Five Ways To Design A Better Job For Yourself
What’s easier for a robot: playing chess or gardening on a windy day? How about playing a video game or balancing on one foot?
Some tasks that are trivial for humans, yet immensely difficult for robots. This is encapsulated by Moravec’s paradox, named after Hans Moravec, a robotics researcher at Carnegie Mellon University.1 Complex, abstract tasks, such as chess or algebra, are tiring for us yet trivial for robots. Small movements and balancing, on the contrary, are easy for us yet taxingly difficult for artificially intelligent beings. These uniquely human benefits come in handy when thinking of what your post-automation job will look like.
What makes us human
The automation-resistant tasks that remain for us at work after automation further progresses will need our uniquely human abilities. Skills like creativity, empathy, and dexterity are much easier for people to exhibit than computers.2 After all, we’ve practiced these skills since birth, with many opportunities to learn and adapt. Armed with insights about what tasks you’ll be doing after a wave of automation, you can look to the future and design a more automation-resistant role within your organization.
References
- ThinkAutomation (n.d). What is Moravec’s Paradox and What does it Mean for Modern AI? Retrieved at https://www.thinkautomation.com/bots-and-ai/what-is-moravecs-paradox-and-what-does-it-mean-for-modern-ai/.
- Autor, D. (2014). Polanyi’s paradox and the shape of employment growth (Vol. 20485). Cambridge, MA: National Bureau of Economic Research.
- Blazejewski, S., & Walker, E. M. (2018). Digitalization in Retail Work: Coping With Stress Through Job Crafting. Socio-Economic Studies, 29(1), 79-100.
- Zhang, W., Guan, X., Zhou, X. and Lu, J. (2019), The effect of career adaptability on career planning in reaction to automation technology, Career Development International, 24(6), 545-559.
- Bersin, J. (2019). Untangling the HR Tech Market 2020. Presentation at the HR Technology Conference 2019.
- Parker, Sharon & Grote, Gudela. (2019). Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in A Digital World. Journal of Applied Psychology. 10.1111/apps.12241.
- Hackman, R.J., & Oldham, G. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Performance, 16(2), 250-279.
- de Witte, M., & Steijn, B. (2000). Automation, job content, and underemployment. Work, Employment, and Society, 14(2), 245-264.
- Elsbach, K. D., & Hargadon, A. B. (2006). Enhancing creativity through “mindless” work: A framework of workday design. Organization Science, 17(4), 470-483.
About the Author
Natasha Ouslis
Natasha is a behavior change consultant, writer, and researcher. She started her own workplace behavioral science consulting firm after working as a consultant at fast-growing behavioral economics companies including BEworks. Natasha is also finishing her PhD in organizational psychology at Western University, specializing in team conflict and collaboration, where she completed her Master of Science in the same field. She has a monthly column on workplace behavioral design in the Habit Weekly newsletter and is a Director and science translator at the nonprofit ScienceForWork.
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