Wearables and User Interface Design: Impacts on Belief in Free Will

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 713)

Abstract

This research investigates the social implications of sensor driven self-quantification technologies designed to direct user behaviors. These self-sensoring prescriptive applications (SSPA’s), often referred to as “wearables,” have a strong presence in healthcare as a means to monitor and improve health, modify behavior, and reduce medical costs. However, the commercial sector is quickly adopting SSPA’s to monitor and/or modify consumer behaviors as well [1, 2, 3]. Interestingly, the direct impact biosensor data have on user decision making, attitude formation, and behavior has not been well researched. SSPA’s offer an opportunity for users to monitor the “self” in terms of quantitative, objective, biological terms that may be beyond the user’s control. Research suggests some states of the body (e.g. chronic pain, hunger) can affect underlying beliefs in free will (BFW), finding that the less control a person has over those physical states, the weaker their BFW [4]. It is not known, however, whether reminders about physical states of the body, such as heart rate monitors used during exercise, may also serve to reduce BFW. This is an important gap in knowledge when considering that reduced BFW can have numerous negative impacts on individual behavior [5, 6, 7]. This preliminary work examined the impact of such technologies on underlying BFW. Participants who monitored their heart rate during a short walk using a wearable heart rate and activity tracker had lower BFW than participants who merely look at the device’s various tracking features and participants in the control condition.

Keywords

Belief in free will Wearable Activity tracker Self-quantification Self-sensoring 

References

  1. 1.
    Swan, M.: Health 2050: the realization of personalized medicine through crowdsourcing, the quantified self, and the participatory biocitizen. J. Per. Med. 2(3), 93–118 (2012). doi: 10.3390/jpm2030093 CrossRefGoogle Scholar
  2. 2.
    Swan, M.: The quantified self: fundamental disruption in big data science and biological discovery. Big Data 1(2), 85–99 (2013). doi: 10.1089/big.2012.0002 CrossRefGoogle Scholar
  3. 3.
    Bolluyt, J.: Wearable tech devices: Can they really change your mood? CheatSheet.com, 29 June 2015. http://www.cheatsheet.com/technology/can-wearable-devices-improve-your-focus-or-your-mood.html/?a=viewall
  4. 4.
    Ent, M.R., Baumeister, R.F.: Embodied free will beliefs: some effects of physical states on metaphysical opinions. Conscious. Cogn. 27(1), 147–154 (2014). doi: 10.1016/j.concog.2014.05.001 CrossRefGoogle Scholar
  5. 5.
    Mueller, C.M., Dweck, C.S.: Praise for intelligence can undermine children’s motivation and performance. J. Pers. Soc. Psychol. 75(1), 33–52 (1998). doi: 10.1037/0022-3514.75.1.33 CrossRefGoogle Scholar
  6. 6.
    Vohs, K.D., Schooler, W.: The value of believing in free will: encouraging a belief in determinism increases cheating. Psychol. Sci. 19(1), 49–54 (2008). doi: 10.1111/j.1467-9280.2008.02045.x CrossRefGoogle Scholar
  7. 7.
    MacKenzie, M.J., Vohs, K.D., Baumeister, R.F.: You didn’t have to do that: belief in free will promotes gratitude. Pers. Soc. Psychol. Bull. 40(11), 1423–1434 (2014). https://doi.org/10.1177/001088048102200214
  8. 8.
    Baker, D.A.: Self “sensor” ship: an interdisciplinary investigation of the persuasiveness, social implications, and ethical design of self-sensoring prescriptive applications. Doctoral dissertation, Arizona State University (2016)Google Scholar
  9. 9.
    US Food and Drug Administration. General wellness: Policy for low risk devices draft guidance for industry and Food and Drug Administration staff. U.S. Department of Health and Human Services Food (2015)Google Scholar
  10. 10.
    US Federal Trade Commission: Prepared statement of the federal trade commission on opportunities and challenges in advancing health information technology. Washington, DC. (2016)Google Scholar
  11. 11.
    Boulos, M.N.K., Brewer, A.C., Karimkhani, C., Buller, D.B., Dellavalle, R.P.: Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online J. Public Health Inform. 5(3), 1–23 (2014). doi: 10.5210/ojphi.v5i3.4814 Google Scholar
  12. 12.
    Nahmias, E., Morris, S., Nadelhoffer, T., Turner, J.: Surveying freedom: folk intuitions about free will and moral responsibility. Philos. Psychol. 18(5), 561–584 (2005). doi: 10.1080/09515080500264180 CrossRefGoogle Scholar
  13. 13.
    Monroe, A.E., Malle, B.F.: From uncaused will to conscious choice: the need to study, not speculate about people’s folk concept of free will. Rev. Philos. Psychol. 1, 211–224 (2010)CrossRefGoogle Scholar
  14. 14.
    Wegner, D.M., Wheatley, T.: Apparent mental causation: sources of the experience of will. Am. Psychol. 54(7), 480–492 (1999)CrossRefGoogle Scholar
  15. 15.
    Feldman, G., Baumeister, R.F., Wong, K.F.E.: Free will is about choosing: the link between choice and the belief in free will. J. Exp. Soc. Psychol. 55, 239–245 (2014). doi: 10.1016/j.jesp.2014.07.012 CrossRefGoogle Scholar
  16. 16.
    Campbell, J.K.: A compatibilist theory of alternative possibilities. Philos. Stud. 88(3), 319–330 (1997). doi: 10.1023/A:1004280421383 CrossRefGoogle Scholar
  17. 17.
    Paulhus, D.L., Carey, J.M.: The FAD-Plus: measuring lay beliefs regarding free will and related constructs. J. Pers. Assess. 93(1), 96–104 (2011) https://doi.org/10.1080/00223891.2010.528483
  18. 18.
    Garmin vivoactive HR. Activity Tracking. www.garmin.com, https://buy.garmin.com/en-US/US/cIntoSports-c571-p1.html. Accessed 22 Mar 2017

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Missouri University of Science and TechnologyRollaUSA

Personalised recommendations