Pub Date : 2024-08-19DOI: 10.1177/17504813241267116
Danica Damljanovic
{"title":"Is human perception of AI robots introducing a new type of bias?","authors":"Danica Damljanovic","doi":"10.1177/17504813241267116","DOIUrl":"https://doi.org/10.1177/17504813241267116","url":null,"abstract":"","PeriodicalId":46726,"journal":{"name":"Discourse & Communication","volume":"5 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-19DOI: 10.1177/17504813241267068
William Housley, Patrik Dahl
Large Language Models (LLMs) and generative Artificial Intelligence (A.I.) have become the latest disruptive digital technologies to breach the dividing lines between scientific endeavour and public consciousness. LLMs such as ChatGPT are platformed through commercial providers such as OpenAI, which provide a conduit through which interaction is realised, via a series of exchanges in the form of written natural language text called ‘prompt engineering’. In this paper, we use Membership Categorisation Analysis to interrogate a collection of prompt engineering examples gathered from the endogenous ranking of prompting guides hosted on emerging generative AI community and practitioner-relevant social media. We show how both formal and vernacular ideas surrounding ‘natural’ sociological concepts are mobilised in order to configure LLMs for useful generative output. In addition, we identify some of the interactional limitations and affordances of using role prompt engineering for generating interactional stances with generative AI chatbots and (potentially) other formats. We conclude by reflecting the consequences of these everyday social-technical routines and the rise of ‘ethno-programming’ for generative AI that is realised through natural language and everyday sociological competencies.
{"title":"Membership categorisation, sociological description and role prompt engineering with ChatGPT","authors":"William Housley, Patrik Dahl","doi":"10.1177/17504813241267068","DOIUrl":"https://doi.org/10.1177/17504813241267068","url":null,"abstract":"Large Language Models (LLMs) and generative Artificial Intelligence (A.I.) have become the latest disruptive digital technologies to breach the dividing lines between scientific endeavour and public consciousness. LLMs such as ChatGPT are platformed through commercial providers such as OpenAI, which provide a conduit through which interaction is realised, via a series of exchanges in the form of written natural language text called ‘prompt engineering’. In this paper, we use Membership Categorisation Analysis to interrogate a collection of prompt engineering examples gathered from the endogenous ranking of prompting guides hosted on emerging generative AI community and practitioner-relevant social media. We show how both formal and vernacular ideas surrounding ‘natural’ sociological concepts are mobilised in order to configure LLMs for useful generative output. In addition, we identify some of the interactional limitations and affordances of using role prompt engineering for generating interactional stances with generative AI chatbots and (potentially) other formats. We conclude by reflecting the consequences of these everyday social-technical routines and the rise of ‘ethno-programming’ for generative AI that is realised through natural language and everyday sociological competencies.","PeriodicalId":46726,"journal":{"name":"Discourse & Communication","volume":"50 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-14DOI: 10.1177/17504813241267117
Lynn de Rijk, Mieke Breukelman, Evi Dalmaijer, Wyke Stommel
For humanoid robots, gender-ambiguous presentation is implemented as a potential way to avoid gender-stereotypical design. Using conversation analysis, we look at video recorded user interaction in the presence of a designedly gender-ambiguous robot, showing how this design choice is actually dealt with within a social context. Robot gender becomes relevant initially when a user refers to the robot with a dual-gendered package (‘young lady young gentleman’), with another user proposing ‘her’ for the robot, and the talk then evolving to the pursuit of agreement on the robot’s proposed femininity. Robot gender attribution is treated by these users as a collaborative endeavor rather than an individual choice. It includes displays of accountability and orientations to delicateness of gender attribution. By implication, the analysis shows that ambiguous design shifts the burden of gender attribution from robot designers to users.
{"title":"‘This uh. . . young lady young gentleman’: Gender attribution in the context of a gender-ambiguous robot","authors":"Lynn de Rijk, Mieke Breukelman, Evi Dalmaijer, Wyke Stommel","doi":"10.1177/17504813241267117","DOIUrl":"https://doi.org/10.1177/17504813241267117","url":null,"abstract":"For humanoid robots, gender-ambiguous presentation is implemented as a potential way to avoid gender-stereotypical design. Using conversation analysis, we look at video recorded user interaction in the presence of a designedly gender-ambiguous robot, showing how this design choice is actually dealt with within a social context. Robot gender becomes relevant initially when a user refers to the robot with a dual-gendered package (‘young lady young gentleman’), with another user proposing ‘her’ for the robot, and the talk then evolving to the pursuit of agreement on the robot’s proposed femininity. Robot gender attribution is treated by these users as a collaborative endeavor rather than an individual choice. It includes displays of accountability and orientations to delicateness of gender attribution. By implication, the analysis shows that ambiguous design shifts the burden of gender attribution from robot designers to users.","PeriodicalId":46726,"journal":{"name":"Discourse & Communication","volume":"23 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-14DOI: 10.1177/17504813241271492
Ole Pütz, Elena Esposito
LLM-based chatbots’ ability to generate contextually appropriate and informative texts can be taken as an indication that they are also able to understand text. We argue instead that the separation of the two competences to generate and to understand text is the key to their performance in dialog with human users. This argument requires a shift in perspective from a concern with machine intelligence to a concern with communicative competence. We illustrate our argument with empirical examples of what conversation analysis calls ‘repair’, showing that the management of trouble by chatbots is not based on an underlying understanding of what is going on but rather on their use of the feedback by human conversational partners. In the conclusion we suggest that strategies for the interaction between chatbots and users should not aim to improve computational skills but to develop a new communicative competence.
