Andrea Macdonald, founder of ideaXme interviews Tom Lawry, National Director of AI for Health and Life Sciences at Microsoft . This interview is for the technology geeks amongst us as well as the general public who’d like to know more about what’s happening next in health.

Before becoming National Director for AI in the health the health space, Tom was Director Worldwide Health at Microsoft.

Intelligent Health: Artificial Intelligence, Machine Learning and Cognitive Services

Tom’s current position involves working with providers, health and life science organisations to plan and implement innovative analytical and predictive solutions that improve the quality and efficiency of health services delivered around the globe. At Microsoft, he creates strategies for digital transformation applied to performance optimisation including Artificial Intelligence (AI), Machine Learning (ML) and Cognitive Services and to move those sectors forward within the context of both individual and population health.

In this ideaXme interview Tom Lawry:

-Discusses specific examples, from cutting costs of healthcare to reducing fatalities amongst patients, of how AI has performed and delivered results within medicine and healthcare. Moreover, he shares how this is set to improve in the next 10 years.

-Talks of the specific ways in which AI can improve your health as an individual. The pervasiveness of AI, across most sectors from health to entertainment, in society now.

-He demystifies the “intelligence” as well as the associated technologies.

-He sparks curiosity in what’s happening next within the sector. He describes his mission to drive AI for the good of humanity “AI for Good” within the sectors of health and life sciences.

He talks of the risks which must be mitigated in order to optimise the potential of AI including protecting both organisations’ as well as individuals’ data.

AI in Health

He tells the audience of his national and international work within the sector. His answers questions about book AI in Health: A Leaders Guide to Winning in the New Age of Intelligent Health. 

Lastly, he talks of AI law and ethics.

Andrea Macdonald, founder of ideaXme: [00:00:22] On today’s episode, we’re going to talk about AI in health. AI is the new technology revolution. I am here with Tom Lawry, the Head of AI in Health at Microsoft USA. In your words, who are you?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:00:44] First of all, thanks for having me. ideaXme is a great production and it’s great to be back! In my role as National Director for Artificial Intelligence, for Health & Life Sciences at Microsoft, essentially, I have the privilege of working with some of the top provider organizations, health payors and life science companies around the world as a strategic adviser to help them look at the work they’re doing, how they might do it differently and how they might do it better with the introduction and use of artificial intelligence.

Andrea Macdonald, founder of ideaXme: [00:01:16] You recently wrote a book about AI in health, AI in Health: A Leader’s Guide to Winning in the New Age of Intelligent Health Systems. Could you talk a little bit about that book?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:01:23] Yes, thank you. It’s a book that was published last year, that focuses on AI in health, but it’s not a book about technology. It’s really a book about how AI can, in fact, be used to change the way health care works, the way big organizations like hospitals work, the way physicians practice and the ways in which AI can help drive a much more intelligent health system and experience for health consumers today.

Andrea Macdonald, founder of ideaXme: [00:01:54] As I mentioned, we have a broad audience of creators and pioneers and scientists who shape our world, as well as university students who would like to do so in the future, and we also have a huge number of listeners and viewers amongst the public.

Andrea Macdonald, founder of ideaXme: [00:02:16] Could you paint a picture of AI as well as the AI technology systems that feed into the process, for example, machine learning, NLP and neural networks so that people who are not working in the field get an idea of what is involved?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:02:35] Absolutely. We’re using a lot of big words there. The thing about artificial intelligence is it’s a highly complex system of technologies. When you strip it down, it essentially is a number of things that can be understood and applied to make health care better.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:02:54] So, you talked about things like machine learning. Machine learning is nothing more than the ability for us to use technology to predict things. Let’s look at something in healthcare. Often times when I’m working with clinicians and others, one of the exercises we go through is to simply say, if there were three things you could predict to make what you do better, what would they be? Things like machine learning give us the ability to predict things at a higher level than what the individual physician or clinicians can do.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:03:27] Things like Natural Language Processing that you mentioned, or NLP is simply the ability of artificial intelligence to look through massive amounts of information, to look for trends, clues and themes. For example, when Covid first hit, there were thousands of articles on the Covid family of viruses, and yet none of those had been brought together for researchers to use. We used Natural Language Processing to bring together 40,000 research studies and articles in a matter of days to make that searchable and make it available to groups like frontline physicians in public health or in the early stages of drug development. These are all tools that have some complexity, but when you strip it down, it’s helping us do things to make humans better at something they care about.

