The DOI matches its Crossref record; 43 of the 45 references it cites were found in a registry or an index.
The social power of algorithms
Open accessAbstract
This article explores the questions associated with what might be thought of as the social power of algorithms. The article, which introduces a special issue on the same topic, begins by reflecting on how we might approach algorithms from a social scientific perspective. The article is then split into two sections. The first deals with the issues that might be associated with an analysis of the power of the algorithms themselves. This section outlines a series of issues associated with the functionality of the algorithms and how these functions are powerfully deployed within social world. The second section then focuses upon the notion of the algorithm. In this section, the article argues that we need to look beyond the algorithms themselves, as a technical and material presence, to explore how the notion or concept of the algorithm is also an important feature of their potential power. In this section, it is suggested that we look at the way that notions of the algorithm are evoked as a part of broader rationalities and ways of seeing the world. Exploring the notion of the algorithm may enable us to see how algorithms also play a part in social ordering processes, both in terms of how the algorithm is used to promote certain visions of calculative objectivity and also in relation to the wider governmentalities that this concept might be used to open up.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“When professionals cannot analyze the reasoning behind AI decisions, they miss out on the learning process (Beer 2017), lacking opportunities to reflect on, deepen, or update their expertise (Beane 2019).”
From To Engage or Not to Engage with AI for Critical Judgments: How Professionals Deal with Opacity When Using AI for Medical Diagnosis (2022) · cites this paper as Beer 2017
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Beer (2017) noted that power is “operationalized through the algorithm, in that the algorithmic output cements, maintains or produces certain truths” (p.8) and users' understanding of the world is changed through their algorithmic interaction.”
From Expanding on the Frames: Making a Case for Algorithmic Literacy (2023) · cites this paper as Beer, 2017
The cited source says what the claim attributes to it.
In the citing paper
“While machine algorithms shape human actions, humans shape these algorithms through their actions, which create a recursive relationship (Beer, 2017).”
From Artificial Intelligence and Management: The Automation–Augmentation Paradox (2021) · cites this paper as Beer, 2017
In the citing paper
“The collective impact of algorithms has spurred discussions on the autonomy afforded to end users.(Ananny and Crawford 2018;Beer 2017;Taddeo and Floridi 2018b;Möller et al. 2018;Malhotra et al. 2018;Shin and Park 2019;Hauer 2019;Bauer and Dubljević 2020).”
From The ethics of algorithms: key problems and solutions (2022) · cites this paper as Beer 2017
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Foucault Effect: Studies in Governmentality
Burchell, G., Gordon, C., & Miller, P. J. (1991) · Medical Entomology and Zoology · Cited by 10,178
Simians, Cyborgs and Women: The Reinvention of Nature
McNeil, M., & Haraway, D. (1992) · Feminist Review · doi:10.2307/1395245 · Cited by 6,794
Simians, Cyborgs, and Women: The Reinvention of Nature.
Green, P. A., & Haraway, D. (1992) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2076334 · Cited by 5,437
How We Became Posthuman: Virtual Bodies in Cybernetics, Literature, and Informatics
Hayles, N. K. (1999) · doi:10.7208/chicago/9780226321394.001.0001 · Cited by 5,284
(2011) · Cited by 4,430
The Black Box Society: The Secret Algorithms That Control Money and Information
Pasquale, F. (2015) · doi:10.4159/harvard.9780674736061 · Cited by 3,796
’Society Must Be Defended’: Lectures at the College de France
Coté, M. (2004) · Canadian Journal of Communication · doi:10.22230/cjc.2004v29n3a1488 · Cited by 2,511
How We Became Posthuman: Virtual Bodies in Cybernetics, Literature and Informatics
Tambling, J., & Hayles, N. K. (2001) · The Modern Language Review · doi:10.2307/3735725 · Cited by 2,153
The Data Revolution: Big Data, Open Data, Data Infrastructures & Their Consequences
Kitchin, R. (2014) · doi:10.4135/9781473909472 · Cited by 1,469 · cited 1×
“Here, we see the role of algorithms, as decision-making parts of code (see Beer, 2013, p. 65), as being analytic and decisive (for a discussion of the role of algorithms in data analytics, see Kitchin, 2014, pp. 100–112).”
