Artificial Intelligence and Management: The Automation–Augmentation Paradox

In the paper

“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).”

What the sources say

• Partly supported

  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)

  cites Amershi et al., 2014 sourceExperimental — accuracy not yet measured

In the paper

“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).”

What the sources say

• Supported

  The Introduction states that humans can transfer knowledge across domains and tasks. Section 4.3 defines transfer learning as applying knowledge acquired in one domain to a problem in a new domain, supporting the claim's description of generalizing between task contexts. (LLM, conf=0.94)

  cites Parisi, Kemker, Part, Kanan, & Wermter, 2019 source

In the paper

“Paradox theory, however, warns that such a narrow trade-off perspective does not adequately represent reality (Smith & Lewis, 2011).”

What the sources say

• Supported

  In “Alternative Perspectives on Organizational Tensions: Beyond Contingency Theory,” the paper says that choosing between dualities can oversimplify complex, dynamic contexts, whereas paradox theory attends to persistent tensions. It also qualifies the point: a narrower choice-based approach can be valuable in a narrower context and shorter time horizon. (LLM, conf=0.89)

  cites Smith & Lewis, 2011 source

In the paper

“According to paradox theory, these organizational responses fuel reinforcing cycles that can be either negative or positive (Smith & Lewis, 2011).”

What the sources say

• Supported

  In “Managing Tensions: Enabling Vicious and Virtuous Cycles,” the paper states that responses to paradoxical tensions fuel reinforcing cycles that can be negative or positive. This directly supports the citing sentence; the paper also discusses both vicious and virtuous cycles. (LLM, conf=0.95)

  cites Smith & Lewis, 2011 source

In the paper

“Contrary to automation, augmentation demands continued human involvement and experimentation (Amershi et al., 2014).”

What the sources say

• Partly supported

  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)

  cites Amershi et al., 2014 sourceExperimental — accuracy not yet measured

In the paper

“Organizations facing such a salient tension tend to apply management strategies to address it.”

What the sources say

• Supported

  The paper’s “Paradoxical Tensions: Latent and Salient” section describes responses to tensions as involving management strategies. “Managing Tensions: Enabling Vicious and Virtuous Cycles” further says that awareness of tensions triggers a management strategy. The paper addresses organizational tensions generally, rather than AI specifically; the cited sentence applies that general account to its context. (LLM, conf=0.87)

  cites Smith & Lewis, 2011 source

In the paper

“Owing to their inherent complexity and uncertainty, augmentation efforts often fail (Amershi et al., 2014).”

What the sources say

• Partly supported

  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)

  cites Amershi et al., 2014 sourceExperimental — accuracy not yet measured

In the paper

“Computer scientists may be expert technologists, but they are generally not trained social or behavioral scientists (Rahwan et al., 2019).”

What the sources say

• Supported

  In “The interdisciplinary study of machine behaviour,” the paper identifies computer scientists among those who commonly study machines, then says these scientists are typically not trained behaviourists. This supports the citing sentence’s paraphrase. (LLM, conf=0.94)

  cites Rahwan et al., 2019 source

In the paper

“AI is, for example, the major driver behind the current trend toward personalized medicine, with treatments being tailored to each patient's specific biological profile (Fleming, 2018;Lichfield, 2018).”

What the sources say

• Partly supported

  The Pattern Recognition passage says some expect AI to accelerate a trend toward treatments designed for patients with specific biological profiles. It presents this as a potential future contribution, not as evidence that AI is already the major driver of the trend or that such tailoring is currently occurring. (LLM, conf=0.87)

  cites Fleming, 2018 sourceExperimental — accuracy not yet measured
• ?Not matched

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  cites Lichfield, 2018

In the paper

“Through augmentation, humans and machines become so closely intertwined that they collectively exhibit entirely new, emergent behaviors, which neither show individually (Amershi et al., 2014).”

