The DOI matches its Crossref record; 65 of the 67 references it cites were found in a registry or an index.
Augmenting the algorithm: Emerging human-in-the-loop work configurations
Open accessAbstract
How do configurations of humans and algorithms evolve as firms adopt artificial intelligence (AI) capabilities, and what are the implications for work and organization? We explored these questions through a two-year long case study of an organization in the international maritime trade that introduced automated algorithmic support for data analysis and prediction work. Drawing on a human–machine configuration perspective, we found that humans and the algorithm were configured and reconfigured in multiple ways over time as the organization dealt with the introduction of algorithmic analysis. In contrast to replacing human work, the emergent configurations required new roles and redistribution of extant expertise to augment and improve the accuracy of the algorithm. Our analysis suggests that the new configuration resembled a human-in-the-loop pattern, comprised of both the augmentation work of auditing (i.e. the generation of a ground truth and assessment of the algorithmic output against this) as well as the work of altering the algorithm and the data acquisition architecture. Our research points to the strategic importance of a human-in-the-loop pattern for organizational reflexivity to ensure that the performance of the algorithm meets the organization’s requirements and changes in the environment.
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
“In short, the deployment of algorithmic man-agement in organizational work introduces novel “human–machine configurations” that could transform relationships between managers and workers and their respective roles (Grønsund and Aanestad, 2020).”
From Algorithmic management in a work context (2021) · cites this paper as Grønsund and Aanestad, 2020
Experimental — accuracy not yet measuredIn the citing paper
“Simultaneously, the AI algorithms can be considered performative in the sense that they assist in decision-making, the extent to which their use can form organizational processes, or even take autonomous decisions (Faraj et al., 2018; Grønsund & Aanestad, 2020) that leads to new organization capabilities through AI.”
From Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes (2023) · cites this paper as Grønsund & Aanestad, 2020
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
Strategies for Theorizing from Process Data
Langley, A. (1999) · The Academy of Management Review · doi:10.5465/amr.1999.2553248 · Cited by 7,008 · cited 1×
“The third stage of analysis involved a deeper production of case narratives (Langley, 1999) and vignettes from our empirical material, while still engaging in the field and collecting data.”
BackgroundUnderstanding dynamic capabilities
Winter, S. G. (2003) · Strategic Management Journal · doi:10.1002/smj.318 · Cited by 5,315 · cited 2×
“While the terms ‘reconfigure' and ‘configurations’ are central to extant definitions of dyna mic capabilities (Teece et al., 1997; Eisenhardt and Martin, 2000; Winter, 2003), the terms are not unpacked in detail, neither generally nor specifically relating to human-machine interplay.”
BackgroundPlans and Situated Actions: The Problem of Human-Machine Communication
Kantowitz, B. H., & Suchman, L. A. (1990) · The American Journal of Psychology · doi:10.2307/1423221 · Cited by 5,307 · cited 2×
“To do this, we build on Lucy Suchman’s seminal study at Xerox PARC (Suchman, 1987) which challenged fundamental ideas about humans’ and machines’ cognition and communication; ideas that had guided the design of the intelligent interface of the advanced copying machines used by the scientists she…”
MethodA Set of Principles for Conducting and Evaluating Interpretive Field Studies in Information Systems1
Klein, H. K., & Myers, M. D. (1999) · MIS Quarterly · doi:10.2307/249410 · Cited by 5,263 · cited 1×
“For example, from one of the meetings we produced and circulated a summary of our understanding of the strategic conditions and problem context, which served as a means for confirmation and contextualization (Klein and Myers, 1999).”
BackgroundA model for types and levels of human interaction with automation
Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/3468.844354 · Cited by 4,195 · cited 1×
“, human) performance to fully automatic performance (Parasuraman et al., 2000).”
BackgroundWhy Are There Still So Many Jobs? The History and Future of Workplace Automation
Autor, D. H. (2015) · Journal of Economic Perspectives · doi:10.1257/jep.29.3.3 · Cited by 3,917 · cited 1×
“In addition, one may see indirect effects where not only does automation substitute labour , it also “complements labor, raises output in ways that lead to higher demand for labor, and interacts with adjustments in labor supply” (Autor, 2015, p. 5).”
