2: A lawyer and a surgeon walk into a bar… part 1

Host:
Hello, and welcome to the second episode of Ashurst Business Agenda. In this episode, we are joined by James Kinross, senior lecturer in colorectal surgery and a consultant surgeon at the Imperial College, London. Alongside James, we have our own Chris Georgiou, partner and head of Ashurst Advance. This is a two-part conversation. And in this somewhat unlikely episode, you'll hear from James and Chris discussing the similarities of the legal and surgeon professions, the innovations and efficiencies gained through the growing use of artificial intelligence and robotics, and the continued disruption technology brings to both professions now and what that might look like in the future. You are listening to Ashurst Business Agenda.

Gentlemen, welcome. I want to firstly, address the elephant in the room. We have a lawyer and a surgeon, and no, this isn't a start of a joke where they walk into a bar, but you're here on a podcast exploring the future of business. So I want to ask Chris firstly, to highlight what you think are some of the parallels between the medical and legal industries.

Chris Georgiou:
Well, I guess we thought it would be quite interesting and hopefully instructional as well to compare two, apparently very different industries and professions and see those parallels and what we might learn from each other. Particularly, looking at approach to digitalization, to transformation.  And when you look at the parallels, you've got similar individuals, I guess, with similar backgrounds, similar outlooks entering their respective professions. People are highly academic, used to being at the top of their game, huge fear of failure, traditionally, very risk averse. 

You've got industries which are often team-based and you've got these very kind of high performing teams supporting frequently high pressure, high stakes, high stress environment. Lets stick in with the theme of risk, both doctors and lawyers and managing risk every day. And both professions have that low probability high consequence issue that things don't go wrong very often, but when they do the consequences could be very serious, but obviously in different ways. 

And I think what we've seen in both industries is a shift from being largely reactionary to much more pro proactive and the roles that we employ involve not only reacting to problems as they occur or symptoms, I guess, in medical world, but also being able to proactively plan for and avoid future problems. So there's quite a few parallels and there should be much that we can learn from each other's experience as our professions transform and as they digitalized.

Host:
So James, I'm interested in your point of view, do you think there are any other parallels between the two professions?

James Kinross:
Well, I do. First of all, wouldn't it be great to walk into a bar? We are currently in locked down in London and that would be wonderful. So I think I would totally agree with absolutely everything Chris has said. I would also add that, we're both quite hierarchical professions and there's quite a lot of ritual and there's quite a lot of best practice, which is handed down from generation to generation. 

We like to believe in medicine, certainly that it's evidence-based and that it's led by data, but quite often it's not. And there's room for a lot of disruption there, as we adopt technologies from other industries and bring them into healthcare. Certainly I think we like to believe that we are innovative and that we constantly push that envelope, but actually, I don't believe, we are particularly in healthcare, particularly in surgery, we actually are quite conservative, and that's because of the point that Chris made.

It's because of risk it's because every time you introduce a new innovation, a new change, the potential unintended consequences, particularly if there are known, carry significant risk. So we tend to be quite risk averse, I think as professionals, because we just don't want to cause either client harm or patient harm and, for us, that's certainly a major motivating force.

Host:
No, I mean, it really interested exploring the theme of innovation and it's something that you've both mentioned. I want to challenge both of you. I'm really particularly interested in robotics. And I know that we have seen some great advances in robotics and surgically assisted robotics in procedures. 

I read a statistic recently that showed there's 15% growth, over just a couple of years within all procedures using robotics. James, what are some of these key challenges that are inevitable because of the digitization, the AI and the technology advances within your profession?

James Kinross:
That's a brilliant question. And I'll try and unpack it because there's a couple of themes actually in the question that you've asked there. So robotics is really an interesting paradox. I am a robotic surgeon. That's the first caveat that I should probably put out there. And I absolutely believe that 15 to 20 years from now, most minimally invasive surgery will be robotic in one form or another. We will move away from laparoscopy to robotic surgery. I'm not explaining the rationale for that, but the paradox with robotics is that there is no evidence that a robot improves the outcome for the patient at all. And there is no evidence over the last 20 years at robotic surgery.

