Biometric Technology and Ethics: Beyond Security Applications

• Albrecht, J. P. (2016). How the GDPR will change the world. European Data Protection Law Review, 2, 287–289.

  Google Scholar 

• Alterman, A. (2003). “A piece of yourself”: Ethical issues in biometric identification. Ethics and Information Technology, 5(3), 139–150.

  Google Scholar 

• Ball, K. (2005). Organization, surveillance and the body: Towards a politics of resistance. Organization, 12(1), 89–108.

  Google Scholar 

• Bhattacharyya, D., Ranjan, R., Alisherov, F., & Choi, M. (2009). Biometric authentication: A review. International Journal of u-and e-Service, Science and Technology, 2(3), 13–28.

  Google Scholar 

• Breland, A. (2017). How white engineers built racist code—and why it’s dangerous for black people. https://www.theguardian.com/technology/2017/dec/04/racist-facial-recognition-white-coders-black-people-police. Accessed 1 Nov 2018.

• Brown, W. S. (1996). Technology, workplace privacy and personhood. Journal of Business Ethics, 15(11), 1237–1248.

  Google Scholar 

• Brusoni, S., & Vaccaro, A. (2017). Ethics, technology and organizational innovation. Journal of Business Ethics, 143(2), 223–226.

  Google Scholar 

• Buchholz, R. A., & Rosenthal, S. B. (2002). Technology and business: Rethinking the moral dilemma. Journal of Business Ethics, 41(1–2), 45–50.

  Google Scholar 

• Campisi, P. (2013). Security and privacy in biometrics (Vol. 24). New York: Springer.

  Google Scholar 

• Carpenter, D., McLeod, A., Hicks, C., & Maasberg, M. (2018). Privacy and biometrics: An empirical examination of employee concerns. Information Systems Frontiers, 20(1), 91–110.

  Google Scholar 

• Cavoukian, A., Chibba, M., & Stoianov, A. (2012). Advances in biometric encryption: Taking privacy by design from academic research to deployment. Review of Policy Research, 29(1), 37–61.

  Google Scholar 

• Corcoran, P., & Costache, C. (2016). Smartphones, biometrics, and a brave new world. IEEE Technology and Society Magazine, 35(3), 59–66.

  Google Scholar 

• Custers, B., Dechesne, F., Sears, A. M., Tani, T., & van der Hof, S. (2018). A comparison of data protection legislation and policies across the EU. Computer Law and Security Review, 34(2), 234–243.

  Google Scholar 

• D’Mello, S. K., Craig, S. D., & Graesser, A. C. (2009). Multimethod assessment of affective experience and expression during deep learning. International Journal of Learning Technology, 4(3–4), 165–187.

  Google Scholar 

• D’Mello, S. K., & Graesser, A. (2010). Multimodal semi-automated affect detection from conversational cues, gross body language, and facial features. User Modeling and User-Adapted Interaction, 20(2), 147–187.

  Google Scholar 

• Davis, J., & Nathan, L. P. (2015). Value sensitive design: Applications, adaptations, and critiques. In Handbook of ethics, values, and technological design (pp. 11–40). New York: Springer.

• de Vries, R. E., & van Gelder, J.-L. (2015). Explaining workplace delinquency: The role of Honesty–Humility, ethical culture, and employee surveillance. Personality and Individual Differences, 86, 112–116.

  Google Scholar 

• Dhanani, L. Y., Beus, J. M., & Joseph, D. L. (2018). Workplace discrimination: A meta-analytic extension, critique, and future research agenda. Personnel Psychology, 71(2), 147–179.

  Google Scholar 

• Dierksmeier, C., & Seele, P. (2018). Cryptocurrencies and business ethics. Journal of Business Ethics, 152(1), 1–14.

  Google Scholar 

• Dixon, P. (2008). Ethical issues implicit in library authentication and access management: Risks and best practices. Journal of Library Administration, 47(3–4), 141–162.

  Google Scholar 

• Economist, T. (2017). Advances in AI are used to spot signs of sexuality. https://www.economist.com/news/science-and-technology/21728614-machines-read-faces-are-coming-advances-ai-are-used-spot-signs. Accessed 1 Nov 2018.

• European Commission. (2018a). What does the General Data Protection Regulation (GDPR) govern? https://ec.europa.eu/info/law/law-topic/data-protection/reform/what-does-general-data-protection-regulation-gdpr-govern_en. Accessed 28 Dec.

• European Commission. (2018b). What data can we process and under what conditions? https://ec.europa.eu/info/law/law-topic/data-protection/reform/rules-business-and-organisations/principles-gdpr/what-data-can-we-process-and-under-which-conditions_en. Accessed 29 Dec.