MethodThe Black Box Society: The Secret Algorithms That Control Money and Information
(2016) · Contemporary Sociology: A Journal of Reviews · doi:10.1177/0094306116641409c · Cited by 1,334
Research works printed but not linked: 4
- Foucault M., 2002, Power: Essential works of Foucault 1954–1984
- Foucault M., 2014, On the government of the living: Lectures at the collège de France 1979–1980
- Thrift N., 2006, Knowing capitalism
- 10.1177/0162243915608948 · DOI
Cited by
Sorted by citations
Items 101–200 of 939
Pan, C. A., Yakhmi, S., Iyer, T., Strasnick, E., Zhang, A. X., & Bernstein, M. S. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3512929 · Cited by 77
“Since online platforms have become the “new governors” of speech [83], they have been analyzed through the lens of political theory and legitimacy [16, 48, 83, 100, 131, 149, 151].”
BackgroundCalculating dating goals: data gaming and algorithmic sociality on Blued, a Chinese gay dating app
Wang, S. (2018) · Information Communication & Society · doi:10.1080/1369118x.2018.1490796 · Cited by 65
“From a social scienti fi c point of view, algorithms exist not only in codes but also in the social consciousness as part of a knowledge apparatus (Beer, 2017; Gillespie, 2014).”
BackgroundInfluentialPrinsloo, P. (2017) · E-Learning and Digital Media · doi:10.1177/2042753017731355 · Cited by 81
“It is therefore important to understand algorithms and algorithmic decision-making, regardless of context, as ‘deeply relational and being a product of a set of associations’ (Beer, 2017a: 7).”
BackgroundInfluentialMiddle-Aged Video Consumers' Beliefs About Algorithmic Recommendations on YouTube
Alvarado, O., Heuer, H., Vanden Abeele, V., Breiter, A., & Verbert, K. (2020) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3415192 · Cited by 70
“opinions of people about the content they recommend [9]. Likewise, Willson and Beer suggest studying algorithms that work semi-autonomously and exert power with no supervision from human counterparts [4, 53]. This body of work highlights the relevance of recommendation systems and their implications for users and soci…”
BackgroundShin, D. (2020) · Journalism Practice · doi:10.1080/17512786.2020.1841018 · Cited by 64
“In order to understand user attitudes and algorithm behaviors, research must consider algorithm quality, user heuristics, and recognized value (Bolin and Schwarz 2015).”
BackgroundInfluentialThe Stakes of Uncertainty: Developing and Integrating Machine Learning in Clinical Care
ELISH, M. C. (2018) · Ethnographic Praxis in Industry Conference Proceedings · doi:10.1111/1559-8918.2018.01213 · Cited by 59
Epic, Steam, and the role of skin-betting in game (platform) economies
Thorhauge, A. M., & Nielsen, R. K. L. (2021) · Journal of Consumer Culture · doi:10.1177/1469540521993929 · Cited by 70
“The critical analysis of software and programed systems has received a great deal of attention (Beer, 2017; Gillespie, 2014; Kitchin, 2017; Rieder, 2017) due to the increasingly important role programed systems play in the con fi guration of communication and interaction processes in society.”
MethodThe influence of algorithms on political and dating decisions
Agudo, U., & Matute, H. (2021) · PLoS ONE · doi:10.1371/journal.pone.0249454 · Cited by 65
“…in recommendation and persuasion algorithms being widely used nowadays, offering people advice on what to read, what to buy, where to eat, or whom to date, and people often assume that these AI judgments are objective, efficient, and reliable [4–6]; a phenomenon often known as machine bias [7].”
BackgroundBernards, N. (2019) · Environment and Planning A Economy and Space · doi:10.1177/0308518x19862576 · Cited by 60
“The analysis of such mass volumes of data is made possible by the application of computerized algorithms which are distinguished from the static ‘models’ used in traditional statistical analyses by their dynamic and recursive character (Beer, 2017).”
MethodRobo-advisors and the financialization of lay investors
Tan, G. K. S. (2020) · Geoforum · doi:10.1016/j.geoforum.2020.09.004 · Cited by 56
“Even though investors do not completely understand the ‘black box’ operations behind algorithms, they perceive algorithms to be objective and neutral mechanisms that are efficient and reliable (Beer, 2017).”
Reframing biometric surveillance: from a means of inspection to a form of control
Marciano, A. (2018) · Ethics and Information Technology · doi:10.1007/s10676-018-9493-1 · Cited by 62
“The combination of machines, numbers, and biology legitimizes a technical, scientific, and objective discourse around biometrics (Muller 2004), which is significant because it plays a crucial role in the production of ‘truths’ (Beer 2017).”
