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This column is part of Globe Careers' Leadership Lab series, where executives and experts share their views and advice about leadership and management. Follow us at @Globe_Careers. Find all Leadership Lab stories at tgam.ca/leadershiplab.

In the Information Age, we have more choices than ever before – which makes choosing harder than ever. If you go to your local Barnes & Noble store, you can choose from maybe 50,000 books; but Amazon offers millions. Thankfully, it also has a 'model of you', based on everything you've ever done on the site. Effectively, this model does your browsing for you, and presents you with your own bookshelf, different from everyone else's. Netflix has a similar model for movies. These customer models generate 33 per cent of Amazon's revenue and 75 per cent of Netflix's.

Such models aren't just for books and movies: increasingly, they are being created for everything we consume, online or offline. Even Walmart uses machine learning to decide which goods to stock and where to put them in the store. Machine learning is the new 'middleman' in just about every transaction – from products to jobs, medical treatments, even relationships. These days, a third of all marriages start out on the Internet, and the matchmakers are machine-learning algorithms. There are children alive today that wouldn't have been born if not for machine learning.

There is one big problem with all of this: each company's 'model of you' is based only on its own interactions with you, because that is all it has access to. As a result, these models are narrow and incomplete. There is a better way, and it involves pooling all of the data you generate, and from it, creating one complete, 360-degree 'Model of You'.

Think of all the variables that characterize you, and how they depend on each other. In principle, machine learning can figure out what those dependencies are. As a result, it will soon be able to predict what you need right now, or whether two people are a good romantic match – not just based on their profiles, but on their entire lives. It will also be able to predict whether you'll like a particular job at a particular company, based on everything it knows about you, the job, and the company. And from your vital signs – continuously captured by your smartphone's sensors – it will be able to predict whether you're about to have a heart attack, and call 911.

One day soon, everything that gets bought and sold will be based on these models. Personal models are the ultimate platform, and the world economy will run on them. I don't think it's an exaggeration to say that this may be the greatest business opportunity in history – and that whoever provides people with their personal models will be running the world economy. Not surprisingly, powerful companies are already pursuing it, full tilt: Google has Google Now; Apple has Siri; Microsoft has Cortana; Facebook has M; Amazon has Echo. And there are others.

Wouldn't it be crazy to try to compete with these giants? Actually, no. The problem is that each of these companies has an existing business model. So, they want to serve you, but they also want to make money in their own specific ways: Apple by selling you gadgets, Google by showing you ads, and so on.

What we really need is a different kind of company – one that is to your personal data a bit like your bank is to your money. Your bank stores your money and keeps it safe, but it does more than that: it invests it on your behalf. Similarly, your data bank will store your data, learn and continually update the Model of You and use it to accomplish things for you.

Once you have a personal model, you will be able to tell it that you're looking for a job, and have it instantly interview for all the open positions that match your specifications, by interacting at high speed with the models of the employers' HR departments. While one copy of your model is doing this, another can be browsing for a new car for you, exhaustively researching all the options and haggling with car dealer bots, so you don't have to.

Whoever wins this race has a good chance of becoming the world's first trillion-dollar company. And, as with every wave of technological innovation, there are tremendous opportunities in riding the coattails of the change.

If we do this right, a bright future lies ahead where our lives will be happier and more productive. If we don't, it will be a huge missed opportunity.

Pedro Domingos is a Professor of Computer Science and Engineering at the University of Washington and the author of The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World (Basic Books, 2015). He was a featured speaker at the Rotman School of Management's Machine Learning Conference in 2015 and 2016.

A version of this article appeared in the Fall 2016 issue of Rotman Management, the magazine of the University of Toronto's Rotman School of Management. Reprinted with permission.

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