And you really need to ask yourself, why, why is that? Is it because they're genuinely is no patient benefit from having a robotic operation? Or is it because simply as professionals, we have not been asking the right questions or not being properly applying those tools because ultimately it is a tool in the correct way. And I suspect that's probably true. And there's another factor though, which is that these are commercial instruments and it's a multi-billion dollar market, right? And that there is significant bias and influence that that industry has on clinicians and how they assess these technologies.

The second part in the answer to that question is that the real value in robotics, in my opinion, is not the mechanics, right? So we have spent the last 30 years of innovation in surgery trying to make our incisions smaller because the belief is, is that when you have smaller incisions, patients get off the operating table faster, they get home quicker, they'll have less pain, but also the mechanics gives you less tissue, trauma, and more precision in the way that you make your dissection. 

And then there's less inadvertent entry. Actually the revolution should be in making better decisions. It's not incisions, it's decisions. So it's about doing the right operation at the right time for the right person and doing that operation in the safest possible way. 

And so to do that, what you really need is better information management and you need decision support, and you need better imaging and you need help taking some of the cognitive burden of the person performing that operation when they're under stress. And they're there in a dynamic and challenging situation.

In combination with the machine, that's giving you the mechanical precision, you need to blend it together. And I think the real benefit of robotics is that they are really not just precise machines that give certain ergonomic and flexible advantages, but they also are complex sensing instruments that allow us to constantly measure the performance of a surgeon and to constantly feed that performance back and to augment the decisions as they perform that procedure or task in real time. And this is really what we're talking about here, which is digital surgery that's information management. So that's, I believe is the future, but yeah, robots are definitely here to stay. No question.

Chris Georgiou:
I like James' points about hierarchy actually, because when I reflect on the legal profession, we are, and always have been a very hierarchical profession. And one of the consequences I think you get from that, is that it does stifle innovation and creates barriers because I think, there's a kind of lack of democracy. 

If you like about people, generating ideas and being listened to and being... And feeling able to put forward new ways of working ideas for change. I think that hierarchy is a problem for us. And one of the areas that we need to focus on how we generate much more from the rank and file, really about ideas for what we can learn and how we can take, take the professions forward.

James Kinross:
So I think that's a brilliant point. I can talk about process in one second, but I want to come back into your point about the expert. So part of the reason that some of the trials in robotic surgery haven't demonstrated significant benefit is because those trials have been performed by people who are already experts. 

So if you've got a lawyer that's done 10,000 cases, well, that's pretty good, therefore, the game that you get from providing them with the technology is kind of marginal. That doesn't mean it's not important, it just means that the way you assess it and measure it needs to be different. 

And actually, we think in performing complex tasks or difficult procedures, probably the significant gains are actually in the hands of the non-experts. So the people, either who are training and learning, you have to go through really a difficult learning curve to get to a point where they can be considered an expert and their performance by the way, can be constantly measured.

James Kinross:
And so that they can constantly have feedback and get up that curve faster, which hasn't historically happened in surgery. That's a whole other topic for conversation. And then actually what you can do is you can just level up the whole playing field. So surgeons who perhaps wouldn't be able to take on procedures because they simply don't have the technical skillset can suddenly do something that they were otherwise not capable of doing. And again, like robotic surgery really in its first instance was an extension of what we were doing, right? 

It was trying to replicate what we were all already doing in surgery and actually, genuinely, innovative robotic surgery should be giving us the abilities that we don't currently have in our profession, Right? So it's about allowing you to do something that is not possible with open surgery or with, with, with minimally invasive surgery.

Host:
So Chris are robots here to stay or artificial intelligence here to stay for the legal profession and in what sort of applications do you see them being Relevant?

Chris Georgiou:
That's really interesting because in the legal profession, robotics is certainly slowly making inroads, but it's more in the line of robotic process automation. So taking tasks that would be regularly and repetitively done by humans and replacing that task effectively with a bot that performs that task for it. 

