The Wellbeing Paradox in an AI World

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Abstract: As artificial intelligence transforms work through automation, a "wellbeing paradox" may emerge if its social and psychological impacts are not consciously managed. This practitioner-focused research brief explores the tensions between AI's productivity gains and potential threats to human thriving. Through a review of recent studies at the intersection of technology, jobs and wellbeing, it identifies challenges like job insecurity, social isolation, technostress, employee surveillance and over-reliance on algorithms that could undermine individuals' sense of purpose, autonomy, relationships and overall wellbeing. Meanwhile, AI provides an opportunity to cultivate resilience for workers through career support, meaningful reskilling, internal mobility and social connection in the workplace. The brief also outlines strategies for organizations to optimize human-AI collaboration through transparency, explainability and prioritizing augmentation over automation. It concludes with a "digital ergonomics" framework of boundary-setting, mindfulness, presence and wellbeing nudges to proactively design technology that enhances rather than depletes human capacities and fulfillment.

While artificial intelligence promises to enhance our lives through increased productivity and possibility, a "wellbeing paradox" may emerge if we are not mindful. As AI steadily integrates into our personal and professional worlds, disrupting long-held patterns and assumptions, it brings opportunity but also challenges for human thriving.

Today we will explore the tensions between AI's labor-augmenting benefits and potential social and emotional tradeoffs if we do not proactively cultivate wellbeing. Through a review of recent studies at the intersection of technology, work and human flourishing, alongside practical strategies, organizations can help ensure AI becomes a compass rather than Threat to wellbeing.

A Brave New World of Work

The rise of AI is redrawing the boundaries of "work" as we've known it. As machines assume more routine physical and cognitive tasks, roles once central to livelihood and identity will change (Frey and Osborne, 2013). While opening up new creative and interpersonal occupations, this disruption causes unease as people wrestle with an uncertain future. As AI master's domains like image recognition andlanguage translation, about 47% of total US employment is at high risk for computerization in the coming decades according to one study (Arntz, Gregory and Zierahn, 2016). Beyond specific functions eliminated or transformed, AI diffuses into ever wider spheres of life through apps, devices and digital services that mediate much of modern work and leisure.

This profound restructuring brings both promise and peril. On one hand, AI-enhanced productivity could boost economic growth and free up time for higher-quality, more meaningful activities (Brynjolfsson and McAfee, 2014). But the rapid pace and uncertainty of change also fuels stress as people lack opportunities to develop new skills or struggle amidst industry disruption. As AI advances, the parameters of many jobs will evolve constantly in ways difficult to foresee. Additionally, a substantial portion of the populace risks being left behind without proper support as technological literacy becomes ever more prerequisites for participation in society and the economy.

Potential Pitfalls for Wellbeing

A robust and growing body of evidence underscores both challenges and opportunities AI may present for individual and social wellbeing if its diffusion is not carefully managed:

• Job insecurity and loss of purpose. Even as new roles emerge, the disruption of familiar work patterns threatens feelings of stability, competence and contribution central to wellbeing (Westervelt, 2016). A Finnish study found elevated rates of disability and mortality among workers affected by long-term layoffs (Kivimäki et al., 2003). The loss of meaningful work can diminish life satisfaction and health.

• Social isolation. As human-to-human contact decreases through automation and online mediation, belongingness needs may suffer (Cigna, 2018). Isolation correlates strongly with increased mental health issues, cognitive decline and even early mortality according to research (Holt-Lunstad et al., 2015).

• Technostress. Constantly multitasking amidst an overabundance of information and notifications taxes our limited cognitive capacities, inducing stress and distractibility (Misra and Stokols, 2012). "Techno-overload" disproportionately burdens those with fewer resources to cope.

• Employee surveillance. Monitoring workers' digital activities, emotions and biometric signals encroaches on privacy and discretion central to feeling respected and autonomous (Stanton and Barnes-Farrell, 1996). This risks undermining motivation and wellbeing.

