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Cited by 2,755Impact of AI and Big Data on Business and SocietyArtificial Intelligence ApplicationsAI and HR Technologies

Artificial Intelligence and Management: The Automation–Augmentation Paradox

Raisch, Sebastian, Krakowski, Sebastian·2021·Academy of Management Review
DOI 10.5465/amr.2018.0072
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Abstract

Taking three recent business books on artificial intelligence (AI) as a starting point, we explore the automation and augmentation concepts in the management domain. Whereas automation implies that machines take over a human task, augmentation means that humans collaborate closely with machines to perform a task. Taking a normative stance, the three books advise organizations to prioritize augmentation, which they relate to superior performance. Using a more comprehensive paradox theory perspective, we argue that, in the management domain, augmentation cannot be neatly separated from automation. These dual AI applications are interdependent across time and space, creating a paradoxical tension. Overemphasizing either augmentation or automation fuels reinforcing cycles with negative organizational and societal outcomes. However, if organizations adopt a broader perspective comprising both automation and augmentation, they could deal with the tension and achieve complementarities that benefit business and society. Drawing on our insights, we conclude that management scholars need to be involved in research on the use of AI in organizations. We also argue that a substantial change is required in how AI research is currently conducted in order to develop meaningful theory and to provide practice with sound advice.

Integrity signals

Registry

Crossref · 10.5465/amr.2018.0072

Cites

103 of 103 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

25 of 142 cited sources checked · 10 supported · 0 flagged · accuracy not yet measured

  • Interpretationcitation

    The tight coupling between humans and machines makes it increasingly difficult or impossible to decouple their influence on the resulting model.

    “The resulting tight coupling between humans and machines, with the two influencing one another, makes it increasingly difficult, or even impossible, to decouple their influence on the resulting model (Amershi et al., 2014).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Amershi et al., 2014 source

      Passage [2] says that rapid interaction cycles tightly couple the user and system, making their influence on the resulting model difficult to decouple. The Summary says it is impossible to study the system in isolation from the user, but does not say that decoupling their influence is impossible or becoming increasingly difficult. Neither passage has a page number in our copy. (LLM, conf=0.83)

      Experimental — accuracy not yet measured
  • Premisecitation

    Humans possess the capacity to transfer learning, allowing them to generalize from one task context to another.

    “Humans, on the other hand, possess the capacity to transfer learning, allowing them to generalize from one task context to another (Parisi, Kemker, Part, Kanan, & Wermter, 2019).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Parisi, Kemker, Part, Kanan, & Wermter, 2019 source
  • Premisecitation

    A narrow trade-off perspective does not adequately represent reality.

    “Paradox theory, however, warns that such a narrow trade-off perspective does not adequately represent reality (Smith & Lewis, 2011).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Smith & Lewis, 2011 source
  • Premisecitation

    Augmentation demands continued human involvement and experimentation.

    “Contrary to automation, augmentation demands continued human involvement and experimentation (Amershi et al., 2014).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Amershi et al., 2014 source

      The Interactive Machine Learning section says users can steer models through rapid interaction cycles and experimentation, supporting continued human involvement in the systems the paper discusses. The paper does not establish the broader claim that augmentation, as opposed to automation, necessarily demands that involvement. (LLM, conf=0.78)

      Experimental — accuracy not yet measured
  • Premisecitation

    Owing to their inherent complexity and uncertainty, augmentation efforts often fail.

    “Owing to their inherent complexity and uncertainty, augmentation efforts often fail (Amershi et al., 2014).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Amershi et al., 2014 source

      The section on evaluating interactive machine-learning systems discusses failures of proposed solutions and says the interleaving of human interaction and algorithms makes their causes difficult to identify. It does not say augmentation efforts often fail or attribute their failure to inherent complexity and uncertainty. No page number was available in our copy. (LLM, conf=0.76)

      Experimental — accuracy not yet measured
  • Classified as probably not a substantial claim. 58
  • May combine two claims. 67
  • The quote only partly states this claim. 1

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    Premisecitation

    Overfitting is a key risk in machine learning, meaning a machine may learn a model that explains errors and fails to generalize beyond training data.

    “Overfitting is a key risk in this context, which means that a machine may learn a complete model that also explains the errors, consequently failing to generalize appropriately beyond its training data (Fan, Han, & Liu, 2014).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Fan, Han, & Liu, 2014 source

      Section 3.2 (page unavailable) explains that using too many features accumulates noise and worsens classification of new observations, supporting the risk of poor generalization. It does not explicitly describe a machine learning a model that explains training errors, so that part of the attributed definition is not supported by our copy. (LLM, conf=0.82)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Responsibility requires intentionality, which is an exclusively human ability.

    “Setting objectives is closely related to taking responsibility for the associated tasks and outcomes; consequently, while organizations can extend accountability to machines, responsibility requires intentionality, which is an exclusively human ability (Floridi, 2008).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Floridi, 2008 source

      In ‘Reply to Johnson and Miller’ (page unavailable), Floridi distinguishes human responsibility from accountability that may apply to other agents. In ‘Reply to Grodzinsky, Miller and Wolf’ (page unavailable), he says he has not attributed moral responsibility to artificial agents, but he does not say responsibility requires intentionality or that intentionality is exclusively human; he discusses artificial agents exhibiting ‘intentionality*’. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Machines have no sense of self or purpose, which means managers need to define their objectives.

    “First, machines have no sense of self or purpose, which means managers need to define their objectives (Braga & Logan, 2017).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Braga & Logan, 2017 source

      The Introduction says machines have no sense of self or objectives, and §4.3 says computers lack purpose and goals and function as programmed by human manufacturers and users. The paper does not specifically say that managers need to define machines’ objectives; that is a managerial inference from its argument. (LLM, conf=0.82)

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    Premisecitation

    In complex cases, rule-based automation is impossible, but managers could use an augmentation approach to explore the problem further.

