Older and Younger Adults Are Influenced Differently by Dark Pattern Designs: Conclusion & References

Table of Links

Abstract & Introduction

Background

Research Framework

Methods

Results

Discussion

Limitations and Future Work

Conclusion & References

Appendix

8 Conclusion

We studied the attitudinal and behavioral impact of dark pattern designs on older and younger adults. While an individual’s levels of privacy concerns may change in response to these design strategies, the behavioral effects of such strategies are dominant and individuals still end up disclosing their data despite heightened concerns. Furthermore, while older adults respond with more concern to some of these dark pattern designs than young adults, they are actually more vulnerable to such design strategies, perhaps due to a loss-aversive nature. Therefore, policy designers and technology developers should become familiar with the unique privacy attitudes and behaviors of older adults when it comes to disclosure. The solution may be a combination of identifying technology designs that counter the effects of dark patterns, as well as establishing rules and regulations around their use. Until that happens, older adults may continue to be disproportionately affected by dark pattern designs.

References

[1] Idris Adjerid, Alessandro Acquisti, Laura Brandimarte, and George Loewenstein. Sleights of privacy: Framing, disclosures, and the limits of transparency. In Proceedings of the ninth symposium on usable privacy and security, pages 1–11, 2013.

[2] Irwin Altman. The environment and social behavior: privacy, personal space, territory, and crowding. 1975.

[3] Reza Ghaiumy Anaraky, Kaileigh A. Byrne, Pamela J. Wisniewski, Xinru Page, and Bart P. Knijnenburg. To disclose or not to disclose: Examining the privacy decision-making processes of older vs. younger adults. In To Appear Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. ACM, 2021.

[4] Reza Ghaiumy Anaraky, Bart P Knijnenburg, and Marten Risius. Exacerbating mindless compliance: The danger of justifications during privacy decision making in the context of facebook applications. AIS Transactions on HumanComputer Interaction, 12(2):70–95, 2020.

[5] Reza Ghaiumy Anaraky, Tahereh Nabizadeh, Bart P Knijnenburg, and Marten Risius. Reducing default and framing effects in privacy decision-making. Proceedings of the Special Interest Group On Humancomputer Interaction, 2018.

[6] Solomon E Asch. Studies of independence and conformity: I. a minority of one against a unanimous majority. Psychological monographs: General and applied, 70(9):1, 1956.

[7] Paritosh Bahirat, Martijn C. Willemsen, Yangyang He, Qizhang Sun, and Bart P. Knijnenburg. Overlooking context: How do defaults and framing reduce deliberation in smart home privacy decision-making? In To Appear Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. ACM, 2021.

[8] Susan B Barnes. A privacy paradox: Social networking in the united states. First Monday, 2006.

[9] Andrew Besmer and Heather Richter Lipford. Moving beyond untagging: photo privacy in a tagged world. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 1563–1572, 2010.

[10] Cabral A Bigman, Joseph N Cappella, and Robert C Hornik. Effective or ineffective: Attribute framing and the human papillomavirus (hpv) vaccine. Patient education and counseling, 81:S70–S76, 2010.

[11] Jeremy Birnholtz and McKenzie Jones-Rounds. Independence and interaction: understanding seniors’ privacy and awareness needs for aging in place. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 143–152, 2010.

[12] Christoph Bösch, Benjamin Erb, Frank Kargl, Henning Kopp, and Stefan Pfattheicher. Tales from the dark side: Privacy dark strategies and privacy dark patterns. Proceedings on Privacy Enhancing Technologies, 2016(4):237–254, 2016.

[13] Marc Bourreau, Alexandre De Streel, and Inge Graef. Big data and competition policy: Market power, personalised pricing and advertising. Personalised Pricing and Advertising (February 16, 2017), 2017.

[14] Petter Bae Brandtzæg, Marika Lüders, and Jan Håvard Skjetne. Too many facebook “friends”? content sharing and sociability versus the need for privacy in social network sites. Intl. Journal of Human–Computer Interaction, 26(1112):1006–1030, 2010.

[15] US Census Bureau. Historical Living Arrangements of Adults. Section: Government.

[16] Kaileigh A Byrne and Reza Ghaiumy Anaraky. Strive to win or not to lose? age-related differences in framing effects on effortbased decision-making. The Journals of Gerontology: Series B, 75(10):2095–2105, 2020.

[17] Chrysanthos Dellarocas, Xiaoquan Michael Zhang, and Neveen F Awad. Exploring the value of online product reviews in forecasting sales: The case of motion pictures. Journal of Interactive marketing, 21(4):23–45, 2007.

[18] Miriam K Depping and Alexandra M Freund. Normal aging and decision making: The role of motivation. Human Development, 54(6):349–367, 2011.

[19] Tamara Dinev, Allen R McConnell, and H Jeff Smith. Research commentary—informing privacy research through information systems, psychology, and behavioral economics: thinking outside the “apco” box. Information Systems Research, 26(4):639–655, 2015.

[20] Isaac Dinner, Eric J Johnson, Daniel G Goldstein, and Kaiya Liu. Partitioning default effects: why people choose not to choose. Journal of Experimental Psychology: Applied, 17(4):332, 2011.

[21] Mary Ann Eastlick, Sherry L Lotz, and Patricia Warrington. Understanding online b-to-c relationships: An integrated model of privacy concerns, trust, and commitment. Journal of business research, 59(8):877–886, 2006.

[22] Kelwin Fernandes, Pedro Vinagre, and Paulo Cortez. A proactive intelligent decision support system for predicting the popularity of online news. In Portuguese Conference on Artificial Intelligence, pages 535–546. Springer, 2015.

