Recommender systems and their ethical challenges

Milano, Silvia; Taddeo, Mariarosaria; Floridi, Luciano

doi:10.1007/s00146-020-00950-y

Cited by 223 publications

(138 citation statements)

References 37 publications

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“…The methods applied in this study consist of systematic literature review, taxonomies derived and follows existing research studies on this topic that apply literature review with taxonomy [5], in pursuit of narratives [6]. Academic literature and practical studies are consulted intensively to discuss the IoT technologies and their relation to the I4.0.…”

Section: Methodsmentioning

confidence: 99%

Artificial intelligence in cyber physical systems

Radanliev

Roure

Kleek

et al. 2020

Preprint

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This article conducts a literature review of current and future challenges in the use of artificial intelligence (AI) in cyber physical systems. The literature review is focused on identifying a conceptual framework for increasing resilience with AI through automation supporting both, a technical and human level. The methodology applied resembled a literature review and taxonomic analysis of complex internet of things (IoT) interconnected and coupled cyber physical systems. There is an increased attention on propositions on models, infrastructures and frameworks of IoT in both academic and technical papers. These reports and publications frequently represent a juxtaposition of other related systems and technologies (e.g. Industrial Internet of Things, Cyber Physical Systems, Industry 4.0 etc). We review academic and industry papers published between 2010 and 2020. The results determine a new hierarchical cascading conceptual framework for analysing the evolution of AI decision-making in cyber physical systems. We argue that such evolution is inevitable and autonomous because of the increased integration of connected devices (IoT) in cyber physical systems. To support this argument, taxonomic methodology is adapted and applied for transparency and justifications of concepts selection decisions through building summary maps that are applied for designing the hierarchical cascading conceptual framework.

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Section: Methodsmentioning

confidence: 99%

Artificial intelligence in cyber physical systems

Radanliev

Roure

Kleek

et al. 2020

Preprint

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“…The methods applied in this study consist of systematic literature review, taxonomies derived and follows existing research studies on this topic that apply literature review with taxonomy (Milano et al 2020), in pursuit of narratives (O'Hara 2020). Academic literature and practical studies are consulted intensively to discuss the IoT technologies and their relation to the I4.0.…”

Section: Methodsmentioning

confidence: 99%

Artificial Intelligence in Cyber Physical Systems

Radanliev¹,

Roure

Kleek

et al. 2020

SSRN Journal

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This article conducts a literature review of current and future challenges in the use of artificial intelligence (AI) in cyber physical systems. The literature review is focused on identifying a conceptual framework for increasing resilience with AI through automation supporting both, a technical and human level. The methodology applied resembled a literature review and taxonomic analysis of complex internet of things (IoT) interconnected and coupled cyber physical systems. There is an increased attention on propositions on models, infrastructures and frameworks of IoT in both academic and technical papers. These reports and publications frequently represent a juxtaposition of other related systems and technologies (e.g. Industrial Internet of Things, Cyber Physical Systems, Industry 4.0 etc.). We review academic and industry papers published between 2010 and 2020. The results determine a new hierarchical cascading conceptual framework for analysing the evolution of AI decision-making in cyber physical systems. We argue that such evolution is inevitable and autonomous because of the increased integration of connected devices (IoT) in cyber physical systems. To support this argument, taxonomic methodology is adapted and applied for transparency and justifications of concepts selection decisions through building summary maps that are applied for designing the hierarchical cascading conceptual framework.

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“…While there have been discussions on the ethics of recommender systems and personalization (Bozdag & Timmermans, 2011;Helberger, 2019;Milano et al, 2020), and on how to fulfill main algorithmic principles such as fairness, transparency, accountability, accuracy, and privacy (algo:aware, 2018), in this hypothetical radical scenario, algorithms could even be exchanged, remixed, tested, plugged, and even sold or rented. On top of this opening, it is expected that not all users would have the knowledge to build their own algorithms.…”

Section: Algorithmic Sovereignty In Theorymentioning

confidence: 99%

Thinking Outside the Black-Box: The Case for “Algorithmic Sovereignty” in Social Media

Reviglio

Agosti

2020

Social Media + Society

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This article is an interdisciplinary critical analysis of personalization systems and the gatekeeping role of current mainstream social media. The first section presents a literature review of data-driven personalization and its challenges in social media. The second section sheds light on increasing concerns regarding algorithms’ ability to overtly persuade—and covertly manipulate—users for the sake of engagement, introducing the emergence of the exclusive ownership of behavioral modification through hyper-nudging techniques. The third section empirically analyzes users’ expectations and behaviors regarding such data-driven personalization to frame a conceptualization of users’ agency. The fourth section introduces the concept of “algorithmic sovereignty.” Current projects that aim to grant this algorithmic sovereignty highlight some potential applications. Together this novel theoretical framework and empirical applications suggest that, to preserve trust, social media should open their personalization algorithms to a social negotiation as the first step toward a more sustainable social media landscape. To decentralize the immense power of mainstream social media, guarantee a democratic oversight, and mitigate the unintended undesirable consequences of their algorithmic curation, public institutions and civil society could help in developing and researching public algorithms, fostering a collective awareness so as to eventually ensure a fair and accountable “algorithmic sovereignty.”

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Recommender systems and their ethical challenges

Cited by 223 publications

References 37 publications

Artificial intelligence in cyber physical systems

Artificial intelligence in cyber physical systems

Artificial Intelligence in Cyber Physical Systems

Thinking Outside the Black-Box: The Case for “Algorithmic Sovereignty” in Social Media

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