    “In such cases, rule-based automation is impossible, but managers could use an augmentation approach to explore the problem further (Holzinger, 2016).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Holzinger, 2016 source

      The Introduction says some hard medical problems make full automation difficult or even impossible, and that human experts working with interactive machine learning can help discover new insights. It does not say rule-based automation is impossible in complex cases generally, or specifically propose this approach for managers. (LLM, conf=0.87)

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    • Rests on an assumption: Most managerial tasks are more complex, and their rules and models are not fully known or readily available.

  • Classified as probably not a substantial claim.

    Interpretationcitation

    Augmentation is a coevolutionary process during which humans learn from machines and machines learn from humans.

    “Augmentation is therefore a coevolutionary process during which humans learn from machines and machines learn from humans (Amershi, Cakmak, Knox, & Kulesza, 2014;Rahwan et al., 2019).”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites Amershi, Cakmak, Knox, & Kulesza, 2014 source
    • cites Rahwan et al., 2019 source

      The Collective machine behaviour section says machines may learn from humans and humans may learn from machines, with feedback affecting both. Human-machine co-behaviour also discusses reciprocal influence, but the paper does not identify augmentation specifically as a coevolutionary process; it describes mutual learning as a possibility. (LLM, conf=0.84)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    While differentiation allows engaging in both automation and augmentation, integration enables finding linkages that transcend the two poles.

    “While such differentiation allows for engaging in both automation and augmentation, integration enables the finding of linkages that transcend the two poles (Smith & Lewis, 2011).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Smith & Lewis, 2011 source

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    Interpretationcitation

    The juxtaposition of automation and augmentation stimulates learning and fosters adaptability, allowing the combination of machine rationality and human intuition, which enables more comprehensive information processing and better decisions.

    “The two AI approaches' juxtaposition stimulates learning and fosters adaptability, allowing the combination of (machine) rationality and (human) intuition, which enables more comprehensive information processing and better decisions (Calabretta, Gemser, & Wijnberg, 2017).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Calabretta, Gemser, & Wijnberg, 2017 source

      Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

      Experimental — accuracy not yet measured

  • Classified as probably not a substantial claim.

    Premisecitation

    A first step toward enabling a virtuous cycle is acceptance of tensions as paradoxical.

    “A first step toward enabling such a virtuous cycle is the acceptance of the tensions as paradoxical (Smith & Lewis, 2011).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Smith & Lewis, 2011 source

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    Interpretationcitation

    Because emotions and subjective factors affect humans, augmentation is difficult or impossible to replicate, so every augmentation initiative is a new learning effort.

    “Since emotions and other subjective factors affect humans, augmentation is difficult or even impossible to replicate, which means every augmentation initiative is a new learning effort (Holzinger, 2016).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Holzinger, 2016 source

      Section 3 (page unavailable) says experiments and evaluations of interactive machine learning can be difficult or even impossible to replicate because human agents are subjective and individual. It does not specifically identify emotions as the cause or say that every augmentation initiative is a new learning effort. (LLM, conf=0.85)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Interpretationcitation

    Humans in the loop could explain the system's outputs, rendering algorithmic decisions more accountable and transparent.

    “Furthermore, humans”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Binns, Van Kleek, Veale, Lyngs, Zhao, & Shadbolt, 2018 source

      The Introduction (p. 1) says human decision-makers can be asked to rationalise their decisions and held accountable. The paper also discusses explanations of algorithmic outputs as a route to transparency and accountability (Interpreting intelligent systems, p. 2), but it does not say that humans in the loop would explain those outputs. (LLM, conf=0.83)

      Experimental — accuracy not yet measured

  • Classified as probably not a substantial claim.

    Premisecitation

    Tensions' systemic nature is a central tenet of paradox theorizing.

    “Tensions' systemic nature is a central tenet of paradox theorizing (Jarzabkowski, Bednarek, Chalkias, & Cacciatori, 2019;Smith & Lewis, 2011).”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites Jarzabkowski, Bednarek, Chalkias, & Cacciatori, 2019 source
    • cites Smith & Lewis, 2011 source

      Checked before — its earlier verdict is held back until a new check runs.

  • May combine two claims.

    Interpretationcitation

    While machine algorithms shape human actions, humans shape these algorithms through their actions, creating a recursive relationship.

    “While machine algorithms shape human actions, humans shape these algorithms through their actions, which create a recursive relationship (Beer, 2017).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Beer, 2017 source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Premisecitation

    In the digital age, human and machine agents are so closely intertwined in hybrid collectives that their relations determine their actions.

    “In order to fully understand the automation-augmentation paradox's societal implications, scholars could adopt a relational ontology which accepts that, in the digital age, human and machine agents are so closely intertwined in hybrid collectives that their relations determine their actions (Floridi & Taddeo, 2016).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Floridi & Taddeo, 2016 source

      The Introduction says that the ethics of data, algorithms and practices are intertwined, and the Abstract discusses interactions among hardware, software and data. Neither passage addresses a relational ontology in which human and machine agents form hybrid collectives or their relations determine their actions. Searches for “hybrid collectives” and “relations determine their actions” found no supporting passage in our copy; page numbers were not available. (LLM, conf=0.75)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S2 (checkable).

    Premisecitation

    Complexifying theories is essential for understanding complex phenomena.

    “Complexifying theories is essential for understanding complex phenomena (Tsoukas, 2017), because”
    Quote in the paperNot a substantial claim1 of 2 sources checked
    • cites Tsoukas, 2017 source
    • cites Weick, 2007: 16 source

  • May combine two claims.