• Evans, R., McNamee, M., & Owen, G. (2017). Ethics, nanobiosensors and elite sport: The need for a new governance framework. Science and Engineering Ethics, 23(6), 1487–1505.

  Google Scholar 

• Eyers, J. (2017). Westpac testing AI to monitor staff and customers. Australian Financial Review. November 14. https://www.afr.com/technology/westpac-testing-ai-to-monitor-staff-and-customers-20171114-gzks7h. Accessed 29 Dec 2018.

• Fairweather, N. B. (1999). Surveillance in employment: The case of teleworking. Journal of Business Ethics, 22(1), 39–49.

  Google Scholar 

• Grafsgaard, J., Wiggins, J. B., Boyer, K. E., Wiebe, E. N., & Lester, J. (2013). Automatically recognizing facial expression: Predicting engagement and frustration. In Proceedings of the 6th International Conference on Educational Data Mining (pp. 43–50).

• Greenwood, M., & Van Buren, I. I. I., H. J (2010). Trust and stakeholder theory: Trustworthiness in the organisation–stakeholder relationship. Journal of Business Ethics, 95(3), 425–438.

  Google Scholar 

• Gregersen, A., Langkjær, B., Heiselberg, L., & Wieland, J. L. (2017). Following the viewers: Investigating television drama engagement through skin conductance measurements. Poetics, 64, 1–13.

  Google Scholar 

• Gurdus, E. (2017). UnitedHealthcare and Fitbit to pay users up to $1,500 to use devices, Fitbit co-founder says. https://www.cnbc.com/2017/01/05/unitedhealthcare-and-fitbit-to-pay-users-up-to-1500-to-use-devices.html. Accessed 4 Nov 2018.

• Hassib, M., Schneegass, S., Eiglsperger, P., Henze, N., Schmidt, A., & Alt, F., EngageMeter: A system for implicit audience engagement sensing using electroencephalography. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017 (pp. 5114–5119): ACM.

• Henschke, A. (2017). Ethics in an age of surveillance: Personal information and virtual identities. Cambridge: Cambridge University Press.

  Google Scholar 

• Herschel, R., & Miori, V. M. (2017). Ethics and big data. Technology in Society, 49, 31–36.

  Google Scholar 

• Holland, P. J., Cooper, B., & Hecker, R. (2015). Electronic monitoring and surveillance in the workplace: The effects on trust in management, and the moderating role of occupational type. Personnel Review, 44(1), 161–175.

  Google Scholar 

• Hoofnagle, C. J., King, Jennifer, Li, Su, & Turow, J. (2010). How different are young adults from older adults when it comes to information privacy attitudes and policies?. Available at https://doi.org/10.2139/ssrn.1589864.

• Hou, R. (2017). Neoliberal governance or digitalized autocracy? The rising market for online opinion surveillance in China. Surveillance and Society, 15(3/4), 418–424.

  Google Scholar 

• Introna, L., & Nissenbaum, H. (2010). Facial recognition technology a survey of policy and implementation issues. Lancaster University Management School Working Paper (Vol. 2010/030): Lancaster University.

• Jain, A. K., Hong, L., & Pankanti, S. (2000). Biometric identification. Communications of the ACM, 43(2), 90–98.

  Google Scholar 

• Jain, A. K., & Kumar, A. (2012). Biometric recognition: an overview. In Second generation biometrics: The ethical, legal and social context (pp. 49–79). New York: Springer.

• Jain, A. K., Ross, A. A., & Nandakumar, K. (2011). Introduction. In Introduction to biometrics (pp. 1–49). New York: Springer.

  Google Scholar 

• Karkazis, K., & Fishman, J. R. (2017). Tracking US professional athletes: The ethics of biometric technologies. The American Journal of Bioethics, 17(1), 45–60.

  Google Scholar 

• Kirchberg, V., & Tröndle, M. (2012). Experiencing exhibitions: A review of studies on visitor experiences in museums. Curator, 55(4), 435–452.

  Google Scholar 

• Kirchberg, V., & Tröndle, M. (2015). The museum experience: Mapping the experience of fine art. Curator, 58(2), 169–193.

  Google Scholar 

• Klare, B. F., Burge, M. J., Klontz, J. C., Bruegge, R. W. V., & Jain, A. K. (2012). Face recognition performance: Role of demographic information. IEEE Transactions on Information Forensics and Security, 7(6), 1789–1801.

