Artificial Intelligence and Management: The Automation–Augmentation Paradox

In the paper

“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).”

What the sources say

• Partly supported

  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)

  cites Fan, Han, & Liu, 2014 sourceExperimental — accuracy not yet measured

In the paper

“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).”

What the sources say

• Partly supported

  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)

  cites Floridi, 2008 sourceExperimental — accuracy not yet measured

In the paper

“First, machines have no sense of self or purpose, which means managers need to define their objectives (Braga & Logan, 2017).”

What the sources say

• Partly supported

  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)

  cites Braga & Logan, 2017 sourceExperimental — accuracy not yet measured

In the paper

“In such cases, rule-based automation is impossible, but managers could use an augmentation approach to explore the problem further (Holzinger, 2016).”

What the sources say

• Partly supported

  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)

  cites Holzinger, 2016 sourceExperimental — accuracy not yet measured

In the paper

“While such a transition relaxes the tension temporarily, the issue resurfaces when conditions change over time (Smith & Lewis, 2011).”

What the sources say

• Partly supported

  The paper’s “Dilemma Dilemma” passage says a choice between competing demands is temporary and the tension will resurface. “Paradoxical Tensions: Latent and Salient” adds that change can make persistent tensions salient. The paper does not address a transition to automation or show that such a transition temporarily relaxes the tension. (LLM, conf=0.87)

  cites Smith & Lewis, 2011 sourceExperimental — accuracy not yet measured

In the paper

“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).”

What the sources say

• Supported

  The Interactive Machine Learning section says the model updates in response to user input, while users examine its outputs and adapt their subsequent inputs. The Summary describes this as a tight coupling in which the user and learning system influence one another. That supports the reciprocal process attributed to the paper; “augmentation” is the citing authors’ framing. (LLM, conf=0.87)

  cites Amershi, Cakmak, Knox, & Kulesza, 2014 source
• Partly supported

  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)

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

In the paper

“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).”

What the sources say

• Supported

  In “Managing Tensions: Enabling Vicious and Virtuous Cycles” (page unavailable), the paper describes combining splitting with synergistic integration to attend to opposing poles simultaneously. Its conceptual account supports applying that distinction to automation and augmentation; it does not present those as the paper’s own example. (LLM, conf=0.87)

  cites Smith & Lewis, 2011 source

In the paper

“Paradox theory suggests that managing tensions through the dynamic strategies of acceptance and resolution fosters sustainability (Smith & Lewis, 2011).”

What the sources say

• Supported

  Proposition 3 in “The Outcome: Sustainability” states that dynamic, ongoing strategies of acceptance and resolution for managing paradoxical tensions foster sustainability. The “Managing Tensions” section likewise describes acceptance and resolution as complementary strategies in the dynamic equilibrium model. (LLM, conf=0.95)

  cites Smith & Lewis, 2011 source

In the paper

“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).”

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 Calabretta, Gemser, & Wijnberg, 2017 sourceExperimental — accuracy not yet measured

In the paper

“A first step toward enabling such a virtuous cycle is the acceptance of the tensions as paradoxical (Smith & Lewis, 2011).”

What the sources say

• Supported

  In “Managing Tensions: Enabling Vicious and Virtuous Cycles,” the paper states that acceptance lays the groundwork for virtuous cycles and describes accepting tensions as paradoxical as part of that approach. This supports the citing sentence’s characterization of acceptance as a first step. (LLM, conf=0.94)

  cites Smith & Lewis, 2011 source

In the paper

“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).”

What the sources say

• Partly supported

  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)

  cites Holzinger, 2016 sourceExperimental — accuracy not yet measured

In the paper

“While acceptance lays the groundwork for virtuous cycles, it has to be complemented with a subsequent resolution strategy (Smith & Lewis, 2011).”

What the sources say

• Supported

  In “Managing Tensions: Enabling Vicious and Virtuous Cycles,” the paper says acceptance lays the groundwork for virtuous cycles and describes acceptance and resolution as complementary strategies. It also says acceptance enables more challenging resolution strategies, supporting the cited sentence’s sequence. (LLM, conf=0.92)

  cites Smith & Lewis, 2011 source

In the paper

“Furthermore, humans”

What the sources say

• Partly supported

  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)

  cites Binns, Van Kleek, Veale, Lyngs, Zhao, & Shadbolt, 2018 sourceExperimental — accuracy not yet measured

In the paper

“Tensions' systemic nature is a central tenet of paradox theorizing (Jarzabkowski, Bednarek, Chalkias, & Cacciatori, 2019;Smith & Lewis, 2011).”