History of AI

Andrea Macdonald, founder of ideaXme: [00:04:22] Can you talk to us about the chronology of AI? It was first spoken about in the 1950s. Can you talk to us a little bit about the progress of AI and the associated technologies?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:04:37] Absolutely. Well, I’m not only kind of geeky, but I also love history. Technically, we have references to AI going back to the 1600s, believe it or not. Artificial intelligence started really coming into the world in the mid-century of the 1950s. There were a number of things that were being done to advance the cause of machines, basically mimicking more functions that are normally the purview of humans and the human brain. A number of things have been around since the 1950s. What’s happened just in the last decade, though, is the introduction of the cloud, great progress is being made by moving data from those big computers stored somewhere in the basement into places like the cloud.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:05:28] We’ve seen, for example, one of the benchmarks for advancements in artificial intelligence is what’s known as human parity, which is getting something that a computer can do to the point where it equals what a human is capable of. Just in the last few years, and Microsoft has led the way in many of these things, we’ve reached human parity on things like vision, speech, knowledge extraction and a host of other things where a computer is as good as an average human.

[00:06:00] Why that’s important is that there are many things we could do, say a decade ago, in the lab that were experimental. But these were things that would be hard to replicate and take out into the world and make them repeatable at an industrial strength. We’ve reached that point where many of these functions that previously could be done are now industrial strength built into the components of many IT systems that allow organizations to start working with things like conversational AI or a much greater ability to make predictions on things like cancer treatments, drug development, and just a host of things that have come up in the world just in the last few years because of our technology advances.

Andrea Macdonald, founder of ideaXme: [00:06:49] The Cloud is the engine room of AI. Could you explain why that is so important and the relationship between the Cloud and data storage?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:07:03] Yeah, well that alone would take at least one more episode. In a nutshell, think about the evolution of computers, from the big systems that historically resided somewhere in the basement of a big company to the advent of the personal computer then the smartphones. So much of that, the applications and the data behind it have the ability now, because of the Cloud, to basically be fluid. Before, data you might have on your personal computer or at the big company you work for on their big data systems on their own computers, was kind of all kept behind the garden wall. They were tethered to those systems and it was extremely difficult for data to move or be aggregated.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:08:01] The Cloud gives us the ability to make data very fluid, to bring multiple types of data together in a very agile fashion, to start doing really interesting creative things in the use of that data to hopefully do good in industries like healthcare. So, the Cloud really did create that openness. Then along with that, as everyone knows, comes the importance of things like privacy and security standards, but that has been one of the major breakthroughs, particularly in the last decade that’s opened the door to so many of the things we’re seeing progress today.

Andrea Macdonald, founder of ideaXme: [00:08:38] Could you explain briefly to the audience what the Cloud is? Because the Cloud isn’t in the clouds. It’s a series of network systems, isn’t it?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:08:50] The simple definition I would offer is you have these massive server farms that are all interconnected through this relatively open network, though, there are different forms of the Cloud, and essentially the data you put there can reside virtually anywhere in the series of data farms. A lot of it historically goes back to the 1950s and the creation of these worldwide computer networks to safeguard against major parts of the world going down and the ability to transfer data. Essentially, the Cloud refers to server farms around the world that are all interconnected with these universal protocols and standards that allow anyone to put information in, take it out and, in keeping with a growing set of security and privacy standards, to make sure that the data is at least a safe and reliable, probably more so than the computer that you may be storing data in today.

Manage Data as an Asset

Andrea Macdonald, founder of ideaXme: [00:09:59] In your book, you talk of protecting your data and managing your data as if it was your most precious asset.

