Why tech products should be designed alongside psychologists
Technology has drastically changed how we behave and what we feel and think. Every day, the first and last thing1 most of us do is check our phones. Sounds and vibrations from our phones distract us dozens of times a day.2 Phones and computers mediate a lot of our social interaction: Zoom meetings are not just for work, but personal events from baby showers to funerals.
Our social media feeds not only move our moods temporarily,3 but they also change how we view and how much we like ourselves.4 Technology also impacts the choices we make, from our shopping decisions (e.g., Uber can deter us from buying a car)5 to our political beliefs (e.g., YouTube can radicalize us into white supremacy).6
Technology changes human behavior, emotion, and cognition, despite being largely built or designed by technologists without a background in psychological science ( the term I’ll use to refer to the scientific study of human psychology, not the therapeutic practice of counseling) and whose jobs don’t explicitly involve applying or conducting psychological science.
Many of these technologists are scientists — e.g., data scientists building statistical models to predict human behavior. For example, about 18,000 employees across Alphabet, Amazon, Apple, Meta, and Microsoft have job titles containing the words “science” or “scientist.” But only about 200 (1%) have the word “behavior” or “behavioral” (including British spelling of these terms) in their job titles. There are psychologists who work in technology companies, but their jobs most often don’t involve applying psychological science. Job descriptions that overtly mention behavioral science are still relatively rare in the product teams that build most consumer technology.
Given that technology companies change human behavior at scale, profit from behavior change, and generally pride themselves on embracing scientific innovation, why do so many of them lack psychologists with a more formal and central role in product development?
The answer to this question holds the key to technology products that cause less unintended harm to people because they are designed with a more realistic understanding of human psychology.
Why psychologists are few and peripheral
A weak pipeline from academic psychology to the technology sector
When technology companies were more focused on enterprise rather than consumer applications, hardware rather than software, and technical professionals rather than non-technical amateurs, technology companies did not have the same need for psychologists. Technology companies were popular employers of computer scientists, not psychological scientists.
This pattern has continued to the present. For example, computer and computational science were the most popular university subjects for Googlers (29% of Google employees studied them, excluding other engineering subjects); psychology ranks thirteenth (less than 2% of Googlers studied it).
This situation likely led to psychologist underrepresentation in the leadership of technology companies, which leads to the potential contributions of psychology being unfamiliar or, potentially, underestimated. To continue our example, Google directors show a similar pattern in their university studies, favoring computer and computational science (26%) over psychology (3%).
References
- Keating, L. (2017, March 2). Survey Finds Most People Check Their Smartphones Before Getting Out Of Bed In The Morning. Tech Times. https://www.techtimes.com/articles/199967/20170302/survey-finds-people-check-smartphones-before-getting-out-bed.htm
- Push Notifications Statistics (2021). (2021, August 31). Business of Apps. https://www.businessofapps.com/marketplace/push-notifications/research/push-notifications-statistics/#:%7E:text=The%20average%20US%20smartphone%20user,Restraint%%2020can%20be%20key%2C%20therefore
- Lewis, T. (2014, July 1). Facebook Emotions Are Contagious, Study Finds. Yahoo!News. https://news.yahoo.com/facebook-emotions-contagious-study-finds-133519750.html
- Duffy, A. C. B. J. (2021, October 5). Instagram’s grim appeal as a silent self-esteem breaker. CNN. https://edition.cnn.com/2021/10/05/health/instagram-self-esteem-parenting-wellness/index.html
- Hampshire, R. C., Simek, C., Fabusuyi, T., Di, X., & Chen, X. (2017). Measuring the Impact of an Unanticipated Disruption of Uber/Lyft in Austin, TX. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2977969