BackgroundInterpretive case studies in IS research: nature and method
Walsham, G. (1995) · European Journal of Information Systems · doi:10.1057/ejis.1995.9 · Cited by 3,834 · cited 1×
“We have conducted an in-depth, qualitative case study based on the interpretive research paradigm (Walsham, 1995).”
MethodArtificial Intelligence and Management: The Automation–Augmentation Paradox
Raisch, S., & Krakowski, S. (2021) · Academy of Management Review · doi:10.5465/amr.2018.0072 · Cited by 2,755 · cited 4×
“This suggests that the processes of automation and augmentation influence one another in a reciprocal manner (Raisch and Krakowski, 2020), and that their organizing emerges as a core capability.”
BackgroundMethodInfluentialThe structure of ill structured problems
Simon, H. A. (1973) · Artificial Intelligence · doi:10.1016/0004-3702(73)90011-8 · Cited by 2,600 · cited 1×
“…that algorithms are more appropriate for structured problem-solving and where outcomes can be clearly described; and human processing is more apt for ill-structured problem-solving, to which solutions tend to require human interpretation and judgment (e.g., Simon, 1973; Shrestha et al., 2019).”
BackgroundRankings and Reactivity: How Public Measures Recreate Social Worlds
Espeland, W. N., & Sauder, M. (2007) · American Journal of Sociology · doi:10.1086/517897 · Cited by 2,584
(2006) · Cited by 2,256
Walsham, G. (2006) · European Journal of Information Systems · doi:10.1057/palgrave.ejis.3000589 · Cited by 2,217 · cited 2×
“Using a sparse form of open coding (Walsham, 2006) of our field notes, we sought out patterns and selected empir ically informed themes such as “secrecy” and “obscuring”, all relating to episodes of questioning the validity of external data.”
BackgroundMethodLicklider, J. C. R. (1960) · IRE Transactions on Human Factors in Electronics · doi:10.1109/thfe2.1960.4503259 · Cited by 1,938 · cited 1×
“Thirdly, across this continuum and these functions, automation may augment human performance of a particular task through increasing the capability of humans to approach a problem situation, gain comprehension, and derive solutions (Engelbart, 1962, p. 1; Licklider, 1960).”
BackgroundLeonardi, P. M. (2011) · MIS Quarterly · doi:10.2307/23043493 · Cited by 1,889 · cited 1×
“This aligns with, e.g., Leonardi (2011) taking as his unit of analysis the process by which human and technology are intertwined.”
BackgroundPlans and Situated Actions: The Problem of Human Machine Communication.
Woolgar, S., & Suchman, L. A. (1989) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2073874 · Cited by 1,600 · cited 2×
“To do this, we build on Lucy Suchman’s seminal study at Xerox PARC (Suchman, 1987) which challenged fundamental ideas about humans’ and machines’ cognition and communication; ideas that had guided the design of the intelligent interface of the advanced copying machines used by the scientists she…”
MethodWhat can machine learning do? Workforce implications
Brynjolfsson, E., & Mitchell, T. (2017) · Science · doi:10.1126/science.aap8062 · Cited by 1,131 · cited 2×
“These are still relatively rarer (Brynjolfsson and Mitchell, 2017), nevertheless, popular debates tend to profess a “ replace ment” trope, where human jobs are taken over by intelligent machines (McAfee and Brynjolfsson, 2017).”
BackgroundOrganizational Decision-Making Structures in the Age of Artificial Intelligence
Shrestha, Y. R., Ben-Menahem, S. M., & von Krogh, G. (2019) · California Management Review · doi:10.1177/0008125619862257 · Cited by 1,108 · cited 1×
“It has long been suggested that algorithms are more appropriate for structured problem-solving and where outcomes can be clearly described; and human processing is more apt for ill-structured problem-solving, to which solutions tend to require human interpretation and judgment (e.g., Simon, 1973; Shrestha et al., 2019…”
BackgroundAUGMENTING HUMAN INTELLECT: A CONCEPTUAL FRAMEWORK
Engelbart, D. C. (1962) · Defense Technical Information Center (DTIC) · doi:10.21236/ad0289565 · Cited by 1,093 · cited 1×
“Thirdly, across this continuum and these functions, automation may augment human performance of a particular task through increasing the capability of humans to approach a problem situation, gain comprehension, and derive solutions (Engelbart, 1962, p. 1; Licklider, 1960).”
