The position of specialised professionals is coming to an end - machine learning and AI is set to change it tommasourbinati/iStock


When I were a lad, watching the news on the telly, waiting to be allowed to use the set to plug in my ZX Spectrum, I'd be told to concentrate on the stories from the nearby towns: car workers being laid off as robots took their jobs. Stay in school, son, and get into a profession. A degree and a place in a management trainee scheme was the preferred route. Don't make things, be a knowledge worker, I'd be told. The future isn't (one word, Benjamin) plastics. Not goods, but services. Information is the new oil. Bits, not atoms, the most valuable of commodities.



And that's pretty much how it turned out. Today, around 80 per cent of the UK's economy is services. In 2015, the latest figures show, the UK exported more services than goods. We don't make much stuff, but we're really good at moving information around. It's what makes the City of London the financial powerhouse it is. It's what gives British law its own special reputation. It's what distinguishes British advertising agencies, architects and academic centres. Not a nation of shopkeepers, but a nation of knowledge pushers, data filers, accounts completers and money movers.

The most valuable and well-paid jobs in the UK create value by changing meanings. And at the top of that pile are the professions: the subset of jobs to which entry is controlled by specialist qualifications and social acceptance. The bankers, lawyers, accountants and so on, who are allowed to do their jobs because they have proven, to someone, that they understand the secret knowledge, the secret words they need to intone to get their jobs done. Those dudes, frankly, make a lot of cash.

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But here's the idea: the rarefied position of the specialist professions is coming to an end, a change driven by both the increasing capabilities of digital systems - machine learning, big data, all the good AI buzzwords - and the changes wrought by a digital society.

Machine learning versus AI: what's the difference? Machine Learning Machine learning versus AI: what's the difference?


Let's take those social changes first. The internet is good at two things: introducing people and making distance irrelevant. It's weird to think, given the normalisation of the way we live today, but for the majority of human existence if you wanted to find an expensive professional to help you - say, a lawyer - you'd have to find one both through a specific type of introduction, and one that was local to you. There was no Googling it, and ordering something from a site hosted who knows where.



Futhermore, that specific introduction is sometimes even codified into the rules of the profession: you can't simply hire a barrister, for example. There are rules, and it is just not done.



So here's the deal with some professions: only certain people with certain knowledge are allowed to do certain work, and getting access to those people is limited by where you are and who you know. Naturally, in this world all sorts of dodgy power relationships evolve, but this has been the case for so long that it seems natural.

Thinking in this way, however, ignores the artificial nature of these restrictions: what if the actual function of those jobs could be done by someone or something whose expertise wasn't controlled by a guild? What if you could employ someone or something directly, and someone or something could fulfil their function from anywhere on the planet? If that were to happen, it would give all comers access to the same level of professional services.

If that were to happen, it would rapidly plunge traditional professions into a new economic reality. If that were to happen, it would drive the price of professional services down rapidly and irreversibly. If that were to happen, the power given by academic and geographic rarity would be neutralised.



That is what is happening.


Banking and legal jobs now belong to the computers Matt Blease

You see, it turns out that the professions have a dirty secret: most of the things they do aren't that tricky. A good deal of law, accountancy, even medicine can be aligned to a flowchart. Start at the top and work down: is the patient alive or dead? If dead, stop. And so on, and so on. A high proportion of rarefied professional work is actually entirely diagrammable in this way.



And if you can do that, you can make it into a computer program. A complex one, for sure, but if a modern AI can beat a Go grandmaster, it can fight a traffic ticket in court, do your accounts, check your contracts, organise your diary, or invest your money. And all of those are specific examples of tasks that, in 2016, have given rise to companies whose digital systems have replaced humans. Digital systems whose location is utterly irrelevant. Digital systems that are only getting smarter.



Task by task, certificate by certificate, AI-powered companies are doing the jobs that have traditionally been expensive solely through artificial means. Computers were built to manipulate data. In 2017, we'll find they're really good at it. Perhaps learning to make things would have been a better idea.

The WIRED World in 2017 is WIRED's fifth annual trends briefing, predicting what's coming next in the worlds of technology, science and design