What the sources say

• Supported

  The Introduction states almost exactly that the systemic nature of paradoxes is a central tenet of much paradox theorizing. This supports the citing sentence’s paraphrase. (LLM, conf=0.95)

  cites Jarzabkowski, Bednarek, Chalkias, & Cacciatori, 2019 source
• Supported

  In “Conceptual Clarity: Distinguishing Among Organizational Tensions,” the paper defines paradoxical elements as interrelated within a larger system. “Paradoxical Tensions: Latent and Salient” further describes tensions as embedded in organizational systems and as forming a system of interrelated tensions. These passages support the claim that their systemic nature is central to the paper’s paradox theorizing. (LLM, conf=0.92)

  cites Smith & Lewis, 2011 source

In the paper

“While machine algorithms shape human actions, humans shape these algorithms through their actions, which create a recursive relationship (Beer, 2017).”

What the sources say

• Supported

  In the Abstract, Beer describes algorithms as embedded in social practices and says their outcomes are recursively modelled back into algorithm design. In “Power and the algorithm,” he also describes algorithms shaping choices and human agents designing them. Together, these passages support the claimed two-way relationship. (LLM, conf=0.92)

  cites Beer, 2017 source

In the paper

“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).”

What the sources say

• ?Could not verify

  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)

  cites Floridi & Taddeo, 2016 sourceExperimental — accuracy not yet measured

In the paper

“Complexifying theories is essential for understanding complex phenomena (Tsoukas, 2017), because”

What the sources say

• Supported

  The Abstract argues that theories should be complexified because theoretical complexity is needed to account for organizational complexity. The claim is a concise paraphrase of that argument, with organizational phenomena as the paper’s focus. (LLM, conf=0.92)

  cites Tsoukas, 2017 source
• ?Not checked — no full text of the sourcecites Weick, 2007: 16 source

In the paper

“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 paper

“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.”

In the paper

“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).”

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

“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”

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

“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.”

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
• ?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 authors distinguished two broad AI applications in organizations: 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

“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.”

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
• ?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 three books have developed a common AI narrative for practicing managers.”

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

“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.”

In the paper

“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).”

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

In the paper

“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.”

In the paper

“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).”

What the sources say

• ?Not checked — no full text of the sourcecites Poole & van de Ven, 1989 source

In the paper

“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.”

In the paper

“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.”

In the paper

“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.”

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

“For example, HR managers can use their emotional and social intelligence to provide a”

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: 74

In the paper

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

In the paper

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

In the paper

“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.”

In the paper

“Fourth, machines do not possess human senses, perceptions, emotions, and social skills (Braga &”

What the sources say

• ?Not matched

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

  cites Braga &

In the paper

“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).”

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

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

In the paper

“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.”

In the paper

“Resolution involves seeking responses to paradoxical tensions through a combination of differentiation and integration practices (Poole & van de Ven, 1989).”

What the sources say

• ?Not checked — no full text of the sourcecites Poole & van de Ven, 1989 source

In the paper

“We suggest that organizations benefit if they differentiate between and integrate across automation and augmentation.”

In the paper

“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).”

What the sources say

• ?Not checked — no full text of the sourcecites Larrick, 2004 source
• ?Not checked — no full text of the sourcecites Skitka et al., 2000 source

In the paper

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

In the paper

“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.”

In the paper

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

In the paper

“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.”

In the paper

“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).”

What the sources say

• ?Not checked — no full text of the sourcecites Huang, Hsu, & Ku, 2012 source

In the paper

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

In the paper

“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.”

In the paper

“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.”

In the paper

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

In the paper

“Their cognitive limitations mean that humans' search field is restricted, while machines do not face such information-processing limitations (Davenport & Kirby, 2016: 17).”

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: 17

In the paper

“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.”

In the paper

“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).”

