Description
The number of older adults living independently at home is expanding, which is often said to bring the need for more technological assistance. Dutch policy aims to allow older adults to remain living at home as long as possible and use technologies to support. Artificial Intelligence (AI), as part of these technologies, has the potential to improve personalized care and ageing in place. However, trust and willingness to use AI seem essential for responsible sectoral embedding. Interest in eXplainable AI (XAI) originated from the recognition that AI infrastructures often operate in an opaque, “black-boxed” way. XAI should assist in trust by providing understanding of the underlying logic of the decision-making process, and possibility to identify biases and mistakes. Our earlier research showed different notions and needs regarding explanations. We propose a layered XAI-model with explanations on practical, data specific or even algorithmic levels, to suit different skills and knowledge of the users. As a follow-up, we conducted 28 interviews to investigate ‘what XAI is’ in the worlds of older adults. What do they know about AI and how do they experience and imagine our society with AI? What is XAI and how to value explainability? Findings show that current knowledge on (X)AI is low and the older adults expressed different needs towards explainability. Sometimes it is not valuable to know more about the ‘inside’ of an AI-system. Also, XAI is different from the current technological discourse because XAI is not only technological, but a constellation between human and machine.| Period | 26 Jun 2025 |
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| Event title | British Society of Gerontology: 54th Annual Conference |
| Event type | Conference |
| Location | Guildford, United KingdomShow on map |
| Degree of Recognition | International |
Sectorplan keywords OU
- CW Humane artificial intelligence (sectorplan)
Documents & Links
Related content
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Projects
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Inclusive Humane Artificial Intelligence
Project: Research
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Research output
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What should AI explain to you? Visions of older adults regarding explainable AI
Research output: Contribution to journal › Article › Academic › peer-review