Code example for programmatically calling GPT-4o through OpenAI’s API. The code is written in Python, which is currently the de facto the lingua franca of AI/ML. However, most LLM providers support a range of programming languages for use with their API.
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AI in transdisciplinary research: Opportunities and challenges

Artificial intelligence (AI) offers new opportunities for transdisciplinary research (TDR). But what does responsible use of AI look like? A recent ISOE publication shows how AI can be usefully integrated into TDR processes.
The integration of artificial intelligence into transdisciplinary research opens up new possibilities in knowledge integration, participation, and science communication. At the same time, its use requires critical and responsible action. The current ISOE publication “Opportunities and Risks of Using AI Technologies in Transdisciplinary Research” highlights how AI can be usefully integrated into transdisciplinary research processes.

AI can support research, for example, in the analysis of unstructured data, hypothesis generation, and literature research. In participatory processes, it facilitates the involvement of stakeholders, the visualization of complex content, and efficient communication. In science communication, AI also offers opportunities to create texts, images, and videos, make complex content more understandable, and make knowledge more widely accessible.

At the same time, there are clear limitations and challenges: AI models can deliver erroneous or misleading results, and linking different forms of knowledge – known as strong knowledge integration – remains difficult. In addition, ethical aspects such as bias, lack of transparency, data protection issues, and social and environmental impacts must be taken into account.
 

Responsible use is essential

For the responsible use of AI in TDR, the authors recommend using AI as a supplement to human expertise and always critically examining its results. Wherever possible, open and transparent models should be used and ethical and participatory standards adhered to.

The publication offers practical guidance and supports informed decisions about the use of AI in transdisciplinary research projects. It is aimed at scientists and other actors in the transdisciplinary research environment.
 

Contact:

Dr. Nicola Schuldt-Baumgart

Head of Science Communication and Knowledge Transfer, Press Spokeswoman Go to Profile
Knowledge and Participation

Knowledge and Participation —

What kind of knowledge is needed for social-ecological transformations? How can the perspectives and experiences of different stakeholder groups be incorporated into this process?

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