Intersectional Inquiry, on the Ground and in the Algorithm

Robertson, Shanthi; Magee, Liam; Soldatić, Karen

doi:10.1177/10778004221099560

Cited by 3 publications

(1 citation statement)

References 49 publications

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“…Such prompts may themselves be toxic or biased or problematic, as in the case of Microsoft Tay AI which developed racist tendencies after only one day of user prompts (Vincent 2016). Yet even without overt bigotry, every prompt is based on the specific ideologies of users, their social and cultural background, and their set of inherent and underlying prejudices (Robertson et al 2022). For instance, GPT-3 and InstructGPT employed a sign-up and waiting list to provide accessand only those aware of this technology would have known to register for access.…”

Section: Prompting As Further Trainingmentioning

confidence: 99%

Truth Machines: Synthesizing Veracity in AI Language Models

Munn¹,

Magee²,

Arora³

2023

Preprint

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As AI technologies are rolled out into healthcare, academia, human resources, law, and a multitude of other domains, they become de-facto arbiters of truth. But truth is highly contested, with many different definitions and approaches. This article discusses the struggle for truth in AI systems and the general responses to date. It then investigates the production of truth in InstructGPT, a large language model, highlighting how data harvesting, model architectures, and social feedback mechanisms weave together disparate understandings of veracity. It conceptualizes this performance as an operationalization of truth, where distinct, often conflicting claims are smoothly synthesized and confidently presented into truth-statements. We argue that these same logics and inconsistencies play out in Instruct's successor, ChatGPT, reiterating truth as a non-trivial problem. We suggest that enriching sociality and thickening "reality" are two promising vectors for enhancing the truth-evaluating capacities of future language models. We conclude, however, by stepping back to consider AI truth-telling as a social practice: what kind of "truth" do we as listeners desire?

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Section: Prompting As Further Trainingmentioning

confidence: 99%

Truth Machines: Synthesizing Veracity in AI Language Models

Munn¹,

Magee²,

Arora³

2023

Preprint

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Sensing technologies, digital inclusion, and disability diversity

Nectoux,

Magee,

Soldatic

2023

Journal of Computer-Mediated Communication

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This article focuses on uses and experiences of everyday sensory technologies by racially and ethnically diverse persons with disabilites, bringing our research to the junction of critical technology studies, migration studies, and critical disability studies. We draw on a large-scale qualitative project that involves new and second-generation migrants with disabilities from a socio-economically disadvantaged area in Sydney, Australia. Findings show the negotiated exchanges of inclusion and exclusion that disabled people from diverse racial and ethnic minority backgrounds encounter with sensory and other technologies. While such technologies have rightfully been criticized for their roles in the surveillance, regulation, exclusion, and financialization of disability and ethnically diverse groups, these negotiations show how processes of agency, awareness, and peer support produce and in turn benefit from encounters with technology in complex ways. We argue the continued emergence of automation warrants both critique and cautious ongoing experimentation.

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Health Equity and Health Inequity of Disabled People: A Scoping Review

Wolbring,

Deloria

2024

Sustainability

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Health equity is an important aspect of wellbeing and is impacted by many social determinants. The UN Convention on the Rights of Persons with Disabilities (CRPD) is a testament to the lack of health equity and the many health inequity issues based on social determinants experienced by disabled people. The health equity/health inequity situation of disabled people is even worse if their identities intersect with those of other marginalized groups. Many societal developments and discussions including discussions around the different sustainability pillars can influence the health equity/health inequity of disabled people. The general aim of this study was to better understand the academic engagement with the health equity and health inequity of disabled people beyond access to healthcare. To fulfill our aim, we performed a scoping review of academic abstracts using a hit count manifest coding and content analysis approach to abstracts obtained from SCOPUS, the 70 databases of EBSCO-HOST, Web of Science, and PubMed. Health equity and health inequity abstracts rarely cover disabled people as a group, less with many specific groups of disabled people, and even less or not at all with the intersectionality of disabled people belonging to other marginalized groups. Many social determinants that can influence the health equity and health inequity of disabled people were not present. Ability-based concepts beyond the term ableism, intersectionality-based concepts, and non-health based occupational concepts were not present in the abstracts. Our qualitative content analysis of the 162 abstracts containing health equity and disability terms and 177 containing health inequity and disability terms found 65 relevant abstracts that covered problems with health equity disabled people face, 17 abstracts covered factors of health inequity, and 21 abstracts covered actions needed to deal with health inequity. Our findings suggest a need as well as many opportunities for academic fields and academic, policy, and community discussions to close the gaps in the coverage of health equity and health inequity of disabled people.

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Intersectional Inquiry, on the Ground and in the Algorithm

Cited by 3 publications

References 49 publications

Truth Machines: Synthesizing Veracity in AI Language Models

Truth Machines: Synthesizing Veracity in AI Language Models

Sensing technologies, digital inclusion, and disability diversity

Health Equity and Health Inequity of Disabled People: A Scoping Review

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