What the sources say

• Partly supported

  The section “Increasing Collaboration Across the Fields of Human Computer Interaction and Machine Learning” (page not provided) describes an inherent coupling of humans and machines and benefits from their interaction. It does not say that this coupling produces entirely new, emergent behaviors that neither exhibits alone. (LLM, conf=0.83)

  cites Amershi et al., 2014 sourceExperimental — accuracy not yet measured

In the paper

“These differences lead to entirely new machine behaviors (Rahwan et al., 2019).”

What the sources say

• Supported

  The Outlook section states that machines exhibit behaviours fundamentally different from those of animals and humans, supporting the claim that their differences give rise to new kinds of behaviour. It also describes some machine behaviours as potentially qualitatively different from those of biological agents. Page numbers are not available in the supplied copy. (LLM, conf=0.86)

  cites Rahwan et al., 2019 source

In the paper

“Only such studies can examine the feedback loops between human influence on machine behavior and machine influence on human behavior, which cause the emergent behaviors that are otherwise impossible to predict (Rahwan et al., 2019).”

What the sources say

• Partly supported

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

  cites Rahwan et al., 2019 sourceExperimental — accuracy not yet measured

In the paper

“For example, Symrise's master perfumers iterate between automation (i.e., when generating alternative fragrance formulas) and augmentation (i.e., when selecting and refining the most promising formula).”

In the paper

“Data scientists provided the investment bankers with organizational support to develop their augmentation skills.”

What the sources say

• ?Not matched

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

  cites Arnold & Noonan, 2017

In the paper

“Another example involves Amazon, which discontinued the use of an automated AIhiring tool found to discriminate against female applicants for technical jobs (Dastin, 2018).”

What the sources say

• ?Not matched

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

  cites Dastin, 2018

In the paper

“However, real-world applications show that machine biases caused by noisy data, statistical errors, or socially vexed predictors often lead to new, even more systematic discrimination.”

In the paper

“Simultaneously, the bank implemented another AI-based solution to augment the development of trading strategies.”

What the sources say

• ?Not matched

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

  cites Arnold & Noonan, 2017

In the paper

“For example, much like JP Morgan Chase, Unilever differentiates clearly between automation (used for the initial candidate assessment) and augmentation (used for the final selection) in their talent-acquisition process.”

What the sources say

• ?Not matched

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

  cites Feloni, 2017

In the paper

“The investment bankers used the time freed up by automation to collaborate closely with the AI-based tool to explore new strategies for adaptive trading.”

What the sources say

• ?Not matched

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

  cites Arnold & Noonan, 2017

In the paper

“UBS used an AI-based solution to automate the task of reading and executing client demands for fund transfers, which previously took an investment banker 45 minutes per demand.”

What the sources say

• ?Not matched

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

  cites Arnold & Noonan, 2017

In the paper

“Integration is ensured by retaining overall human responsibility for the entire process.”

What the sources say

• ?Not matched

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

  cites Feloni, 2017

In the paper

“These dual AI applications are interdependent across time and space, creating a paradoxical tension.”

• Also stated in: § Abstract · plain

  “These dual AI applications are interdependent across time and space, which creates a paradoxical tension.”

In the paper

“Overemphasizing either augmentation or automation fuels reinforcing cycles with negative organizational and societal outcomes.”

• Also stated in: § Abstract · plain

  “Overemphasizing either augmentation or automation fuels reinforcing cycles that not only harm an organization's performance but also have negative societal implications.”

In the paper

“we argue that, in the management domain, augmentation cannot be neatly separated from automation.”

• Also stated in: § Abstract · plain

  “we argue that augmentation cannot be neatly separated from automation in the management domain.”

In the paper

“Management scholars have therefore provided very little insight into AI during the last two decades (Kellogg, Valentine, & Christin, 2020;Lindebaum, Vesa, & den Hond, 2020).”