Andrea Macdonald, founder of ideaXme: [00:10:09] In reading a number of articles that were looking to the future of AI since having read your book, many experts talk of the increased data regulations coming on board. Could you talk about those and how big organizations need to ready themselves for the new laws and regulations coming?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:10:37] There’s a couple of things I can say about that, Andrea. One is, it’s interesting to me when I hear many healthcare leaders talk about how data is the new currency in healthcare. If that’s the case, I always like to pose the question: If data is the new currency in healthcare, are you managing your data in the same way as you are managing your finances? The answer is usually no!

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:11:02] The second part would be just to say I truly see data as an amazing asset that can be applied to do good in the world, not just in healthcare. An example would be to look at healthcare today and the amount of time it takes for medical knowledge to double. In 1950, a newly minted physician would go their entire practice before medical knowledge doubled, every 50 years. According to one study as of last year, medical knowledge is doubling every 73 days. Think about that. You’re a newly minted top trained physician and you just graduated today knowing a couple of months from now they’ll be twice the amount of medical knowledge to deal with. It’s a challenge, but it’s also a great opportunity for all of this knowledge, if sorted, if leveraged, to be applied to do much better in all those things we care about when it comes to health and medicine.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:11:59] With that in mind, it’s incumbent upon healthcare organizations to really look at how they’re managing and how they’re provisioning all the data they have, knowing that it’s doubling at a very rapid rate. They can either let it languish or they can take advantage of the rate at which medical knowledge is doubling to do good. With that comes a host of key issues and that’s where many times the technology, in this case AI, often gets out ahead of the guardrails, legislations and regulations eventually put on it.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:12:16] Today, in most parts of the world, there’s regulations such as data regs in America and GDPR in Europe that govern all data, not just healthcare. But beyond that, it’s important to look at how we use these things in a way that’s not only safe in compliance with current regulations and legal restrictions, but we also take that one step further to look at how we’re applying all of that data in general or your specific information as a patient in a way that is responsible and ethical. That’s an area that’s a very hot topic. There are a number of things that we’re championing when it comes to going beyond just what’s legal and keeping with all the regulations of your country.

Looking at the Future of Artificial Intelligence

Andrea Macdonald, founder of ideaXme: [00:13:22] Looking 10 years ahead from now, AI already is impacting pretty much all areas of our lives from business right the way through to health, sport and entertainment, you name it, AI is involved somewhere down the line. Comparing how things are today, how do you predict, using three different categories, AI will change those categories? For example, I’m a sports person, I’m a scientist or I’m a politician. How will AI impact individuals in those positions today and in 10 years’ time?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:14:21] Let’s start with the consumer. I want you to think about today, no matter where your listener is, how the world has become much more intelligent thanks to things like the Cloud, the Internet and all those apps on your smartphone. I’d be willing to bet that the audiences today, who are listening to (or reading) this interview are doing so on their smartphone in their purse, pocket or on the desk or tabletop from a coffee shop. You have it close because you use it to do all kinds of things to make your life easier and better, professionally and personally.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:15:06] As that happens, what’s interesting to me today is, there’s a shortfall, in my view, in all of those things you manage with those smart applications when it comes to turning to the health system, many times there’s a lag between what you’re doing with those smart applications and what you can do in healthcare today. So, moving forward, there’s the rise of what I call the intelligent health consumer, which is increasingly, and I think Covid brought this around and put a finer point on it, consumers are waking up to the fact that the health system doesn’t have to be the way it is. It can be much more personalized. It can be much more directed by those consumers who want to play a bigger role in their own health. Any app you have on your smartphone, is smart because behind that is some component of artificial intelligence. So, as we move forward, you’re going to see a lot more being driven by smart companies doing things that answer the question: How do we make that process of seeking and achieving care better?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:16:18] Then companies will take that one step further in the next 10 years by looking at how to apply those things to keep you healthier in the first place, to reduce the need to turn up at the NHS facility or wherever you are for service, because those very smart systems will have helped keep you and your family healthier over time. Beyond that, the second part would be to look at how that affects, say, physicians or clinicians. We know today, for example, worldwide, especially here in the United States, physician burnout is a huge issue. In America, the studies show that up to 40% of all physicians are at a point where they’re showing one of several signs of burnout, which doesn’t help them, and it certainly doesn’t help if you’re the patient of a physician who is burning out. So, increasingly, the value of AI is not to replace these great knowledge workers, but to help augment the work they do.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:17:20] There was one study by Accenture that showed that up to a third of all activities carried out by a physician can be automated with artificial intelligence. These are the highly repetitive activities that if we can automate them, give the physicians time to do things like actually talk to the patient, or spend more time on research or something as simple as getting home and seeing their family for dinner a little more often.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:17:47] Those are just a couple of examples. The secondary theme of my book is how artificial intelligence is leading to the emergence of what I call intelligent health systems, which are entities that leverage data and AI to create strategic advantages through the provision of health and medical services, but the operative thing is that they’re going to do so across all touch points, experiences and channels. It’s not just a use case or two that points to AI, it’s truly for those who are moving towards Intelligent Health Systems. They’re going to revolutionize that experience for the consumer and for the physicians as well.