    Findingnone given

    In the Symrise case, machines can neither smell nor fully predict how humans will perceive new fragrances, or the emotions and memories they trigger.

    “In the Symrise case, machines can neither smell nor fully predict how humans will perceive new fragrances, or the emotions and memories they trigger.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    Master perfumers have the skills to smell and predict fragrance perception and can tell a compelling story about a fragrance and its meaning, which is important for its commercialization.

    “Master perfumers have these skills and can also use them to tell a compelling story about a fragrance and its meaning, which is important for its commercialization.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    Unilever saved 70,000 person-days of interviewing and assessing candidates, resulting in annual cost savings of GBP 1 million and a reduction of time-to-hire by 90% (from an average of four months to two weeks).

    “At the same time, the company managed to save 70 000 person-days of interviewing and assessing candidates, which resulted in annual cost savings of GBP 1 million and a reduction of the time-to-hire by 90% (from an average of four months to two weeks) (Feloni, 2017).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Feloni, 2017

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

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    Findingcitation

    Unilever reported that the combination of automation and augmentation led to a 16% increase in new hires' ethnic and gender diversity, making it the most diverse class to date.

    “Unilever has reported that the combination of automation and augmentation has led to a 16% increase in new hires' ethnic and gender diversity, making it the”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Feloni, 2017

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    The three books advised organizations to prioritize augmentation, which they related to superior performance.

    “Their combined advice was that organizations should prioritize augmentation, which the authors related to superior performance.”
    • Also stated in: § REVIEWED MATERIALS · plain
      “Building on this analysis, the three books have advised organizations to focus on augmentation rather than on automation.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Daugherty & Wilson, 2018

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Davenport & Kirby, 2016

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim.

    Premisecitation

    The three books distinguished two broad AI applications in organizations: automation and augmentation.

    “The authors distinguished two broad AI applications in organizations: automation and augmentation.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Brynjolfsson & McAfee, 2014

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Daugherty & Wilson, 2018

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Davenport & Kirby, 2016

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The two more recent books provided managers with ample advice on how to develop and implement an augmentation strategy.

    “In addition, the two more recent books (Daugherty & Wilson, 2018;Davenport & Kirby, 2016) provided managers with ample advice on how to develop and implement such an augmentation strategy.”
    • Also stated in: § REVIEWED MATERIALS · plain
      “The two more recent books also provided managers with ample advice on how to develop and implement such an augmentation strategy in their organizations.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Daugherty & Wilson, 2018

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Davenport & Kirby, 2016

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim.

    Premisenone given

    The three books have developed a common AI narrative for practicing managers.

    “The three books have developed a common AI narrative for practicing managers.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Brynjolfsson & McAfee, 2014

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Daugherty & Wilson, 2018

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Davenport & Kirby, 2016

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    Organizations adopting a broader perspective comprising both automation and augmentation can deal with the tension and achieve complementarities that benefit business and society.

    “However, if organizations adopt a broader perspective comprising both automation and augmentation, they could deal with the tension and achieve complementarities that benefit business and society.”
    • Also stated in: § Abstract · plain
      “However, organizations adopting a broader perspective comprising both automation and augmentation are not only able to deal with the tension but also achieve complementarities that benefit business and society.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Premisecitation

    Managers need to use their intuition and common-sense judgment to make a final decision about the most desirable option.

    “Managers need to use their intuition and common-sense judgment-reconciling the machine output with reality-to make a final decision about the most desirable option (Brynjolfsson & McAfee, 2014: 92).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Brynjolfsson & McAfee, 2014

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    Organizations may opt for one or the other application at a given point in time, which softens the underlying tension temporarily but fails to resolve it.

    “Organizations may opt for one or the other application at a given point in time, which softens the underlying tension temporarily but fails to resolve it.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Engagement with one side of a paradox may create conditions for the other's existence, and over time there is mutual influence with swings from one side to the other.

    “Engagement with one side of the tension may set the stage, or even create the conditions necessary, for the other's existence; in addition, over time there is often a mutual influence between the opposing forces, with swings from one side to the other (Poole & van de Ven, 1989).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Poole & van de Ven, 1989 source

  • May combine two claims.

    Interpretationreasoning

    If organizations automate a task hitherto reserved for humans, this change could affect other closely related human tasks and lead managers to start interacting with machines.

    “If organizations automate a task hitherto reserved for humans, this change could affect other, closely related human tasks, and lead managers to start interacting with machines.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Managerial tasks are generally embedded in a managerial process with interdependencies between tasks.

  • May combine two claims.

    Interpretationreasoning

    Increasing the temporal and spatial scale of analysis reveals that automation and augmentation are not only contradictory but also interdependent in the management domain.

    “If we increase our analysis's temporal scale (from one point in time to its evolution over time) and spatial scale (from one to multiple tasks), we comprehend that, in the management domain, the two AI applications are not only contradictory but also interdependent.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    The three books described the relationship between automation and augmentation as a trade-off decision.

    “The three books described the relationship between automation and augmentation as a trade-off decision: Organizations attempting to use AI have the choice of either automating the task or using an augmentation approach.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Brynjolfsson & McAfee, 2014

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Daugherty & Wilson, 2018

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Davenport & Kirby, 2016

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    HR managers can use emotional and social intelligence to provide a human touch, build true relationships, entice talent, and convince others to support decisions.

    “For example, HR managers can use their emotional and social intelligence to provide a”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Davenport & Kirby, 2016: 74

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    Managers will therefore remain involved in complex managerial processes and interact with machines on a wide range of tasks.