What the sources say

• ?Not checked — no full text of the sourcecites Kellogg, Valentine, & Christin, 2020 source
• ?Not checked — no full text of the sourcecites Lindebaum, Vesa, & den Hond, 2020 source

In the paper

“Consistent with the books' recommendations, companies have started adopting an augmentation strategy.”

What the sources say

• ?Not matched

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

  cites Nadella, 2016
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  cites Deutsche Telekom (2018)
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  cites IBM Think Blog, 2017

In the paper

“While rule-based automation allows such delegation, because the rules can be explicitly formulated, codified, and passed on to data scientists, complex tasks' augmented learning relies on domain experts' tacit knowledge, which cannot be easily codified (Brynjolfsson & Mitchell, 2017).”

What the sources say

• ?Not checked — no full text of the sourcecites Brynjolfsson & Mitchell, 2017 source

In the paper

“The nature of the task determines whether organizations opt for one or the other approach.”

What the sources say

• ?Not matched

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

  cites Brynjolfsson & McAfee, 2014
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  cites Daugherty & Wilson, 2018
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  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Davenport & Kirby, 2016

In the paper

“The tension is further reinforced because some organizational actors prefer augmentation (e.g., managers at risk of losing their jobs to automation) while others prioritize automation (e.g., owners interested in efficiencies) (Davenport & Kirby, 2016: 61).”

What the sources say

• ?Not matched

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

  cites Davenport & Kirby, 2016

In the paper

“Such substantial changes therefore make the automated solutions function less effectively (Davenport & Kirby, 2016: 72).”

What the sources say

• ?Not matched

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

  cites Davenport & Kirby, 2016

In the paper

“The experts' revision of the learned knowledge is therefore an important part of the augmented learning process (Fails & Olsen, 2003).”

What the sources say

• ?Not checked — no full text of the sourcecites Fails & Olsen, 2003 source

In the paper

“Consequently, augmentation may enable a transition to automation over time.”

In the paper

“If these models are sufficiently robust, they can subsequently be used to automate a task.”

In the paper

“Technical and social limitations make the full automation of complex managerial processes impossible in the foreseeable future.”

In the paper

“They cannot take on other tasks, since they do not possess the general intelligence to learn from their experience in one domain to conduct tasks in other domains (Davenport & Kirby, 2016: 35).”

What the sources say

• ?Not matched

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

  cites Davenport & Kirby, 2016

In the paper

“In turn, humans can only take responsibility if they retain some level of involvement with and control over the relevant tasks.”

In the paper

“Second, with respect to complex managerial tasks, machines can only provide a range of options that all relax certain real-life constraints.”

In the paper

“The two AI applications in management are therefore interdependent not only across time but also across space.”

In the paper

“Machines cannot fully capture ambiguous predictors, such as cultural fit or interpersonal relations, for which there are simply no codified data available.”

In the paper

“Such automation can, in turn, trigger further augmentation in closely related managerial tasks.”

In the paper

“We argue that the emerging coexistence of interdependent automated and augmented tasks will persist in the management domain.”

In the paper

“This choice creates a tension, since these AI approaches rely on competing logics with different organizational demands.”

In the paper

“Viewed as a paradox, automation and augmentation are no longer separate, but are mutually enabling and constituent of one another.”

In the paper

“The phenomenon of”

What the sources say

• ?Not matched

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

  cites Taylor & Stone, 2009

In the paper

“These interdependencies cause managerial interventions in one task to have ripple effects throughout the process (L üscher & Lewis, 2008).”

What the sources say

• ?Not matched

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

  cites L üscher & Lewis, 2008

In the paper

“Third, machines are limited to the specific task for which they have been trained.”

What the sources say

• ?Not matched

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

  cites Davenport & Kirby, 2016

In the paper

“A paradox lens can help increase the scale or level of analysis for a more systemic perspective (Schad & Bansal, 2018), which allows organizations to perceive not only the contradictions but also the interdependencies between automation and augmentation.”