  Google Scholar 

• Kokolakis, S. (2017). Privacy attitudes and privacy behaviour: A review of current research on the privacy paradox phenomenon. Computers and Security, 64, 122–134.

  Google Scholar 

• Li, Y., Kobsa, A., Knijnenburg, B. P., & Nguyen, M. C. (2017). Cross-cultural privacy prediction. Proceedings on Privacy Enhancing Technologies, 2017(2), 113–132.

  Google Scholar 

• Loch, K. D., Conger, S., & Oz, E. (1998). Ownership, privacy and monitoring in the workplace: A debate on technology and ethics. Journal of Business Ethics, 17(6), 653–663.

  Google Scholar 

• Lodge, J. (2006). Ethical EU eJustice: Elusive or illusionary? Journal of Information, Communication and Ethics in Society, 4(3), 131–144.

  Google Scholar 

• Lodge, J. (2012). The dark side of the moon: Accountability, ethics and new biometrics. In Second generation biometrics: The ethical, legal and social context (pp. 305–328). New York: Springer.

• Lupton, D. (2013). Quantifying the body: Monitoring and measuring health in the age of mHealth technologies. Critical Public Health, 23(4), 393–403.

  Google Scholar 

• Lupton, D. (2016a). The diverse domains of quantified selves: Self-tracking modes and dataveillance. Economy and Society, 45(1), 101–122.

  Google Scholar 

• Lupton, D. (2016b). Personal data practices in the age of lively data. Digital sociologies, 335–350.

• Lupton, D. (2016c). You are your data: Self-tracking practices and concepts of data. In Lifelogging (pp. 61–79): Springer.

• Lupton, D. (2017). Feeling your data: Touch and making sense of personal digital data. New Media and Society, 19(10), 1599–1614.

  Google Scholar 

• Malsch, I. (2013). The just war theory and the ethical governance of research. Science and Engineering Ethics, 19(2), 461–486.

  Google Scholar 

• Maltseva, K., & Lutz, C. (2018). A quantum of self: A study of self-quantification and self-disclosure. Computers in Human Behavior, 81, 102–114.

  Google Scholar 

• Martella, C., Gedik, E., Cabrera-Quiros, L., Englebienne, G., & Hung, H. (2015). How was it?: Exploiting smartphone sensing to measure implicit audience responses to live performances. In Proceedings of the 23rd ACM International conference on Multimedia (pp. 201–210). Brisbane Australia.

• Martella, C., Miraglia, A., Frost, J., Cattani, M., & van Steen, M. (2017). Visualizing, clustering, and predicting the behavior of museum visitors. Pervasive and Mobile Computing, 38, 430–443.

  Google Scholar 

• Martin, A. J., Wellen, J. M., & Grimmer, M. R. (2016). An eye on your work: How empowerment affects the relationship between electronic surveillance and counterproductive work behaviours. The International Journal of Human Resource Management, 27(21), 2635–2651.

  Google Scholar 

• Martin, K. (2016). Understanding privacy online: Development of a social contract approach to privacy. Journal of Business Ethics, 137(3), 551–569.

  Google Scholar 

• Martin, K. (2018). Ethical implications and accountability of algorithms. Journal of Business Ethics, 1–16.

• Martin, K., & Freeman, R. E. (2003). Some problems with employee monitoring. Journal of Business Ethics, 43(4), 353–361.

  Google Scholar 

• Martin, K. E., & Freeman, R. E. (2004). The separation of technology and ethics in business ethics. Journal of Business Ethics, 53(4), 353–364.

  Google Scholar 

• McDaniel, B., D’Mello, S., King, B., Chipman, P., Tapp, K., & Graesser, A. (2007). Facial features for affective state detection in learning environments. In D.S. McNamara and J.G. Trafton (Eds.) Proceedings of the 29th Annual Cognitive Science Society, (pp. 467–472), Austin.

• McStay, A. (2014). Privacy and philosophy: New media and affective protocol. New York, Peter Lang.

  Google Scholar 

• McStay, A. (2016). Empathic media and advertising: Industry, policy, legal and citizen perspectives (the case for intimacy). Big Data and Society, 3(2), 1–11.

  Google Scholar 

• McStay, A. (2018). Emotional AI: The rise of empathic media. Bangor: Sage.

  Google Scholar 

• Milligan, C. S. (1999). Facial recognition technology, video surveillance, and privacy. Southern California Interdisciplinary Law Journal, 9, 295.

  Google Scholar 

• Miltgen, C. L., & Peyrat-Guillard, D. (2014). Cultural and generational influences on privacy concerns: A qualitative study in seven European countries. European Journal of Information Systems, 23(2), 103–125.

