AI in the Near Future: Dr Merlin Stone on the Parallels of Marketing and Medicine
If I were to follow that through, which is politically very, very controversial, why do I say that the National Health Service (NHS) has such poor results compared to the rest of Europe? It’s because the more money spent on it, the lower the quality gets because the spending mechanism is not about improving outcomes, sadly; and all the statistics now show that we're roughly, in terms of outcomes, rather like an Eastern European country — Simply put: no one is challenging the data.
Everybody has good stories about the NHS, but many people have bad stories about failed diagnoses and failing to have efficient treatment. It's not about public or private medicine, it's about data. So in Europe most health systems are public, but they’re split between the provider and the insurer, and the insurer can challenge the provider looking at the data about achievements and saying why aren't you doing blood tests early on which is what we don't do here in the UK? And we're spending lots of money rectifying stuff, which you wouldn't have had to rectify if you’d done a blood test to start.
A Better Future?
Peter: Are there any countries that you know of that are performing well by analyzing the data?
Dr. Stone: Yes, because the health insurer does it; that’s how they develop the view about whether they should pay the provider — by looking at the data — and that's what you see in Germany, Italy, France and all the Nordic countries and so on. A simplistic view perhaps, but the structure is part of it — you need the people who are delivering of course, but you also need somebody to look at the data and challenge the quality of the delivery.
Peter: But is that really AI?
Dr. Stone: Yes, they use AI to do it.
In the UK, are we just analyzing tons of raw data without applying intelligence besides human intelligence looking at results?
When it’s a very complex set of data you need AI. You need data mining, which is an early part of AI before you have an idea. You just tell me what’s happening in the system. You can argue that no hypothesis based work would have picked up the killer doctor, Harold Shipman for instance. Why would you have identified this guy? You might have done some simple outline analysis, but basically you want to look at the whole system and tell me what’s going wrong.
Peter: Shouldn’t mortality rates per doctor have shown disparities?
Dr. Stone: But you've got a million things to look at — why would you look at mortality rates per doctor? Just tell me what's going wrong. That's in a way what AI does — it goes to the meta-level. It says: actually don't worry about getting it right. That's our job in the end; I’m the artificial brain; I'm going to help you by always identifying the things that are going wrong. And not just bad things that are going on, they may be good things. In this field, the Nuffield organisation, which is a research body, clearly says that efficient hospitals are also better hospitals. The ones who are under tough financial pressure and manage with it are also the better hospitals because they're better managed. But that's quite a big statement and has been backed by loads of researchers. My preference would be to feed the data into a system, which tells me what's working and what's not — rather than hiring lots of highly specialized researchers!
Peter: It can be depressing looking at how things are at present, but you sound very positive about the future of AI.
Dr. Stone: My dream is that one day all the stuff that’s done by all these highly skilled analysts and stats people won't be needed anymore because we're just going to say: ‘Alexa, tell me what's working in my local health service?’ Yes that clearly will require AI. Alexa will have access to the data. The computer power is there now.