What the sources say

• ?Not checked — no full text of the sourcecites Schad & Bansal, 2018 source

In the paper

“Such interactions are often iterative, resulting in the augmentation of adjacent tasks.”

In the paper

“To conclude, the augmentation of a managerial task may enable its subsequent automation.”

In the paper

“As the books suggest, the process of using AI for a managerial task starts with a choice between automation and augmentation.”

What the sources say

• ?Not matched

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

  cites Brynjolfsson & McAfee, 2014
• ?Not matched

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

  cites Daugherty & Wilson, 2018
• ?Not matched

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

  cites Davenport & Kirby, 2016

In the paper

“Over time, this close collaboration with machines sometimes allows managers to identify rules or models that either optimize the utility function or come sufficiently close to an optimal solution to be practically useful.”

In the paper

“Ultimately, organizations become entrenched in their automated processes, because automation is limited to specific tasks in well-understood domains and imposes formal rules that narrow organizations' choices and penalize deviation (Lindebaum et al., 2020).”

What the sources say

• ?Not checked — no full text of the sourcecites Lindebaum et al., 2020 source

In the paper

“Switching to augmentation allows machine limitations to be overcome by subsequently using humans' more holistic and intuitive information processing to choose between options and contextualize beyond the specific task at hand (Brynjolfsson & McAfee, 2014: 92).”

What the sources say

• ?Not matched

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

  cites Brynjolfsson & McAfee, 2014: 92

In the paper

“Organizations can purposefully iterate between distinct automation and augmentation tasks, allowing long-term engagement with both forces.”

In the paper

“In contrast, we have argued that focusing on either automation or augmentation can lead to reinforcing cycles that harm long-term performance.”

In the paper

“Differentiation allows organizations to recognize and appreciate automation and augmentation's distinctive benefits and leverage them separately.”

In the paper

“If organizations are unaware of a tension's paradoxical nature they risk applying partial strategies, which cause vicious cycles that escalate the tension.”

In the paper

“While managers initially perceive automation and augmentation as a trade-off, they may eventually recognize that they cannot simply choose between these dual AI applications, because either choice intensifies the need for its opposite.”

In the paper

“The use of automation allows exploration beyond humans' abilities by searching through the whole landscape of possible options.”

In the paper

“Through integration, automation and augmentation jointly generate outcomes that neither application can enable individually.”

In the paper

“This is particularly true of managerial contexts characterized by high degrees of ambiguity, complexity, and rare events, which limit deterministic approaches' applicability (Davis & Marcus, 2015).”

What the sources say

• ?Not checked — no full text of the sourcecites Davis & Marcus, 2015 source

In the paper

“Integration therefore requires humans to retain overall responsibility for a managerial process.”

In the paper

“While these dynamics are likely to promote increasing augmentation and automation, technological and social limitations prevent progress toward the full automation of managerial processes in organizations.”

What the sources say

• ?Not checked — no full text of the sourcecites Davis & Marcus, 2015 source

In the paper

“Organizations are likely to prioritize automation due to its promise of short-term cost efficiencies (Davenport & Kirby, 2016: 204).”

What the sources say

• ?Not matched

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

  cites Davenport & Kirby, 2016: 204

In the paper

“The integration of automation and augmentation leads to additional benefits that accrue from the synergies between these interdependent activities.”

In the paper

“Consequently, the whole industry may be”

What the sources say

• ?Not matched

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

  cites Davenport & Kirby, 2016: 204

In the paper

“This AI application requires extensive resources to work through iterative cycles of human-machine learning.”

In the paper

“Conversely, organizations that accept a tension as paradoxical and pay attention to its competing demands could enable virtuous cycles (Schad et al., 2016).”

What the sources say

• ?Not checked — no full text of the sourcecites Schad et al., 2016 source

In the paper

“To conclude, one-sided orientations toward either automation or augmentation cause vicious cycles, because they neglect the dynamic interdependencies between AI's dual applications in management.”