BackgroundAutomation, skills use and training
Nedelkoska, L., & Quintini, G. (2018) · OECD social employment and migration working papers · doi:10.1787/2e2f4eea-en · Cited by 1,092 · cited 1×
“For instance, by automating routine manual and cognitive tasks, human capacity is freed to take on non-routine tasks and capacity and productivity can increase, which again drives an increase in demand for non-routine problem-solving (Nedelkoska and Quintini, 2018).”
BackgroundAgainst Reflexivity as an Academic Virtue and Source of Privileged Knowledge
Lynch, M. (2000) · Theory Culture & Society · doi:10.1177/02632760022051202 · Cited by 946
The Alignment of Technology and Structure through Roles and Networks
Barley, S. R. (1990) · Administrative Science Quarterly · doi:10.2307/2393551 · Cited by 941
Working and organizing in the age of the learning algorithm
Faraj, S., Pachidi, S., & Sayegh, K. (2018) · Information and Organization · doi:10.1016/j.infoandorg.2018.02.005 · Cited by 929 · cited 2×
“, 2017; Markus, 2017) and intelligent technologies (Bailey and Barley, 2019; Faraj et al., 2018; von Krogh, 2018; Rai et al., 2019), including the implications for organizational strategy (Constantiou and Kallinikos, 2015; Woerner and Wixom, 2015; Bhimani, 2015) and work in settings ranging from education (Marjanovic…”
BackgroundRamaprasad, A. (1983) · Behavioral Science · doi:10.1002/bs.3830280103 · Cited by 915
Debating big data: a literature review on realizing value from big data
Günther, W. A., Rezazade Mehrizi, M. H., Huysman, M., & Feldberg, F. (2017) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2017.07.003 · Cited by 880 · cited 2×
“Information Systems (IS) researchers have raised fundamental questions as to the ramifications of both datafication processes (Galliers et al., 2017, Günther et al., 2017; Markus, 2017) and intelligent technologies (Bailey and Barley, 2019; Faraj et al., 2018; von Krogh, 2018; Rai et al., 2019),…”
BackgroundThe Rapid Adoption of Data-Driven Decision-Making
Brynjolfsson, E., & McElheran, K. (2016) · American Economic Review · doi:10.1257/aer.p20161016 · Cited by 843 · cited 1×
“The capabilities of utilizing data has in itself become a significant strategic asset and an object of strategy formulation (DalleMule and Davenport, 2017; Iansiti and Lakhani, 2020), and data-driven decision-making is increasingly implemented (Brynjolfsson and McElheran, 2016).”
BackgroundMachine, platform, crowd: Harnessing our digital future
Peregrina, Á. F. A. (2018) · Economía industrial · Cited by 681
Artificial intelligence in organizations: New opportunities for phenomenon-based theorizing
von Krogh, G. (2018) · Academy of Management Discoveries · doi:10.5465/amd.2018.0084 · Cited by 641 · cited 7×
“More nuanced accounts instead emphasize interrelation and augmentation (Bailey and Barley, 2019; von Krogh, 2018; Markus, 2017; Davenport and Kirby, 2016), where humans and algorithms interact to perform a task.”
BackgroundInfluentialThe SAGE Handbook of Process Organization Studies
Langley, A., & Tsoukas, H. (2016) · SAGE Publications Ltd eBooks · doi:10.4135/9781473957954 · Cited by 628
Society-in-the-loop: programming the algorithmic social contract
Rahwan, I. (2018) · Ethics and Information Technology · doi:10.1007/s10676-017-9430-8 · Cited by 553 · cited 1×
“6, the loop of algorithm-auditing figures design by human training as congruent with interactive machine learning (Rahwan, 2018).”
BackgroundNew games, new rules: big data and the changing context of strategy
Constantiou, I. D., & Kallinikos, J. (2015) · Journal of Information Technology · doi:10.1057/jit.2014.17 · Cited by 526 · cited 1×
“…(Bailey and Barley, 2019; Faraj et al., 2018; von Krogh, 2018; Rai et al., 2019), including the implications for organizational strategy (Constantiou and Kallinikos, 2015; Woerner and Wixom, 2015; Bhimani, 2015) and work in settings ranging from education (Marjanovic and…”
Background(2014) · Digital Commons at University of Maryland Carey Law (University of Maryland Francis King Carey School of Law) · Cited by 524
The ‘problem ’ with automation: inappropriate feedback and interaction, not ‘over-automation’
Norman, D. A. (1990) · Philosophical transactions of the Royal Society of London. Series B, Biological sciences · doi:10.1098/rstb.1990.0101 · Cited by 519
Newell, S., & Marabelli, M. (2015) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2015.02.001 · Cited by 494 · cited 2×
“Advances in ‘data-driven intelligence engines’ (Baptista et al., 2017a) based on availability of data and artificial intelligence (AI) have the potential to transform the nature of work and organizations (Newell and Marabelli, 2015).”