{"title":"Performance without understanding: How ChatGPT relies on humans to repair conversational trouble","authors":"Ole Pütz, Elena Esposito","doi":"10.1177/17504813241271492","DOIUrl":"https://doi.org/10.1177/17504813241271492","url":null,"abstract":"LLM-based chatbots’ ability to generate contextually appropriate and informative texts can be taken as an indication that they are also able to understand text. We argue instead that the separation of the two competences to generate and to understand text is the key to their performance in dialog with human users. This argument requires a shift in perspective from a concern with machine intelligence to a concern with communicative competence. We illustrate our argument with empirical examples of what conversation analysis calls ‘repair’, showing that the management of trouble by chatbots is not based on an underlying understanding of what is going on but rather on their use of the feedback by human conversational partners. In the conclusion we suggest that strategies for the interaction between chatbots and users should not aim to improve computational skills but to develop a new communicative competence.","PeriodicalId":46726,"journal":{"name":"Discourse & Communication","volume":"33 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.1177/17504813241266903
Katarzyna Molek-Kozakowska
This study explores the range of discursive patterns used to present artificial intelligence as a revolutionary but controversial technology in online science journalism. It uses a triangulated dataset of over a hundred recent mini-narratives sourced from New Scientist, Nature daily briefings, and Scientific American to reconstruct typical storylines in the thematic domains of research, business, and society, and to map their narrative trajectories (utopian, dystopian). The qualitative analysis uses the categories of agency, sentiment, point of view, and news value to capture these outlets’ contributions to the evolving sociotechnical imaginary of AI technologies. While acknowledging some risks of AI technologies, elite commercial science journalism highlights the benefits and celebrates the scientific advancements produced with or by AI. Also, AI technologies are communicated strategically to increase newsworthiness, through diverse complications in storylines with oscillating sentiments and a focus on impacts and novelty. This tends to prime news recipients to accept the inevitable technological progress and normalizes algorithms as increasingly independent research-performing agents.
{"title":"Story-ing AI – mini-narrative patterns of contemporary online science journalism","authors":"Katarzyna Molek-Kozakowska","doi":"10.1177/17504813241266903","DOIUrl":"https://doi.org/10.1177/17504813241266903","url":null,"abstract":"This study explores the range of discursive patterns used to present artificial intelligence as a revolutionary but controversial technology in online science journalism. It uses a triangulated dataset of over a hundred recent mini-narratives sourced from New Scientist, Nature daily briefings, and Scientific American to reconstruct typical storylines in the thematic domains of research, business, and society, and to map their narrative trajectories (utopian, dystopian). The qualitative analysis uses the categories of agency, sentiment, point of view, and news value to capture these outlets’ contributions to the evolving sociotechnical imaginary of AI technologies. While acknowledging some risks of AI technologies, elite commercial science journalism highlights the benefits and celebrates the scientific advancements produced with or by AI. Also, AI technologies are communicated strategically to increase newsworthiness, through diverse complications in storylines with oscillating sentiments and a focus on impacts and novelty. This tends to prime news recipients to accept the inevitable technological progress and normalizes algorithms as increasingly independent research-performing agents.","PeriodicalId":46726,"journal":{"name":"Discourse & Communication","volume":"4 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141772239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-25DOI: 10.1177/17504813241265572
Jinyan Li, Shuqiong Wu
{"title":"Book review: Othman Khalid Al-Shboul, The Politics of Climate Change Metaphors in the U.S. Discourse: Conceptual Metaphor Theory and Analysis from an Ecolinguistics and Critical Discourse Analysis Perspective","authors":"Jinyan Li, Shuqiong Wu","doi":"10.1177/17504813241265572","DOIUrl":"https://doi.org/10.1177/17504813241265572","url":null,"abstract":"","PeriodicalId":46726,"journal":{"name":"Discourse & Communication","volume":"26 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141772240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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