In the paper

“Over time, these organizations lose the human skills required to alter their processes (Endsley & Kiris, 1995).”

What the sources say

• ?Not checked — no full text of the sourcecites Endsley & Kiris, 1995 source

In the paper

“However, transitioning to a more encompassing paradox perspective requires cognitive and behavioral complexity (Miron-Spektor, Ingram, Keller, Smith, & Lewis, 2018).”

What the sources say

• ?Not matched

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

  cites Miron-Spektor, Ingram, Keller, Smith, & Lewis, 2018

In the paper

“At these transition points, automation and augmentation become mutually enabling.”

In the paper

“This strategy forces organizations' competitors to also pursue automation in order to remain cost competitive.”

In the paper

“However, our analysis suggests that management research limited to augmentation may be as biased as computer science's traditional focus on automation.”

In the paper

“This problem is particularly pernicious, since machines then confirm humans' biased intuition, which makes humans even less likely to question their preconceived positions (Huang et al., 2012).”

What the sources say

• ?Not checked — no full text of the sourcecites Huang et al., 2012 source

In the paper

“Balancing automation and augmentation could, however, enable a virtuous cycle of selective deskilling (i.e., humans offload tasks where their abilities are inferior to those of machines) and strategic requalification (i.e., humans stay ahead of machines in their core abilities), thereby gradually enhancing both human and machine capabilities.”

In the paper

“Similarly, automated candidate assessment based on predetermined criteria and consistent machine processing could help eliminate humans' implicit biases in their hiring decisions.”

In the paper

“Instead, they tend to use laboratory settings for their research, which reduce the inherent variability that characterizes human behavior.”

In the paper

“In contrast, augmentation is likely to reduce such machine biases through human back-testing and feedback.”

In the paper

“There is a risk that organizations could take a narrow perspective of either automation or augmentation, triggering unintended consequences that affect society negatively.”

In the paper

“This skill-enhancement cycle could also help”

What the sources say

• ?Not matched

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

  cites Daugherty & Wilson, 2018: 214

In the paper

“Balancing automation and augmentation helps prevent the escalating cycles that focusing on just one of these AI applications could cause.”

In the paper

“Furthermore, the combination of automation and augmentation could enable new business models.”

In the paper

“For example, using automation for credit approval could reduce bankers' bias that might previously have kept people from qualifying for credit due to their ethnicity, gender, or postal code (Daugherty & Wilson, 2018: 167).”

What the sources say

• ?Not matched

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

  cites Daugherty & Wilson, 2018: 167

In the paper

“However, realizing these benefits is contingent upon organizations' active management of the automation-augmentation paradox.”

In the paper

“These varied benefits suggest that automation and augmentation's combination creates complementary returns that lead to superior firm performance.”

In the paper

“The automation-augmentation paradox suggests that both perspectives are equally biased.”

In the paper

“Daugherty and Wilson (2018: 179) cited the example of an automated AI system, used to predict defendants' future criminal behavior, that was biased against Black defendants.”

What the sources say

• ?Not matched

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

  cites Daugherty & Wilson, 2018: 179

In the paper

“Consequently, the combined use of automation and augmentation allowed UBS to exploit cost efficiencies while exploring new client solutions (Arnold & Noonan, 2017).”

What the sources say

• ?Not matched

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

  cites Arnold & Noonan, 2017

In the paper

“However, the intense interaction between managers and machines increases the risk of human biases being carried over to machines.”

In the paper

“Employees and managers whose basic skills are made redundant by automation could be given the opportunity to gradually build higher-level augmentation skills that remain in demand.”

In the paper

“The resulting hybrid organizational systems exhibit behaviors and produce organizational, as well as societal, effects that are impossible to predict precisely and are often entirely unanticipated (O'Neil, 2016).”

What the sources say

• ?Not matched

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

  cites O'Neil, 2016

In the paper

“Data are collected widely, with diverse stakeholders updating them continuously and collectively through their actions (Gregory et al., 2020).”