    “Managers will therefore remain involved in these processes and interact with machines on a wide range of tasks.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    The two AI applications in management are not only contradictory but also interdependent.

    “We conclude that the two AI applications in management are not only contradictory but also interdependent.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    Automation and augmentation are contradictory because organizations choose either one or the other approach to address a given task at a specific point in time.

    “Automation and augmentation are contradictory, because organizations choose either one or the other approach to address a given task at a specific point in time.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Machines do not possess human senses, perceptions, emotions, and social skills.

    “Fourth, machines do not possess human senses, perceptions, emotions, and social skills (Braga &”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Braga &

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    Relatively routine and well-structured tasks can be automated, while more complex and ambiguous tasks cannot be automated but can be addressed through augmentation.

    “Relatively routine and well-structured tasks can be automated, while more complex and ambiguous tasks cannot, but can be addressed through augmentation (Brynjolfsson & McAfee, 2014: 138ff;Daugherty & Wilson, 2018: 107ff;Davenport & Kirby, 2016: 34ff).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Brynjolfsson & McAfee, 2014

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Daugherty & Wilson, 2018

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Davenport & Kirby, 2016

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    Eventually, organizations will face the same choice again, demonstrating the two applications' interdependent nature and cyclical relationship.

    “Eventually, organizations will face the same choice again, demonstrating the two applications' interdependent nature and cyclical relationship.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    While a transition to automation relaxes the tension temporarily, the issue resurfaces when conditions change over time.

    “While such a transition relaxes the tension temporarily, the issue resurfaces when conditions change over time (Smith & Lewis, 2011).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Smith & Lewis, 2011 source

      Checked before — its earlier verdict is held back until a new check runs.

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    The books' trade-off perspective is largely limited to a given task at a specific point in time.

    “The arguments that the books have provided are difficult to refute, but their perspective is largely limited to a given task at a specific point in time.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Resolution involves seeking responses to paradoxical tensions through a combination of differentiation and integration practices.

    “Resolution involves seeking responses to paradoxical tensions through a combination of differentiation and integration practices (Poole & van de Ven, 1989).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Poole & van de Ven, 1989 source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Organizations benefit if they differentiate between and integrate across automation and augmentation.

    “We suggest that organizations benefit if they differentiate between and integrate across automation and augmentation.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Prior studies show that maintaining overall human responsibility reduces human bias and prevents human-machine collaboration biases.

    “Prior studies have shown that maintaining overall human responsibility not only reduces human bias (Larrick, 2004), but also prevents human-machine collaboration biases (Skitka et al., 2000).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Larrick, 2004 source
    • cites Skitka et al., 2000 source

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Differentiation allows organizations to benefit from both AI applications' unique benefits.

    “Differentiation allows organizations to benefit from both AI applications' unique benefits.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Once actors accept that automation and augmentation can and should coexist, they can explore their dynamic relationship mindfully as part of the organization's vision or guiding principles.

    “Once actors accept that automation and augmentation can and should coexist, they can explore the dynamic relationship between them mindfully, which could be part of their organization's vision or guiding principles regarding the use of AI in management.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Human experts are either made redundant through automation or lose specific skills for tasks they no longer pursue.

    “Human experts are either made redundant through automation or they lose their specific skills regarding the tasks they no longer pursue.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Assigning overall responsibility for processes to humans leads to increased vigilance and verification behavior, consideration of a wider range of inputs, and greater cognitive complexity.

    “As these studies have shown, assigning the overall responsibility for processes to humans leads to increased vigilance and verification behavior, the consideration of a wider range of inputs prior to making decisions, and the use of greater cognitive complexity when processing such information.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    Continued human involvement implies that human biases persist, so augmentation outcomes are never fully consistent, reliable, or persistent.

    “Furthermore, the continued human involvement implies that human biases persist, which means augmentation outcomes are never fully consistent, reliable, or persistent (Huang, Hsu, & Ku, 2012).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Huang, Hsu, & Ku, 2012 source

  • May combine two claims.

    Interpretationreasoning

    In contexts of high ambiguity, complexity, and rare events, automation and augmentation provide different, partly conflicting, but also complementary logics and functionalities that organizations require.

    “In such contexts, automation and augmentation provide different, partly conflicting, but also complementary logics and functionalities that organizations require.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Paradox theory suggests that managing tensions through acceptance and resolution fosters sustainability.

    “Paradox theory suggests that managing tensions through the dynamic strategies of acceptance and resolution fosters sustainability (Smith & Lewis, 2011).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Smith & Lewis, 2011 source

      Checked before — its earlier verdict is held back until a new check runs.

  • May combine two claims.

    Interpretationreasoning

    Automation is associated with short-term thinking, loss of human expertise, and lock-in effects that together fuel a reinforcing cycle making search activities increasingly difficult.

    “To conclude, while automation can free up resources for potential search activities, it is also associated with short-term thinking, the loss of human expertise, and lock-in effects that, together, fuel a reinforcing cycle, which makes it increasingly difficult for organizations to implement such search activities.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationreasoning

    The use of AI in management causes an organizational tension that persists across time and space.

    “While these solutions may be appropriate within the strict boundaries that time and space impose, the use of AI in management causes an organizational tension that persists across time and space.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Interpretationnone given

    Automation enables organizations to drive cost efficiencies, establish faster processes, and ensure greater information-processing rationality and consistency.

    “Automation enables organizations to drive cost efficiencies, establish faster processes, and ensure greater information-processing rationality and consistency.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Humans' cognitive limitations restrict their search field, while machines do not face such information-processing limitations.

    “Their cognitive limitations mean that humans' search field is restricted, while machines do not face such information-processing limitations (Davenport & Kirby, 2016: 17).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Davenport & Kirby, 2016: 17

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    Organizations will experience a persistent tension between automation and augmentation, although the optimal balance depends on contingencies such as AI expertise and environmental contexts.

