Algorithmically Controlled Automated Decision-Making and Societal Acceptability: Does Algorithm Type Matter?

Grangé, Camille

doi:10.24251/hicss.2022.629

Cited by 3 publications

(2 citation statements)

References 45 publications

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“…Within the algorithm factors category, one was the anthropomorphic presentation of an algorithm, along with its complexity, understandability, accuracy, and ability to learn. Similarly, Grange [41] indicated the use of machine learning or "black-box" techniques as a tool to automate decisions. Because humans may be unaware of how algorithms are designed to operate, it is critical that the perceptions of those impacted by algorithmic-based decisions are taken on board throughout the design, implementation, and review processes.…”

Section: Agency and Decision-making Algorithmsmentioning

confidence: 99%

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Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis

Heaton,

Nichele,

Clos

et al. 2024

J Med Internet Res

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Background Since September 2020, the National Health Service (NHS) COVID-19 contact-tracing app has been used to mitigate the spread of COVID-19 in the United Kingdom. Since its launch, this app has been a part of the discussion regarding the perceived social agency of decision-making algorithms. On the social media website Twitter, a plethora of views about the app have been found but only analyzed for sentiment and topic trajectories thus far, leaving the perceived social agency of the app underexplored. Objective We aimed to examine the discussion of social agency in social media public discourse regarding algorithm-operated decisions, particularly when the artificial intelligence agency responsible for specific information systems is not openly disclosed in an example such as the COVID-19 contact-tracing app. To do this, we analyzed the presentation of the NHS COVID-19 App on Twitter, focusing on the portrayal of social agency and the impact of its deployment on society. We also aimed to discover what the presentation of social agents communicates about the perceived responsibility of the app. Methods Using corpus linguistics and critical discourse analysis, underpinned by social actor representation, we used the link between grammatical and social agency and analyzed a corpus of 118,316 tweets from September 2020 to July 2021 to see whether the app was portrayed as a social actor. Results We found that active presentations of the app—seen mainly through personalization and agency metaphor—dominated the discourse. The app was presented as a social actor in 96% of the cases considered and grew in proportion to passive presentations over time. These active presentations showed the app to be a social actor in 5 main ways: informing, instructing, providing permission, disrupting, and functioning. We found a small number of occasions on which the app was presented passively through backgrounding and exclusion. Conclusions Twitter users presented the NHS COVID-19 App as an active social actor with a clear sense of social agency. The study also revealed that Twitter users perceived the app as responsible for their welfare, particularly when it provided instructions or permission, and this perception remained consistent throughout the discourse, particularly during significant events. Overall, this study contributes to understanding how social agency is discussed in social media discourse related to algorithmic-operated decisions This research offers valuable insights into public perceptions of decision-making digital contact-tracing health care technologies and their perceptions on the web, which, even in a postpandemic world, may shed light on how the public might respond to forthcoming interventions.

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Section: Agency and Decision-making Algorithmsmentioning

confidence: 99%

“…This was related to the app not working as perceived by the Twitter user. This indicated that the app was perceived as having the capacity to think or act autonomously, leading to the opposition of system use [40,41,88].…”

Section: Functioningmentioning

confidence: 99%

Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis

Heaton,

Nichele,

Clos

et al. 2024

J Med Internet Res

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“ChatGPT says no”: agency, trust, and blame in Twitter discourses after the launch of ChatGPT

Heaton,

Nichele,

Clos

et al. 2024

AI Ethics

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ChatGPT, a chatbot using the GPT-n series large language model, has surged in popularity by providing conversation, assistance, and entertainment. This has raised questions about its agency and resulting implications on trust and blame, particularly when concerning its portrayal on social media platforms like Twitter. Understanding trust and blame is crucial for gauging public perception, reliance on, and adoption of AI-driven tools like ChatGPT. To explore ChatGPT’s perceived status as an algorithmic social actor and uncover implications for trust and blame through agency and transitivity, we examined 88,058 tweets about ChatGPT, published in a ‘hype period’ between November 2022 and March 2023, using Corpus Linguistics and Critical Discourse Analysis, underpinned by Social Actor Representation. Notably, ChatGPT was presented in tweets as a social actor on 87% of occasions, using personalisation and agency metaphor to emphasise its role in content creation, information dissemination, and influence. However, a dynamic presentation, oscillating between a creative social actor and an information source, reflected users’ uncertainty regarding its capabilities and, thus, blame attribution occurred. On 13% of occasions, ChatGPT was presented passively through backgrounding and exclusion. Here, the emphasis on ChatGPT’s role in informing and influencing underscores interactors’ reliance on it for information, bearing implications for information dissemination and trust in AI-generated content. Therefore, this study contributes to understanding the perceived social agency of decision-making algorithms and their implications on trust and blame, valuable to AI developers and policymakers and relevant in comprehending and dealing with power dynamics in today’s age of AI.

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Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis (Preprint)

Heaton¹,

Nichele²,

Clos³

et al. 2023

Preprint

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BACKGROUND Since September 2020, the NHS Covid-19 contact tracing app has been used to mitigate the spread of Covid-19 in the UK. Since its launch, this app has been part of the discussion regarding the perceived social agency of decision-making algorithms. On the social media website Twitter, a plethora of views about the app have been found but only analysed for sentiment and topic trajectories thus far, leaving the perceived social agency of the app underexplored. OBJECTIVE We aimed to examine the discussion of social agency in social media public discourse regarding algorithmic-operated decisions, particularly when the AI agency responsible for specific information systems is not openly disclosed in an example such as the Covid-19 contact tracing app. To do this, we analysed the presentation of the NHS Covid-19 App on Twitter, focusing on the portrayal of social agency and the impact of its deployment on society. We also aimed to discover what the presentation of social agents communicates about the perceived responsibility of the app. METHODS Using Corpus Linguistics and Critical Discourse Analysis, underpinned by Social Actor Representation, we used the link between grammatical and social agency and analysed a corpus of 118,316 tweets from September 2020 to July 2021 to see whether the app was portrayed as a social actor. RESULTS We found that active presentations of the app – seen mainly through personalisation and agency metaphor – dominated the discourse. The app was presented as a social actor in 96% of the cases considered and grew in proportion to passive presentations in time. These active presentations showed the app to be a social actor in five main ways: informing, instructing, providing permission, disrupting, and functioning. We found a small number of occasions where the app was presented passively, through backgrounding and exclusion. CONCLUSIONS We concluded that Twitter users presented the NHS Covid-19 App as an active social actor with a clear sense of social agency. The study also revealed that Twitter users perceived the app as responsible for their welfare, especially when it provided instructions or permission, and this perception remained consistent throughout the discourse, particularly during significant events. Overall, this study contributes to understanding how social agency is discussed in social media discourse related to algorithmic-operated decisions.

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Algorithmically Controlled Automated Decision-Making and Societal Acceptability: Does Algorithm Type Matter?

Cited by 3 publications

References 45 publications

Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis

Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis

“ChatGPT says no”: agency, trust, and blame in Twitter discourses after the launch of ChatGPT

Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis (Preprint)

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