Counterventions: a reparative reflection on interventionist HCI

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Williams, R., Boyd, L., & Gilbert, J. E. (2023). Counterventions: a reparative reflection on interventionist HCI. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1-11. https://doi.org/10.1145/3544548.3581480

Publication date: 19 Apr 2023 Added to AutiHub: 9 Aug 2026 Type: Other Article language: English
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Authors

Publication authors
3
Publication authors identified as autistic
1 / 3 (33.3%)
  1. Rua M. Williams *
  2. LouAnne Boyd
  3. Juan E. Gilbert

Abstract

Research in HCI applied to clinical interventions relies on normative assumptions about which bodies and minds are healthy, valuable, and desirable. To disrupt this normalizing drive in HCI, we define a “counterventional approach” to intervention technology design informed by critical scholarship and community perspectives. This approach is meant to unsettle normative assumptions of intervention as urgent, necessary, and curative. We begin with a historical overview of intervention in HCI and its critics. Then, through reparative readings of past HCI projects in autism intervention, we illustrate the emergent principles of a counterventional approach and how it may manifest research outcomes that are fundamentally divergent from dominant approaches. We then explicate characteristics of “counterventions” – projects that aim to contest dominant sociotechnical paradigms through privileging community and participants in research inquiry, interaction design, and analysis of outcomes. These divergent research imaginaries have transformative implications for how interventionist HCI might be conducted in future.

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Cited references
79
With a DOI
64
Without a DOI, from raw bibliography text
13
8 / 79 (10.1%) cited references include at least one author identified as autistic.
References with data to complete
5 / 79 (6.3%)
References with detected author names
74 / 79 (93.7%)
Without detected author names
5
Without a structured title
2
Without a stable identifier
13
References with raw author names still to review
1
References with external metadata lookup issues
3
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
207
From DOI or external metadata
207
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
2
44 / 207 (21.3%) names are linked to an author already present in AutiHub. 163 / 207 (78.7%) names are not yet linked.
Names linked to a person identified as autistic
8 / 207 (3.9%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 8 / 44 (18.2%). Distinct people identified as autistic: 2 / 174 (1.1%).
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