BackgroundShin, D. (. (2019) · Javnost - The Public · doi:10.1080/13183222.2019.1589249 · Cited by 53
“The great potential of an algorithm-driven economy is broadly acknowledged, and there is mounting enthusiasm and pressure to achieve the vision of an algorithm-based society (Beer 2017).”
BackgroundThe Datafication of Hate: Expectations and Challenges in Automated Hate Speech Monitoring
Laaksonen, S.-M., Haapoja, J., Kinnunen, T., Nelimarkka, M., & Pöyhtäri, R. (2020) · Frontiers in Big Data · doi:10.3389/fdata.2020.00003 · Cited by 71
“The online discussants were not fooled by the idea of objectivity often connected to algorithms (e.g., Beer, 2016; Markham et al., 2018): according to one anonymous forum poster, “algorithm is just a fancier name for a list of things that represents hate speech according to the one who made it.”
BackgroundMethodBarrett, B., & Kreiss, D. (2019) · Internet Policy Review · doi:10.14763/2019.4.1446 · Cited by 52
“There is a very well-documented literature on machine learning, artificial intelligence, and algorithms that stresses continual change (e.g., Ananny, 2016; Beer, 2017; Klinger and Svensson, 2018).”
BackgroundTruth from the machine: artificial intelligence and the materialization of identity
Keyes, O., Hitzig, Z., & Blell, M. T. (2021) · Interdisciplinary Science Reviews · doi:10.1080/03080188.2020.1840224 · Cited by 63
Not “what”, but “where is creativity?”: towards a relational-materialist approach to generative AI
Bueno, C. C., Chow, P.-S., & Popowicz, A. (2024) · AI & Society · doi:10.1007/s00146-024-01921-3 · Cited by 58
Zarouali, B., Boerman, S. C., Voorveld, H. A. M., & van Noort, G. (2022) · Internet Research · doi:10.1108/intr-01-2021-0049 · Cited by 67
Adorjan, M., & Ricciardelli, R. (2021) · Canadian Review of Sociology/Revue canadienne de sociologie · doi:10.1111/cars.12319 · Cited by 57
Krippner, G. R., & Hirschman, D. (2022) · Theory and Society · doi:10.1007/s11186-022-09500-5 · Cited by 55
“6 In developing our analysis, we are mindful of several difficulties present in the now expansive literature on algorithms (see Beer, 2017; Christin, 2020; Dourish, 2016; Rieder, 2017; Seaver, 2017; 2018).”
MethodHoff, J.-L. (2023) · Futures · doi:10.1016/j.futures.2023.103131 · Cited by 64
Scherr, S., Haim, M., & Arendt, F. (2018) · New Media & Society · doi:10.1177/1461444818801010 · Cited by 51
Algorithmic paranoia: the temporal governmentality of predictive policing
Sheehey, B. (2018) · Ethics and Information Technology · doi:10.1007/s10676-018-9489-x · Cited by 48
“For instance, factors like gang affiliation and number of prior narcotic arrests have been removed in the latest iteration of the SSL because they have been found to not significantly impact the score.51 Other variables, such as age at most recent arrest and recent shooting incidents, are given more weight since these…”
BackgroundInfluentialUsing fair AI to predict students’ math learning outcomes in an online platform
Li, C., Xing, W., & Leite, W. L. (2022) · Interactive Learning Environments · doi:10.1080/10494820.2022.2115076 · Cited by 55
“Bias in data that re fl ects humans ’ hidden values is a major source of algorithmic bias (Beer, 2017).”
BackgroundJacobsen, B. N., & Simpson, J. (2023) · Information Communication & Society · doi:10.1080/1369118x.2023.2234980 · Cited by 62
Hacia una visión contemporánea de la Tecnología Educativa
Castañeda, L., Salinas, J., & Segura, J. A. (2020) · Digital Education Review · doi:10.1344/der.2020.37.240-268 · Cited by 64
“…y, en general, cómo la tecnología da forma a los procesos educativos formales, informales y no formales, incluso a su moralidad (Kroes & Verbeek, 2014), en una época en la que, por ejemplo, algoritmos opacos están tomando decisiones pedagógicas (Beer, 2017; P. B. de Laat, 2017; Williamson, 2017).”
BackgroundThe Datafication of Intimacy: Mobile Dating Apps, Dependency, and Everyday Life
Ridder, S. D. (2021) · Television & New Media · doi:10.1177/15274764211052660 · Cited by 50
The return of the social: Algorithmic identity in an age of symbolic demise
Kotliar, D. M. (2020) · New Media & Society · doi:10.1177/1461444820912535 · Cited by 45
“It is a reconfiguration that favors effectivity over “authenticity” or fixity (Cheney-Lippold, 2011, 2017: 6), a configuration that is logistical (Morris, 2015) rather than epistemological (Lash, 2007), and one that leaves language, social theory, and social expertise behind.”