  Google Scholar 

• Mingers, J., & Walsham, G. (2010). Toward ethical information systems: The contribution of discourse ethics. MIS Quarterly, 34(4), 833.

  Google Scholar 

• Moore, P., & Piwek, L. (2017). Regulating wellbeing in the brave new quantified workplace. Employee Relations, 39(3), 308–316.

  Google Scholar 

• Murry, W. D., Wimbush, J. C., & Dalton, D. R. (2001). Genetic screening in the workplace: Legislative and ethical implications. Journal of Business Ethics, 29(4), 365–378.

  Google Scholar 

• Naker, S., & Greenbaum, D. (2017). Now you see me: Now you still do: Facial recognition technology and the growing lack of privacy. Boston University Journal of Science & Technology Law, 23, 88.

  Google Scholar 

• Nissenbaum, H. (2004). Privacy as contextual integrity. Washington Law Review, 79, 119–158.

  Google Scholar 

• Nissenbaum, H. (2009). Privacy in context: Technology, policy, and the integrity of social life. Stanford: Stanford University Press.

  Google Scholar 

• Nissenbaum, H. (2011). A contextual approach to privacy online. Daedalus, 140(4), 32–48.

  Google Scholar 

• NIST (2018). National Institute of Standards and Technology Face Recognition Vendor Test. https://www.nist.gov/programs-projects/face-recognition-vendor-test-frvt. Accessed 4 Nov.

• Norval, A., & Prasopoulou, E. (2017). Public faces? A critical exploration of the diffusion of face recognition technologies in online social networks. New Media and Society, 19(4), 637–654.

  Google Scholar 

• Nunan, D., & Di Domenico, M. (2017). Big data: A normal accident waiting to happen? Journal of Business Ethics, 145(3), 481–491.

  Google Scholar 

• Odoherty, K. C., Christofides, E., Yen, J., Bentzen, H. B., Burke, W., Koenig, N. H. A., et al. (2016). If you build it, they will come: Unintended future uses of organised health data collections. BMC Medical Ethics, 17(54), 1–16.

  Google Scholar 

• Park, Y. J. (2013). Digital literacy and privacy behavior online. Communication Research, 40(2), 215–236.

  Google Scholar 

• Park, Y. J., & Skoric, M. (2017). Personalized ad in your Google Glass? Wearable technology, hands-off data collection, and new policy imperative. Journal of Business Ethics, 142(1), 71–82.

  Google Scholar 

• Pentina, I., Zhang, L., Bata, H., & Chen, Y. (2016). Exploring privacy paradox in information-sensitive mobile app adoption: A cross-cultural comparison. Computers in Human Behavior, 65, 409–419.

  Google Scholar 

• Prabhakar, S., Pankanti, S., & Jain, A. K. (2003). Biometric recognition: Security and privacy concerns. IEEE Security and Privacy, 99(2), 33–42.

  Google Scholar 

• Royakkers, L., Timmer, J., Kool, L., & Rinie van, E. (2018). Societal and ethical issues of digitization. Ethics and Information Technology, 20(2), 127–142.

  Google Scholar 

• Schuelke-Leech, B. A. (2018). A model for understanding the orders of magnitude of disruptive technologies. Technological Forecasting and Social Change, 129, 261–274.

  Google Scholar 

• Schumacher, G. (2012). Behavioural biometrics: Emerging trends and ethical risks. In Second Generation Biometrics: The Ethical, Legal and Social Context (pp. 215–227). New York: Springer.

• Sheehy, B. (2015). Defining CSR: Problems and solutions. Journal of Business Ethics, 131(3), 625–648.

  Google Scholar 

• Shi, X., & Wu, X. (2017). An overview of human genetic privacy. Annals of the New York Academy of Sciences, 1387(1), 61–72.

  Google Scholar 

• Smith, G. J. D., San Roque, M., Westcott, H., & Marks, P. (2013). Surveillance texts and textualism: Truthtelling and trustmaking in an uncertain world. Surveillance and Society, 11(3), 215–221.

  Google Scholar 

• Soleymani, M., Asghari-Esfeden, S., Pantic, M., & Fu, Y. Continuous emotion detection using EEG signals and facial expressions. In Multimedia and Expo (ICME), 2014 IEEE International Conference on, 2014 (pp. 1–6): IEEE**.

• Sprokkereef, A., and de Hert, P. (2012). Biometrics, privacy and agency. In Second generation biometrics: The ethical, legal and social context (pp. 81–101). New York: Springer.