Background(2012) · Routledge eBooks · doi:10.4324/9780203854921 · Cited by 438
Open Strategy: Dimensions, Dilemmas, Dynamics
Hautz, J., Seidl, D. N., & Whittington, R. (2016) · Long Range Planning · doi:10.1016/j.lrp.2016.12.001 · Cited by 411 · cited 1×
“For instance, mandated data sharing can undermine competitiveness as competitors get hold of strategically sensitive information (Hautz et al., 2017, p. 302), and drive, e.g., ship crews to obfuscate or manipulate data about their true destination.”
BackgroundSuchman, L. A. (1993) · Computer Supported Cooperative Work (CSCW) · doi:10.1007/bf00749015 · Cited by 400
Do Categories Have Politics? The language/action perspective reconsidered
Suchman, L. A. (1993) · Springer eBooks · doi:10.1007/978-94-011-2094-4_1 · Cited by 336
Exploring the impact of artificial Intelligence: Prediction versus judgment
Agrawal, A., Gans, J. S., & Avi Goldfarb, B. (2019) · Information Economics and Policy · doi:10.1016/j.infoecopol.2019.05.001 · Cited by 315
Machine, Platform, Crowd: Harnessing Our Digital Future
Brynjolfsson, E., & McAfee, A. P. (2017) · Cited by 313
Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World
Bhattacharya, D. (2021) · Strategic Analysis · doi:10.1080/09700161.2021.1918951 · Cited by 311 · cited 2×
“This approach allows us to pay attention not only to the intertwining of human and machine work, augmentation and automation, but also their underlying feedback mechanisms as a possible source of competitive advantage (Davenport and Kirby, 2016; Iansiti and Lakhani, 2020).”
BackgroundBeyond design and use: How scholars should study intelligent technologies
Bailey, D. E., & Barley, S. R. (2019) · Information and Organization · doi:10.1016/j.infoandorg.2019.100286 · Cited by 215
Social Media and the Emergence of Reflexiveness as a New Capability for Open Strategy
Baptista, J., Wilson, A., Galliers, R. D., et al. (2016) · Long Range Planning · doi:10.1016/j.lrp.2016.07.005 · Cited by 188 · cited 1×
“For instance, Baptista et al. (2017b) showed the need for the organization to develop “reflexiveness” to adequately deal with social media data in strategizing.”
BackgroundUsing AI to Enhance Business Operations
Tarafdar, M., Beath, C. M., & Ross, J. W. (2020) · The MIT Press eBooks · doi:10.7551/mitpress/12588.003.0015 · Cited by 174 · cited 1×
“Tarafdar et al. (2019), for example, argues that an organization needs five crucial capabilities: data science competence, business domain proficiency, enterprise architecture expertise, operational IT backbone expertise, and digital inquisitiveness.”
BackgroundBig Data: Extending the Business Strategy Toolbox
Woerner, S. L., & Wixom, B. H. (2015) · Journal of Information Technology · doi:10.1057/jit.2014.31 · Cited by 151 · cited 1×
“, 2019), including the implications for organizational strategy (Constantiou and Kallinikos, 2015; Woerner and Wixom, 2015; Bhimani, 2015) and work in settings ranging from education (Marjanovic and Cecez-Kecmanovic, 2017), policing (Waardenburg et al.”
BackgroundJust How Smart Are Smart Machines
Davenport, T. H., & Kirby, J. (2016) · Dialnet (Universidad de la Rioja) · Cited by 135
Jaton, F. (2017) · Social Studies of Science · doi:10.1177/0306312717730428 · Cited by 119 · cited 1×
“While trained data scientists may be in short supply, “citizen data scientists” (Watson, 2017), subject matter experts (Scheepers et al., 2018) or human labelers (Jaton, 2017) could play crucial roles.”