BackgroundArtificial Intelligence in Public Relations: Role and Implications
Buhmann, A., & White, C. L. (2022) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-80071-597-420221036 · Cited by 44
Inevitable challenges of autonomy: ethical concerns in personalized algorithmic decision-making
Lu, W. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03864-y · Cited by 54
“The prioritization of these goals and values often re fl ects prevalent social norms, moral standards, or the speci fi c interests and preferences of the developers (Beer, 2017).”
de Oliveira, T. M. (2020) · Fronteiras - estudos midiáticos · doi:10.4013/fem.2020.221.03 · Cited by 44
Brown, N. M. (2018) · Culture Studies ↔ Critical Methodologies · doi:10.1177/1532708617750178 · Cited by 47
Masso, A., & Kasapoğlu, T. (2020) · Information Communication & Society · doi:10.1080/1369118x.2020.1739731 · Cited by 43
“Although some studies have interpreted algorithms as constructing technical and material presence (Beer, 2017), other studies have demonstrated (Amoore & Piotukh, 2015) these calculative devices matter beyond their speci fi c functions as they progressively shape, transform and govern all areas of…”
ResultHeiland, H. (2023) · New Technology Work and Employment · doi:10.1111/ntwe.12282 · Cited by 53
Vimalkumar, M., Gupta, A., Sharma, D., & Dwivedi, Y. K. (2021) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00144 · Cited by 45
Moore, J. (2019) · Frontiers in Big Data · doi:10.3389/fdata.2019.00032 · Cited by 42
“In examining “the algorithm as a thing and the algorithm as a word,” I choose words rather than the content of techniques as the site of critique (Beer, 2017, p. 9).”
MethodThe Ethics of AI in Health Care: A Mapping Review
Morley, J., Machado, C. C. V., Burr, C., Cowls, J., Joshi, I., Taddeo, M., & Floridi, L. (2020) · Philosophical studies series · doi:10.1007/978-3-030-81907-1_18 · Cited by 145
How Digital Platforms Organize Immaturity: A Sociosymbolic Framework of Platform Power
Harracá, M., Castelló, I., & Gawer, A. (2023) · Business Ethics Quarterly · doi:10.1017/beq.2022.40 · Cited by 44
News on Events and Social Media: A Comparative Analysis of Facebook Users’ Reactions
Salgado, S., & Bobba, G. (2019) · Journalism Studies · doi:10.1080/1461670x.2019.1586566 · Cited by 48
“Algorithms produce, process, filter, prioritize, and recommend content, and by doing so they shape and engage with the contemporary everyday (Willson 2017) and have thus become crucial actors in social ordering processes (Beer 2017).”
BackgroundSilva, D. E., Chen, C., & Zhu, Y. (2022) · New Media & Society · doi:10.1177/14614448221098042 · Cited by 46
“Beer (2017) warns that low transparency increases the risk that the public may “mis-judge [algorithms’] power, to overemphasize their importance, to misconceive of the algorithm as a lone detached actor. . . ” (p. 3).”
BackgroundRobo-advisors (RAs): the programmed self-service market for professional advice
Wexler, M. N., & Oberlander, J. (2021) · Journal of Service Theory and Practice · doi:10.1108/jstp-07-2020-0153 · Cited by 48
Towards a Data-Driven Public Administration: An Empirical Analysis of Nascent Phase Implementation
Broomfield, H., & Reutter, L. M. (2021) · Scandinavian Journal of Public Administration · doi:10.58235/sjpa.v25i2.7117 · Cited by 47
“The calculative systems and techniques to process information have become ever faster, more comprehensive and more autonomous in recent years (Beer 2017).”
BackgroundCurating Quality? How Twitter’s Timeline Algorithm Treats Different Types of News
Bandy, J., & Diakopoulos, N. A. (2021) · Social Media + Society · doi:10.1177/20563051211041648 · Cited by 41
“, 2019a), journalism studies (Bechmann & Nielbo, 2018), mass communication studies (Beer, 2017), and social media studies (Auxier & Vitak, 2019).”