What the sources say

• ?Not matched

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

  cites Gregory et al., 2020

In the paper

“If we increase the complexity further, we have to acknowledge that these human and machine agents do not simply coexist in separate worlds (working on separate tasks), but are interdependent (interacting on the same or closely related tasks).”

In the paper

“In machinelearning systems, humans shape and reshape algorithms through their daily actions and interactions (Deng, Bao, Kong, Ren, & Dai, 2017).”

What the sources say

• ?Not checked — no full text of the sourcecites Deng, Bao, Kong, Ren, & Dai, 2017 source

In the paper

“In a management context, machines may influence human behavior but without setting a static norm of conduct or an unsurpassable rule (Cheney-Lippold, 2011).”

What the sources say

• ?Not checked — no full text of the sourcecites Cheney-Lippold, 2011 source

In the paper

“No single actor in these systems has full control over these outcomes.”

In the paper

“There is widespread fear-and initial empirical evidence-that this lack of accountability can have harmful societal consequences regarding equality (Autor, 2015), privacy (Acquisti, Brandimarte, & Loewenstein, 2015), security (Brundage et al., 2018), and transparency (Castelvecchi, 2016).”

What the sources say

• ?Not checked — no full text of the sourcecites Autor, 2015 source
• ?Not checked — no full text of the sourcecites Acquisti et al., 2015 source
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  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Brundage et al., 2018

In the paper

“The bulk of extant management research has relied on the behavioral assumptions of boundedly rational human actors, who-due to their information-processing limits and cognitive biases-engage in satisficing rather than maximizing behavior (Argote & Greve, 2007;Cyert & March, 1963).”

What the sources say

• ?Not checked — no full text of the sourcecites Argote & Greve, 2007 source
• ?Not matched

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

  cites Cyert & March, 1963

In the paper

“In the past, management theories emphasized managers' domain expertise, which granted them expert power and status in their organizations (Finkelstein, 1992).”

What the sources say

• ?Not checked — no full text of the sourcecites Finkelstein, 1992 source

In the paper

“Although domain expertise remains relevant for managers regarding educating and challenging machines, automation and augmentation will lead to institutionalized knowledge-for example, in the form of algorithmswhich is often superior to individual managers' expert knowledge.”

In the paper

“For example, AI is often applied in open systems, blurring organizational boundaries (Panait & Luke, 2005).”

What the sources say

• ?Not checked — no full text of the sourcecites Panait & Luke, 2005 source

In the paper

“If we increase the complexity even further, we finally see that humans and machines influence one another in an iterative process.”

In the paper

“However, our broader paradox perspective of AI in management reveals that humans also shape machine behavior.”

In the paper

“The use of AI in management leads to hybrid organizational systems manifesting collective behaviors.”

In the paper

“Managers participate in writing and rewriting the rules that shape behavior.”

In the paper

“These developments could lead to important shifts in managers' roles, competencies, and status.”

In the paper

“Such automation leads to machine behavior that deviates significantly from the human behavior that management theories traditionally describe.”

In the paper

“Traditional managerial and organizational solutions may be inadequate for sufficiently addressing such systemic problems (Schad & Bansal, 2018).”

What the sources say

• ?Not checked — no full text of the sourcecites Schad & Bansal, 2018 source

In the paper

“However, these agents are very limited in their capabilities, because fundamental technical and ethical challenges limit their potential for human-level emotional sentience in the foreseeable future(McDuff & Czerwinski, 2018).”

What the sources say

• ?Not checked — no full text of the sourcecites McDuff & Czerwinski, 2018 source

In the paper

“As argued above, the emergent use of AI in management leads to iterative interactions between humans and machines.”

In the paper

“The use of AI for managerial tasks implies that machines are no longer simple artifacts, but a new class of agents in organizations (Floridi & Sanders, 2004).”

What the sources say

• ?Not checked — no full text of the sourcecites Floridi & Sanders, 2004 source