    “While the optimal balance between automation and augmentation depends on contingencies, such as organizations' AI expertise and the nature of the environmental contexts they face, organizations will experience a persistent tension between these interrelated applications of AI in management.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    By switching, the machine's independent output can challenge human intuition and judgment, with human feedback enabling further rounds of machine analysis.

    “By switching, the machine's independent output can be used to challenge human intuition and judgment, with human feedback enabling further rounds of machine analysis (Hoc, 2001).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Hoc, 2001 source

  • Classified as probably not a substantial claim. May combine two claims.

    Premisereasoning

    By managing paradox, organizations enable learning and creativity, promote flexibility and reliance, and unleash human potential.

    “By managing paradox, organizations enable learning and creativity, promote flexibility and reliance, and unleash human potential.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Prior research shows that automation can deskill humans, make them complacent, and diffuse their sense of responsibility.

    “Prior research has shown that automation can deskill humans, make them complacent, and diffuse their sense of responsibility (Parasuraman & Manzey, 2010;Skitka, Mosier, & Burdick, 2000).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Parasuraman & Manzey, 2010 source
    • cites Skitka, Mosier, & Burdick, 2000 source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Managers limiting their perspective to either automation or augmentation risk developing partial and incomplete managerial solutions.

    “Managers limiting their perspective to either automation or augmentation risk developing partial and incomplete managerial solutions.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Stimulating exchange between organizational actors with different perspectives could develop more complex understandings of the phenomenon.

    “Stimulating an exchange between organizational actors with different perspectives, such as data scientists and business managers, could develop more complex understandings of the phenomenon.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Paradox scholars acknowledge that narrow attention to one pole can trigger unintended organizational and societal consequences.

    “However, paradox scholars have also acknowledged that narrow organizational attention to just one of the tensions' poles can trigger unintended organizational and societal consequences (Schad & Bansal, 2018).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Schad & Bansal, 2018 source

  • May combine two claims.

    Interpretationreasoning

    Excluding humans at the automation stage may help break path dependencies and promote greater novelty.

    “Excluding humans at this stage may help break path dependencies and promote greater novelty.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Augmentation provides complementary benefits arising from the mutual enhancing of human and machine skills.

    “As described above, augmentation provides complementary benefits arising from the mutual enhancing of human and machine skills.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Retaining human responsibility for managerial processes promotes integration, which transcends automation and augmentation.

    “Consequently, retaining human responsibility for managerial processes promotes integration, which transcends automation and augmentation.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Paradox theory offers a constructive response to tensions by envisioning a virtuous cycle where organizations overcome defensiveness, embrace tensions, and find synergies that accommodate and transcend opposing poles.

    “Paradox theory offers a more constructive response to tensions by envisioning a virtuous cycle, with organizations overcoming their defensiveness to embrace these tensions and viewing them as an opportunity to find synergies that accommodate and transcend the opposing poles (Schad et al., 2016).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Schad et al., 2016 source

  • Classified as probably not a substantial claim.

    Premisecitation

    Acceptance must be complemented with a subsequent resolution strategy.

    “While acceptance lays the groundwork for virtuous cycles, it has to be complemented with a subsequent resolution strategy (Smith & Lewis, 2011).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Smith & Lewis, 2011 source

      Checked before — its earlier verdict is held back until a new check runs.

  • May combine two claims.

    Interpretationcitation

    Organizations experiencing augmentation failure may reinforce augmentation efforts to legitimize large investments, escalating commitment, with failure leading to continued augmentation and continued failure.

    “To legitimize their large augmentation investments, organizations experiencing failure may be tempted to reinforce their augmentation efforts further, which could escalate their commitment (Sabherwal & Jeyaraj, 2015;Staw, 1981), with failure leading to continued augmentation, in turn leading to continued failure.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Sabherwal & Jeyaraj, 2015 source
    • cites Staw, 1981 source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    By juxtaposing and integrating their different perspectives, theories, and methodologies, computer scientists and management scholars can jointly create a foundation for meaningful research on the use of AI in management.

    “By juxtaposing and integrating their different perspectives, theories, and methodologies, computer scientists and management scholars can jointly create a foundation for meaningful research on the use of AI in management.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims. The quote only partly states this claim.

    Interpretationreasoning

    With respect to managerial tasks, humans will remain in the loop and interact closely with machines.

    “With respect to managerial tasks, humans will remain”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    The limited work to date has provided separate accounts with clear-cut contrasts between augmentation and automation.

    “The limited work to date has provided separate accounts with clear-cut contrasts between augmentation and automation.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationnone given

    Differentiation allows for independent analyses with and without human involvement.

    “Differentiation allows for independent analyses with (i.e., augmentation) and without (i.e., automation) human involvement.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationreasoning

    Management scholars are particularly well-equipped to study human-machine interactions in real-world settings and to explore their organizational and societal implications.

    “Management scholars are particularly well-equipped to study these human-machine interactions in real-world settings, as well as to explore the organizational and societal implications thereof.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    While augmentation allows identifying patterns in large volumes of patient data, automation makes the design and manufacture of tailored drugs economically viable.

    “While augmentation allows for identifying patterns in large volumes of patient data, automation makes the design and manufacture of tailored drugs economically viable.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    Currently, computer scientists, roboticists, and engineers are the scholars most commonly studying AI.

    “Currently, computer scientists, roboticists, and engineers are the scholars most commonly studying AI.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationreasoning

    Automation could free up scarce resources for augmentation, which could help identify the rules or models that enable automation.

