Author(s):

  • Robert L. Goldstone

Abstract:

Our lives are being measured in rapidly increasing ways and frequency. These measurements have beneficial and deleterious effects at both individual and social levels. Behavioral measurement technologies offer the promise of helping us to know ourselves better and to improve our well-being by using personalized feedback and gamification. At the same time, they present threats to our privacy, self-esteem, and motivation. At the societal level, the potential benefits of reducing bias and decision variability by using objective and transparent assessments are offset by threats of systematic, algorithmic bias from invalid or flawed measurements. Considerable technological progress, careful foresight, and continuous scrutiny will be needed so that the positive impacts of behavioral measurement technologies far outweigh the negative ones.

Documentation:

https://doi.org/10.1177/09637214211053834

References:
Acquisti, A., Brandimarte, L., Loewenstein, G. (2015). Privacy and human behavior in the age of information. Science, 347(6221), 509–514. https://doi.org/10.1126/science.aaa1465
Google Scholar | Crossref
Aleven, V., McLaughlin, E. A., Glenn, R. A., Koedinger, K. R. (2017). Instruction based on adaptive learning technologies. In Mayer, R. E., Alexander, P. A. (Eds.), Handbook of research on learning and instruction (2nd ed., pp. 522–560). Routledge.
Google Scholar
Allemand, M., Flückiger, C. (2022). Personality change through digital-coaching interventions. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211067782
Google Scholar
Angwin, J., Larson, J., Mattu, S., Kirchner, L. (2016, May 23). Machine bias: There’s software used across the country to predict future criminals. And it’s biased against blacks. Propublica. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
Google Scholar
Bathina, K. C., ten Thij, M., Lorenzo-Luaces, L., Rutter, L. A., Bollen, J. (2021). Individuals with depression express more distorted thinking on social media. Nature Human Behavior, 5(4), 458–466. https://doi.org/10.1038/s41562-021-01050-7
Google Scholar | Crossref
Beier, M. E. (2022). Life-span learning and development and its implications for workplace training. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211003891
Google Scholar | SAGE Journals
Beilock, S. (2011). Choke: What the secrets of the brain reveal about getting it right when you have to. Atria Books.
Google Scholar
Bitrián, P., Buil, I., Catalán, S. (2020). Gamification in sport apps: The determinants of users’ motivation. European Journal of Management and Business Economics, 29(3), 365–381. https://doi.org/10.1108/EJMBE-09-2019-0163
Google Scholar | Crossref
Castronova, E. (2007). Exodus to the virtual world: How online fun is changing reality. Palgrave Macmillan.
Google Scholar
Coppersmith, G. (2022). Digital life data in the clinical whitespace. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211068839
Google Scholar
de Barbaro, K., Fausey, C. M. (2022). Ten lessons about infants’ everyday experiences. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211059536
Google Scholar
D’Ignazio, C., Klein, L. F. (2020). Data feminism. MIT Press.
Google Scholar | Crossref
D’Mello, S. K., Tay, L., Southwell, R. (2022). Psychological measurement in the information age: Machine-learned computational models. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211056906
Google Scholar
Doignon, J.-P., Falmagne, J.-C. (2012). Knowledge spaces. Springer Science & Business Media.
Google Scholar
Dorsey, E. R., Glidden, A. M., Holloway, M. R., Birbeck, G. L., Schwamm, L. H. (2018). Teleneurology and mobile technologies: The future of neurological care. Nature Reviews Neurology, 14(5), 285–297. https://doi.org/10.1038/nrneurol.2018.31
Google Scholar | Crossref
Espeland, W. N., Saunder, M. (2016). Engines of anxiety: Academic rankings, reputation, and accountability. Russell Sage Foundation.
Google Scholar
Goldstone, R. L., Lupyan, G. (2016). Discovering psychological principles by mining naturally occurring data sets. Topics in Cognitive Science, 8(3), 548–568. https://doi.org/10.1111/tops.12212
Google Scholar | Crossref
Grundmann, F., Scheibe, S., Epstude, K. (2020). When ignoring negative feedback is functional: Presenting a model of motivated feedback disengagement. Current Directions in Psychological Science, 30(1), 3–10. https://doi.org/10.1177/0963721420969386
Google Scholar | SAGE Journals
Gurrin, C., Smeaton, A. F., Doherty, A. R. (2014). LifeLogging: Personal big data. Foundations and Trends in Information Retrieval, 8(1). https://doi.org/10.1561/1500000033