So for example, if you regularly have to go onto a particular websites company's house or a land registry, take information from it, put it into a spreadsheet, create a document of that, and those are all the same process. Then the purpose, I guess, of robotics, there is really not necessarily to kind of improve an outcome, although it does, it does in one sense, but it's to speed things up, create consistency, reduce costs, increase efficiency, and probably the biggest value that you get out of that is the freeing up of your specialist resource to then do something else.

Whereas it sounds like actually, James, you use robot, and the specialists that are actually using the robots to kind of enhance the process that they're actually doing. Whereas I think in our industry, it's replacing the specialist time and therefore it's got a more narrow focus only really on those areas where you can reduce relevant series of tasks to a very defined and similar process that you want to do again and again and again and again, at high speed consistently, perhaps 24/7 and a lower cost as well.

James Kinross:
Listening to you talk about that. It makes me think that, in clinical practice, we're going through a similar transition and the best example would be imaging. Surgery is actually quite specific because it's a technical task, right? It's a physical procedure that you're doing. And actually what we're really trying to just improve processes across the board, because we know that when those processes fail, that it causes harm. 

So the best example is imaging. And at the moment in AI, deep learning, the golden goose for deep learning is x-ray interpretation or imaging interpretation. And because then what allows you to do is to take the heavy lifting of people who have to interpret those images. And actually, 90% of their job can be automated, but what you really want, those expert radiologists to be doing is focusing on those challenging outline cases where, actually there is a significant gray area, both literally and figuratively, quite often if it's CT scans.

But where actually you really need an expert who has that multi-variate experience and the emotional context and the patient context that can think beyond the machine to give you an answer. And that is absolutely where the technology is being applied. But I just wanted to come back to one other kind of interesting point that you made, which is that, yes, we're trying to level up clinicians so that, we generally kind of lift the whole bar, but actually there is a real danger here that we will not achieve that. And the danger is not in the technology, right? The key thing here is always about human behavior, economics and policy that underpins all of this stuff, right? And the anxiety is that we're not really going to democratize this technology as you apply it.

And actually what we're going to do is we're going to create a two tier system. Because they will be an economical financial penalty, some people will be able to afford this software, they will be able to afford these tools and some health care systems will not. Some health care systems will have access to 4G 5G, and we'll be able to fully leverage all of this as it comes out and other healthcare systems won't.  So actually the key words for us at the moment are around equity, sustainability and genuine democratization. And that we don't devolve into a two tier system, where actually we widen the health divide, we don't close it. And actually how you translate these technologies suddenly becomes really, really important.

Chris Georgiou:
Again, I think that's a really interesting point because that opens up the question of how a professional is using technology? And it sounds from what you're saying as though the medical professional is using technology to enable people to do things that they wouldn't otherwise be able to do. And I'm not sure how much that is the case with the legal profession at the moment. 

On the whole, the suites of technology that people are starting to deploy, are being done effectively to replace tasks that people could have done before, but they do them generally more quickly, more accurately and more cheaply. So we've started to use a whole range of tools like many others, including contract review software. 

So the software with embedded AI that can read documents, understand and learn where clauses are, find data that you essentially teach it to find and extract that data out. So you might be able to review hundreds and thousands of contracts and take certain data and information out of them using the tool for example or perhaps you might have contract assembly software that automatically generates first drafts of contracts for you.

But all of those tasks are actually things that you humans could quite easily have done before, but not necessarily to the same speed and necessarily the same accuracy as well. So I don't think we've seen a lot of evidence yet. I think partly because the development of AI is still not matured in the same way it has in perhaps other industries. And I think that potentially is a real game changer. But at the moment, the tools are largely not enhancing and enabling people to do things they couldn't have done, but just replacing tasks that humans could have been done before making increasing efficiency probably.