    “Automation could free up scarce resources for augmentation, which, in turn, could help identify the rules or models that enable automation.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationreasoning

    These applications provide complementary functionalities that are both potentially useful for organizations.

    “These applications provide complementary functionalities that are both potentially useful for organizations.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    A one-sided focus on automation could cause extensive job losses and deskilling of managers who relinquish tasks to machines, leading to rising unemployment and social inequality.

    “First, a one-sided focus on automation could cause extensive job losses and result in the deskilling of managers who relinquish tasks to machines, which could lead to the further risks of rising unemployment and social inequality (Brynjolfsson & McAfee, 2014: 171; see also Autor, 2015).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Brynjolfsson & McAfee, 2014: 171

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Autor, 2015 source

  • May combine two claims.

    Interpretationcitation

    Integration ensures that machine outputs challenge humans and human inputs challenge machines, allowing mutual learning and debiasing.

    “Integration ensures that machine outputs are used to challenge humans, and human inputs to challenge machines (Hoc, 2001), allowing for mutual learning (Panait & Luke, 2005) and debiasing (Larrick, 2004).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Hoc, 2001 source
    • cites Panait & Luke, 2005 source
    • cites Larrick, 2004 source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    This virtuous cycle could help organizations reduce the digital transition's negative effects on their employees and the labor market at large.

    “This virtuous cycle could help organizations reduce the digital transition's negative effects on their employees and the labor market at large.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    If organizations adopt a more comprehensive perspective, the outcomes could be positive for both business and society.

    “However, if organizations adopt a more comprehensive perspective, the outcomes could be positive for both business and society.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationreasoning

    Together, AI's dual applications in management provide organizations with a range of benefits that neither automation nor augmentation can provide alone.

    “Together, AI's dual applications in management provide organizations with a range of benefits that neither automation nor augmentation can provide alone.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationreasoning

    Researchers need to accept that automation and augmentation are interdependent AI applications in management that cannot be neatly separated and designated as either good or evil.

    “Similarly, researchers need to accept that automation and augmentation are interdependent AI applications in management that cannot be neatly separated and designated as either good or evil.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Interpretationreasoning

    These laboratory settings permit methodologies aimed at maximizing algorithmic performance but disregard the role of humans and wider organizational and societal implications.

    “These settings permit the use of methodologies aimed at maximizing algorithmic performance, but disregard the role of humans and the wider organizational and societal implications.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Computer scientists' primary objective is to automate as far as possible because they often regard humans as a mere disturbance in the system.

    “Their primary objective is to automate as far as possible, because they often regard humans as”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Cummings, 2014: 62 source

  • May combine two claims.

    Interpretationreasoning

    The central argument of the review essay is that automation and augmentation are not only separable and conflicting but fundamentally interdependent.

    “The central argument of this review essay is that automation and augmentation are not only separable and conflicting but in fact fundamentally interdependent.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationnone given

    The analysis suggests that the jury is out on whether the use of AI in management will turn out to be a blessing or a curse.

    “Our analysis of the automation-augmentation paradox suggests that the jury is out on whether the use of AI in management will turn out to be a blessing or a curse.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    One-sided augmentation is likely to cause another digital divide, with social tensions between those with capabilities and resources for augmentation and those without.

    “Conversely, onesided augmentation is likely to cause another”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Norris, 2001 source
    • cites Brynjolfsson & McAfee, 2014: 134f

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Brynjolfsson & Mitchell, 2017 source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Adopting the automation-augmentation model uncritically obscures how automation and augmentation intertwine in managerial practice.

    “However, adopting this intuitively appealing model uncritically obscures how automation and augmentation intertwine in managerial practice.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationreasoning

    The complex interaction between these varied AI applications over time could have both positive and negative organizational and societal implications.

    “The complex interaction between these varied AI applications over time could have both positive and negative organizational and societal implications.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The technological and social worlds are merging, meaning computer scientists and management scholars no longer study separate phenomena.

    “The technological and the social worlds are merging (Orlikowski, 2007), which means that computer scientists and management scholars no longer study separate phenomena.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Orlikowski, 2007 source

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    The automation-augmentation model's popularity stems largely from its clear boundaries and simplicity.

    “The automation-augmentation model's popularity stems largely from its clear boundaries and simplicity.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisereasoning

    Paradoxes are embedded in open systems and their implications extend beyond a single organization's boundaries.

    “Paradoxes are embedded in open systems and their implications extend beyond a single organization's boundaries.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    Automation takes humans out of the loop, reducing human biases and promising greater equality and fairness.

    “Automation takes humans”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Automation and augmentation are not good or evil per se.

    “Automation and augmentation are not good or evil per se.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    The prevailing trade-off perspective is overdrawn; viewed as a paradox, augmentation is both the driver and outcome of automation, and the two applications develop and fold into one another across space and time.

    “We suggest that the prevailing trade-off perspective is overdrawn; viewed as a paradox, augmentation is both the driver and outcome of automation, and the two applications of AI develop and fold into one another across space and time.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationnone given

    This introduction of AI in practice will profoundly change the nature of management.

    “This introduction of AI in practice will profoundly change the nature of management.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Managers in key organizational domains, including customer management, human resources, marketing, product innovation, sales, and strategy, have already started working closely with intelligent machines on automated and augmented tasks.

  • May combine two claims.

    Interpretationreasoning

    It may be difficult or even impossible to distinguish between humans and machines or the respective learning and actions of each.

    “It may therefore be difficult, or even impossible, to distinguish between humans and machines or the respective learning and actions of each.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Inputs from agents within and outside the organization impact the automation and augmentation process, which can have wide-reaching societal implications.