Andrea Macdonald, founder of ideaXme: [00:18:28] AI is going to be fantastic for cost cutting, it’s going to improve workflows, improve diagnostics, it’s going to, on so many different levels, make the average person’s life easier, freeing up more leisure time. Could you talk to us about some of the risks?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:18:57] You paint a very glowing picture, much of that in some form or fashion is already beginning to occur. Part of the earlier conversation we had around legislation and regulations highlights that with everything comes risk. That’s where the creation of things like what I call guardrails to create a way of channelling doing good and mitigating the risks of doing harm is critically important.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:19:27] In that regard at Microsoft, we’ve been champions of this for a number of years and we call it Responsible AI. There are certain things that are incumbent upon everyone to not only understand, but to work towards making sure we are mindful of and have standards that mitigate the potential for harm to be done. A classic example would be what we call bias in Artificial Intelligence.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:19:55] For a quick example, to everyone listening, you’re now commissioned as part of the leadership team of the top hospital in your region, and we’ve decided to use artificial intelligence to reduce what’s known as adverse events. We put patients in the hospital today and as they go through that course of treatment, they’ll be a few that randomly have some event that we didn’t expect – their heart stops, they stop breathing. We call our team, and we get them stabilized and then we ship them off to ICU instead of sending them home. We’re going to use AI to try and predict which one of those patients are going to have a high risk of an adverse event. We’ve done that using AI, we did a pilot and were able to reduce adverse events in the pilot patients by 40%. From a quality perspective, that’s a great win, from a cost perspective, if I’ve kept you out of ICU, that’s a win, but 40% is a statistical average. While it’s good, if I told you that 40% was based on our ability to predict and prevent adverse events at a rate that’s three times greater for white males versus Hispanic females. I’ve still improved quality, I’ve improved costs and it’s legal, but is that OK? These are the issues that we must be mindful of and work towards mitigating.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:21:21] In this case, bias is simply a matter of having an algorithm that’s making accurate predictions, but it’s much more accurate, meaning there’s higher variance in my ability, when predicting by race, by gender and by any of a number of classes where I can correlate things. But it then comes down to that factor of what is right and what is wrong, and I can’t tell you what that is. These are the issues that as AI becomes more pervasive, everyone from the clinicians to the consumers should be mindful of.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:21:59] There are other things around what we call AI principles, but right now, bias is one of the hot topics, simply because we’re seeing predictive capabilities being introduced and there are times where that stress testing for things like bias has not been done to the level that it should be.

