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Attitudes Towards Emotional Artificial Intelligence Use: Transcripts of Citizen Workshops Collected Using an Innovative Narrative Approach, 2021
Creator
Laffer, A, Bangor University
Study number / PID
855688 (UKDA)
10.5255/UKDA-SN-855688 (DOI)
Data access
Restricted
Series
Not available
Abstract
The data were collected during citizen workshops, conducted online via Zoom, exploring attitudes towards emotional artificial intelligence use (EAI). EAI is the use of affective computing and AI techniques to try to sense and interact with human emotional life, ranging from monitoring emotions through biometric data to more active interventions.
10 sets of participants (n=46) were recruited for the following groups:
3 older (65+) groups: n=13
3 younger (18-34) groups: n=12
2 groups, people self-identifying as disabled: n=10
2 groups, members of UK ethnic minorities: n=11
There was an attempt to balance other demographic categories where possible.
Participants were grouped in relation to age as this has been shown to be the biggest indicator of differences in attitude towards emotional AI (Bakir & McStay, 2020; McStay, 2020). It was also considered important to include the views of those who have traditionally been ignored in the development of technology or suffered further discrimination through its use, and so the opinions and perspectives of minority groups and disabled people were sought.
Participants were recruited through a research panel for the workshops, which took place in August 2021. A novel narrative approach was used, with participants taken through a piece of interactive fiction (developed using Twine, viewable here: https://eaitwine.neocities.org/), a day-in-the life story of a protagonist encountering seven mundane use-cases of emotional AI, each structured as a) a neutral introduction to the technology; b) a binary choice involving the use of the technology; c) a ContraVision component demonstrating positive and negative events/outcomes.
The use cases were:
• Home-hub smart assistant
• Bus station surveillance sensor
• Social Media Fake news/Disinformation and profiling.
• Spotify music recommendations (using voice and ambient data).
• Sales call evaluation and prompt tool
• Emotoy that collects and responds to children's...
Terminology used is generally based on DDI controlled vocabularies: Time Method, Analysis Unit, Sampling Procedure and Mode of Collection, available at CESSDA Vocabulary Service.
Methodology
Data collection period
04/08/2021 - 13/08/2021
Country
United Kingdom
Time dimension
Not available
Analysis unit
Individual
Group
Universe
Not available
Sampling procedure
Not available
Kind of data
Text
Data collection mode
An innovative narrative approach to collecting rich qualitative data from participants in an online setting was employed.A multimodal narrative was created using Twine, an interactive fiction writing tool. The narrative was developed drawing on ideas and concepts from Design Fiction, chiefly the use of diegetic prototypes - designed objects or technologies that exist within a fictional world - and incorporates elements of ContraVision, where positive and negative outcomes of the same scenario are shared with participants. This was presented to participants via Zoom (online video conferencing software) during an online workshop. Discussion was invited at different points of the narrative.10 sets of participants (n=46) were recruited for the following groups:3 older (65+) groups: n=133 younger (18-34) groups: n=122 groups, people self-identifying as disabled: n=102 groups, members of UK ethnic minorities: n=11There was an attempt to balance other demographic categories where possible. Participants were grouped in relation to age as this has been shown to be the biggest indicator of differences in attitude towards emotional AI. It was also considered important to include the views of those who have traditionally been ignored in the development of technology or suffered further discrimination through its use, and so the opinions and perspectives of minority groups and disabled people were sought. Participants were recruited through a research panel.
Funding information
Grant number
ES/T00696X/1
Access
Publisher
UK Data Service
Publication year
2022
Terms of data access
The Data Collection is available for download to users registered with the UK Data Service.