Summary information

Study title

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...
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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.

Related publications

Not available