BackgroundFan, Y., & Liu, X. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1009173 · Cited by 40
“, feeling capable, self-governed, well-supported, and satisfied with their state; Brown and Ryan, 2003) Therefore, SDT explains well the influence mechanism of algorithmic decision autonomy on consumer purchase decisions (Beer, 2017).”
BackgroundYapay Zekâ Sosyolojisi Üzerine Bir Değerlendirme
Adaş, E. B., & ERBAY, B. (2022) · Gaziantep University Journal of Social Sciences · doi:10.21547/jss.991383 · Cited by 44
Archambault, S. G., Ramachandran, S., Acosta, E. S., & Fu, S. (2024) · The Journal of Academic Librarianship · doi:10.1016/j.acalib.2024.102865 · Cited by 69
A guideline for understanding and measuring algorithmic governance in everyday life
Latzer, M., & Festic, N. (2019) · Internet Policy Review · doi:10.14763/2019.2.1415 · Cited by 51
“This is accounted for in studies on the socio-technical context of AS, where algorithms are viewed as situated artefacts and generative processes embedded in a complex ecosystem (Beer, 2017; Willson, 2017).”
BackgroundSchäffer, B., & Lieder, F. R. (2022) · Journal of Research on Technology in Education · doi:10.1080/15391523.2022.2148786 · Cited by 52
“In addition to genuine computer science publications (Chowdhary, 2020; Mackworth & Poole, 2017; Russell & Norvig, 2016; Kaplan, 2016), publications in the intersection of computer science, social and cultural sciences are indirectly relevant for this research (e.g., Bostrom, 2017; Beer, 2017).”
BackgroundSurveillance and Datafication in Higher Education: Documentation of the Human
Gourlay, L. J. (2022) · Postdigital Science and Education · doi:10.1007/s42438-022-00352-x · Cited by 56
“Prinsloo (2017: 145) sets out how increased digitization has combined with the proliferation of regimes of audit and quality, to lead to greater use of algorithmic decision-making in higher education.”
Teacher accountability, datafication and evaluation: A case for reimagining schooling
Holloway, J. (2020) · Education Policy Analysis Archives · doi:10.14507/epaa.28.5026 · Cited by 38
Heuer, H., Jarke, J., & Breiter, A. (2021) · Big Data & Society · doi:10.1177/20539517211017593 · Cited by 38
“Beer (2017) examines the social power of algorithms in promoting certain visions of calculative objectivity and provides crucial insights that shape our understanding of contemporary information systems.”
BackgroundPhenomenal algorhythms : The sensorial orchestration of “real-time” in the social media manifold
Lupinacci, L. (2022) · New Media & Society · doi:10.1177/14614448221109952 · Cited by 37
“Algorithmic platforms claim to offer what is relevant to us individually while veiling their very operation behind a discourse of impartiality and objectivity (Beer, 2017; Bucher, 2017, 2018; Carmi, 2020; Kant, 2020).”
BackgroundCognitive ability in virtual reality: Validity evidence for VR game‐based assessments
Weiner, E., & Sanchez, D. R. (2020) · International Journal of Selection and Assessment · doi:10.1111/ijsa.12295 · Cited by 41
Fouquaert, T., & Mechant, P. (2021) · Information Communication & Society · doi:10.1080/1369118x.2021.1883707 · Cited by 36
“Studies have argued that users ’ literacy about curation algorithms and their experiences with them, might a ff ect their attitudes towards how the platform should be used (Beer, 2017).”
BackgroundShin, D., Alimamy, S., & Hwang, Y. (2022) · Cross Cultural & Strategic Management · doi:10.1108/ccsm-06-2020-0125 · Cited by 41
Zhang, Y., Huang, S., & Li, T. (2022) · Information Communication & Society · doi:10.1080/1369118x.2022.2161829 · Cited by 42
“The algorithmic power is manifested when the visibility regimes of digital platforms prompt users to increase online engagement (Beer, 2017; Bucher, 2012), but users have the potential to seize the algorithmic power by strategically interacting with the sys-tem (Ramizo, 2021).”
BackgroundInfluentialFactors influencing trust in algorithmic decision-making: an indirect scenario-based experiment
Marmolejo‐Ramos, F., Marrone, R. L., Korolkiewicz, M. W., Gabriel, F. C., Siemens, G., Joksimovíc, S., Yamada, Y., Mori, Y., Rahwan, T., Sahakyan, M., et al. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1465605 · Cited by 45
Analytics in action: users and predictive data in the neonatal intensive care unit
Maiers, C. (2017) · Information Communication & Society · doi:10.1080/1369118x.2017.1291701 · Cited by 38
“In outlining their makeup, researchers aim to better grasp how algorithms make decisions and shape the world in which they operate (Beer, 2016).”
