve always enjoyed math and science, but also art and design. I don’t have an advanced computer science degree, but a BFA in sculpture and MBA in strategy and consulting. There are people from all walks of life who have the capacity to understand how AI works. The trouble is, many have been conditioned to think this knowledge is entirely out of reach.
The Roadmap for AI Education
To engage a diverse population in determining the fate of AI, industry stakeholders must work to democratize a working knowledge of this often misunderstood technology. Private companies play an important role—and they have a vested interest in making it happen.
Five years ago, 90% of my meetings with business leaders began with a lengthy conversation about what machine learning even is. Today, most of the people I speak with already have a sense of what machine learning is, and many are trying to use it to solve problems. But to bring those strategies to life, companies must invest in upskilling employees across functions—from marketing to the warehouse floor—with a working understanding of AI. Any company that wants to remain competitive over the next decade must commit to putting dollars behind this kind of education. You can invest endless amounts in a flashy application, but if end users aren’t equipped to use it, it’s worthless
The buck doesn’t stop with companies. The media has an outsize role to play in making AI feel like something the general public can understand and influence. Currently, the media narrative around AI is damagingly polarized. AI is either presented as a mysterious, futuristic technology on the level of popular space travel and cryogenic freezing. Or, it’s a terrifying threat that’s going to steal all our jobs and take over civilization.
Even emerging organizations that purport to be democratizing AI often provide resources that are exclusively technical. It is extremely hard to find educational, factual information. The result is that almost 40% of Americans are concerned about the future of AI, while 84% are “AI illiterate”.
Private companies, the media, and educational institutions are all responsible for improving these statistics, and engaging a diverse community in shaping the future of AI. To make this technology work for the good of all people, our society’s understanding of its fate must be informed not by fear, but by knowledge.
- Neural Networks Learn Better by Mimicking Human Sleep Patterns
- 7 “Best” AI Translation Software & Tools (November 2022)
- Conversational AI Is Making Customers and Employees Happier. Here’s How.
- Electricity Helps Find Materials That Can “Learn”
- Lack of Trustworthy AI Can Stunt Innovation and Business Value