What the sources say

• ?Not checked — no full text of the sourcecites Hoc, 2001 source

In the paper

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

In the paper

“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).”

What the sources say

• ?Not checked — no full text of the sourcecites Parasuraman & Manzey, 2010 source
• ?Not checked — no full text of the sourcecites Skitka, Mosier, & Burdick, 2000 source

In the paper

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

In the paper

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

In the paper

“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).”

What the sources say

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

In the paper

“Excluding humans at this stage may help break path dependencies and promote greater novelty.”

In the paper

“As described above, augmentation provides complementary benefits arising from the mutual enhancing of human and machine skills.”

In the paper

“Consequently, retaining human responsibility for managerial processes promotes integration, which transcends automation and augmentation.”

In the paper

“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).”

What the sources say

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

In the paper

“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.”

What the sources say

• ?Not checked — no full text of the sourcecites Sabherwal & Jeyaraj, 2015 source
• ?Not checked — no full text of the sourcecites Staw, 1981 source

In the paper

“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.”

In the paper

“With respect to managerial tasks, humans will remain”

In the paper

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

In the paper

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

In the paper

“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.”

In the paper

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

In the paper

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

In the paper

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

In the paper

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

In the paper

“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).”

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: 171
• ?Not checked — no full text of the sourcecites Autor, 2015 source

In the paper

“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).”

What the sources say

• ?Not checked — no full text of the sourcecites Hoc, 2001 source
• ?Not checked — no full text of the sourcecites Panait & Luke, 2005 source
• ?Not checked — no full text of the sourcecites Larrick, 2004 source

In the paper

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

In the paper

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

In the paper

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

In the paper

“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.”

In the paper

“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.”

In the paper

“Their primary objective is to automate as far as possible, because they often regard humans as”

What the sources say

• ?Not checked — no full text of the sourcecites Cummings, 2014: 62 source

In the paper

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

In the paper

“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.”

In the paper

“Conversely, onesided augmentation is likely to cause another”

What the sources say

• ?Not checked — no full text of the sourcecites Norris, 2001 source
• ?Not matched

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

  cites Brynjolfsson & McAfee, 2014: 134f
• ?Not checked — no full text of the sourcecites Brynjolfsson & Mitchell, 2017 source

In the paper

“However, adopting this intuitively appealing model uncritically obscures how automation and augmentation intertwine in managerial practice.”

In the paper

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

In the paper

“The technological and the social worlds are merging (Orlikowski, 2007), which means that computer scientists and management scholars no longer study separate phenomena.”

What the sources say

• ?Not checked — no full text of the sourcecites Orlikowski, 2007 source

In the paper

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

In the paper

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

In the paper

“Automation takes humans”

In the paper

“Automation and augmentation are not good or evil per se.”

In the paper

“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.”

In the paper

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

In the paper

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

In the paper

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

In the paper

“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).”

What the sources say

• ?Not matched

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

  cites Rai, Constantinides, & Sarker, 2019

In the paper

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

In the paper

“Such a perspective will enable a discussion of”

What the sources say

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

In the paper

“Consequently, it is difficult to apportion accountability for outcomes to specific actors, which creates an”

What the sources say

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

In the paper

“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.”

What the sources say

• ?Not checked — no full text of the sourcecites Schad et al., 2016 source
• ?Not checked — no full text of the sourcecites Sterman, 2000

In the paper

“Nonetheless, they can introduce statistical biases and have other limitations that humans do not have (Elsbach & Stigliani, 2019).”

What the sources say

• ?Not checked — no full text of the sourcecites Elsbach & Stigliani, 2019 source

In the paper

“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.”

In the paper

“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.”

In the paper

“Augmentation therefore implies close collaboration between humans and machines.”

In the paper

“Several current projects are aimed at deploying AIbased agents capable of perceiving and responding to emotional cues.”

What the sources say

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

In the paper

“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).”

What the sources say

• ?Not matched

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

  cites Riley, 2018

In the paper

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

In the paper

“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).”

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
• ?Not matched

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

  cites Daugherty & Wilson, 2018

In the paper

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

In the paper

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

In the paper

“Accepting and embracing this complexity allows for studying AI and its managerial applications”