BackgroundInvestigating Algorithmic Misconceptions in a Media Context: Source of a New Digital Divide?
Zarouali, B., Helberger, N., & de Vreese, C. H. (2021) · Media and Communication · doi:10.17645/mac.v9i4.4090 · Cited by 48
“In our data‐driven media landscape, algorithms play an increasingly important role in how online users use, navi‐ gate, and consume online information and communica‐ tion (Beer, 2017; Lee, 2018; Ricci, 2015).”
BackgroundThe 2016 Manifesto for Teaching Online
(2020) · The MIT Press eBooks · doi:10.7551/mitpress/11840.003.0001 · Cited by 34
‘I like to run to feel’: embodiment and wearable mobile tracking devices in distance running
Toner, J., Allen‐Collinson, J., Jackman, P. C., Jones, L., & Addrison, J. (2023) · Qualitative Research in Sport Exercise and Health · doi:10.1080/2159676x.2023.2225516 · Cited by 37
Lüders, M. H. (2020) · Information Communication & Society · doi:10.1080/1369118x.2020.1758742 · Cited by 38
“Communication research abounds with critical discussions of algorithmic culture (Beer, 2017; Kitchin, 2017; Prey, 2018; Willson, 2017), typically framed to discuss how recommendation systems are never neutral, but always imbued with vested interests of those with the strengths to in fl uence what we…”
BackgroundHoolohan, C., Amankwaa, G., Browne, A. L., Clear, A. K., Holstead, K. L., Machen, R., Michalec, O., & Ward, S. (2021) · Wiley Interdisciplinary Reviews Water · doi:10.1002/wat2.1512 · Cited by 32
“However, digital tools themselves create few opportunities for higher modes of learning (Mukhtarov, Dieperink, & Driessen, 2018), and do not replace deliberative processes (Beer, 2017).”
Data and Organization Studies: Aesthetics, emotions, discourse and our everyday encounters with data
Saifer, A., & Dacin, M. T. (2021) · Organization Studies · doi:10.1177/01708406211006250 · Cited by 32
“In this regard, we shift our attention to data as “a notion that carries some persuasive weight and is likely to be suggestive of wider power claims and rationalities” (Beer, 2017, p. 8).”
BackgroundInfluentialBüchner, S., & Dosdall, H. (2021) · KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie · doi:10.1007/s11577-021-00752-0 · Cited by 36
“Insgesamt hat dieser Abschnitt argumentiert, dass die soziale Wirkmächtigkeit des Algorithmus auf seiner organisationalen Einbettung basiert.”
BackgroundInfluentialChasing Frankenstein's Monster: Information Literacy in the Black Box Society
Lloyd, A. (2019) · Journal of Documentation · doi:10.1108/jd-02-2019-0035 · Cited by 41
Fluid agency in relation to algorithms: Tensions, mediations, and transversalities
Siles, I., Cruz, E. G., & Quijano, P. R. (2023) · Convergence The International Journal of Research into New Media Technologies · doi:10.1177/13548565231174586 · Cited by 31
Beyond the black box in music streaming: the impact of recommendation systems upon artists
O’Dair, M., & Fry, A. (2019) · Popular Communication · doi:10.1080/15405702.2019.1627548 · Cited by 44
‘Digital First’: homelessness and data use in an online service environment
Humphry, J. (2019) · Communication Research and Practice · doi:10.1080/22041451.2019.1601418 · Cited by 30
“As a result, across a wide range of disciplines, there is an emerging programme of research examining the societal implications and politics of this paradigm with privacy, profiling, discrimination and surveillance all priority concerns of algorithmic and data-driven processes (Beer, 2017; Dencik, Hintz, & Cable, 2016…”
BackgroundSqueaky wheels: Missing data, disability, and power in the smart city
Deitz, S. L., Lobben, A. K., & Alferez, A. (2021) · Big Data & Society · doi:10.1177/20539517211047735 · Cited by 33
Platform governance and sociological participation
Lu, P., Zhou, L., & Fan, X. (2023) · The Journal of Chinese Sociology · doi:10.1186/s40711-023-00181-w · Cited by 28
“Others have deployed various tactics and strategies to avoid being “fed” by machines, platforms, and algorithms; they have even tried to change the output results of algorithms (Beer 2017).”
