Hopes and fears for intelligent machines in fiction and reality

Cave, Stephen; Dihal, Kanta

doi:10.1038/s42256-019-0020-9

Cited by 193 publications

(94 citation statements)

References 13 publications

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“…However, it is worth also considering power separately, because power struggles between AI and humans are such a common narrative trope. Alongside the narrative that robots will make humans redundant, an equally well-known narrative is that they will rise up and conquer us altogether (Cave and Dihal 2019). These are both narratives about machines becoming superior to humans: stories in which they become better at every task, leaving humans with nothing to do, from E.M. Forster's 1909 short story 'The Machine Stops' to the Oscar-winning film WALL-E, or in which they outwit and subjugate those who built them, as in the Terminator film franchise or the film Ex Machina (Forster 1909;Stanton 2008;Cameron 1984;Garland 2015).…”

Section: Ai and The Attributes Of Whitenessmentioning

confidence: 99%

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The Whiteness of AI

2020

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This paper focuses on the fact that AI is predominantly portrayed as white—in colour, ethnicity, or both. We first illustrate the prevalent Whiteness of real and imagined intelligent machines in four categories: humanoid robots, chatbots and virtual assistants, stock images of AI, and portrayals of AI in film and television. We then offer three interpretations of the Whiteness of AI, drawing on critical race theory, particularly the idea of the White racial frame. First, we examine the extent to which this Whiteness might simply reflect the predominantly White milieus from which these artefacts arise. Second, we argue that to imagine machines that are intelligent, professional, or powerful is to imagine White machines because the White racial frame ascribes these attributes predominantly to White people. Third, we argue that AI racialised as White allows for a full erasure of people of colour from the White utopian imaginary. Finally, we examine potential consequences of the racialisation of AI, arguing it could exacerbate bias and misdirect concern.

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Section: Ai and The Attributes Of Whitenessmentioning

confidence: 99%

“…One of the most pertinent hopes for artificial intelligence is that it will lead to a life of ease (Cave and Dihal 2019). As a tool that can take over "dirty, dull, or dangerous" jobs, it relieves its owners from work they do not want to do, enabling them to pursue leisure.…”

Section: White Utopiamentioning

confidence: 99%

The Whiteness of AI

2020

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“…Foremost, research has shown that the members of the general public have low understanding of AI in general, alongside AI-specific hopes and fears including loss of control of AI, ethical concerns and the potential negative impact of AI on work. [14][15][16][17][18] Second, while there is general trend toward support for health AI, 19 there is also recent negative press about large technology companies using health data for AI, including patients suing Google and the University of Chicago Medical Center 20 and the view of the National Data Guardian at the UK's Department of Health that the sharing of patient data between the Royal Free Hospital of London and Google DeepMind was legally inappropriate. 21 Third, there is decreasing confidence that accepted approaches to de-identification are sufficient to ensure privacy in the face of AI's capabilities.…”

Section: Open Accessmentioning

confidence: 99%

Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research

2020

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ObjectivesGiven widespread interest in applying artificial intelligence (AI) to health data to improve patient care and health system efficiency, there is a need to understand the perspectives of the general public regarding the use of health data in AI research.DesignA qualitative study involving six focus groups with members of the public. Participants discussed their views about AI in general, then were asked to share their thoughts about three realistic health AI research scenarios. Data were analysed using qualitative description thematic analysis.SettingsTwo cities in Ontario, Canada: Sudbury (400 km north of Toronto) and Mississauga (part of the Greater Toronto Area).ParticipantsForty-one purposively sampled members of the public (21M:20F, 25–65 years, median age 40).ResultsParticipants had low levels of prior knowledge of AI and mixed, mostly negative, perceptions of AI in general. Most endorsed using data for health AI research when there is strong potential for public benefit, providing that concerns about privacy, commercial motives and other risks were addressed. Inductive thematic analysis identified AI-specific hopes (eg, potential for faster and more accurate analyses, ability to use more data), fears (eg, loss of human touch, skill depreciation from over-reliance on machines) and conditions (eg, human verification of computer-aided decisions, transparency). There were mixed views about whether data subject consent is required for health AI research, with most participants wanting to know if, how and by whom their data were used. Though it was not an objective of the study, realistic health AI scenarios were found to have an educational effect.ConclusionsNotwithstanding concerns and limited knowledge about AI in general, most members of the general public in six focus groups in Ontario, Canada perceived benefits from health AI and conditionally supported the use of health data for AI research.

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“…SinceČapek's 1920 play Rossum's Universal Robots, and the stories of Asimov, Frayn [10] and many others, science fiction narratives have played a key role in the exploration of artificial morality [11]. In the study of machine ethics we can, for the first time, begin to investigate artificial morality in fact.…”

Section: T H E L a N D S C A P E O F R O B O T A N D A I E T H I C Smentioning

confidence: 99%

Machine Ethics: The Design and Governance of Ethical AI and Autonomous Systems [Scanning the Issue]

Winfield¹,

Michael²,

Pitt³

et al. 2019

Proc. IEEE

153

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The so-called fourth industrial revolution and its economic and societal implications are no longer solely an academic concern, but a matter for political as well as public debate. Characterized as the convergence of robotics, AI, autonomous systems and information technology-or cyber-physical systems-the fourth industrial revolution was the focus of the World Economic Forum, at Davos, in 2016 [1]. Also in 2016 the US White House initiated a series of public workshops on artificial intelligence (AI) and the creation of an interagency working group, and the European Parliament Committee for Legal Affairs published a draft report with recommendations to the Commission on Civil Law Rules on Robotics.

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Hopes and fears for intelligent machines in fiction and reality

Cited by 193 publications

References 13 publications

The Whiteness of AI

The Whiteness of AI

Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research

Machine Ethics: The Design and Governance of Ethical AI and Autonomous Systems [Scanning the Issue]

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