Understanding Human-Machine Networks

Tsvetkova, Milena; Yasseri, Taha; Meyer, Eric T.; Pickering, J. Brian; Engen, Vegard; Walland, Paul; Lüders, Marika; Følstad, Asbjørn; Bravos, George

doi:10.1145/3039868

Cited by 56 publications

(31 citation statements)

References 228 publications

(202 reference statements)

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“…Reasons for regulations to be constrictive may be to, e.g., address concerns regarding the increasing autonomy of machines [2], raising ethical issues about responsibilities and accountability [59]. Thus, we hypothesise:…”

Section: H1amentioning

confidence: 99%

“…A definition of agency based on the notion of non-deterministic behaviours [1] fails to recognise the increasing variety and complexity of human-machine networks 1 (HMNs) [2], the intention of technology designers [3], and active intervention by bots within social networks [4,5]. The concept of agency is particularly problematic in human-machine interactions [6].…”

Section: Introductionmentioning

confidence: 99%

“…Since human-machine networks can be characterised by independently varying levels of agency [2], either or both may influence selfefficacy [18]. Further, introducing regulation and perceived risk [32], how these influence agency and, in turn, behaviours within an HMN, need consideration [33,34].…”

Section: Introductionmentioning

confidence: 99%

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The Interplay Between Human and Machine Agency

Pickering

Engen

Walland

2017

Lecture Notes in Computer Science

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Abstract. Human-machine networks affect many aspects of our lives: from sharing experiences with family and friends, knowledge creation and distance learning, and managing utility bills or providing feedback on retail items, to more specialised networks providing decision support to human operators and the delivery of health care via a network of clinicians, family, friends, and both physical and virtual social robots. Such networks rely on increasingly sophisticated machine algorithms, e.g., to recommend friends or purchases, to track our online activities in order to optimise the services available, and assessing risk to help maintain or even enhance people's health. Users are being offered ever increasing power and reach through these networks by machines which have to support and allow users to be able to achieve goals such as maintaining contact, making better decisions, and monitoring their health. As such, this comes down to a synergy between human and machine agency in which one is dependent in complex ways on the other. With that agency questions arise about trust, risk and regulation, as well as social influence and potential for computer-mediated self-efficacy. In this paper, we explore these constructs and their relationships and present a model based on review of the literature which seeks to identify the various dependencies between them. IntroductionA definition of agency based on the notion of non-deterministic behaviours [1] fails to recognise the increasing variety and complexity of human-machine networks 1 (HMNs) [2], the intention of technology designers [3], and active intervention by bots within social networks [4,5]. The concept of agency is particularly problematic in human-machine interactions [6]. Machine or material agency may be seen as automation, which originally required some tolerance from human agents [7]. But this is no longer true: technology can actively support human activity [8], and manifests increasingly complex interaction types [9]. Machine and human agency may not be the same and yet equally valid [10]; machine agency may be just "perceived autonomy" [11]; and it 1 In the following we use human-machine network and network interchangeably.certainly enables human agency [12]. Indeed, agency may well be becoming a social and group construct where both humans and machines play a part [13,14]; and used effectively, agency may even lead to innovative review of working practice [15].The enabling contribution of machine agents within a network may have an effect on self-efficacy. Bandura's original definition of self-efficacy as an individual's belief in their ability to be able to achieve a given objective [16][17][18] has also been applied to technology [19,20] and its acceptance [21]. There are, however, constraints on the support and positive contribution of technology to human self-efficacy, not least in terms of anxiety and suspicion around technology use [22,23]. This may be further exacerbated by increasing machine animism: it may not always be obvious what machines ar...

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Section: H1amentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Interplay Between Human and Machine Agency

Pickering

Engen

Walland

2017

Lecture Notes in Computer Science

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“…Os observatórios Web são um meio dedicado ao monitoramento de fatos, eventos e entidades essenciais na rede mundial de computadores, esses observatórios estão presentes nos trabalhos de (ROURE, et al, 2013;KLEEL, et al, 2014;TINATI, et al, 2015;HALCROW;HALFORD, 2016;MADAAN, et al, 2016;HALL, 2017;HARRIS;. Em outros trabalhos além do observatório, são utilizadas pesquisas com computação colaborativa, cooperação humana ou crowdsourcing, vistos em (KLEEL, et al, 2013;KAJAN, 2017;GRIMPE;JIROTKA, 2013;WANG, et al, 2017;BRAMBILLA, et al, 2014;BRAMBILLA, et al, 2015;TSVETKOVA, et al, 2017;KLEIN, 2014 3) Privacidade e Dados Pessoais: algumas das principais preocupações de todas as pessoas que trabalham envolvidas de alguma forma com sistemas, diz respeito à privacidade dos usuários, especialmente quando os dados são compartilhados. Muitos trabalhos discutem a confidencialidade dos dados pessoais e suas propriedades em uso com as máquinas sociais.…”