MethodAI in Human Resource Management: Literature Review and Research Implications
Zhai, Y., Zhang, L., & Yu, M. (2024) · Journal of the Knowledge Economy · doi:10.1007/s13132-023-01631-z · Cited by 41
“The findings of this paper are behaviors that enable both humans and AI to manifest themselves through automation and augmentation (Beer, 2017).”
Verwiebe, R., & Hagemann, S. (2024) · Information Communication & Society · doi:10.1080/1369118x.2024.2358170 · Cited by 50
“For Beer (2017), following Foucault, they possess a total character as the central governance institution of the twenty-first century.”
Lundahl, O. (2022) · Information, Communication & Society · doi:10.1080/1369118x.2020.1864006 · Cited by 29
“This conceptual paper then, fi rstly, contributes to the literature on the social power operating through algorithms (Beer, 2017).”
BackgroundInfluentialTransparency as Manipulation? Uncovering the Disciplinary Power of Algorithmic Transparency
Wang, H. (2022) · Philosophy & Technology · doi:10.1007/s13347-022-00564-w · Cited by 33
“However, as David Beer rightly points out, it is a “mistake” to see the algorithm solely as “technical and self‑con‑ tained object” (Beer, 2017, 4).”
BackgroundYANIT, M., Yanit, M., & Wan, F. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107870 · Cited by 31
Janssen, H., & Singh, J. P. (2022) · Internet Policy Review · doi:10.14763/2022.1.1644 · Cited by 29
Who Owns the Future? Data Trusts, Data Commons, and the Future of Data OwnershipPreprint
Mills, S. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3437936 · Cited by 32
“Recent data incidents such as the Cambridge Analytica scandal demonstrate the power data have over elections (Confessore, 2018; Zittrain, 2013), over our behaviour (Beer, 2017), and over our regulatory capacities (Yeung, 2017).”
Powerful Privacy Norms in Social Network Discourse
McDonald, N., & Forte, A. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479565 · Cited by 29
Regimes of recognition on algorithmic media
Jacobsen, B. N. (2021) · New Media & Society · doi:10.1177/14614448211053555 · Cited by 30
“Much research has already been conducted into the social power and politics of algorithms (Beer, 2009, 2017; Cheney-Lippold, 2016; Gillespie, 2014; Kotliar, 2020; Willson, 2017).”
BackgroundDigital Platforms and Algorithmic Subjectivities
Armano, E., Briziarelli, M., & Risi, E. (2022) · University of Westminster Press eBooks · doi:10.16997/book54 · Cited by 40
Zavadski, A., & Toepfl, F. (2018) · Media Culture & Society · doi:10.1177/0163443718764565 · Cited by 30
Subjectivity and algorithmic imaginaries: the algorithmic other
Gandini, A., Gerosa, A., Giuffrè, L., & Keeling, S. (2023) · Subjectivity · doi:10.1057/s41286-023-00171-w · Cited by 28
“Pivotal to this call by Bucher is the notion of algorithmic imaginaries (2017) .”
Built for expansion': The 'social life' of the WHO's mental health GAP Intervention Guide
Mills, C., & Hilberg, E. (2019) · Sociology of Health & Illness · doi:10.1111/1467-9566.12870 · Cited by 27
Disambiguating the benefits and risks from public health data in the digital economy
Cheung, S. (2020) · Big Data & Society · doi:10.1177/2053951720933924 · Cited by 27
Returning to critical pedagogy in a world of datafication
Pronzato, R., & Markham, A. N. (2023) · Convergence The International Journal of Research into New Media Technologies · doi:10.1177/13548565221148108 · Cited by 27
“For example, classi fi cation and hierarchization processes are not neutral, as they entail deliberate and power-laden choices over what is shown and what remains hidden (Beer, 2017).”
BackgroundŠkobo, M., & Petričević, V. (2023) · Društvene i humanističke studije · doi:10.51558/2490-3647.2023.8.2.317 · Cited by 27
Social Media Algorithms, Bots and Elections in Africa
Ndlela, M. N. (2020) · Springer eBooks · doi:10.1007/978-3-030-30553-6_2 · Cited by 30
Festic, N. (2020) · Regulation & Governance · doi:10.1111/rego.12333 · Cited by 40
Serafimova, S. (2020) · Humanities and Social Sciences Communications · doi:10.1057/s41599-020-00614-8 · Cited by 26
“This power depends on the way in which they are “ a part of broader rationalities, broader programs of social change and development ” (Beer, 2016).”