Google Scholar | Crossref
Hinds, J., Brown, O., Smith, L. G. E., Piwek, L., Ellis, D. A., Joinson, A. N. (2022). Integrating insights about human movement patterns from digital data into psychological science. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211042324
Google Scholar | SAGE Journals
Johnson, W. (2022). What’s to come of all this tracking “who we are”? The intelligence example. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211053831
Google Scholar | SAGE Journals
Kachergis, G., Marchman, V. A., Frank, M. C. (2022). Toward a “standard model” of early language learning. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211057836
Google Scholar | SAGE Journals
Kahneman, D., Sibony, O., Sunstein, C. R. (2021). Noise: A flaw in human judgment. Little, Brown Spark.
Google Scholar
Koretz, D. (2009). Measuring up: What educational testing really tells us. Harvard University Press.
Google Scholar | Crossref
Kröger, J. L., Raschke, P., Bhuiyan, T. W. (2019). Privacy implications of accelerometer data: A review of possible inferences. In ICCSP ’19: Proceedings of the 3rd International Conference on Cryptography, Security and Privacy (pp. 81–87). Association for Computing Machinery. https://doi.org/10.1145/3309074.3309076
Google Scholar | Crossref
Lupton, D. (2016). The quantified self. Polity Press.
Google Scholar
Mitchell, M. (2019). Artificial intelligence: A guide for thinking humans. Farrar, Straus and Giroux.
Google Scholar
Mosleh, M., Pennycook, G., Rand, D. G. (2022). Field experiments on social media. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211054761
Google Scholar | SAGE Journals
O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown.
Google Scholar
Page, S. (2019). The diversity bonus: How great teams pay off in the knowledge economy. Princeton University Press.
Google Scholar
Reber, R., Canning, E. A., Harackiewicz, J. M. (2018). Personalized education to increase interest. Current Directions in Psychological Science, 27(6), 449–454. https://doi.org/10.1177/0963721418793140
Google Scholar | SAGE Journals
Reid, V. M., Dunn, K. (2021). The fetal origins of human psychological development. Current Directions in Psychological Science, 30(2), 144–150. https://doi.org/10.1177/0963721420984419
Google Scholar | SAGE Journals
Roy, B. C., Frank, M. C., DeCamp, P., Miller, M., Roy, D. (2015). Predicting the birth of a spoken word. Proceedings of the National Academy of Sciences, USA, 112(41), 12663–12668. https://doi.org/10.1073/pnas.1419773112
Google Scholar | Crossref
Shariff, A., Green, J., Jettinghoff, W. (2021). The privacy mismatch: Evolved intuitions in a digital world. Current Directions in Psychological Science, 30(2), 159–166. https://doi.org/10.1177/0963721421990355
Google Scholar | SAGE Journals
Singer, E. (2011, June 21). The measured life. MIT Technology Review. https://www.technologyreview.com/s/424390/the-measured-life/
Google Scholar
Spencer, S. J., Steele, C. M., Quinn, D. M. (1999). Stereotype threat and women’s math performance. Journal of Experimental Social Psychology, 35(1), 4–28. https://doi.org/10.1006/jesp.1998.1373
Google Scholar | Crossref
Stafford, T., Vaci, N. (2022). Maximizing the potential of digital games for understanding skill acquisition. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211057841
Google Scholar
Swan, M. (2013). The quantified self: Fundamental disruption in big data science and biological discovery. Big Data, 1(2), 85–99. https://doi.org/10.1089/big.2012.0002
Google Scholar | Crossref
Twenge, J. M. (2019). More time on technology, less happiness? Associations between digital-media use and psychological well-being. Current Directions in Psychological Science, 28(4), 372–379. https://doi.org/10.1177/0963721419838244
Google Scholar | SAGE Journals
Verduyn, P., Gugushvili, N., Kross, E. (2022). Do social networking sites influence well-being? The extended active-passive model. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211053637
Google Scholar | SAGE Journals
Vosoughi, S., Roy, D., Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151. https://doi.org/10.1126/science.aap9559
Google Scholar | Crossref
Warlaumont, A. S., Sobowale, K., Fausey, C. M. (2022). Daylong mobile audio recordings reveal multitimescale dynamics in infants’ vocal productions and auditory experiences. Current Directions in Psychological Science, 31(1), XX–XX. https://doi.org/10.1177/09637214211058166
Google Scholar | SAGE Journals
Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.
Google Scholar