To realize their potential, AI technologies need new systems that leverage them.
Start-up founder: “It will give them insights.”
The top prize in sailing is the America’s Cup. Today the race is as much about technology as about the skills of the crew. Millions of dollars go into boat design. Since the physics of wind, water, and ships are well understood, competitors use simulators to identify the most effective designs and to test boats without actually building them. The team with the best simulator gains a big advantage, as Emirates Team New Zealand discovered in 2017, when it won the cup.
Why was this use of AI so novel? Setting aside the impressive technology that allowed for simulations in complex environments, the key impact was at the system level. The AI wasn’t handing Emirates Team New Zealand some insights. Instead, it was being built into a system of decision-making. Translation software, an early application of AI, is a good example. It predicts how people would translate a given text from one language to another on the basis of how real humans have translated previous texts. AI classifying medical images, another early application, predicted what expert radiologists would say that scans showed. Both applications leverage the wisdom of the crowd, which can often make far more accurate predictions than one person can.
And that’s the real lesson from the America’s Cup. Emirates Team New Zealand didn’t take the people out of the process. Yes, it is possible to imagine a fully automated solution that makes every decision. But that approach is surely a rarity. AI prediction provides information that improves decisions, which are made by people. Interestingly, with AI the difference is not so much whether machines do more but who the best people to make decisions are.It’s curtains for the taxi industry.
The platforms and their AI had two important effects. First, vastly more people could now be involved in making decisions about rides, and second, drivers’ control over decisions decreased. Because the ride-share platform could match drivers and passengers and identify the best routes, all the drivers had to do was focus on providing comfortable and pleasant rides that satisfied the customers assigned to them.
In all these cases the application of AI has changed how and by whom decisions are made. But the introduction of AI into your company’s decision-making doesn’t affect just you. It also affects your partners in the value chain and the ecosystem you operate in. What works for you may create problems for them. Let’s look now at how that can happen.Imagine you’re running a restaurant. Diners come in and order meals. The cooks then make them.
But your local supplier has been used to buying 100 pounds for you each week. Now it faces more unpredictability because of you. Its other customers are also using AI for demand forecasting, and demand starts to fluctuate wildly. So the supplier decides to adopt AI for its own demand forecasting. It used to order 25,000 pounds of avocados a week. Now its order varies from 5,000 pounds to 50,000 pounds.
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