BackgroundTo resist, or to align? The enactment of data-based school governance in Italy
Landri, P. (2021) · Educational Assessment Evaluation and Accountability · doi:10.1007/s11092-021-09367-7 · Cited by 26
“In sum, they have the agential capacity, but it is difficult to understand how their power is exercised in practice (Beer, 2017; Kitchin, 2014).”
BackgroundAI-powered narrative building for facilitating public participation and engagement
Marmolejo‐Ramos, F., Workman, T., Walker, C., Lenihan, D., Moulds, S., Correa, J. C., Hanea, A. M., & Sonna, B. (2022) · Discover Artificial Intelligence · doi:10.1007/s44163-022-00023-7 · Cited by 31
“Given the societal role of ADA-related technologies [6], these governmental plans seem to be reasonably sensitive to the changes associated with the so-called Industry 4.”
BackgroundEuropean Union’s Regulating of Social Media: A Discourse Analysis of the Digital Services Act
Schlag, G. (2023) · Politics and Governance · doi:10.17645/pag.v11i3.6735 · Cited by 44
“Most providers have created applications where users (and law enforcement agencies) can report violations of these terms (Beer, 2017; Hoffmann, 2019; Kunst et al., 2021; Porten‐Cheé et al., 2020) and algorithms support the automatic detection of forbidden content (Katzenbach & Ulbricht, 2019).”
BackgroundInfluentialBeing recognized in an algorithmic system: Cruel optimism in gay visibility on Douyin and Zhihu
Wang, S., & Zhou, T. (2022) · Sexualities · doi:10.1177/13634607221106912 · Cited by 25
‘Folk’ in the Age of Algorithms: Theorizing Folklore on Social Media Platforms
Flinterud, G. (2023) · Folklore · doi:10.1080/0015587x.2023.2233839 · Cited by 38
“Sociologist David Beer conceptualizes it according to its ‘ social power ’ , as driven by the ‘ need to understand what algorithms are and what they do in order to fully grasp their influence and consequences ’ (Beer 2017, 3).”
BackgroundMendonça, R. F., Almeida, V. A. F., & Filgueiras, F. D. B. (2023) · doi:10.1093/oso/9780192870070.001.0001 · Cited by 28
Brigstocke, J., Bresnihan, P., Dawney, L., & Millner, N. (2021) · Progress in Human Geography · doi:10.1177/0309132520986227 · Cited by 29
“…have explicitly focused on authority, arguing that authority is increasingly privatized (Cutler et al., 1999); internalized (Dean, 1996; Huxley, 2006); fragmented (Sassen, 2006); diffuse and deterritorialized (Agnew, 2005; Green, 2016); and automated and depersonalized (Amoore, 2013; Beer, 2017).”
Backgroundde Oliveira, T. M., Wang, Z., & Xu, J. (2022) · Online Media and Global Communication · doi:10.1515/omgc-2022-0005 · Cited by 25
Logged in or locked in? Young adults’ negotiations of social media platforms and their features
Gangneux, J. (2019) · Journal of Youth Studies · doi:10.1080/13676261.2018.1562539 · Cited by 28
“Furthermore, scholars have demonstrated that the ways in which social media platforms are perceived and imagined also affect users’ expectations, uses and understandings of the platforms (Beer 2017; Bucher 2017).”
Background“Good” and “Bad” Machine Agency in the Context of Human-AI Communication: The Case of ChatGPT
Brandtzaeg, P. B., You, Y., Wang, X., & Lao, Y. (2023) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-48057-7_1 · Cited by 25
Reichmann, W. (2018) · Ethik in mediatisierten Welten · doi:10.1007/978-3-658-21083-0_9 · Cited by 24
Metadata
- Authors
- Beer, D.
- Affiliations
- University of York (GB)
- Corresponding author
- Beer, David
- ORCID
- Beer, David
- Venue
- Information, Communication & Society
- Publisher
- Informa UK Limited
- Published
- 2016-08-08
- Volume
- 20
- Issue
- 1
- Pages
- 1-13
- ISSN
- 1369-118X (ISSN-L)
- 1468-4462
- OpenAlex
- W2507975203
- Cited by
- 945
- References
- 45
- Citations by year
- 2026: 196 · 2025: 91 · 2024: 101 · 2023: 157 · 2022: 99 · 2021: 108 · 2020: 64 · 2019: 69 · 2018: 45 · 2017: 15
- FWCI
- 104.91
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Information Communication & Society (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Cybernetics and Technology in Society
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Keywords
- algorithms, social power, social ordering, governmentality, rationality, algorithmic governance
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review