WorkCookie - Get Ahead with Industrial/Organizational Psychology in the Workplace

A critical look at what the research says about technology, attention, and AI-intensified work, separating what is well supported from what is still emerging, and asking what our tools are costing the thinking they were meant to serve.

In this Episode:  Meagan Bond, Tom Bradshaw, Nic Kruegar, Natasha Desjardins, Gaby Cadena, Lee Crowson
 
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References
 

National Highway Traffic Safety Administration. (2025). Distracted driving in 2023 (Traffic Safety Facts Research Note, DOT HS 813 704). https://crashstats.nhtsa.dot.gov/Api/Public/Publication/813704. Source for the 2023 figure of 3,275 deaths in distraction-affected crashes.

Redelmeier, D. A., & Tibshirani, R. J. (1997). Association between cellular-telephone calls and motor vehicle collisions. The New England Journal of Medicine, 336(7), 453–458. Source for the study of 699 drivers, which found about four times the risk of a collision during phone use and no safety advantage for hands-free phones.

Strayer, D. L., Drews, F. A., & Crouch, D. J. (2006). A comparison of the cell phone driver and the drunk driver. Human Factors, 48(2), 381–391. Source for the driving-simulator finding that hand-held and hands-free conversations delayed braking and increased collisions, with impairment that the authors concluded can be as profound as the impairment from driving at the legal alcohol limit.

Stothart, C., Mitchum, A., & Yehnert, C. (2015). The attentional cost of receiving a cell phone notification. Journal of Experimental Psychology: Human Perception and Performance, 41(4), 893–897. Source for the finding that call and text notifications, even when unanswered, increased errors on a sustained attention task, which the authors attribute to mind wandering.

Mark, G., Gudith, D., & Klocke, U. (2008). The cost of interrupted work: More speed and stress. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 107–110). ACM. Source for the finding that 48 interrupted participants finished faster with no loss of quality and reported more stress, frustration, time pressure, and effort.

Marcora, S. M., Staiano, W., & Manning, V. (2009). Mental fatigue impairs physical performance in humans. Journal of Applied Physiology, 106(3), 857–864. Source for the study in which 16 participants cycled to exhaustion after 90 minutes of a demanding computer task or 90 minutes of documentaries, and lasted about 640 seconds versus about 754 seconds, with higher perceived exertion after the demanding task.

Van Cutsem, J., Marcora, S., De Pauw, K., Bailey, S., Meeusen, R., & Roelands, B. (2017). The effects of mental fatigue on physical performance: A systematic review. Sports Medicine, 47(8), 1569–1588. Source for review evidence that mental fatigue impairs endurance performance, largely through higher perceived exertion.

Brown, D. M. Y., Graham, J. D., Innes, K. I., Harris, S., Flemington, A., & Bray, S. R. (2020). Effects of prior cognitive exertion on physical performance: A systematic review and meta-analysis. Sports Medicine, 50(3), 497–529. Source for meta-analytic support of the same pattern in endurance performance.

Gantois, P., Lima-Junior, D., Fortes, L. S., Batista, G. R., Nakamura, F. Y., & Fonseca, F. S. (2021). Mental fatigue from smartphone use reduces volume-load in resistance training: A randomized, single-blinded cross-over study. Perceptual and Motor Skills, 128(4), 1640–1659. Source for the finding that 16 recreationally trained adults completed less back-squat volume-load after 30 minutes of smartphone social media use than after a documentary.

Chang, A.-M., Aeschbach, D., Duffy, J. F., & Czeisler, C. A. (2015). Evening use of light-emitting eReaders negatively affects sleep, circadian timing, and next-morning alertness. Proceedings of the National Academy of Sciences, 112(4), 1232–1237. Source for the finding that reading on a light-emitting device before bed, compared with a printed book, lengthened the time to fall asleep, suppressed melatonin, delayed the circadian clock, and reduced next-morning alertness.

Johnston, W. M., & Davey, G. C. L. (1997). The psychological impact of negative TV news bulletins: The catastrophizing of personal worries. British Journal of Psychology, 88(1), 85–91. Source for the finding that a 14-minute negative news bulletin left viewers more anxious and sadder than viewers of positive or neutral bulletins and more likely to catastrophize a personal worry.

Mark, G. (2023). Attention span: A groundbreaking way to restore balance, happiness and productivity. Hanover Square Press. Source for the screen-attention figures (about 2.5 minutes in 2003, 75 seconds in 2012, and about 47 seconds in more recent years) and for the finding that people interrupt themselves about as often as others interrupt them.

Lee, H.-P. (Hank), Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI ’25). ACM. Source for the survey of 319 knowledge workers (936 examples) in which higher confidence in AI was associated with less self-reported critical thinking.

Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö., & Mariman, R. (2025). Generative AI without guardrails can harm learning: Evidence from high school mathematics. Proceedings of the National Academy of Sciences, 122(26), e2422633122. https://doi.org/10.1073/pnas.2422633122. Source for the randomized field experiment with roughly 1,000 high school students in which a standard chatbot raised practice performance by 48 percent and lowered later exam performance by 17 percent, while a hint-giving tutor matched the control group on the exam.

Shen, J. H., & Tamkin, A. (2026). How AI impacts skill formation. arXiv:2601.20245. https://arxiv.org/abs/2601.20245. Source for the randomized trial with 52 software engineers in which the AI-assisted group averaged 50 percent on a quiz about a new programming library, against 67 percent for the hand-coding group. The authors are at Anthropic.

Budzyń, K., et al. (2025). Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: A multicentre, observational study. The Lancet Gastroenterology & Hepatology. https://doi.org/10.1016/S2468-1253(25)00133-5. Source for the finding that, at four centers in Poland, the adenoma detection rate of 19 experienced endoscopists in colonoscopies without AI fell from 28.4 percent to 22.4 percent after routine AI exposure.