• Automation bias. People naturally trust algorithms over human judgment, even when algorithms are wrong (Logg, Minson and Moore, 2019). Over-reliance on AI risks crowding out critical thinking and self-development.

• Lack of meaningful usage. If AI mainly duplicates human capacities like memorization rather than expanding them in deeper, more nuanced ways, it may fail to fulfill higher psychological needs or long-term social benefits.

Clearly, managing these risks demands attention not just to functionality but human impacts. However, amidst disruption also lies great promise if we thoughtfully guide AI to enhance rather than substitute for our humanity. The following sections explore strategies for navigating this "wellbeing paradox" constructively.

Nurturing Resilience in Workers

With jobs in flux, cultivating resilience - the ability to recover from challenges - in employees grows ever more critical for wellbeing and competitiveness alike. Forward-thinking organizations recognize the importance of "whole-person development" that addresses not just skills but employees' overall sense of purpose, autonomy and community (Deloitte, 2018). Some approaches include:

• Career navigation support. Provide resources to explore new paths proactively rather than reactively. Reskilling programs, mentoring, career coaching and flexibility help workers manage change (Harvard Business Review, 2017).

• Meaningful reskilling. Focus not just on skills but how roles impact society, fulfill higher needs and leverage employees' interests. Meaning correlates strongly to work satisfaction, performance and retention.

• Internal mobility. Create openings for skills developed elsewhere in the company to retain talent amidst disruption and foster a learning culture.

• Autonomy and mastery. Allow discretion and complex problem-solving wherever feasible to satisfy basic psychological needs, buffering against change's threats to wellbeing (Deci and Ryan, 2000).

• Social support. Foster peer support groups, regular team-building and an inclusive culture where people feel seen and valued beyond tasks alone. Belonging strengthens resilience to change.

With AI as a lens and lever, progressive employers help workers thrive through transitions by tapping their deeper needs for contribution, agency, relationships and growth - nurturing wellbeing proactively.

Optimizing Human-AI Partnership

Another strategy is optimizing AI to strengthen rather than compromise important human capacities and relationships. Approaches include:

• Augmentation, not automation. Where possible, design AI to enhance human capabilities rather than replace jobs outright by supporting complex, nuanced tasks beyond what either could do alone (Daugherty and Wilson, 2018).

• Transparency. Clearly communicate an algorithm's capabilities and limitations to build appropriate trust and avoid biases like automation bias that could crowd out human judgment.

• Explainability. Ensure models provide insights into their decision-making to facilitate oversight, refinement and complimentary human expertise rather than as black boxes (EU High-Level Expert Group on AI, 2019).

• Accountability. Determine responsible parties and protocols for issues that may arise to establish appropriate governance over increasingly autonomous systems.

• Embed ethics by design. Proactively identify and address potentially problematic biases, such as those around gender or race, during development rather than as afterthoughts.

• Balance monitoring and trust. Track performance helpfully rather than constantly second-guessing workers, which risks harming wellbeing, creativity and responsibility.

By prioritizing augmentation, oversight and equity, organizations can reap AI's benefits while safeguarding crucial human qualities like judgment, collaboration and dignity. This nurtures acceptance of technological change as a partner rather than a dismantler of the social fabric.

Fostering Digital Wellbeing

Just as ergonomic practices promote physical wellbeing, a "digital ergonomics" approach can help create technology that enhances rather than depletes us. Strategies informed by positive psychology, mindfulness and human-centered design include:

• Set boundaries. Reduce notifications, multitasking and "always on" work cultures to prevent techno-overload stress and blurring of work-life borders that threaten wellbeing and productivity alike.

• Focus on presence. Design for deep work uninterrupted by notifications through "do not disturb" features and by limiting open application tabs. Being fully present boosts cognitive performance, relationships and fulfillment.

• Promote mindful usage. Educate on techniques like limiting screen time before bed, observing usage patterns objectively and focusing on one task at a time to counter distraction and regain focus.