- Koppelman, A. (2019, March 18). YouTube and other social networks are radicalizing white men. Big tech could be doing more. CNN Business. https://edition.cnn.com/2019/03/17/tech/youtube-facebook-twitter-radicalization-new-zealand/
- Mitchell, J. P. (2009). Inferences about mental states. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1521), 1309–1316. https://doi.org/10.1098/rstb.2008.0318
- Stich, S., & Ravenscroft, I. (1993, October). What is Folk Psychology? (Technical Report #5). Rutgers University Center for Cognitive Science, Rutgers University. https://ruccs.rutgers.edu/images/tech_rpt/tr-5/folkpsych5.pdf
- Houston, J. P. (1985). Untutored Lay Knowledge of the Principles of Psychology: Do We Know Anything They Don’t? Psychological Reports, 57(2), 567–570. https://doi.org/10.2466/pr0.1985.57.2.567
- Buehler, R., Griffin, D., & Ross, M. (1995). It’s About Time: Optimistic Predictions in Work and Love. European Review of Social Psychology, 6(1), 1–32. https://doi.org/10.1080/14792779343000112
- Ross, L., Greene, D., & House, P. (1977). The “False Consensus Effect”: An Egocentric Bias in Social Perception and Attribution Processes. Journal of Experimental Social Psychology, 13(3), 279–301. https://doi.org/10.1016/0022-1031(77)90049-x
- Nisbett, R. E., & Wilson, T. D. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Review, 84(3), 231–259. https://doi.org/10.1037/0033-295x.84.3.231
- Anderson, C. A., Lindsay, J. J., & Bushman, B. J. (1999). Research in the Psychological Laboratory. Current Directions in Psychological Science, 8(1), 3–9. https://doi.org/10.1111/1467-8721.00002
- Mitchell, G. (2012). Revisiting Truth or Triviality : The External Validity of Research in the Psychological Laboratory. Perspectives on Psychological Science, 7(2), 109–117. https://doi.org/10.1177/1745691611432343
- Wells, G., Horwitz, J., & Seetharaman, D. (2021, September 14). Facebook Knows Instagram Is Toxic for Teen Girls, Company Documents Show. The Wall Street Journal. https://www.wsj.com/articles/facebook-knows-instagram-is-toxic-for-teen-girls-company-documents-show-11631620739
- Ling, K., Beenen, G., Ludford, P., Wang, X., Chang, K., Li, X., Cosley, D., Frankowski, D., Terveen, L., Rashid, A. M., Resnick, P., & Kraut, R. (2005). Using Social Psychology to Motivate Contributions to Online Communities. Journal of Computer-Mediated Communication, 10(4), 00. https://doi.org/10.1111/j.1083-6101.2005.tb00273.x
- Lee, M. K. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5(1), 205395171875668. https://doi.org/10.1177/2053951718756684
About the Author
Juan Manuel Contreras
Juan Manuel Contreras, Ph.D. is an applied science manager at Uber working at the intersection of technology, policy, and law. He was trained as a social psychologist and cognitive neuroscientist at Harvard University and Princeton University.
About us
We are the leading applied research & innovation consultancy
Our insights are leveraged by the most ambitious organizations
“
I was blown away with their application and translation of behavioral science into practice. They took a very complex ecosystem and created a series of interventions using an innovative mix of the latest research and creative client co-creation. I was so impressed at the final product they created, which was hugely comprehensive despite the large scope of the client being of the world's most far-reaching and best known consumer brands. I'm excited to see what we can create together in the future.
Heather McKee
BEHAVIORAL SCIENTIST
GLOBAL COFFEEHOUSE CHAIN PROJECT
OUR CLIENT SUCCESS
$0M
Annual Revenue Increase
By launching a behavioral science practice at the core of the organization, we helped one of the largest insurers in North America realize $30M increase in annual revenue.
0%
Increase in Monthly Users
By redesigning North America's first national digital platform for mental health, we achieved a 52% lift in monthly users and an 83% improvement on clinical assessment.
0%
Reduction In Design Time
By designing a new process and getting buy-in from the C-Suite team, we helped one of the largest smartphone manufacturers in the world reduce software design time by 75%.
0%
Reduction in Client Drop-Off
By implementing targeted nudges based on proactive interventions, we reduced drop-off rates for 450,000 clients belonging to USA's oldest debt consolidation organizations by 46%
