Abstract
Employees are increasingly wearing smart watches for their work duties. While these devices can support employees in their tasks, they can also collect sensitive information like health or location data about them, thus endangering their privacy. Even when collective agreements, allowing employers to collect such data have been signed, we argue that employees should be aware of the data collection and be able to control it. Therefore, we propose different indicators that aim at enhancing employees’ awareness about the current data collection as well as interactions to allow them to stop and resume it according to their preferences. To compare them, we have conducted an online questionnaire-based study with 1,033 participants. The results indicate that our participants wish to have such indicators to raise their awareness and further wish to control the data collection.
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References
Almuhimedi, H., et al.: Your location has been shared 5,398 times! a field study on mobile app privacy nudging. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (2015)
Apple Inc.: About the orange and green indicators in your iPhone status bar (2017). https://support.apple.com/en-us/HT211876. Accessed 09 Sept 2021
Bal, G., Rannenberg, K., Hong, J.: Styx: design and evaluation of a new privacy risk communication method for smartphones. In: Cuppens-Boulahia, N., Cuppens, F., Jajodia, S., Abou El Kalam, A., Sans, T. (eds.) SEC 2014. IAICT, vol. 428, pp. 113–126. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-55415-5_10
Barata, J., da Cunha, P.R.: Safety is the new black: the increasing role of wearables in occupational health and safety in construction. In: Abramowicz, W., Corchuelo, R. (eds.) BIS 2019. LNBIP, vol. 353, pp. 526–537. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-20485-3_41
Bovard, P.P., et al.: Multi-modal interruptions on primary task performance. In: Schmorrow, D.D., Fidopiastis, C.M. (eds.) AC 2018. LNCS (LNAI), vol. 10916, pp. 3–14. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91467-1_1
Choi, B., Hwang, S., Lee, S.H.: What drives construction workers’ acceptance of wearable technologies in the workplace?: indoor localization and wearable health devices for occupational safety and health. Autom. Constr. 84(1), 31–41 (2017)
Christin, D., Engelmann, F., Hollick, M.: Usable privacy for mobile sensing applications. In: Naccache, D., Sauveron, D. (eds.) WISTP 2014. LNCS, vol. 8501, pp. 92–107. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-43826-8_7
Christin, D., Michalak, M., Hollick, M.: Raising user awareness about privacy threats in participatory sensing applications through graphical warnings. In: Proceedings of the 11th International Conference on Advances in Mobile Computing & Multimedia (MoMM) (2013)
Christin, D., Reinhardt, A., Hollick, M., Trumpold, K.: Exploring user preferences for privacy interfaces in mobile sensing applications. In: Proceedings of 11th ACM International Conference on Mobile and Ubiquitous Multimedia (MUM) (2012)
Chung, H., Iorga, M., Voas, J.M., Lee, S.: Alexa, Can I Trust You? Computer 50(9), 100–104 (2017)
Cortina, J.M.: What is coefficient alpha? An examination of theory and applications. J. Appl. Psychol. 78(1), 98 (1993)
Datta, P., Namin, A.S., Chatterjee, M.: A survey of privacy concerns in wearable devices. In: Proceedings of the 2018 IEEE International Conference on Big Data (Big Data) (2018)
S.B. (Destatis): 12111–0004: Bevölkerung (Zensus): Deutschland, Stichtag, Geschlecht, Altersgruppen (2021). https://www-genesis.destatis.de/genesis/online
Franke, T., Attig, C., Wessel, D.: A personal resource for technology interaction: development and validation of the affinity for technology interaction (ATI) scale. Int. J. Hum.-Comput. Interact. 35(6), 456–467 (2019)
Gartner Inc.: Gartner Forecasts Global Spending on Wearable Devices to Total \$81.5 Billion in 2021 (2021). https://www.gartner.com/en/newsroom/press-releases/2021-01-11-gartner-forecasts-global-spending-on-wearable-devices-to-total-81-5-billion-in-2021. Accessed 14 Feb 2021
Glance, D.G., Ooi, E., Berman, Y., Glance, C.F., Barrett, H.R.: Impact of a digital activity tracker-based workplace activity program on health and wellbeing. In: Proceedings of the 6th International Conference on Digital Health Conference (DH) (2016)
Hassib, M., Abdelmoteleb, H., Khamis, M.: Are my Apps Peeking? Comparing nudging mechanisms to raise awareness of access to mobile front-facing camera. In: Proceedings of the 19th International Conference on Mobile and Ubiquitous Multimedia (MUM) (2020)
Hernández Acosta, L., Reinhardt, D.: A survey on privacy issues and solutions for voice-controlled digital assistants. Pervasive Mob. Comput. (2021)
CCS Insight: Healthy Outlook for Wearables As Users Focus on Fitness and Well-Being (2021). https://www.ccsinsight.com/press/company-news/healthy-outlook-for-wearables-as-users-focus-on-fitness-and-well-being/. Accessed 21 Sept 2021