• Emphasize human contact. Foster in-person interactions through community events, walking meetings and limiting fully remote work arrangements to satisfy belongingness needs and buffers against isolation.

• Embed wellbeing nudges. Develop apps and systems that gently remind and incentivize users to take breaks, power down evenings and weekends through gamification. Stanford researchers found such nudges effectively shift habits over time (Mullan, 2020).

A "digital diet" approach to technology sees it not as inherently good or bad but calls for mindful consumption focused on human needs and outcomes rather than throughput alone. This nurtures flourishing alongside functionality in an increasingly digital world.

Conclusion

In the machine age dawning, technology holds promise but also unforeseen costs if not intentionally steered to complement humanity. The wellbeing "paradox" between AI's promise and potential disruption demands care, accountability and a people-centered mindset from leaders. With proactivity and understanding of deeper human needs, organizations can thoughtfully design technology, work and culture to strengthen resilience, fulfillment and dignity through change. This licenses AI's benefits while safeguarding society's hard-won progress on understanding human happiness, health and justice. Ultimately, an empowering partnership between humanity and our creations, not their opposition, will birth the higher potentials of this age for both business and human good. With care and conscience, the rise of AI need not diminish but elevate what is best in us.

References

1. Arntz, M., Gregory, T., & Zierahn, U. (2016). The risk of automation for jobs in OECD countries: A comparative analysis. OECD Social, Employment, and Migration Working Papers, (189).

2. Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & Company.

3. Cigna. (2018). Cigna U.S. loneliness index.

4. Deci, E. L., & Ryan, R. M. (2000). The" what" and" why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227-268.

5. Deloitte. (2018). The future of work: The reshaping of the workplace by persistent digital forces.

6. Daugherty, P. R., & Wilson, H. J. (2018). Human + machine: Reimagining work in the age of AI. Harvard Business Review Press.

7. EU High-Level Expert Group on AI. (2019). Ethics guidelines for trustworthy AI. European Commission.

8. Frey, C. B., & Osborne, M. A. (2013). The future of employment: How susceptible are jobs to computerisation. Oxford Martin School, 114.

9. Harvard Business Review. (2017). Helping employees find meaningful new work in the age of disruption.

10. Holt-Lunstad, J., Smith, T. B., Baker, M., Harris, T., & Stephenson, D. (2015). Loneliness and social isolation as risk factors for mortality: a meta-analytic review. Perspectives on psychological science, 10(2), 227-237.

11. Kivimäki, M., Vahtera, J., Pentti, J., & Ferrie, J. E. (2000). Factors underlying the effect of organizational downsizing on health of employees: longitudinal cohort study. BMJ, 320(7240), 971–975.

12. Logg, J. M., Minson, J. A., & Moore, D. A. (2019). Algorithm appreciation: People prefer algorithmic to human judgment. Organizational Behavior and Human Decision Processes, 151, 90-103.

13. Misra, S., & Stokols, D. (2012). Psychological and health outcomes of perceived information overload. Environment and Behavior, 44(6), 737-759.

14. Mullan, E. (2020). The impact of a smartphone app (Centered) designed to promote digital well-being on mental health and well-being. Journal of Positive School Psychology, 4(1), 37-46.

15. Stanton, J. M., & Barnes-Farrell, J. L. (1996). Effects of electronic performance monitoring on personal control, task satisfaction, and task performance. Journal of Applied Psychology, 81(6), 738.

16. Westervelt, A. (2016). The lonely American just got a whole lot lonelier.

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Jonathan H. Westover, PhD is Chief Academic & Learning Officer (HCI Academy); Associate Dean and Director of HR Programs (WGU); Professor, Organizational Leadership (UVU); OD/HR/Leadership Consultant (Human Capital Innovations). Read Jonathan Westover's executive profile here.

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Suggested Citation: Westover, J. H. (2025). The Wellbeing Paradox in an AI World. Human Capital Leadership Review, 28(4). doi.org/10.70175/hclreview.2020.28.4.1