    “Inputs from agents within and outside the organization thereby impact the automation and augmentation process, which, in turn, can have wide-reaching societal implications.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    While machines have fundamental limitations, their actions enjoy far-reaching autonomy because humans delegate knowledge tasks to machine agents and allow agents to act on their behalf.

    “While machines have fundamental limitations, their actions nevertheless enjoy far-reaching autonomy, because humans delegate knowledge tasks to these machine agents and allow agents to act on their behalf (Rai, Constantinides, & Sarker, 2019).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Rai, Constantinides, & Sarker, 2019

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    This will lead to a more comprehensive and ultimately more rigorous and relevant discussion of AI's organizational and societal implications.

    “This will lead to a more comprehensive and, ultimately, more rigorous and relevant discussion of AI's organizational and societal implications.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Distributed morality relies on shared ethical norms developed through collaborative practices.

    “Such a perspective will enable a discussion of”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Mittelstadt et al., 2016 source

  • May combine two claims.

    Interpretationreasoning

    It is difficult to apportion accountability for outcomes to specific actors in hybrid organizational systems, creating an accountability gap.

    “Consequently, it is difficult to apportion accountability for outcomes to specific actors, which creates an”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Mittelstadt et al., 2016 source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationcitation

    More encompassing perspectives, such as paradox theory or systems theory, offer a vantage point from which researchers can observe the dynamic interplay between automation and augmentation.

    “More encompassing perspectives, such as paradox theory (Schad et al., 2016) or systems theory (Sterman, 2000), offer a vantage point from which researchers can observe the dynamic interplay between automation and augmentation.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Schad et al., 2016 source
    • cites Sterman, 2000

  • May combine two claims.

    Interpretationcitation

    Intelligent machines can introduce statistical biases and have other limitations that humans do not have.

    “Nonetheless, they can introduce statistical biases and have other limitations that humans do not have (Elsbach & Stigliani, 2019).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Elsbach & Stigliani, 2019 source

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Premisereasoning

    Management scholars need to acknowledge that humans are no longer the sole agents in management, although most theories to date focus exclusively on human agency.

    “At the most basic level, management scholars need to acknowledge that humans are no longer the sole agents in management, although most theories to date focus exclusively on human agency.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationreasoning

    The use of automation and augmentation in management relates to the core of management scholars' research.

    “While management scholars may (and should) become involved in the broader discussion of AI and its societal implications, the use of automation and augmentation in management relates to the core of management scholars' research.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Augmentation implies close collaboration between humans and machines.

    “Augmentation therefore implies close collaboration between humans and machines.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Several current projects are aimed at deploying AI-based agents capable of perceiving and responding to emotional cues.

    “Several current projects are aimed at deploying AIbased agents capable of perceiving and responding to emotional cues.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites McDuff & Czerwinski, 2018 source

  • May combine two claims.

    Premisecitation

    In the JP Morgan Chase example, HR managers engage in augmentation to initially set the machine's objectives and constraints and to subsequently select from the candidates that the machine suggested.

    “The talent acquisition process in our JP Morgan Chase example functions similarly: HR managers now engage in augmentation to initially set the machine's objectives and constraints (objective setting) and to subsequently select from the candidates that the machine suggested (candidate selection)(Riley, 2018).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Riley, 2018

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Interpretationnone given

    Intelligent machines used for automation do not have these limitations; they have practically unlimited information-processing capacity and exhibit perfectly consistent behavior.

    “However, intelligent machines used for automation do not have these limitations; they have practically unlimited information-processing capacity and exhibit perfectly consistent behavior.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    General human skills that complement machines, such as creativity, common sense, and advanced communication, as well as integration skills such as AI literacy, will gain further importance in an era of automation and augmentation.

    “At the same time, general human skills that complement machines, such as creativity, common sense, and advanced communication (Davenport & Kirby, 2016: 30), as well as integration skills such as AI literacy, will gain further importance in an era of automation and augmentation (Daugherty & Wilson, 2018: 191).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Davenport & Kirby, 2016

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Daugherty & Wilson, 2018

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisenone given

    Managers define objectives, set constraints, generate and choose training data, and provide machines with feedback.

    “Managers define the objectives, set constraints, generate and choose the training data, and provide machines with feedback.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationreasoning

    Since automation and augmentation are interdependent, this interaction spreads across organizations.

    “Since automation and augmentation are interdependent, this interaction spreads across organizations.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    Accepting and embracing complexity allows for studying AI and its managerial applications in the wild.

    “Accepting and embracing this complexity allows for studying AI and its managerial applications”
    Quote in the paperNot a substantial claim
112 of 112

  • The paper relies on this without support.

    AI is becoming increasingly pervasive in managerial contexts.

    “Nonetheless, these scholars' understanding will be required, because AI is becoming increasingly pervasive in managerial contexts.”

  • The paper relies on this without support.

    Most managerial tasks are more complex, and their rules and models are not fully known or readily available.

    “However, most managerial tasks are more complex, and the rules and models are therefore not fully known or readily available.”

  • The paper relies on this without support.

    Managerial tasks are generally embedded in a managerial process with interdependencies between tasks.

    “However, in practice managerial tasks rarely occur in isolation, but are generally embedded in a managerial process.There are interdependencies between the various tasks constituting this process.”

  • The paper relies on this without support.

    The three reviewed business books provide a suitable basis for identifying and analyzing the automation-augmentation tension in management.

    “Inspired by three recent business books, we have explored the emergent use of AI-based applications in organizations to automate and augment managerial tasks.”

  • The paper relies on this without support.

    The Symrise, UBS, and Unilever examples are representative of how organizations manage the automation-augmentation paradox.

    “A recent initiative at UBS's investment-banking division illustrates this virtuous cycle.”

