00:00Will AI transform healthcare? Yes. If we don't do anything, our health systems are going to
00:05collapse. You have a risk of becoming very efficient at being inefficient.
00:15This is a live edition of The Big Question. I would like to welcome our guest, the CEO
00:20of Health AI, Ricardo Baptista Leiter. Ricardo, pleasure to meet you.
00:26Thank you. Take a seat. AI, of course, promises to transform healthcare. How we will actually see
00:32that transformation in Europe over the next few years. Are you able to share your insights with
00:37us on that to start with? We at Health AI, we are the global agency for responsible AI and health,
00:41a global nonprofit based out of Geneva, working with governments to build ecosystems. Will AI
00:46transform healthcare? My answer to you is yes. The question is, will it do it for the better or
00:54for the worse? And what I mean by that is that if we just start to introduce artificial intelligence
01:01into our current models of care, into our current health systems here in Europe, we have a huge risk
01:07because our health systems are fully focused on reacting to when people get sick. They are disease
01:12reactive systems. And so we need to fix the system so that it focuses on prevention, on promotion of
01:19health and on quality of life. If you retrofit AI into our current models of care, you have a risk
01:25of becoming very efficient at being inefficient. The opportunity is here to use this intelligence
01:32revolution to transform healthcare completely so we can lower the burden of disease so that we can
01:37make sure that the citizens across Europe and the world can have better health outcomes in the future.
01:42What are the biggest problems in healthcare that AI could realistically help solve at the moment?
01:47AI is already here. It's already transformed. Even during COVID, the development of new vaccines,
01:52almost every company was using some forms of AI. We're seeing AI across. So research and development,
01:58diagnostics, imaging technology, every field of imaging right now is using some form of AI.
02:04Treatments, robotics and surgeries. When we think about virtual assistants, virtual scribes,
02:09supporting doctors in clinical decision making, even when we talk about the non-clinical aspects of
02:15healthcare in terms of fraud detection, financial claims with insurances, all of these fields have
02:22the potential of improving in terms of outcomes, be it in terms of cost saving, but also in terms of
02:28efficiency, in terms of improving health outcomes.
02:37Healthcare systems are under enormous financial pressure at the moment, of course.
02:41Can AI realistically reduce costs while also improving outcomes for patients?
02:46If we don't do anything, our health systems are going to collapse. They are not sustainable.
02:51People are just getting sicker and sicker. We're seeing a population that is getting older
02:56and with multiple morbidity. And so if we do not change the system completely,
03:01we will not be able to have the resources to make sure everyone will have access to the health they
03:06need. Mind you, no minister of health, no prime minister or president in the world will ever say
03:12they're going to shut down the health system because it went bankrupt. What bankruptcy translates
03:15into healthcare is into longer waiting lists. People who do not have money in their pocket,
03:21who are in more vulnerable situations, are the ones that are going to be left behind.
03:25So if we are serious about making sure that universal health coverage is a reality,
03:30artificial intelligence can augment the capacity of clinicians, of healthcare professionals,
03:35of nurses, of the admin staff, so that we can maximize our current workforce so that we can be
03:40much more impactful in improving people's lives.
03:43If the potential health benefits are that significant, what sort of investment is needed
03:47to make it happen?
03:49We are seeing a lot of companies right now with amazing innovations, but they're hitting a brick wall.
03:54The question is why? There's the issue of trust. And that's what at HealthAI, working with governments,
03:59we're trying to build the governance system so that we can put in the proper ecosystem in terms of
04:04regulatory maturity so that governments and regulatory bodies are more capable to respond
04:08to the needs of AI and so that citizens and healthcare professionals can trust the technology.
04:14But then there's the money issue. Billions are being invested in research and development.
04:17Who is going to pay?
04:18If we want to make sure that this technology reaches everyone and not just a privileged few,
04:23health systems and insurances will have to step up. But the problem is right now,
04:27we don't have the health technology assessment models in place so that we can assess the technology.
04:32This is incredibly important. It's part of our work with governments,
04:36which is how do we separate on one hand the snake oil from what is actually working?
04:41Because a lot of technology that is being promised out there is actually not that effective.
04:44So how do you separate those two? And out of those technologies that do work,
04:49how do you make sure that you're paying the fair price? So developing those models will be critical
04:54so we can go from the pilot stage we are in today so that we can scale technologies and those
04:59technologies can help the systemic transformation. Is it something governments can realistically fund
05:03though? Or do you think we need to lean more on the private sector for this investment?
05:07If you look, the latest global AI patent report shows that 61% of all AI-related patents came from
05:14China, 21% came from the United States, 2% came from the EU plus United Kingdom. That is a
05:21concerning figure. When we look at AI and health, when you look at the United States, it's primarily
05:26funded by the private sector, venture capital. When you look at China, the other big powerhouse,
05:31it's mainly state-driven. This is actually the biggest opportunity for Europe, which is to be
05:37right in the middle, to bring together the public and the private sector to work together. I think
05:42it's critical that the European institutions understand that they need to work closer with
05:46the private sector, that the regulators need to create a pathway of conversation with companies
05:50developing the innovations from the start, from the moment they start developing the technology
05:55all the way to access to market. If we can find that perfect balance between private and public
06:00sector, Europe can really take a step forward and potentially overcome the lagging that we are
06:07right now. AI thrives on data, but health data is sensitive. How can we guarantee privacy and security
06:14while still, of course, allowing AI systems to learn from medical data? I think here in Europe,
06:19we have a huge advantage in comparison to other jurisdictions because we have already a lot of
06:25frameworks and mature regulation when it comes to data privacy, when it comes to European
06:30health data space legislation, which can be actually incredibly impactful even in fostering
06:36innovation if it's well implemented and ensuring access to the data for developers. The question I would
06:41ask people to think about is when they travel around the world, they go with a credit card in their
06:48pockets and they can withdraw cash in any ATM machine around the world. And our financial data is highly
06:55sensitive. The financial sector has been able to put in the incentives within their commercial model
07:00so it has a global system. In many parts of Europe, if I go to a hospital or a clinic
07:05and I go to the
07:05clinic across the street, they can't access my health data. And so there is a fundamental problem that we need
07:11to solve. And that's where I think the European health data space legislation could be a huge opportunity,
07:16not just at the European level, but at the domestic level where governments need to prioritize. If that data is
07:21a commodity
07:22and it's worth money, why can't we redistribute that money to the people who share their data and
07:27create a model through which we can incentivize even through financial incentives so that people
07:32can be part of this process and control how their data is being shared? There are huge opportunities to
07:36have data governance models that can accelerate innovation, but most importantly, improve health
07:41outcomes for all. Ricardo, on that note, thank you very much for joining us in the big question. We are
07:46going
07:46to have to end it there. But it's been great to get your insights on this.
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