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

Winfield, Alan F. T.; Michael, Katina; Pitt, Jeremy; Evers, Vanessa

doi:10.1109/jproc.2019.2900622

Cited by 145 publications

(99 citation statements)

References 42 publications

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“…Alongside other domains [136], it is crucial that research in Industrial Electronics focuses on the design, development and deployment of AI that is responsible, safe and ethical [137]. It is imperative that future research initiatives establish an ethics policy, guidelines and standards for Industrial Informatics that ensure AI-based insights, feedback, control and decisions are safe, reliable and accountable [138].…”

Section: A Advances In Researchmentioning

confidence: 99%

Toward Intelligent Industrial Informatics: A Review of Current Developments and Future Directions of Artificial Intelligence in Industrial Applications

Silva

Sierla

Alahakoon

et al. 2020

EEE Ind. Electron. Mag.

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Research, the universal pursuit of new knowledge, is embarking on a fresh journey into Artificial Intelligence (AI). Nature reports that AI arose nine places to fourth most popular search-term, and that search-terms machine-learning and deep-learning appeared in the top-20 search for the first time in 2018. It is pertinent for Industrial Informatics to embrace this renewed surge of interest in AI with clear direction and purpose that engages scholars, practitioners and professionals alike. This article aims to

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Section: A Advances In Researchmentioning

confidence: 99%

Toward Intelligent Industrial Informatics: A Review of Current Developments and Future Directions of Artificial Intelligence in Industrial Applications

Silva

Sierla

Alahakoon

et al. 2020

EEE Ind. Electron. Mag.

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“…Ethical concerns commonly associated with robots and other artificially intelligent systems programmed with AI are typically divided into two groups: (1) the moral behaviour of humans as they design, construct, use, and treat artificially intelligent beings, and 2 Winfield et al 2019;Université de Montreal 2018). In this paper we focus on the first group, given that the presence of AMAs in citizen science is currently very limited.…”

Section: Risks Explorationmentioning

confidence: 99%

Opportunities and Risks for Citizen Science in the Age of Artificial Intelligence

Ceccaroni

Bibby

Roger

et al. 2019

Citizen Science: Theory and Practice

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Introduction Technologies that allow computers and machines to perform tasks normally requiring human intelligence are often referred to as artificial intelligence (AI). These technologies allow machines to complete tasks with traits or capabilities ordinarily associated with human cognition, such as reasoning, problem solving, common-sense knowledge management, planning, learning, translation, perception, vision, speech recognition, and social intelligence (Kaplan and Haenlein 2019). Research in AI is rapidly increasing, as indicated when c omparing the annual publishing rate of papers focused on AI between 1996 and 2017 against the publishing rates of papers focused on any topic or against the publishing rates of papers in the field of computer science (see the growth of annually published papers by topic in Shoham et al. [2018; p. 9]). This growth in AI publications has prompted researchers to critically explore the potential promises and risks of AI (Scherer 2016; Webb 2019; Yudkowsky 2008) as well as ethics and responsibilities (Miller 2019; Cowls and Floridi 2018; Scherer 2016; Dawson et al. 2019). AI has been used in citizen science projects for about 20 years. It was first used in this context in 2000, in collaborative AI databases such as the Generic Artificial Consciousness (GAC)/Mindpixel Digital Mind Modeling Project (McKinstry 2009) and the Open Mind Common Sense project (Singh et al. 2002). In these models, usersubmitted propositions were meant to create a database of common-sense knowledge that could function as a kind of digital brain. This relationship between collective knowledge and algorithmic processing evolved in many directions and, in 2019, is predominantly represented by machine learning, especially applied to computer vision, which includes diverse methods of automatically identifying objects from digital photographs. For example, the iNaturalist platform, a citizen science project and online social network, is designed to enable citizen scientists and ecologists alike to upload observations from the natural world, such as images of animals and plants (Van Horn et al. 2018). The platform is one among many (Wäldchen et al. 2018) that include an automated

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“…Por fim, questões ético-legais podem surgir através da capacidade de decisão de máquinas inteligentes (TADDEO;FLORIDI, 2018;WINFIELD et al, 2019), representadas pelo risco de última posição…”

Section: Perspectiva Socialunclassified

Um Estudo Quantitativo Sobre Os Riscos Da Indústria 4.0 No Contexto Industrial: Uma Revisão Sistemática Da Literatura

Soltovski

Resende

Pontes

et al. 2020

RGD

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RESUMOA Indústria 4.0 é um tema em ascensão tanto no meio acadêmico como no contexto prático de empresas. As pesquisas atuais focam seus esforços nos estudos dos benefícios dos conceitos e tecnologias envolvidos no conceito da Quarta Revolução Industrial, no entanto, poucas procuram entender quais os pontos negativos. Dessa forma, através de uma revisão bibliográfica sistematizada realizada em janeiro de 2019, esse estudo procura entender quais são riscos em evidência na literatura que empresas do setor industrial podem enfrentar no contexto da Indústria 4.0. Foram selecionados 66 artigos através das bases de dados Scopus e Web of Science, os quais foram bibliometricamente estudados em relação aos autores e periódicos mais relevantes. Em seguida, estudando os 28 riscos mapeados na literatura por Soltovski et al. (2019), foi possível entender quais são mais representativos na literatura na perspectiva da sustentabilidade (ambiental, econômico e social) e na perspectiva tecnológica. De forma geral, descobrimos que os riscos relacionados à conectividade, como cyber atacks e vazamento de dados privados através de tecnologias, como Internet das Coisas, são os mais discutidos na literatura. Além disso, constatamos que existe carência de estudos na perspectiva ambiental e econômica. Por fim, foram sumarizadas contribuições gerenciais e potenciais direcionamentos para futuros pesquisadores.Palavras-chave: Indústria 4.0. Sustentabilidade. Gestão de Risco. ABSTRACTIndustry 4.0 is a growing topic, both in academia and in the practical context of companies. Current research focuses its efforts on studies of benefits and technologies involved in the concept of the Fourth Industrial Revolution, however, they rarely understand what the negative points are. Thus, through a systematic literature review conducted in January 2019, this study can understand what are the risks in evidence in the literature that companies in the industrial sector may face in the context of Industry 4.0. 66 articles were selected on the Scopus and Web of Science databases, which are the bibliometrically studied in relation to the most relevant authors and journals. Then, studying the 28 risks mapped in the literature by Soltovski et al. (2019), it was possible to understand which are the most representative in the literature from the perspective of sustainability (environmental, economic and social) and from a technological perspective. In general, we found that risks related to connectivity such as cyber attacks and data leakage are using technologies like the Internet of Things that are most discussed in the literature. In addition, we note that there is a lack of studies from an environmental and economic perspective. Finally, managerial contributions were summarized and directed to future researchers.Keywords: Industry 4.0. Sustainability. Risk Management.

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

Cited by 145 publications

References 42 publications

Toward Intelligent Industrial Informatics: A Review of Current Developments and Future Directions of Artificial Intelligence in Industrial Applications

Toward Intelligent Industrial Informatics: A Review of Current Developments and Future Directions of Artificial Intelligence in Industrial Applications

Opportunities and Risks for Citizen Science in the Age of Artificial Intelligence

Um Estudo Quantitativo Sobre Os Riscos Da Indústria 4.0 No Contexto Industrial: Uma Revisão Sistemática Da Literatura

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