Andrea Macdonald, founder of ideaXme: [00:22:19] Could you also talk to us about the situations, in your book you provide some examples, of when AI gets it wrong and clearly the human factors of wisdom and empathy were missing.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:22:36] There are many of those, unfortunately. There are far more examples where AI is doing good, and it’s not bias, and it really is producing overall good. This is where we have to be mindful of not rushing ahead just because we create what we call correlational value. Probably one of the better-known examples, particularly in the consumer press in the last couple of years, was a great smartphone application where you as a consumer could take an image of, say, a skin lesion, and it would be able to calculate the likelihood of that being cancerous. It was another case example of something that worked really well if you were a light skinned person, but it didn’t work so well if you were a darker skinned person, there are things like that.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:23:49] One of the biggest issues for everyone to recognise is when we look at technology like machine learning which gives us the ability to predict things in health care, just because you can predict something, it doesn’t mean it’s right. This is an example of, in the world of data science and the world of ethics, it’s something known as correlation versus causation. Let’s say I’ve brought data together and I’m using some AI, I can correlate two things as somehow being highly likely. Correlating something doesn’t mean causation. I’ve got examples I use in some of my workshops where I can have a high correlational value between things like cheese consumption and the number of people who die by becoming tangled in their bed sheets. There’s almost a perfect correlation, but if you look at that, any reasonable person would say, well, that isn’t really the cause. If you eat too much cheese, you don’t die because you’re tangled in your bed sheet.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:24:55] This is where it’s about understanding what computers and AI are good at such as variance analysis and pattern recognition and also recognizing what AI is not good at that humans are great at and always will be including reasoning, judgment and common sense. No one has figured out how to teach computers any of that, which is why it’s that marriage, when it comes to health care, of having predictive capabilities that are looked at and managed by that well-trained, experienced clinician to be able to say this is aiding in decision or that’s not right. I know, given my experience, given all these other things, this is the way I need to go.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:25:41] Many times people who don’t really understand those differences, don’t get it right. Those are the people that typically talk about how AI was going to replace physicians or other things that anyone who recognizes the value and capabilities of AI understands that it’s that marriage of putting those things in and behind knowledge workers, be they physicians, nurses or finance specialists. If a knowledge worker is armed with these tools and they’re in control, that’s how we drive value and that’s not just in healthcare, that’s in anything you might want to do with artificial intelligence.

Andrea Macdonald, founder of ideaXme: [00:26:21] Can I just take you back to another one of the issues to watch out for. You mentioned it in your book where the FDA have a new set of challenges as the machine learns, it effectively changes the offering, as it were. It’s sort of a moveable thing. Could you talk to us a little bit about that and how things moved forward since then?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:26:54] It’s a simple example, but it also speaks to the complexity of not only the capabilities, but what we need to look at how we manage. In the world of AI, machine learning and predictive capabilities, there are things known as continuous learning algorithms, which is to say we set it up to predict something. Let’s say who might be at risk of a having a stroke using some medical device that is a self-worn device. That algorithm may start predicting using a certain pattern, but with each case, with each patient, with the more data it gets, it keeps learning just like a human does when you take a class. The more you learn, the more you read, the more you study. It changes the way you think. Continuous learning algorithm does that similarly.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:27:51] The model in which companies like the Food and Drug Administration (FDA) license and certify that something is safe for consumer use in a medical situation absolutely blows up as it continuously changes. This is because they like to have everything lined up so they can certify and test and say, OK, it’s good to go this way. The moment you throw the on switch on with a continuous learning algorithm, it’s changing the way that algorithm works and arrives at that predictive conclusion. That produces great good, but it also produces the risk that somehow if that does go sideways or off track, it needs to be monitored. There needs to be the ability to kind of stop and back up the tape to be able to ask: How is this making a decision? Is it making a decision that’s consistently good? In the interest of why we certified this, is it producing good unevenly, which goes back to that bias issue? It’s a great opportunity and everyone’s still trying to work out how to manage it in a way that is fair, safe and consistent?

