In January of this year, the European Parliament proposed that robots be called “electronic persons,” and have all the rights and responsibilities of any European citizen. The move was less about what robots and artificial intelligence are today, and more about what they might become.
It’s exciting to see major institutions like the EU start to take seriously what we’ve long been anticipating at GE—the day when our co-workers aren’t always human. And just as we’ve long sought to make our human teams diverse, new advances in artificial intelligence and machine learning are helping us discover diversity in our machines.
The machines that work alongside us are becoming increasingly sophisticated and developing specific areas of expertise. Take a Predix-powered jet engine flying in a hot, dry environment like a desert. Over time, the machine mind in the engine – what we call a Digital Twin — accumulates a set of data and the engine acclimates to make it different from the same type of engine that spends its time flying in a tropical climate. But to get the full range of insights about how a certain jet engine performs, we can analyze the unique experiences of GE’s 36,000 jet engines in operation around the world. This allows us to include an unprecedented diversity of backgrounds and experiences to achieve the most accurate assessment of how that one engine is performing.
We’re living at a time when both machine and human diversity, and the better outcomes they promise, are vital. Organizations are thirty-five times more complex than they were in 1955, and complexity is only increasing. We need all the knowledge, insight, and ingenuity we can muster. In every aspect of business, we need different machines with different experiences offering different outcomes for the systems and assets they control.
But it’s not enough for machines to have different experiences – we need to use these insights to enable them to take initiative. Think about your calendar app. It knows when your co-workers are free to meet and how long it will take you to travel to your next appointment. It takes the initiative to remind you when you have an appointment coming up or when you’re double booked. We take it for granted, but until recently this kind of help was available only to people who had a personal assistant.
A fully networked industrial infrastructure combined with machine learning is about to unleash similar changes, but on a much bigger scale. GE’s Predix platform collects data from sensors on big machines like jet engines, crunches the numbers using A.I., and then takes the initiative to speak up when repairs are needed or key milestones are close.
For those companies that use Predix it is, in effect, a new kind of employee offering entirely new capabilities. Like our most valued employees, it doesn’t wait to be asked to make itself useful. It takes the initiative.
Imagine the impact of both machine initiative and machine diversity on a company like Walmart, which relies on a tightly connected, global network of systems to get goods and services to customers. What if insights from their physical stores were connected all the way to the first links in their supply chains? What new types of decisions might Walmart’s managers be prompted to make by their machine colleagues?
Machines empowered by artificial intelligence are already a commercial reality. The global market for AI is currently about $8 billion and expected to grow to $47 billion by 2020. Intelligent machines will likely be adding their diverse viewpoints to every conceivable area of human activity. A World Economic Forum poll even predicted that an A.I. will have a seat on the board of directors of a major corporation by 2025, just eight years away.
How do you think machine intelligence will change the way that decisions are made and value created? Where do you think A.I. will be employed?