BackgroundExploring Big Data's Strategic Consequences
Bhimani, A. (2015) · Journal of Information Technology · doi:10.1057/jit.2014.29 · Cited by 108 · cited 1×
“…Krogh, 2018; Rai et al., 2019), including the implications for organizational strategy (Constantiou and Kallinikos, 2015; Woerner and Wixom, 2015; Bhimani, 2015) and work in settings ranging from education (Marjanovic and Cecez-Kecmanovic, 2017), policing (Waardenburg et al., 2018), recruitment…”
BackgroundEditor’s Comments: Next-Generation Digital Platforms: Toward Human–AI Hybrids
Rai, A., Constantinides, P., & Sarker, S. (2019) · Journal of the Association for Information Systems · Cited by 96
Datification, Organizational Strategy, and IS Research: What’s the Score?
Markus, M. L. (2017) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2017.08.003 · Cited by 90 · cited 8×
“…researchers have raised fundamental questions as to the ramifications of both datafication processes (Galliers et al., 2017, Günther et al., 2017; Markus, 2017) and intelligent technologies (Bailey and Barley, 2019; Faraj et al., 2018; von Krogh, 2018; Rai et al., 2019), including the…”
BackgroundInfluentialPreparing for the Cognitive Generation of Decision Support
Watson, H. J. (2017) · Journal of the Association for Information Systems · Cited by 84
Seidel, S., Berente, N., Lindberg, A., Lyytinen, K., & Nickerson, J. V. (2018) · Communications of the ACM · doi:10.1145/3210753 · Cited by 79
Dynamic Reconfiguration in Planetary Exploration: A Sociomaterial Ethnography1
Mazmanian, M., Cohn, M. L., & Dourish, P. (2014) · MIS Quarterly · doi:10.25300/misq/2014/38.3.09 · Cited by 76 · cited 1×
“Reconfiguration, then, is the process by which new configurations of humans and machines and related objects of work practice emerge (Mazmanian et al., 2014, p. 832; Suchman, 2012).”
BackgroundHuman centered automation: oxymoron or common sense?
Sheridan, T. B. (2002) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.1995.537867 · Cited by 73
Galliers, R. D., Newell, S., Shanks, G., & Topi, H. (2017) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2017.08.002 · Cited by 70 · cited 1×
“Information Systems (IS) researchers have raised fundamental questions as to the ramifications of both datafication processes (Galliers et al., 2017, Günther et al., 2017; Markus, 2017) and intelligent technologies (Bailey and Barley, 2019; Faraj et al., 2018; von Krogh, 2018; Rai et al., 2019),…”
BackgroundA Trichordal Temporal Approach to Digital Coordination: The Sociomaterial Mangling of the CERN Grid1
Venters, W., Oborn, E., & Barrett, M. (2014) · MIS Quarterly · doi:10.25300/misq/2014/38.3.13 · Cited by 69 · cited 1×
“Emergent theoretical concepts such as augmentation and assemblage provided a “ repertoire of lenses ” (Venters et al., 2014) which helped us illuminate and validate observations related to regularities such as ‘ training of the robot ’ (the CDO's terms when referring to the algorithm).”
BackgroundMarjanovic, O., & Ćećez-Kecmanović, D. (2017) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2017.07.001 · Cited by 57
Hiring algorithms : An ethnography of fairness in practice
van den Broek, E., Sergeeva, A., & Huysman, M. (2019) · Data Archiving and Networked Services (DANS) · Cited by 50
Brohman, M. K., Addas, S., Dixon, J., & Pinsonneault, A. (2020) · MIS Quarterly · doi:10.25300/misq/2020/15089 · Cited by 44
Taking a Strong Process Approach to Analyzing Qualitative Process Data
Jarzabkowski, P. A., Jane, L., & Spee, P. (2016) · SAGE Publications Ltd eBooks · doi:10.4135/9781473957954.n15 · Cited by 39 · cited 1×
“Here quotes, memos, and early analytical notes were documented to permit a better understanding of what was going on, what the key conditions were, who the key entities were, and what constituted an event of interest (Jarzabkowski et al., 2016).”
BackgroundInternet of Things – Will Humans be Replaced or Augmented?