Lau, J., Zimmerman, B., Schaub, F.: Alexa, are you listening?: privacy perceptions, concerns and privacy-seeking behaviors with smart speakers. ACM Hum.-Comput. Interact. 2(CSCW), 1–31 (2018)
Maltseva, K.: Wearables in the workplace: the brave new world of employee engagement. Bus. Horiz. 63, 493–505 (2020)
Mayring, P.: Qualitative content analysis. Companion Qual. Res. 1(2), 159–176 (2004)
Meyers, N.: Employee privacy in the electronic workplace: current issues for IT professionals. In: Proceedings of the 14th Australasian Conference on Information Systems (ACIS) (2003)
Mhaidli, A.H., Venkatesh, M.K., Zou, Y., Schaub, F.: Listen only when spoken to: interpersonal communication cues as smart speaker privacy controls. In: Proceedings of the 20st Privacy Enhancing Technologies Symposium (PoPETs) (2020)
Micallef, N., Just, M., Baillie, L., Alharby, M.: Stop annoying me! an empirical investigation of the usability of app privacy notifications. In: Proceedings of the 29th Australian Conference on Computer-Human Interaction (OZCHI) (2017)
Mirzamohammadi, S., Sani, A.A.: Viola: trustworthy sensor notifications for enhanced privacy on mobile systems. IEEE Trans. Mob. Comput. 17(11), 2689–2702 (2018)
Motti, V.G., Caine, K.: Users’ privacy concerns about wearables. In: Brenner, M., Christin, N., Johnson, B., Rohloff, K. (eds.) FC 2015. LNCS, vol. 8976, pp. 231–244. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-48051-9_17
Peissner, M., Hipp, C.: Potenziale der Mensch-Technik-Interaktion für die effiziente und vernetzte Produktion von morgen. Fraunhofer-Verlag Stuttgart (2013)
Pielot, M., Church, K., de Oliveira, R.: An in-situ study of mobile phone notifications. In: Proceedings of the 16th International Conference on Human-Computer Interaction with Mobile Devices & Services (MobileHCI) (2014)
Pizza, S., Brown, B., McMillan, D., Lampinen, A.: Smartwatch in Vivo. In: Proceedings of the 34th Conference on Human Factors in Computing Systems (CHI) (2016)
Prange, S., Shams, A., Piening, R., Abdelrahman, Y., Alt, F.: PriView-exploring visualisations to support users’ privacy awareness. In: Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI) (2021)
Raij, A., Ghosh, A., Kumar, S., Srivastava, M.: Privacy risks emerging from the adoption of innocuous wearable sensors in the mobile environment. In: Proceedings of the 29th ACM Conference on Human Factors in Computing Systems (SIGCHI) (2011)
Reidenberg, J.R., Russell, N.C., Herta, V., Sierra-Rocafort, W., Norton, T.B.: Trustworthy privacy indicators: grades, labels, certifications, and dashboards. Wash. UL Rev. 96, 1409 (2018)
Schall, M.C.J., Sesek, R.F., Cavuoto, L.A.: Barriers to the adoption of wearable sensors in the workplace: a survey of occupational safety and health professionals. Hum. Factors 60(3), 351–362 (2018)
Shaw, P.A., Mikusz, M.A., Davies, N.A.J., Clinch, S.E.: Using smartwatches for privacy awareness in pervasive environments. Poster at the 18th International Workshop on Mobile Computing Systems and Applications (HotMobile) (2017)
Stocker, A., Brandl, P., Michalczuk, R., Rosenberger, M.: Mensch-zentrierte IKT-Lösungen in einer Smart Factory. e & i Elektrotechnik und Informationstechnik 131(7) (2014)
Tiefenau, C., Häring, M., Gerlitz, E., von Zezschwitz, E.: Making privacy graspable: can we nudge users to use privacy enhancing techniques? CoRR (2019)
Tomczak, D.L., Lanzo, L.A., Aguinis, H.: Evidence-based recommendations for employee performance monitoring. Bus. Horiz. 61(2), 251–259 (2018)
Udoh, E.S., Alkharashi, A.: Privacy risk awareness and the behavior of smartwatch users: a case study of Indiana University students. In: Proceedings of the 2016 Future Technologies Conference (FTC) (2016)
Weber, D., Voit, A., Le, H.V., Henze, N.: Notification dashboard: enabling reflection on mobile notifications. In: Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct (MobileHCI). ACM (2016)
Williams, M., Nurse, J.R., Creese, S.: (smart) watch out! encouraging privacy-protective behavior through interactive games. Int. J. Hum.-Comput. Stud. 132, 121–137 (2019)
Zebra Technologies: Quality Drives a Smarter Plant Floor: Manufacturing Vision Study (2017)
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We would like thank our participants and our group members for their feedback on the questionnaire.
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Richter, A., Kühtreiber, P., Reinhardt, D. (2022). Enhanced Privacy in Smart Workplaces: Employees’ Preferences for Transparency Indicators and Control Interactions in the Case of Data Collection with Smart Watches. In: Meng, W., Fischer-Hübner, S., Jensen, C.D. (eds) ICT Systems Security and Privacy Protection. SEC 2022. IFIP Advances in Information and Communication Technology, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-031-06975-8_3
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DOI: https://doi.org/10.1007/978-3-031-06975-8_3
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