Designing (with) AI for Wellbeing

Generated image of people walking with technology devices
Figure 1: An image from the website of the workshop "Designing (with) AI for Wellbeing" at CHI 2024.

Dimitra Dritsa and Loes van Renswouw present their workshop at CHI 2024. Check out the website here.

What’s your name?

Hi, we are Dimitra Dritsa and Loes van Renswouw!


Dimitra Dritsa, Loes van Renswouw, Sara Colombo, Kaisa Väänänen, Sander Bogers, Arian Martinez, Jess Holbrook, and Aarnout Brombacher. 2024. Designing (with) AI for Wellbeing. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24), May 11– 16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA, 7 pages.

TL;DR (if you had to describe this work in one sentence, what would you tell someone?):

In our one-day CHI 2024 workshop, we aim to bring together researchers and practitioners to foster community building and create a conceptual framework that enables the emergence of rich, meaningful, and ethical solutions for designing (with) AI for wellbeing, considering the significant value but also the challenges and risks related to this topic.

What problem is this research addressing, and why does it matter?

The integration of AI in technologies such as wearable activity trackers holds considerable promise in providing personalized, data-driven insights and solutions that empower individuals to make informed choices, adopt healthier habits, and maintain a balanced and fulfilling life.

However, these technologies often generate insights that are wrong or misunderstood, which can create issues in the absence of a healthcare professional in the loop. The generated feedback is also frequently not relevant due to differences in lifestyle, habits, or personal characteristics. The data available for algorithm training are often limited, and do not represent marginalized communities, while simply collecting more data is not always the answer, due to privacy concerns and challenges in longitudinal data collection in the wild. Core challenges related to using data and AI as design material also complicate this process. For example, designers face difficulties in anticipating AI failures, which is necessary for designing mitigation strategies in the human-data interaction loop.

Given these challenges and others, there is a need for innovative design strategies that leverage the power of designing with data and AI while also incorporating the considerations that designing for wellbeing brings.

What are some questions you’d like to discuss at and after the workshop? 

  • How can we find designerly ways to avoid privacy risks in personal health (e.g., activity, fitness, sleep, stress..) data collection, increase transparency regarding the purpose of data use, and increase the agency of the users in negotiating (changes in) the use of their personal data?
    • How can we create systems that enable smooth transitions between individual and collaborative personal health data experiences?
    • How can we promote the capacity of designers to envision AI failures in interactions with personal health data? How can we create designerly, personalized solutions for mitigating such failures?
    • How can we design AI-enabled systems that consider differences in personal health data and AI literacy among individuals to avoid misinterpretations?
    • How can we control the appropriateness of generative AI outputs in applications where there is no expert to act as an intermediary for quality checks?
    • How can we create positive data collection in-the-wild experiences that ensure long-term adherence for the acquisition of data sufficient in volume and generalizability for algorithm training, or design creative alternative solutions?
    • How can we ensure that the AI output is relevant considering the large interpersonal variations in personal health data and other relevant qualities?
    • How can we enhance user experience in AI-enabled systems for promoting wellbeing by incorporating the ability of continuous improvement, during product development but also after implementation?
    • How can we bring short- and long-term positive changes in wellbeing through AI-enabled systems?

How do you plan to grow the community interested in this topic?

We plan to publish the material generated
during the workshop on our website (, and later launch a special issue on the topic, in the Behaviour & Information Technology journal by Taylor & Francis. We also plan to maintain and expand this emerging community by using a dedicated Teams and Slack workspace (stay tuned!) and an emailing list, and by proposing follow-up workshops.


Dimitra Dritsa. Photo by Vincent van den Hoogen.

Dimitra Dritsa is a Postdoctoral Researcher at Eindhoven University of Technology, Department of Industrial Design. She obtained her PhD at University of Technology Sydney, where she investigated how we can make sense of data from wearables to understand stress in the urban space and promote wellbeing at the individual and urban scale. Her current research focuses on designing data analysis and visualization methods and tools that support human-data interaction and facilitate sensemaking, taking into account data subjectivity and uncertainty.

Loes van Renswouw. Photo by Vincent van den Hoogen.

Loes van Renswouw is a Postdoctoral Researcher in the Industrial Design Department at Eindhoven University of Technology. With a background in architecture, her research focuses on enhancing the influential power of healthy active environments by integrating smart and interactive applications. She explored different perspectives on large datasets as well as persuasive technologies and how these can inform the design of intelligent solutions. Researching and designing with data, she maintains a user-centered approach towards these so-called interActive Urban Environments.