Dell’Acqua, F., McFowland, E., III, Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2023). Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality (Harvard Business School Working Paper No. 24-013). Source for the field experiment with 758 consultants at the Boston Consulting Group, with large gains inside the AI frontier and a 19 percentage point drop in correct solutions outside it.

Parra-Moyano, J., Reinmoeller, P., & Schmedders, K. (2025, July 1). Research: Executives who used gen AI made worse predictions. Harvard Business Review. Source for the experiment with about 300 executives and managers forecasting a stock price, in which those who consulted ChatGPT became more optimistic and more confident and were less accurate than those who consulted peers.

Fernandes, D., Villa, S., Nicholls, S., Haavisto, O., Buschek, D., Schmidt, A., Kosch, T., Shen, C., & Welsch, R. (2026). AI makes you smarter but none the wiser: The disconnect between performance and metacognition. Computers in Human Behavior, 175, 108779. Source for two experiments with about 500 participants in which ChatGPT users scored higher on LSAT reasoning problems and overestimated their performance.

Doshi, A. R., & Hauser, O. P. (2024). Generative AI enhances individual creativity but reduces the collective diversity of novel content. Science Advances, 10(28), eadn5290. Source for the finding that stories written with AI-generated ideas were rated as more novel and more useful and were more similar to one another.

Niederhoffer, K., Rosen Kellerman, G., Lee, A., Liebscher, A., Rapuano, K., & Hancock, J. (2025, September). AI-generated “workslop” is destroying productivity. Harvard Business Review. Source for the survey of 1,150 full-time U.S. employees by BetterUp Labs and the Stanford Social Media Lab, in which 40 percent reported receiving workslop in the past month, at nearly two hours per incident and about $186 per employee per month.

Ranganathan, A., & Ye, X. M. (2026, February). AI doesn’t reduce work—it intensifies it. Harvard Business Review. Source for the eight-month study of a U.S. technology company of about 200 people, which found a faster pace, a broader scope, and longer hours after generative AI adoption.

Bedard, J., Kropp, M., Hsu, M., Karaman, O., Hawes, J., & Rosen Kellerman, G. (2026, March 5). When using AI leads to “brain fry.” Harvard Business Review. Source for the survey of 1,488 full-time U.S. workers in which 14 percent reported AI brain fry, and in which high AI oversight was associated with more mental effort, more mental fatigue, and more information overload.

“They just don’t feel like a good fit.” Sounds harmless, but what exactly does fit mean, and who gets to define it?

We explored culture fit, comfort, psychological safety, belonging, and how organizations can distinguish genuine alignment from familiarity, assumptions, or preferences that may unintentionally shape who feels comfortable and included at work.

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We explored career advancement and the formal and informal factors that influence who gets access to opportunities, visibility, sponsorship, development, and leadership pathways.

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Performance evaluations are designed to measure performance, but the standards used to judge that performance may not always be as neutral as they appear.

We examined the lenses of performance evaluation: How organizations define performance, how managers interpret behavior, and how standards around competence, communication, leadership, and professionalism can shape evaluations.

In this Episode:  LindaAnn Rogers, Nic Krueger, Natasha Desjardins, Gaby Cadena
 
I/O Career Accelerator Course: https://www.seboc.com/job
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References
Accessible resources and APA citations
Falcone, P., & Tan, W. (2013). The performance appraisal tool kit: Redesigning your performance review template to drive individual and organizational change. AMACOM.
 
2. Best detailed guide to the process and tools
U.S. Office of Personnel Management. (n.d.). A handbook for measuring employee performance: Aligning employee performance plans with organizational goals.
Read the free handbook
Includes an eight-step process, worksheets, and examples. Start with Chapter 3. Practice guidance, particularly useful for examining how an organization moves from strategy to individual standards.
 
3. Best research foundation for setting expectations
Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57(9), 705–717.  https://doi.org/10.1037/0003-066X.57.9.705
Read the free full article hosted by Stanford
A peer-reviewed synthesis of research explaining how goals affect performance and the conditions that influence their effectiveness. It informs goal design, rather than supplying a complete appraisal system.
 
4. Actual tools for understanding the job
National Center for ONET Development. (n.d.). ONET questionnaires. O*NET Resource Center.
Access the free questionnaires

Two people can have similar qualifications, work in the same role, and still walk away with different compensation. Why?

This episode explores the dynamics of compensation negotiation, including salary expectations, market knowledge, organizational pay practices, negotiation behavior, and how value is perceived during the process.

In this episode:  LindaAnn Rogers, Tom Bradshaw, Nic Krueger, Natasha Desjardins, Dr. Tim Sharples, Gaby Cadena

 

I/O Career Accelerator Course: https://www.seboc.com/job

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Follow us on LinkedIn: https://bit.ly/sebocLI

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References

Agan, A. Y., Cowgill, B., & Gee, L. K. (2025). Salary history and employer demand: Evidence from a two-sided audit. American Economic Journal: Applied Economics, 17(3), 380–413.  https://doi.org/10.1257/app.20230365

Cullen, Z. B., Pakzad-Hurson, B., & Perez-Truglia, R. (2025). Pushing the envelope: The effects of salary negotiations (Working Paper No. 33903). National Bureau of Economic Research.  https://doi.org/10.3386/w33903

Leibbrandt, A., & List, J. A. (2015). Do women avoid salary negotiations? Evidence from a large-scale natural field experiment. Management Science, 61(9), 2016–2024.  https://doi.org/10.1287/mnsc.2014.1994