The complex interplay between automation and augmentation in the use of artificial intelligence (AI) in management
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This 2023 paper explores the dual roles of artificial intelligence (AI) in the area of management—automation and augmentation.
It examines the prevailing narrative encouraged by recent business literature, which advises organisations to prioritise augmentation, where humans collaborate with AI, over automation, where AI replaces human tasks.
Automation vs. Augmentation
Automation refers to AI systems taking over tasks previously performed by humans, while augmentation involves AI assisting humans in tasks, enhancing their capabilities.
Interdependence of Automation and Augmentation
The authors challenge the clear-cut separation between automation and augmentation presented in business literature. They argue that these two roles of AI are interconnected and create a paradoxical tension within organisational and management contexts.
Paradoxical Tension
This tension arises because focusing too much on either automation or augmentation can lead to negative consequences for both organisations and society.
Overemphasis on automation may lead to job losses and societal issues, whereas overemphasis on augmentation may ignore the efficiencies and benefits automation can offer.
AI's Impact on Society and Business
The paper underscores the broader implications of AI's dual roles, highlighting the need for thoughtful consideration of how AI strategies impact not just organisational performance but also societal outcomes.
The analysis expands on the persistence of the tension between automation and augmentation in AI's application within management, emphasising that this tension is paradoxical because it's enduring and involves interdependent yet contradictory elements.
Persistence of Tension: The tension between automation and augmentation in management is enduring due to the inherent limitations and distinctive roles of machines and humans.
Despite advancements in AI, machines cannot fully replace human intelligence, particularly in complex managerial tasks, underscoring the ongoing necessity for human involvement.
Machine Limitations
Several intrinsic limitations of machines highlight the need for ongoing human interaction:
Machines lack self-awareness and purpose, requiring humans to define objectives and take responsibility.
In complex tasks, machines provide options, but human intuition is necessary for final decision-making.
AI systems are trained for specific tasks and can't generalize their learning to unrelated domains.
Machines lack human sensory perceptions, emotions, and social skills, essential in nuanced managerial tasks.
Cyclical Relationship
Automation and augmentation have a cyclical relationship where initial automation might lead to further augmentation in adjacent tasks, and vice versa.
Over time, tasks that were augmented may become automated as understanding and technologies evolve, but changing conditions may necessitate a return to augmentation.
Management Strategies
Organisations may fall into vicious cycles if they focus narrowly on either automation or augmentation, neglecting the interplay between the two.
This can lead to detrimental effects, such as deskillment, complacency, and lock-in to automated processes, or continual failure and escalating commitment in augmentation efforts.
Virtuous Cycles
A constructive approach involves recognising the paradoxical nature of the tension and adopting strategies that combine differentiation (leveraging the distinct benefits of automation and augmentation separately) and integration (iterating between automation and augmentation to exploit their respective strengths).
This balanced approach can foster innovation, adaptability, and comprehensive engagement with AI in management.
Organisational Outcomes
Augmentation can significantly boost productivity, enhance service quality, and spur innovation by merging human intuition with machine efficiency.
Differentiation between automation and augmentation allows organisations to reap unique benefits from each: automation brings cost efficiency and consistency, while augmentation fosters creativity and adaptability.
Integrating automation and augmentation can lead to synergies, like freeing up resources through automation for more complex, augmented tasks, potentially enabling innovative business models like personalised medicine.
Societal Outcomes
The paradox has broad implications beyond individual organisations, affecting labour markets and social equality.
Focusing solely on automation might lead to job losses and increased unemployment, exacerbating social inequality. Conversely, an exclusive focus on augmentation might deepen the digital divide, creating disparities between those who can and cannot engage in augmented tasks.
Balancing automation and augmentation could foster a cycle of deskilling in areas where machines excel and upskilling in areas where human skills are paramount, potentially enhancing job satisfaction by shifting focus to more creative and fulfilling tasks.
The use of AI in management could impact social equality and fairness. Automation might reduce human biases in decisions, promoting fairness, while augmentation could help mitigate machine biases through human oversight.
In conclusion, navigating the automation-augmentation paradox effectively requires a nuanced approach that acknowledges the interdependence of these two aspects of AI in management.
Organisations that successfully balance and integrate automation and augmentation can not only enhance their performance and innovation but also contribute positively to broader societal challenges like employment and social justice.