Andrea Macdonald, founder of ideaXme: [00:29:08] Putting you on the spot, if I may, if you were invited in to be the head of AI at one of the top hospitals in London such as St Thomas’ Hospital, for argument’s sake, what do you do on your first day? What are your priorities?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:29:32] There are many great examples, by the way, of what’s happening with AI applied to health and medicine coming out of the UK and London and some of the great organizations based there. Before this role, I was Director of Worldwide Health at Microsoft. So, I spent a lot of time working with a lot of great organizations in the UK and Europe.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:29:51] It goes back to the book. The thing about AI is it’s become what I call a shiny object where everyone loves to talk about it and how it’s going to create a bright future. Though, that only happens if leaders understand what it is and how to apply it, which is what I call the leadership imperative. It’s imperative to understand what it is and what it isn’t. It’s imperative to be bringing your clinicians and others along in that journey from the beginning. That’s everything from looking at how over time that will change the way clinicians practice medicine to having what I call the ‘when AI meets HR conversation,’ because as time moves on, there are some jobs, frankly, that will be automated out of existence.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:30:45] Most jobs in healthcare will be augmented, meaning the way in which you do that job is going to change, which means a different skillset and different training and perhaps in the future, looking at the type of person you recruit to come into healthcare will be required. That’s before you even talk about all those other things on how to make all of that growing data better, more of what we call interoperable to be able to, with agility, make better predictions, provide better services that really serve the needs of all those consumers that those organizations are chartered to be the best at.

Andrea Macdonald, founder of ideaXme: [00:31:26] Talking to the geeks in the audience, I count myself as one of them, I’m interested in everything. Could you talk to us a little more of the types of technologies and trends that the geeks amongst the public should look out for, for example, Data Whisperers and Quantum Physics?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:31:54] You have read my book, Thank you! Data Whispers, that’s a term we made up for my book. We look at things like today where we have all this data in healthcare, but it could be in any industry. Whatever industry you’re in, think about all of the data you have and how if there were no boundaries to that data and you could bring it together, you could be doing things differently and better.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:32:23] In healthcare, there’s a massive amount of data, typically, anywhere in the world, the data is stuck in silos – electronic medical records, patient administration system labs. Then the process today of doing any analytics and especially in AI, is that we pull the data out, we put it somewhere and we stage it and do all these cool things. Eventually, we get to make predictions and there’s a lot of studies that show when you’re doing analytics, 80% of all effort is just getting ready to do the analysis. Imagine a time when it’s not only that, but we have tools with artificial intelligence that do that automatically and it brings us information.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:33:14] The term Data Whisperer is simply formed from when a good colleague of mine, who’s the Chief Science Officer for Microsoft, did a project a while back where he applied AI to search engine queries. It was just looking at a search engine, not looking for health care, but just looking at patterns from anyone putting their hands on the keyboard, conducting a search with the search engine. Long story short, he was able to identify a group of Internet users that had pancreatic cancer before they had a diagnosis. The concept is simply large amounts of data are whispering things to us all the time. We either don’t have the tools to hear it or we’re not paying attention. Imagine all the data, back to the UK, that the NHS has today, what are the secrets that if all of a sudden, we knew what that data was telling us might allow us to be ahead of either an individual patient’s medical condition or health, or equally important, a population of patients’ health. Such as all the diabetics in the UK and our ability to say: We know things now that this data has within it, and we have the ability to proactively not only understand it but get ahead of it and use it to do something positive.

Andrea Macdonald, founder of ideaXme: [00:34:37] Tom, Lawry, before I let you go, can we talk about Rich Connectedness? I’m fascinated to learn of with whom you’ve with connected during the course of your life, who has helped you move your human story forward. Could you talk to us a little bit about that and name some names?

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:34:58] It’s always interesting because like many others, my journey has not been linear.

