Ms Wakenhut and Mr Wieseke, before we dive into the exciting results of your study, I would like to know what motivated you personally to become intensively involved with the use of artificial intelligence in qualitative research and what expectations you have of this development?

DW: As a provider of qualitative research software, we have been working on this topic for a number of years and have been using AI in various areas of our platform for some time, such as translation and sentiment analysis. In June last year, we integrated an AI assistant into our software, which is primarily used for analysis based on pre-trained language models. This type of support has long been requested by many qualitative researchers. We believe that artificial intelligence can enrich qualitative research and ultimately make it not only more efficient, but also better.

RW: AI is here to stay, and we are at the beginning of a journey that we want to actively shape. We advise our clients on the use of AI and it is interesting to see how different their experiences and expectations are. It is also exciting to see in our day-to-day project work how AI is already changing the way data is collected, analysed and interpreted.

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Your webinar provides insights into the results of your study on artificial intelligence in qualitative research. Could you give us a brief overview of the key findings that participants can expect without anticipating too much?

RW: We wanted to understand the current situation: What is the experience, what are the challenges, what are the concerns, what are the opportunities? What we can say is that the general mood is positive, the industry is open to new technologies and there is a high level of experimentation and curiosity.

DW: Of course, there are concerns and hurdles, and we will discuss those too. In the webinar, we will present the key findings, including the different applications of AI, the expected impact on research practice and the potential challenges. Overall, however, people seem to see more opportunities than risks, which is not always the case with new technologies in Germany. I remember the early days of Kernwert almost 20 years ago, when we encountered a lot of scepticism about online qualitative research.

You mention that qualitative research is facing changes due to technological developments. Could you give us some examples of how research practice has already changed through the use of artificial intelligence and what impact this has had on the industry?

RW: An impressive example is translation. We have seen that the translation of guidelines, results or other texts is now very often done by an AI, which has already become routine for many. For multi-country studies with an international project team, this is of course a huge relief. Interestingly, the use of AI has become so commonplace that it is no longer recognised as such. For example, "Is deepl really AI?" was asked several times in the comments on our study. The service provider landscape has already changed in this area. Overall, it can be said that AI is currently being used primarily for routine tasks. All tasks that can be standardised are predestined for this. There is a lot of experimentation going on, and we will see how the industry changes in the coming months and years.

Over 100 qualitative researchers took part in your study. What experiences have they already had with artificial intelligence, and are there any particular examples or findings that stand out in your study?

DW: We were delighted that so many people responded. Thanks again to everyone. The survey is a snapshot; developments and therefore experiences are very dynamic. All in all, the researchers interviewed were curious about the new opportunities and eager for experimentation.

It was interesting to see that confidence in AI grows with experience. Many have already had good experiences and even though not everything is perfect and AI is still a learning field, the results are seen as positive. Perhaps the experience of digitalisation in recent years has helped us all to become more flexible and open to new technologies and to be more relaxed about smaller challenges.

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How do the participants perceive the development of the use of artificial intelligence in qualitative research? Are there uniform assessments or different perspectives that emerged in your study?

RW: Most qualitative researchers agree on what is at the heart of qualitative research: interacting with real people and understanding their attitudes and actions. The human factor is therefore central and few want to change this. However, the role of AI is viewed differently. While some see the positive potential, others are sceptical and have reservations. Some are concerned about the authenticity and depth of insights generated by AI, while others fear the loss of the human element in qualitative research. However, there is a unanimous desire to discuss the topic.

Finally, looking to the future, what developments do you see in relation to the use of artificial intelligence in qualitative research? And how would you like your webinar to contribute to further dialogue within the industry?

DW: Qualitative research is extremely diverse, ranging from interviews to research communities. The use of artificial intelligence and the requirements for AI applications are equally diverse. In the future, AI algorithms will become increasingly sophisticated, allowing more complex data to be analysed and deeper insights to be gained more quickly. As a result, the integration of AI into everyday research will continue to progress. At the same time, however, we need to keep an eye on ethical issues and data protection to ensure that AI is used responsibly. There is currently a great need to learn from each other and to share experiences and insights in dealing with AI. This webinar aims to make a small contribution to this.

 

Ruth Wakenhut is a sociologist and Head of Business Development at KERNWERT, where she advises on the planning and implementation of digital studies, the choice of methods and the use of AI.
Dirk Wieseke is co-founder and managing director of KERNWERT and, together with his team, has been developing software and services for digital research with a qualitative focus since 2005. research approaches.