Prof. Ariel Stern from the Hasso Plattner Institute explains which approaches could be used to improve digitalization in the healthcare sector.

The Hasso Plattner Institute (HPI) is researching methods to reduce the burden on the healthcare system. An interdisciplinary exchange with researchers from all over the world is intended to help. To this end, HPI has launched the Digital Health Innovation Forum. Host Prof. Ariel Dora Stern from HPI explains her approach in an interview. She wants to drive innovation in the field of AI and machine learning in the healthcare sector.

You spoke several times at the conference about cutting-edge research. How do you want to contribute to this?

We are a research institute and first and foremost we want to highlight the excellent work of outstanding scientists – both here in Potsdam and worldwide. Especially in the digital health community, I often attend conferences where I am the only one with a professorship. And I find myself talking enthusiastically about the great research of others in panels, in my own keynotes and Q&A sessions. This has made me realize that there is an unmet need: Many outside academia are passionately interested in current research findings and evidence-based decisions in business and politics – and too rarely get access to it.

What do you think of open science and open data?

I’m a big fan of it. It’s important for research and development. In academic research, it’s incredibly important that we have access to good, high-quality data so that we can do better research. At our department, we do applied data science with health data. We need good data for this. The next step is that we also need good and open data sources for the economy. After all, we can’t develop good products if they are all based on the same data set. Over 90 percent of AI models, some of which are used in hospitals, have not been trained on public data sources.

But is it also not the point for companies to use publicly accessible data for commercial products?

No, not at all. Open source is very important, especially if we create good standards. It’s much more efficient for everyone. For cutting-edge research, it is important that we as scientists are in regular contact with industry, the open source community and politicians.

Are you probably in contact with politicians about regulation?

We heard several times at the conference that there are many problems and wishes here. We need to be agile when it comes to regulation. We are currently conducting a project with American data in which we are talking about innovation in regulation. When we talk about innovation, we often talk about product innovation or process innovation. We say: “Okay, we are developing new software products, new medical products, new pharmaceutical products”. But there is also innovation in regulation, in legislation, and here too we have the opportunity to change things, to make things better.

The world is changing relatively quickly. It would be very naïve of us to say: “The regulation that we made 20, 10 or 2 years ago still fits the technologies that we will have next year”. That’s why we need to remain innovative and flexible in terms of regulation and legislation.

Does self-learning AI also play a role in this?

Yes, definitely. But I don’t think it would be right to regulate now and say: “That’s it. We’re done now.” We need to observe how the technology develops and then react in a truly informed, timely and agile manner.

We also need data security, that’s clear. But the price of not using the technologies that are already available is real – and high! Not adapting AI in certain areas costs lives. These are mistakes that can be avoided in hospitals, so if we can do it, we have to do it.

We need more IT specialists in the healthcare sector to drive forward digitalization in the healthcare sector. We need to react quickly and agilely and have tools with which we can react. What annoys me a bit is this mentality: “There might be a few security gaps. We’ll do everything without technology for now.” We can’t afford that in the healthcare sector. It’s just too expensive at the moment.

In the US, there’s a great group of white hat hackers who then work with the medtech community: wehearthackers.org [1]. The white hat communities, for example, issue warnings and say: “Hey, this could be problematic, let’s work together on solutions”.

How can we prevent Big Tech from coming in and incorporating other people’s innovations?

They’re already doing that. If the best technologies are based on public standards, that’s still better than keeping everything behind closed doors. But we still have work to do. We want to get everyone to take a big step back and say, “What do we have in common and what are issues or priorities that we can discuss together that we can move forward on”. With the cuts in science funding in the US, it is especially important that the scientific community sticks together and that we get good projects with good intentions off the ground together.

Are you also hoping to attract researchers from the USA?

Under ideal circumstances, countries around the world would invest more money in science, not less. But we are clearly not living in ideal circumstances. Given that the US has already cut thousands of scientific jobs and plans to cut tens of thousands more, I very much hope that other countries will step in and welcome good researchers. Including Germany. Of course, the difficult situation in the US could be an advantage for recruitment, science and the economy in other countries – but as I said, these are far from ideal circumstances.

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