Abstract
Advances in the development of AI and its application in many areas of society have given rise to an ever-increasing need for society’s members to understand at least to a certain degree how these technologies work. Where users are concerned, most approaches in Explainable Artificial Intelligence (XAI) assume a rather narrow view on the social process of explaining and show an undifferentiated assessment of explainees’ understanding, which mostly are considered passive recipients of information. The actual knowledge, motives, needs and challenges of (lay)users in algorithmic environments remain mostly missing. We argue for the consideration of explanation as a social practice in which explainer and explainee co-construct understanding jointly. Therefore, we seek to enable lay users to document, evaluate, and reflect on distinct AI interactions and correspondingly on how explainable AI actually is in their daily lives. With this contribution we want to discuss our methodological approach that enhances the documentary method by the implementation of ‘digital diaries’ via the mobile instant messaging app WhatsApp – the most used instant messaging service worldwide. Furthermore, from a theoretical stance, we examine the socio-cultural patterns of orientation that guide users’ interactions with AI and their imaginaries of the technologies – a sphere that is mostly obscured and hard to access for researchers. Finally, we complete our paper with empirical insights by referring to previous studies that point out the relevance of perspectives on explaining and understanding as a co-constructive social practice.
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Notes
- 1.
With reference to WhatsApp [39] it currently holds more than two billion users in 180 countries.
- 2.
More recent results regarding the suitability of our method as well as first insights into the diaries conducted will be provided during the HCI conference in June 2022.
- 3.
In consequence, the following might be legally required only for researches located in the EU as we are. However, research ethics suggest that the steps detailed here would be apt also for other researchers. See also [23].
- 4.
The user names are anonymized below for data protection reasons.
- 5.
The background is a wave of cease-and-desist letters circulating in 2018 with regard to influencers, which was instigated by the Verband Sozialer Wettbewerb (German Association of Social Competition) and initially culminated in a highly controversial preliminary injunction issued by the Berlin Regional Court against the popular influencer Vreni Frost in June 2018.
- 6.
HypeAuditor is a software tool that has been available since 2018 and is mainly used by companies in the field of influencer marketing. It was originally intended for the precise analysis of accounts and, in particular, their reach. It is intended to enable companies to identify accounts with purchased reach (i.e., primarily purchased followers and/or likes) without much effort. It also serves companies in ongoing campaign analysis with influencers. See also: https://hypeauditor.com/.
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Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research for this article was funded by the collaborative research centre ‘‘Constructing Explainability” (DFG TRR 318/1 2021 – 438445824) at Paderborn University and Bielefeld University.
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Finke, J., Horwath, I., Matzner, T., Schulz, C. (2022). (De)Coding Social Practice in the Field of XAI: Towards a Co-constructive Framework of Explanations and Understanding Between Lay Users and Algorithmic Systems. In: Degen, H., Ntoa, S. (eds) Artificial Intelligence in HCI. HCII 2022. Lecture Notes in Computer Science(), vol 13336. Springer, Cham. https://doi.org/10.1007/978-3-031-05643-7_10
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