James Kinross:
I'm so old that I remember when doctors used to wear white coats. So then I was a junior doctor and I first qualified, I got my white coat and I was really proud about having it. And the white coat had two massive pockets on it. And I didn't really understand the value of those things until being a day one when I used to carry around with me books and, pockets full of syringes, and God knows what else. 

And I was really proud to be a doctor, but I wasn't really a doctor for the first year of my practice. I was basically a glorified secretary running behind my various attendings, carrying their objects, trying to manage their lives and basically manage a process, right? So my job was to make sure that, that firm ran smoothly. And if it failed, the consequences were significant. Like people literally didn't get their operations or, they didn't get their diagnostics. And I did not understand that at the time. I believe that I was performing a different task.

And we have invested quite a lot of time and effort in trying to make sure that our health organizations run efficiently and that we empower our people usually, at quite a junior level who deploy a lot of that process, do that job efficiently. The second issue that I just was really thinking about when I was hearing you talking was this idea of our professional attitudes towards that process, right? So, particularly as medics, and it might be the same in law, we take a lot of pride in those processes actually, because it's what we've trained to do, but we also consistently overestimate our ability to deliver them and to deliver them well, Right? And we don't necessarily like being challenged on that. And we have not, historically, measured those processes very well.

So actually there are a couple of challenges here. Number one is that, it's how you manage professional attitudes and responses to being presented with data that might show those professionals that actually, they're not quite as good at doing that job as they believe themselves to be. And then how you manage their expectation and ultimately change their behavior once you've empowered them with that data and the machine to do something with that information. And again, we saw that quite interestingly with deep minds work, looking at acute kidney injury, in patients who were being admitted to hospital. We can get into the controversy around that if you'd like in a little bit, but effectively what they were trying to do was to try and create new biomarkers for patients who were developing kidney injury.

James Kinross:
And there were interesting changes in attitudes towards that, because basically renal physicians were turning up at the bedside of patients and that the teams managing those patients were unaware that the physicians were coming to see their patients, because there hadn't been that that level of communication that typically follows along those kind of hierarchical communication pathways. 

All of that was completely disrupted and that created conflict and it created problems. So when you start to introduce these machines, you start to challenge those processes and you start to break down hierarchies. Actually, you have to find new ways of working that everyone's comfortable with. And that takes time.

Chris Georgiou:
Hmm. One of the bunch you raised that actually was around improvement of processes. And that's certainly what we've seen that where technology has its most value to add, really is where you've been able, first of all, to standardize processes. And that there's quite a cultural shift there in whether you see what you're doing in the profession as a process or not. 

And I think that historically again, in the legal professional, I don't think that it comes naturally to lawyers to think about themselves and what they do as a process. You might be for example, a high-performing M&A lawyer advising on these massive, big ticket corporate, acquisitions or a banking lawyer, acting on billion dollar transactions. And you won't really think about yourself as running a process. Of course, if your team does lots of those, and over a course of years, you're doing effectively the same things continually in similar ways and things follow the same process and a similar life cycle.

There's a lot of process aspects there that actually you could, if you apply to your mind to it standardize and, digitize and use [inaudible 00:20:46] to help that. But I think that does involve a mind shift for people. And also, and I'm sure it's the same in your profession James, I think it's about having space to look up from your desk or look up from your operating table or whatever the equivalent is. And to be able to think outside the pressures of the day, that where you're just trying to survive the day and the deadlines that are there, in order to be able to think about these things and step back and look at process and how we continuously improve things.

Host:
You've been listening to part one of a two-part conversation about the similarities between the legal and surgical professions. Be sure to tune into our next episode, to catch part two, as James and Chris go on to discuss what the future of their professions look like in a disrupted and continually evolved business and medical environment.

In the meantime, to learn more about how AI is changing the future of the legal profession, head over to ashurst.com/podcast. To catch up on our dedicated series on all things, artificial intelligence. To ensure you don't miss a future episode, subscribe now on Apple podcasts, Spotify, or your favorite podcast platform. While there please feel free to keep the conversation going and leave us a rating or review. Thanks again for listening and goodbye for now.