Our work

Appl.AI Webinar #3 - Viewer questions

During the Appl.AI webinar # 3 ’How can we improve preventive care with AI?’ we have received many viewer questions. Below you can find the answers from our panel members to the most common subjects.

The webinar consisted of a panel with digital health expert Jildau Bouwman (left) and lead digital innovation expert Bram van Leeuwen (right).

Rewatch the webinar here

Appl.AI Webinar #3: 'How can we improve preventive care with AI?'

Watch webinar

1. What is actually the reason that basic care is so focused on the medical side instead of the preventive side?

Firstly, the development of all kinds of medication has led to an enormous increase in healthy life years (think of antibiotics, for example). This has created a system that supports the medical side of health. To change this, all parties must work together. They will only do that if they see immediate benefits. And the benefits of a preventive system lie in the long term and the benefits and costs often do not lie with the same party.

2. It is clear that eating too much and having too little exercise are the main reasons for obesity and DM type II. Which role should the government play, are there good examples of this?

A good example of government intervention against obesity is the sugartax in Great Britain. This has led to a decrease in the consumption of sugary drinks. In addition, there are examples of countries where there is much more exercise in schools. These are methods that Dutch politicians could also use.

3. I work in healthcare myself and I notice that technical progress is difficult, where does she (Jildau) get her optimism from?

I recognize what you’re saying. Although there are technical developments, they are regularly not properly implemented. In my opinion, one of the reasons is that users are not properly included in the development. As a result, they do not really know how it helps them and it does not meet their needs. I think that if that co-creation does take place, big steps can be taken.


4. How does a user know whether he / she is dealing with high-quality technology that respects privacy?

How could the user be informed about this? One answer could be that there should be an obligation for certification and legislation. In addition, I myself see that legislation (eg the AVG) is certainly not fully complied with. So as a user, in my opinion, you should indeed get more visible how and what your data is used for. How to make this transparent is another point that requires research. In addition, individuals and organizations must also demand more transparency themselves.

5. What is the biggest stumbling block for innovative developments in healthcare?

80% of the innovations do not make it simply because insufficient attention is paid to the implementation and connection to existing care processes. The added value is insufficiently felt by the end users. In addition, the current funding system does not help, which is based on volume instead of quality.

6. AI increasingly seems to be a kind of magical term. I also get the impression from the panel members that AI will solve the problems in healthcare. It can't be that simple, can it?

AI is certainly not the magical solution to the healthcare challenges. I do however believe it can help. The amount of data in healthcare is currently doubling every quarter. AI can help to interpret this data at lightning speed and make suggestions based on it. However, the professional and the patient remain in the lead together and can make choices together on this basis.

7. Apps are developed by companies for profit. How can you guarantee that citizens' data is handled ethically? Does the government do, does Europe do?

There are various guidelines and laws that suppliers must comply with. Of course we have the GDPR, but many AI initiatives also fall into the "medical devices" category. The consequence of this is that companies must be transparent in how the device works and how the data is handled. Personally, I expect that when such solutions are reimbursed, people will set higher requirements for transparent data.

 

Rewatch the webinar here

Appl.AI Webinar #3: 'How can we improve preventive care with AI?'

APPL.AI WEBINAR
Our work

Appl.AI Webinar #1: AI’s role in government decision-making

The main question we addressed in our webinar is ‘How can AI help the government in transparent and fair decision-making?’. You can watch this webinar that took place on Wednesday, 27 May 2020. Read more
Knowledge

Data-driven policy: AI in public policy and services

Every day, policy makers and public servants face complex challenges. Some of these challenges are: fighting long-term unemployment, meeting sustainability goals and anticipating technological impact.... Read more
Expertise

Policy Lab: developing data-driven policies

The use of new data sources and technological developments such as Artificial Intelligence offers opportunities for policy makers to gain new insights and respond better to societal developments. TNO has... Read more
Knowledge

AI helps to define information clearly

Whenever we want to make a decision or check something, correct information is crucial. The more clear the information, the better. If not, and for example if different terms are used for the same concept,... Read more
Knowledge

Fair Machine Learning combats biases  

An AI tool bases its calculations on data. If the data is biased, the calculations will be biased. If there was once a male preference within a profession, then this will be adopted by AI tools for recruitment. So... Read more
Knowledge

Towards human-machine teaming

The rising potential of AI, intertwines our lives with the use of AI-technology. It will increasingly behave as a partner rather than a tool. Yet AI-technology is always embedded within a larger organisation,... Read more
Roadmap

Techniques

Read more
Knowledge

Deep Vision extracts information from images

A photo says more than a thousand words. However, it’s difficult for people to get useful information from many photos or videos. Through Deep Vision, we’re developing AI algorithms to make automatic... Read more
Contact

Ir. Carla Rombouts-Gordijn

  • Digital health
  • Data management
  • Lifestyle & health
  • Privacy
  • Artificial intelligence

FOLLOW TNO ON SOCIAL MEDIA

Stay up to date with our latest news, activities and vacancies

TNO.nl collects and processes data in accordance with the applicable privacy regulations for an optimal user experience and marketing practices.
This data can easily be removed from your temporary profile page at any time.
You can also view our privacy statement or cookie statement.