What is Generative AI?

Generative Artificial Intelligence (AI) is an advanced form of AI that enables machines to autonomously generate content such as text, images, music and even videos that can be very similar to that of humans. Unlike traditional AI systems, which are programmed to perform specific tasks based on the data they are given, Generative AI learns from a variety of data how to create new, original content that did not previously exist. This is made possible by complex algorithms that enable AI to understand and creatively apply patterns, styles and contexts. From the creation of personalized media to the development of innovative solutions in medicine and, of course, other industries. We currently believe that this technology has the potential to transform not only the way we work, but also how we think creatively and drive innovation. In this context, the healthcare industry as you know it today is also facing major changes.

Why should the healthcare market engage with Generative AI?

Generative AI is changing the roles of professionals in society in many sectors. This also applies to professionals in the healthcare industry. Generative AI has the potential to revolutionize the way diseases are treated, new drugs are developed and treatments are tailored to individual patients. It will also fundamentally change the daily work of doctors, nurses and other clinical healthcare professionals, as well as their reputation in society.

I am convinced that human qualities such as compassion, communication and instinct are becoming increasingly important and will become a decisive competitive advantage on the labor market in the healthcare world. While repetitive tasks are increasingly being taken over by Generative AI, (inter)human skills are playing an ever greater role.

How can Generative AI be used in healthcare?

Generative AI as a diagnostic assistant

Generative AI can help you diagnose diseases by interpreting data and providing clear, detailed insights into what is known about the patient. For example, it can be used to examine hundreds of X-ray images, MRIs and CT scans and quickly provide a statistical summary of the results. This will lead to more accurate and data-driven diagnoses. You can then use these results and evaluations, combine them with your experience and human impressions and derive appropriate measures for the patient. This is where human skills come into play again. Especially when it comes to communicating the diagnosis appropriately to the patient.

Automation of routine and administrative tasks

I already see this being used a lot in hospitals and doctors’ surgeries.

Medical professionals in particular are beginning to use Generative AI for repetitive and routine administrative tasks that occur every day. This means that tasks that need to be completed but require little human empathy can be automated with Generative AI and you have more time for the human-relevant tasks in care. This can also include small talk with a patient, which often plays an important role in addition to pure medical treatment. From managing and updating patient records to scheduling appointments, generative AI can already bring significant added value and time savings. The article Generative AI for medical reports gives you an example of how ChatGPT can be used to create health documentation.

Generative AI for data generation in drug research

I have not yet been involved in research applications myself, but I have heard many presentations on the subject. For example, at the last Trend Days Health in Lucerne.

The same capabilities that enable Generative AI to create texts and scripts can also be used to develop new drug and vaccine candidates for clinical trials. This can significantly accelerate the development of new drugs. However, the correct use of AI and the subsequent verification of the results by people who are familiar with these areas appear to be important here.

The World Economic Forum has published an interesting article on how Large Language Models (LLMs) can supplement and optimize data generation in the healthcare sector.

Generative AI is already increasingly being used to create synthetic data that is artificially generated to mimic real information. This is particularly useful in situations where there is little training data, such as rare diseases or minorities in the population. It can also reduce the security and privacy measures that healthcare professionals normally have to take when working with real patient data.

Incidentally, synthetic data can even be used to simulate health scenarios such as pandemics or the emergence of antibiotic-resistant organisms that could cause a global health crisis.

What risks need to be considered with Generative AI in the healthcare industry?

Data protection considerations

In addition to all the benefits that Generative AI will bring to the healthcare industry in the long term, the new technologies also pose new challenges, especially data protection concerns.

One reason for this is that most use cases involve the use of personal data. It is therefore extremely important to protect yourself against data leaks, losses and breaches. Hosting on your own servers or on servers that comply with national data protection legislation is an important first measure here.

When using language models such as ChatGPT, the data is stored in the USA. This is one more reason for many people and companies to rely on secure solutions such as SwissGPT or open source models.

Ethical considerations

When using Generative AI, the technology is also used in part to make decisions. If this is the case, it is important that this is also communicated transparently to all those involved. Often, further explanations must then be given to the target group. Once you have lost the trust of your patients due to a lack of transparency, it will be difficult to regain it. Open and honest communication with further explanations is therefore highly recommended.

What future trends will Generative AI bring to the healthcare industry?

Doctors, nurses and other clinical healthcare professionals are, in my opinion, more protected from the risk of being replaced by AI than many other people. Your jobs require you to perform many human skills at an advanced level that machines will not soon be able to imitate.

Intuition and experience play a role in medicine, and that will not change. However, AI offers the opportunity for you to redefine the way you work and even your role in society.

The fact that more and more repetitive tasks are likely to be replaced by AI means that you will have more time to work directly with patients. I suspect that it will lead to new specializations. On the one hand, the need for clinical staff focusing on AI-supported diagnoses, data-driven medicine and ethical AI will grow and, at the same time, human skills such as empathy will once again come to the fore.

Ultimately, our (Western) healthcare will continue to revolve around empathy, compassion and the human touch. Generative AI creates the opportunity to expand these qualities in a way that will make professionals in this field, including you, even more indispensable to society.

Further resources

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