Pavlou, P. A. (2018) · NIM Marketing Intelligence Review · doi:10.2478/gfkmir-2018-0017 · Cited by 28 · cited 1×
“Indeed, a widespread assumption is that “computers and human beings have complementary strengths and problem-solving capabilities […] and human beings generally outperform machines when dealing with ambiguity, vagueness and incomplete information” (Pavlou, 2018, p. 44-45).”
BackgroundCognitive automation as part of Deakin University's digital strategy
Scheepers, R., Lacity, M. C., & Willcocks, L. P. (2018) · London School of Economics and Political Science Research Online (London School of Economics and Political Science) · Cited by 26
Waardenburg, L., Sergeeva, A., & Huysman, M. (2018) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-04091-8_8 · Cited by 23 · cited 2×
“, 2019), including the implications for organizational strategy (Constantiou and Kallinikos, 2015; Woerner and Wixom, 2015; Bhimani, 2015) and work in settings ranging from education (Marjanovic and Cecez-Kecmanovic, 2017), policing (Waardenburg et al., 2018), recruitment (Broek et al.”
BackgroundCall for Papers: Strategic Perspectives on Digital Work and Organizational Transformation
Baptista, J. (2017) · The Journal of Strategic Information Systems · doi:10.1016/s0963-8687(17)30391-8 · Cited by 9
Eisenhardt, K. M., & Martin, J. A. (2000) · Strategic Management Journal · doi:10.1002/1097-0266(200010/11)21:10/11
Dynamic capabilities and strategic management
Teece, D. J., Pisano, G., & Shuen, A. (1997) · Strategic Management Journal · doi:10.1002/(sici)1097-0266(199708)18:7
Flagged first, then by citations
2 of the 67 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- DalleMule, 2017, What’s your data strategy, Harvard Bus. Rev., 95, 112
- Lebovitz, S., Levina, N., Lifshitz-Assaf, H., 2019. Doubting the Diagnosis: How Artificial Intelligence Increases Ambiguity during Professional Decision Making. Available at SSRN 3480593.
Cited by
Sorted by citations
Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2021.102383 · Cited by 783
Budhwar, P., Malik, A., De Silva, M. T. T., & Thevisuthan, P. (2022) · The International Journal of Human Resource Management · doi:10.1080/09585192.2022.2035161 · Cited by 723
“It is also argued that a feedback loop is needed for learning and innovation in organisations (Grønsund & Aanestad, 2020).”
BackgroundInfluentialAlgorithmic management in a work context
Jarrahi, M. H., Newlands, G., Lee, M. K., Wolf, C. T., Kinder, E., & Sutherland, W. (2021) · Big Data & Society · doi:10.1177/20539517211020332 · Cited by 532
“In short, the deployment of algorithmic management in organizational work introduces novel “human–machine configurations” that could transform relationships between managers and workers and their respective roles (Grønsund and Aanestad, 2020).”
BackgroundAlgorithms as work designers: How algorithmic management influences the design of jobs
Parent-Rocheleau, X., & Parker, S. K. (2022) · Human Resource Management Review · doi:10.1016/j.hrmr.2021.100838 · Cited by 512
Kulkov, I., Kulkova, J., Rohrbeck, R., Menvielle, L., Kaartemo, V., & Makkonen, H. S. (2023) · Sustainable Development · doi:10.1002/sd.2773 · Cited by 543
Metadata
- Authors
- Grønsund, T., & Aanestad, M.
- Affiliations
- University of Oslo (NO)
- Corresponding author
- Grønsund, Tor
- ORCID
- Aanestad, Margunn
- Venue
- The Journal of Strategic Information Systems
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 29
- Issue
- 2
- Pages
- 101614
- ISSN
- 0963-8687 (ISSN-L)
- OpenAlex
- W3037276488
- Cited by
- 364
- References
- 67
- Citations by year
- 2026: 55 · 2025: 70 · 2024: 56 · 2023: 102 · 2022: 42 · 2021: 37 · 2020: 2
- FWCI
- 61.20
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The Journal of Strategic Information Systems (publishedVersion, cc-by-nc-nd)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by-nc-nd)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Funders
- Norges Forskningsråd
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- human-in-the-loop, artificial intelligence adoption, algorithmic auditing, maritime trade, algorithmic prediction, data acquisition architecture, human-algorithm collaboration
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