Artifictional intelligence: against humanity’s surrender to computers

Gill, Karamjit S.

doi:10.1007/s00146-018-0873-1

Cited by 11 publications

(12 citation statements)

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“…While our research does not report proven deviance by the governments of these countries in the use of AI, we believe, based on the work of authors such as Collins (2018), O'Neil (2017), Noble (2018), Benjamin (2019), Broussard (2019), Köchling and Wehner (2020), and Brayne (2021), that the presence of these conditions indicates a high risk of deviance in the not‐too‐distant future. Our findings, therefore, invite further reflection, including how to assess the risk of deviances and how governments can implement informed solutions that prevent it.…”

Section: Discussionmentioning

confidence: 73%

Ready but irresponsible? Analysis of the Government Artificial Intelligence Readiness Index

Nzobonimpa,

Savard

2023

Policy & Internet

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Many are the promises of artificial intelligence (AI) and algorithms. Governments around the world are increasingly investing in AI and multiple voices have touted this seemingly unmatched revolution. Better performance, cost reduction, efficient management, crime prediction, and prevention are but a few of the pledges of the AI era. While such promises are recognized, research shows that AI benefits could be overstated. Issues of equity, ethics, justice, and fairness have raised concerns and have been seen as potentially threatening democratic principles. As countries get ready to tap into the AI power, researchers are asking whether preparedness is followed by responsibility checks. In this article, we use the Oxford Insights AI Readiness Index to explore why innovation and readiness in artificial intelligence are not always accompanied by accountability, even for some of the most advanced democracies around the world. Using the Fuzzy‐Set Qualitative Comparative Analysis (fsQCA) approach, we show that advancement in AI is not enough: privacy, transparency, inclusion, and accountability principles are key to ensuring governments tackle the AI challenge responsibly.

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Section: Discussionmentioning

confidence: 73%

Ready but irresponsible? Analysis of the Government Artificial Intelligence Readiness Index

Nzobonimpa,

Savard

2023

Policy & Internet

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“…Collins's 2015 study was aimed at explaining one of the reasons that artificially intelligent computers could not mimic the information transmission of human scientists, thus bringing sociology of scientific knowledge into the realm of AI. The results were first published as Chapter 8 in H. Collins (2018b). 15.…”

Section: Discussionmentioning

confidence: 99%

“…21. More material from the Budapest interviews will be found in Chapter 8 of H. Collins (2018b). 22.…”

Section: Discussionmentioning

confidence: 99%

Scientific conferences, socialization, and the Covid-19 pandemic: A conceptual and empirical enquiry

2023

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Since the 1970s social analysts have seen communication between scientists not solely as information exchange (the algorithmical model), but as a process of socialization into overlapping and mutually embedded scientific domains (the enculturational model). Under the algorithmical model, the impact of the Covid-19 shutdown on travel would be easily remedied by replacing face-to-face communication with online platforms. Conferences and similar gatherings are costly, elitist, and environmentally damaging, but under the enculturational model abandoning them could be disastrous for science, which depends on the development of cross-national trust and mutual agreements through face-to-face interaction and, in turn, disastrous for science’s role in democracy. We explore the problem theoretically and empirically, arguing against recent proposals from some scientists for the wholesale and permanent replacement of conferences with remote communication.

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“…For example, sociologists and philosophers have argued that, however impressive they are in terms of making predictions, ML systems possess no intelligence or meaning in any recognisable human form. This is partially due to their failure to properly understand context, which is a function of their inability to handle language fully (Collins, 2018), and, according to classical phenomenological critiques (Dreyfus, 1967), due to these machines' lack of bodies. As a result, researchers have warned against using anthropomorphising language when discussing ML systems.…”

Section: Machine Learning's Challenge To Sociologymentioning

confidence: 99%

Machine Learning and Postcolonial Critique: Homologous Challenges to Sociological Notions of Human Agency

Borch

2023

Sociology

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This article discusses two seemingly unrelated but homologous challenges to established sociological thinking, namely machine learning technologies and postcolonial critique. Both of these confront conventional human-centric sociological notions. Where the rise of machine learning should prompt sociologists to take the agency of nonhuman systems seriously, postcolonial critique challenges the idea of Eurocentric human agency. I discuss whether this dual agency challenge can be addressed through Latour’s actor-network theory and Luhmann’s sociological systems theory – both of which explicitly aim to transcend classical human-centric approaches. I argue that Latour’s work can align with postcolonial sociology. However, despite broadening the notion of agency, his actor-network concept remains strongly human-centric. It merely expands the range of actors with which humans engage rather than analysing interactions among nonhuman actants, such as machine learning systems. In contrast, such interactions can be understood through Luhmann’s theorisation, which, however, can be subjected to postcolonial critique.

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Artifictional intelligence: against humanity’s surrender to computers

Cited by 11 publications

References 1 publication

Ready but irresponsible? Analysis of the Government Artificial Intelligence Readiness Index

Ready but irresponsible? Analysis of the Government Artificial Intelligence Readiness Index

Scientific conferences, socialization, and the Covid-19 pandemic: A conceptual and empirical enquiry

Machine Learning and Postcolonial Critique: Homologous Challenges to Sociological Notions of Human Agency

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