  • The paper relies on this without support.

    Managers in key organizational domains, including customer management, human resources, marketing, product innovation, sales, and strategy, have already started working closely with intelligent machines on automated and augmented tasks.

    “Managers in key organizational domains, including customer management, human resources, marketing, product innovation, sales, and strategy have already started working closely with intelligent machines on automated and augmented tasks.”
6 of 6

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?

  • Human-AI augmentation is described as an expansion of expertise or knowledge where humans and machines combine complementary strengths to multiply their capabilities.

    “Indeed, scholars describe human-AI augmentation as an expansion of expertise or knowledge where humans and machines ' combine their complementary strengths ' to ' multiply their capabilities ' (Raisch and Krakowski 2021, p. 6).”

    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 Raisch and Krakowski 2021

  • The LLM decision process, at least under the current prompt design and judge model, was able to maintain high decision quality across structures.

    “It suggests that the LLM decision process, at least under the current prompt design and judge model, was able to maintain high decision quality across structures.”

    From Semantic Camouflage in Artificial Organizations: A Real-LLM Multi-Agent Simulation of Information Distortion and Audit (2026) · cites this paper as Raisch & Krakowski, 2021

    The Paradoxical Tension and Outcomes passages discuss AI-assisted managerial decisions, but not an LLM decision process tested across structures. Searches for prompt design, judge models, and decision quality across structures found no passage addressing that result. Page numbers were unavailable in our copy. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

  • The adoption of AI within HRM processes and wider organisation will impact employees in different ways, such as job substitution, training needs, uncertainty regarding roles and responsibilities, limited understanding about how and why AI will be used, trust and confidence, formation of project teams where AI and HI co-exist, and concerns about career progression and development.

    “Our review found that the adoption of AI within HRM processes and wider organisation will impact employees in different ways, such as job substitution, training needs, and uncertainty regarding roles and responsibilities (Frey & Osborne, 2017), limited understanding about how and why AI will be used (Raisch & Krakowski, 2020), trust and confidence (Gunning, 2017), formation of project teams where”

    From Unlocking the value of artificial intelligence in human resource management through AI capability framework (2023) · cites this paper as Raisch & Krakowski, 2020

    The citation is attached specifically to employees’ limited understanding of how and why AI will be used. The Discussion (page not available) calls for scholars to better understand AI in management and discusses transparency, but does not say employees have that limited understanding. Searches for employee understanding, AI-use purposes, and explainability found no passage addressing the attributed point. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

  • Augmentation involves a mutual learning process through which both humans and AI learn from each other and coevolve.

    “After all, these tools are assistants that are designed and trained to augment individual workers, and augmentation involves a mutual learning process through which both humans and AI learn from each other and hence coevolve (Raisch & Krakowski, 2020).”

    From Artificial intelligence and knowledge management: A partnership between human and AI (2023) · cites this paper as Raisch & Krakowski, 2020

  • Automation is not necessarily the opposite of human augmentation and can in fact foster augmentation.

    “Automation is not necessarily the opposite of human augmentation and can in fact foster augmentation (Raisch & Krakowski, 2020).”

    From Artificial intelligence and knowledge management: A partnership between human and AI (2023) · cites this paper as Raisch & Krakowski, 2020

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Example transition is described in the wrong direction

    Minor

    The paper introduces the two examples as transitions from automation to augmentation, but the examples describe augmentation first and automation afterward.

1 of 1

Cites

Flagged first, then by citations

Research works printed but not linked: 13

  1. Bergstein B., 2019, MIT Technology Review, 122, 82
  2. Cariani P., 2010, Constructivist Foundations, 5, 86
  3. Davenport T. H., 2016, Only humans need apply: Winners and losers in the age of smart machines
  4. Derrida J., 1967, De la grammatologie
  5. Ford M., 2015, The rise of the robots: Technology and the threat of mass unemployment
  6. Goodwin, R., Maria, J., Das, P., Horesh, R., Segal, R., Fu, J. & Harris, C. 2017. AI for fragrance design. Proceedings of the Machine Learning for Creativity and Design Workshop at NIPS . San Diego, CA: Neural Information Processing Systems Foundation.
  7. Greenwald H. S., 2017, Frontiers in Robotics and AI, 3, 1
  8. Marr B., 2018, Forbes
  9. Mitchell T. M., 1997, Machine learning
  10. Press G., 2016, Forbes
  11. Rai A., 2019, MIS Quarterly, 43, iii
  12. Taylor M. E., 2009, Journal of Machine Learning Research, 10, 1633
  13. Westcott Grant K., 2018, Forbes

Cited by

Sorted by citations

Related

Authors
Raisch, S., & Krakowski, S.
Affiliations
  • University of Geneva (CH)
  • Stockholm School of Economics (SE)
ORCID
Venue
Academy of Management Review
Publisher
Academy of Management
Published
2021-01
Volume
46
Issue
1
Pages
192-210
ISSN
  • 0363-7425 (ISSN-L)
  • 1930-3807
DOI
10.5465/amr.2018.0072
OpenAlex
W4247155454
Cited by
2,755
References
95
Citations by year
2026: 1391 · 2025: 586 · 2024: 318 · 2023: 235 · 2022: 156 · 2021: 65 · 2020: 3 · 2019: 1
FWCI
117.58
Type
journal article
Language
en
Open access
closed
Locations
Academy of Management Review (publishedVersion)
Funders
  • National Science Foundation
  • European Commission (856688)
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (185164, 181364)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
Keywords
artificial intelligence in organizations, automation, augmentation, paradox theory, human-machine collaboration, organizational performance, societal impact of AI

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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-11.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-11.

Cited sources are checked by gpt-6-sol.

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 ›

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