Section: Figura 1 Tipos De Contribuições De Todos Os Artigosunclassified

Um estudo de mapeamento das contribuições e desafios de pesquisa em máquinas sociais

Silva

Burégio

2018

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ResumoO campo das máquinas sociais ainda é uma área nova, sem uma definição que tenha o senso comum dos pesquisadores, isso cria algumas dificuldades para entender qual o conceito, ou qual projeto de máquinas sociais devemos escolher. Este trabalho tem como objetivo investigar de forma detalhada, os trabalhos apresentados nas oficinas de máquinas sociais e nas principais bases de dados, a partir desta análise criamos um mapa de estudo, um esquema de categorização das obras e também gráficos de bolhas entre as categorizações. Foi produzido panorama da área de máquinas sociais, através da identificação dos principais tópicos, tipos, tendências e desafios através desta pesquisa preliminar, além de definir a maturidade das contribuições existentes. Este trabalho fornece uma base conceitual para a compreensão da área e também detecta os problemas de pesquisa e lacunas existentes no campo das máquinas sociais. Palavras-chave:Máquinas sociais, Caracterização, Mapeamento. AbstractThe field of social machines is still a new area, without a definition that has the common sense of researchers, this creates some difficulties to understand which concept, or which social machine project we should choose. This work aims to investigate in detail the work presented in the social machine workshops and in the main databases, from this analysis we create a study map, a categorization scheme of the works and also graphs of bubbles between the categorizations. It was produced a landscape of the area of social machines, was by identifying the main topics, types, trends and challenges through this preliminary research, as well as defining the maturity of existing contributions. This paper provides a conceptual basis for understanding the area and also detects research problems and gaps in the field of social machines.Esta obra está licenciada sob uma Licença Creative Commons Attribution 3.0. Introdução às Máquinas SociaisDe acordo com BURÉGIO, MEIRA e ROSA (2013), hoje em dia cada vez mais, os meios de computação são utilizados para conectar as pessoas, seja com outras pessoas ou com as máquinas, essa filosofia de conexão mudou a semântica da computação. É interessante salientar que a internet é composta por um conjunto gigantesco de coisas, formada por elementos concretos e abstratos, entre essas coisas se destacam, por exemplo: humanos, máquinas, informações, tecnologias, padrões, regras, governos e outros, sendo que tudo está em constante evolução

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“…Automation correctly thought out will therefore support and enhance human agency, but also introduce a collaborative interplay on the basis of what different actor types do well. In the case of the machines, this does go beyond simply increasing the amount and speed in which data can be processed as seen in the above case studies and recent literature (Tsvetkova et al, 2017), being able to solve increasingly complex data analytics problems. This ultimately provides an opportunity for innovation and emergent behaviours as we will describe in the following section.…”

Section: Strengthening the Synergy Between Machine And Human Actors Tmentioning

confidence: 99%

Automation in Human-Machine Networks: How Increasing Machine Agency Affects Human Agency

Følstad

Engen

Haugstveit

et al. 2017

Advances in Intelligent Systems and Computing

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Efficient human-machine networks require productive interaction between human and machine actors. In this study, we address how a strengthening of machine agency, for example through increasing levels of automation, affect the human actors of the networks. Findings from case studies within air traffic management, crisis management, and crowd evacuation are presented, exemplifying how automation may strengthen the agency of human actors in the network through responsibility sharing and task allocation, and serve as a needed prerequisite of innovation and change.

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Understanding Human-Machine Networks

Cited by 56 publications

References 228 publications

The Interplay Between Human and Machine Agency

The Interplay Between Human and Machine Agency

Um estudo de mapeamento das contribuições e desafios de pesquisa em máquinas sociais

Automation in Human-Machine Networks: How Increasing Machine Agency Affects Human Agency

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