Reports of our death are an exaggeration

Deutsche Bank’s CEO John Cryan thinks his employees’ days are numbered. The rise of the machines will do for them, in due course: not just back office grunts, cranking out settlements and reconciliation: everyone. “Today,” he warns, “we have people doing work like robots. Tomorrow, we will have robots behaving like people”.

Cryan’s high-rolling bankers are vulnerable. Even, we suppose, Cryan himself. No bad thing, some might say — who will miss a few liquidated bankers? But it implies a view, widely held, that technology is about to reach a tipping point: no longer just faster, cheaper, better and less aggravating than the sacks of meat who carry out your routine tasks, but equal —- even better than — the sacks of meat who do the hard stuff.

There is much millenarian hand-wringing about this, on blogs and on the new media.

Not so fast.

Technology is not new. Since someone invented a plough, humans have replaced manual labour with technology to get the boring things done.

Start with this observation: machines follow unambiguous logical instruction sets better than humans do. By definition - that’s what it is to be a machine. They’re quicker, cheaper, less error-prone. Always have been and always will be.

But all machines operate in a tightly constrained environments. They react to pre-conceptualised decisions with pre-configured responses. Take a machine out of its environment and it is useless. (Good luck getting a Jacquard loom to plough a field). But buried in that observation is this one too : humans are better at handling ambiguity, conflict, evaluation of novel questions. Humans are great at configuring machines: they can form theories, test them, adjust them - diagnose what is working and what this haywire. Technology has certainly rendered short-term dislocations - big ones - but the long-term prognosis had been benign: saving the population from automatable labour has freed it to do things it previously had no time to do, or hadn't realised you could do before the technology came along. Technology opens up design space. It has stretched the ecosystem: taken it places it couldn't go before. Technology domesticates the ground you have, but opens up frontiers where you can go. The thing about frontiers is that they're new. They contain the unknown: there be dragons. There lie dilemmas you've not faced before. Try pointing a Jacquard loom at the wild west. Since the wheel, Technological innovation has always generated more work, not less. The population has grown in step with the growth of technology, and we have worked harder with it. So, if your argument is the continued development of the faster, cheaper, more flexible “recipe followers” will reverse that trend - will, net, put people out of work you'll need to explain what is different now. Mr Cryan’s assertion : this is about to change. Mine : That’s a big shout. So for one thing note that Mr Cryan is talking his own book. Banking is a much harder business than it used to be, opportunities to develop new businesses (read: pushing new frontiers) are diminished, managing to margin is de rigeur. Mr Cryan should fire as many people as he can. That is what his investors want to hear. Note also that investment banking is far less of a judgement-based and evaluative industry than it used to be. Much of it can be boiled down to formulating rules and following them by rote. Only the edge cases require judgment. Automating operations to cope with the known knowns is only good business. Humans are bad at rule following. They are expensive. They occupy real estate. They require human resources departments. They screw up. They leave. They don't write things down. But the edge cases are the frontiers: the situations of real risk. Unknown unknowns. Given how crappy their judgments have been over time you might say that is quite a good thing too. So, two things here: the race to automate the known knowns is a race to the bottom. The very value in a banking product is the complexity and skill. Once a process is automated, it's replicable. Margins drop to nil. Everyone will be at it. If Mr. Cryan thinks that is the future of his business, he needs his head read. Your future, sir, is in your people. Your robots may accelerate that future, but they can't conceive of it, and they can't deliver it. High frequency algo trading is the obvious place where the machines already run the show, handling all the trading, routing and interrogation if venues for liquidity. It's a complex business, done at immense volume at lightning speed, and humans have no hope of competing. But there are plenty of humans still employed in programme trading. They code the algorithms. They monitor the algorithms’ performance. They intervene when the algorithms go haywire, as sometimes they do. The algo can only follows its rules instructions: it doesn't know it is going haywire - it can't introspect - let alone what to do if it does. The humans modify the algorithms to stop them going haywire again. They sell. But in any case, the fundamental division of responsibility is the same: machines follow the rules, humans figure them out. Algo-trading is the poster for artificial intelligence: elsewhere, the barriers to implemention are human, not technological. Every bank of onboarding is a disaster : legacy systems piled on legacy systems creaking to deal with hopelessly convoluted approach documentation, credit risk management and regulatory compliance that date from the nineteen-nineties when derivatives trading was a new and exciting idea. Instead of shaking this mess down, slimming down, commoditising, firms have outsourced large parts of it, making the whole mess exponentially worse and less soluble. There is huge scope for more automation