• Sud, M., & VanSandt, C. (2015). Identity rights: A structural void in inclusive growth. Journal of Business Ethics, 132(3), 589–601.

  Google Scholar 

• Sutrop, M., & Laas-Mikko, K. (2012). From identity verification to behavior prediction: Ethical implications of second generation biometrics. Review of Policy Research, 29(1), 21–36.

  Google Scholar 

• Taddicken, M. (2014). The ‘privacy paradox’in the social web: The impact of privacy concerns, individual characteristics, and the perceived social relevance on different forms of self-disclosure. Journal of Computer-Mediated Communication, 19(2), 248–273.

  Google Scholar 

• Trocchia, P. J., & Ainscough, T. L. (2006). Characterizing consumer concerns about identification technology. International Journal of Retail and Distribution Management, 34(8), 609–620.

  Google Scholar 

• Ulman, Y. I., Cakar, T., & Yildiz, G. (2015). Ethical issues in neuromarketing: “I Consume, Therefore I am!”. Science and Engineering Ethics, 21(5), 1271–1284.

  Google Scholar 

• Unar, J., Seng, W. C., & Abbasi, A. (2014). A review of biometric technology along with trends and prospects. Pattern Recognition, 47(8), 2673–2688.

  Google Scholar 

• Van der Ploeg, I. (2003). Biometrics and privacy: A note on the politics of theorizing technology. Information, Communication and Society, 6(1), 85–104.

  Google Scholar 

• Wang, C., & Cesar, P. Do we react in the same manner?: Comparing GSR patterns across scenarios. In Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational, 2014 (pp. 501–510): ACM.

• Wang, C., & Cesar, P. The play is a hit: But how can you tell? In Proceedings of the 2017 ACM SIGCHI Conference on Creativity and Cognition, 2017 (pp. 336–347): ACM.

• Wang, C., Geelhoed, E. N., Stenton, P. P., & Cesar, P. Sensing a live audience. In Proceedings of the 32nd annual ACM conference on Human factors in computing systems, 2014 (pp. 1909–1912): ACM.

• Wang, C., Wong, J., Zhu, X., Röggla, T., Jansen, J., & Cesar, P. Quantifying audience experience in the wild: Heuristics for developing and deploying a biosensor infrastructure in theaters. In Quality of Multimedia Experience (QoMEX), 2016 Eighth International Conference on IEEE, 2016 (pp. 1–6).

• Webb, A. M., Wang, C., Kerne, A., & Cesar, P. Distributed liveness: Understanding how new technologies transform performance experiences. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, 2016 (pp. 432–437): ACM.

• West, J. P., & Bowman, J. S. (2016). Electronic surveillance at work: An ethical analysis. Administration and Society, 48(5), 628–651.

  Google Scholar 

• Whitehill, J., Serpell, Z., Lin, Y.-C., Foster, A., & Movellan, J. R. (2014). The faces of engagement: Automatic recognition of student engagementfrom facial expressions. IEEE Transactions on Affective Computing, 5(1), 86–98.

  Google Scholar 

• Winter, J. S. (2014). Surveillance in ubiquitous network societies: Normative conflicts related to the consumer in-store supermarket experience in the context of the Internet of Things. Ethics and Information Technology, 16(1), 27–41.

  Google Scholar 

• Winter, S. J., Stylianou, A. C., & Giacalone, R. A. (2004). Individual differences in the acceptability of unethical information technology practices: The case of Machiavellianism and ethical ideology. Journal of Business Ethics, 54(3), 273–301.

  Google Scholar 

• Zarsky, T. Z. (2017). Incompatible: The GDPR in the age of big data. Seton Hall Law Review, 47(4), 995–1020.

  Google Scholar 

• Zhao, W., Chellappa, R., Phillips, P. J., & Rosenfeld, A. (2003). Face recognition: A literature survey. ACM Computing Surveys, 35(4), 399–458.

  Google Scholar 

• Zwitter, A. (2014). Big data ethics. Big Data and Society, 1(2), 1–6.

  Google Scholar 

• Wickins, J. (2007). The ethics of biometrics: the risk of social exclusion from the widespread use of electronic identification. Science and Engineering Ethics, 13(1), 45–54.

  Google Scholar 

• Finn, R. L., Wright, D., & Friedewald, M. (2013). Seven types of privacy. In European data protection: coming of age (pp. 3–32). Dordrecht: Springer.

• Jain, A. K., Ross, A., & Prabhakar, S. (2004). An introduction to biometric recognition. IEEE Transactions on circuits and systems for video technology, 14(1), 1–29.

  Google Scholar 

Download references