Early on, I’ve always talked about how, and I consider it a great quality, I’ve never known what I’m not capable of doing. When I get an idea, I just start pursuing it. I’ve been blessed with mentors and others who have helped me along the way, even when I had an idea, and I was certainly not qualified. That started early in my career. I spent 12 years as a hospital executive. I had great mentors who basically took a 24-year-old person and within a year, I was on the management team of a 500-bed hospital in the United States. After a successful career in healthcare, knowing very little about IT, the dotcom era hit and I left a perfectly good career to start a web-based company, and we did very well. But along the way, there have been people who believed in me, whether they were senior hospital administrators or VCs that saw my idea.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:36:17] Today, the biggest part of what I do as an adviser is, I get to impart knowledge, but more so, when I parachute into these organizations trying to solve big problems, I’m always learning far more from others who are the clinical leaders and others that I’m probably imparting.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:36:41] I’ll name a name, Aenor Sawyer is a physician. She’s at the School of Medicine at the University of California, San Francisco. She’s also the head of the Space Medicine Program and an advisor to NASA (Chief Health Innovation Officer for the NASA-funded Translational Research Institute for Space Health (TRISH) and Founder/Director of the UCSF/UC Space Health Innovation Center). and space techs. People talk about telemedicine and Aenor and others are working on things like medical systems that will operate in deep space as we try and send someone to Mars. So, being invited in to work with people like Aenor and all those smart people taking on probably the biggest telemedicine project I can imagine of asynchronous systems between here and Mars, is one of the many opportunities in the world to get excited about.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:37:35] For me, I’m excited by data and AI and how you use that to make the world better for everyone else. It’s about what is it that gets you excited? Anything I get excited about, I have a passion for, I move in that direction and somehow God opens the right doors and it’s been a great ride.

Andrea Macdonald, founder of ideaXme: [00:37:54] Tom Lowry, Head of AI for Health at Microsoft USA, thank you so much for your time. It’s been an absolute pleasure.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:38:04] Thanks Andrea. Great to be with you and great to be back. You have a great program.

Andrea Macdonald, founder of ideaXme: [00:38:08] Thank you.

ENDS

Offline: Rich Connectedness discussion continued

Andrea Macdonald, founder of ideaXme: [00:38:24] Before you go, I would like to ask you a little bit more about Rich Connectedness™. The ideaXme team are working on research for a book about Rich Connectedness™. To define Rich Connectedness™, what we mean by it is not necessarily within the traditional mentoring sphere or educational sphere or context in which people are expected to help each other. It is in circumstances when help is not expected or requested. You mentioned in your book and we have during the course of this interview about empathy and wisdom. Rich Connectedness™ is a combination of experience, empathy and wisdom that makes one human being reach out to another and give them something special, often unexpected.

Andrea Macdonald, founder of ideaXme: [00:39:55] It can be a very short thing in terms of timing.  It spurs you on in a way that keeps you trying, gives you hope. Many of the innovators we interview talk of these special connections with others that helped them move forward.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:43:04] I see it. As you’re talking Andrea, it’s almost like, defining air. I know it’s there, I can’t see it, but I can’t live without it.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:43:52] It’s amazing how many people with whom I have experiences like that, who either leave me thinking in away I never thought of, even ‘change my brain’, my view or my activities.

I’d like to think that I pay it forward as well when it comes to things that I do. That is, I do things that I don’t have to do, that are not part of my job. For me, what I do, as geeky as some people think it is, I think I’m part of this fabric of this ‘fuzzy thing’ that really is going to change the world for the better. My take on it is from within the health space. But I’ve got colleagues  that are doing the same for the environment.

Tom Lawry, National Director of AI for Health & Life Sciences, Microsoft USA: [00:45:44] Often people who interview me ask: Where did you get your Ph.D.? Well, I don’t have one. What’s your degree in data sciences? I don’t have one. 

They ask: How did you get here? It’s a long story. People have invited me in. I’m just a curious person. Once I get something in my mind, I’m curious. I have no filters and I’ve been super lucky to get in front of the right people who then helped me with something to move forward….

Credits: Andrea Macdonald founder ideaXme.

If you enjoyed this interview you might also like our interview with Stephen Furber, ICL Professor, Computer Engineering, University of Manchester and creator of SpiNNaker.

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ideaXme is a global podcast, creator series and mentor programme. Our mission: Move the human story forward!™ ideaXme Ltd. Our passion: Rich Connectedness™!