The AI Boss That Deploys Hong Kong's Subway Engineers

Taco Cowboy writes The subway system in Hong Kong has one of the best uptimes: 99.9%, which beats London's tube or NYC's sub hands down. In an average week as many as 10,000 people would be carrying out 2,600 engineering works across the system — from grinding down rough rails to replacing tracks to checking for damages. While human workers might be the ones carrying out the work, the one deciding which task is to be worked on, however, isn't a human being at all. Each and every engineering task to be worked on and the scheduling of all those tasks is being handled by an algorithm. Andy Chun of Hong Kong's City University, who designed the AI system, says, "Before AI, they would have a planning session with experts from five or six different areas. It was pretty chaotic. Now they just reveal the plan on a huge screen." Chun's AI program works with a simulated model of the entire system to find the best schedule for necessary engineering works. From its omniscient view it can see chances to combine work and share resources that no human could. However, in order to provide an added layer of security, the schedule generated by the AI is still subject to human approval — Urgent, unexpected repairs can be added manually, and the system would reschedule less important tasks. It also checks the maintenance it plans for compliance with local regulations. Chun's team encoded into machine readable language 200 rules that the engineers must follow when working at night, such as keeping noise below a certain level in residential areas. The main difference between normal software and Hong Kong's AI is that it contains human knowledge that takes years to acquire through experience, says Chun. "We asked the experts what they consider when making a decision, then formulated that into rules – we basically extracted expertise from different areas about engineering works," he says.

Comments

Good

[kruach aum]

Everything currently run by committee should ideally be run by an AI with limited human oversight in the future. Groups of humans suck at the two things AIs are great at: remembering things and making decisions.

Re: Good

[kruach aum]

That sounds suspiciously like a decision to me, comrade. Do you have documentation signifying that you are 100% pure AI?

Re:I can't imagine something like that in the U.S.

[oodaloop]

I dunno. If a corporation smells a profit in it, then I think they'll find a way.

Expert System

[DontBlameCanada]

This is a perfect example of an Expert System.

Expert Systems have been one of the most successful and longest used AI models in industry. FPGA routing and layout programs have relied on this form of AI since the early/mid 90's.

Management is becoming obsolete

[Anonymous Coward]

What we see now are the first steps towards making a big chunk of management obsolete. Expert systems are well on their way to out-compete managers who in many situations cannot make decisions of the same quality as an AI. Or to put it differently: An AI can make better decisions than a human in many areas. And in these areas humans (managers) will not be able to compete.

Re:I can't imagine something like that in the U.S.

[i kan reed]

Riiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiight. It's those unions. Those ones whose membership has been steadily and measurably been decreasing for 30 years(almost exactly at the same rate as wage stagnation occurs, as a complete coincidence).

How small does Snowball's organization have to get before you stop believing he's behind everything?

Re:So...

[Shoten]

In other words, this is basically Drools, plus a ton of billable consulting hours?

Actually, it's probably something more like TIBCO BusinessEvents with an orchestration engine added. But what's really cool is that they did the hard part: codifying the actual rules under which the overall system operates. That's where these kinds of systems either fly or fall. There are tons of rules that organizations use to make decisions, but a lot of those rules are quite informal and don't operate at a central point of authority. It takes a lot of digging to find them all, so that the undocumented process (for example) used by the foreman of the team that does rail maintenance to manage overtime among his crew gets incorporated into the overall chaining logic. Otherwise, the new system will either fail to reflect reality as teams rearrange their own schedules out of sync with their directives, or will wreak havoc among the employees.

Re:So...

[K. S. Kyosuke]

Actually, it's probably something more like TIBCO BusinessEvents with an orchestration engine added

Back in my time, we called what they have done now "an expert system". I fail to see why that designation should be suddenly inadequate.

Now is the time fire the experts.

[140Mandak262Jamuna]

We have talked to the experts. Extracted their wisdom. Encoded it into machine readable rules. Proved that all the expertise has been extracted by the 99.9% up time.

So, naturally, the next step is to fire all those people who would no longer have something to contribute. As a purely added bonus all these people fresh out of things to contribute happen to be with years and years of experience, which means seniority and high pay.

The mid level bean counter would think, "well, I should be able to fire at least 20 of them. Savings of 2 million on pay, another million in benefits, almost 10 mill over three years. Even if I have to let the SOBs CEO and CFO grab a mill each, I should be able to get at least 250 K for myself. Time to fire up power point, 'Work Force Optimization due to the increased Efficiency achieved by the AI system. By Gottah Avemyb Onus, Sr Vice President, Hatchet Division'"