[23] Alisa Frik, Julia Bernd, Noura Alomar, and Serge Egelman. A qualitative model of older adults’ contextual decisionmaking about information sharing. In Workshop on the Economics of Information Security (WEIS 2020), 2020.

[24] Eyal Gamliel and Eyal Peer. Attribute framing affects the perceived fairness of health care allocation principles. Judgment and Decision Making, 5(1):11, 2010.

[25] Colin M Gray, Yubo Kou, Bryan Battles, Joseph Hoggatt, and Austin L Toombs. The dark (patterns) side of ux design. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pages 1–14, 2018.

[26] Keith N Hampton, Lauren Sessions Goulet, Cameron Marlow, and Lee Rainie. Why most facebook users get more than they give. Pew Internet & American Life Project, 3(2012):1–40, 2012.

[27] Ward A Hanson and Daniel S Putler. Hits and misses: Herd behavior and online product popularity. Marketing letters, 7(4):297–305, 1996.

[28] Jeremy Rosenberg Harry Brignull, Marc Miquel and James Offer. Dark patterns user interfaces designed to trick people., 2015.

[29] Ganesh Iyer, David Soberman, and J Miguel Villas-Boas. The targeting of advertising. Marketing Science, 24(3):461– 476, 2005.

[30] Eric J Johnson, Steven Bellman, and Gerald L Lohse. Defaults, framing and privacy: Why opting in-opting out 1. Marketing letters, 13(1):5–15, 2002.

[31] Eric J Johnson, Simon Gächter, and Andreas Herrmann. Exploring the nature of loss aversion. 2006. [32] Eric J Johnson, John Hershey, Jacqueline Meszaros, and Howard Kunreuther. Framing, probability distortions, and insurance decisions. Journal of risk and uncertainty, 7(1):35– 51, 1993.

[33] Eric J Johnson, Suzanne B Shu, Benedict GC Dellaert, Craig Fox, Daniel G Goldstein, Gerald Häubl, Richard P Larrick, John W Payne, Ellen Peters, David Schkade, et al. Beyond nudges: Tools of a choice architecture. Marketing Letters, 23(2):487–504, 2012.

[34] Adam N Joinson, Ulf-Dietrich Reips, Tom Buchanan, and Carina B Paine Schofield. Privacy, trust, and self-disclosure online. Human–Computer Interaction, 25(1):1–24, 2010.

[35] Sidney M Jourard. Age trends in self-disclosure. MerrillPalmer Quarterly of Behavior and Development, 7(3):191– 197, 1961.

[36] Daniel Kahneman, Jack L Knetsch, and Richard H Thaler. Anomalies: The endowment effect, loss aversion, and status quo bias. Journal of Economic perspectives, 5(1):193–206, 1991.

[37] Daniel Kahneman, Jack L Knetsch, and Richard H Thaler. The endowment effect, loss aversion, and status quo bias: Anomalies. Journal of Economic perspectives, 5(1):193–206, 1991.

[38] Gideon Keren. Framing, intentions, and trust–choice incompatibility. Organizational Behavior and Human Decision Processes, 103(2):238–255, 2007.

[39] HyeKyoung Kim and Jihoon Song. The quality of word-ofmouth in the online shopping mall. Journal of Research in Interactive Marketing, 2010.

[40] Bart P Knijnenburg and Alfred Kobsa. Making decisions about privacy: information disclosure in context-aware recommender systems. ACM Transactions on Interactive Intelligent Systems (TiiS), 3(3):1–23, 2013.

[41] Bart Piet Knijnenburg and Alfred Kobsa. Increasing sharing tendency without reducing satisfaction: Finding the best privacysettings user interface for social networks. In ICIS, 2014.

[42] Bran Knowles and Vicki L Hanson. The wisdom of older technology (non) users. Communications of the ACM, 61(3):72–77, 2018.

[43] Yee-Lin Lai and Kai-Lung Hui. Internet opt-in and optout: investigating the roles of frames, defaults and privacy concerns. In Proceedings of the 2006 ACM SIGMIS CPR conference on computer personnel research: Forty four years of computer personnel research: achievements, challenges & the future, pages 253–263, 2006.

[44] Roy J Lewicki and Chad Brinsfield. Framing trust: trust as a heuristic. Framing matters: Perspectives on negotiation research and practice in communication, pages 110–135, 2011.

[45] Chia-Ying Li. Persuasive messages on information system acceptance: A theoretical extension of elaboration likelihood model and social influence theory. Computers in Human Behavior, 29(1):264–275, 2013.

[46] Lesa Lorenzen-Huber, Mary Boutain, L Jean Camp, Kalpana Shankar, and Kay H Connelly. Privacy, technology, and aging: A proposed framework. Ageing International, 36(2):232–252, 2011.

[47] Aditi M. Bhoot, Mayuri A. Shinde, and Wricha P. Mishra. Towards the identification of dark patterns: An analysis based on end-user reactions. In IndiaHCI’20: Proceedings of the 11th Indian Conference on Human-Computer Interaction, pages 24–33, 2020.

[48] Naresh K Malhotra, Sung S Kim, and James Agarwal. Internet users’ information privacy concerns (iuipc): The construct, the scale, and a causal model. Information systems research, 15(4):336–355, 2004.

[49] Aqdas Malik, Dhir Amandeep, Marko Nieminen, et al. Facebook photo tagging culture and practices among digital natives. In CCGIDIS 2015-Fifth International Symposium on Communicability, Computer Graphics and Innovative Design for Interactive Systems. Blue Herons Editions, 2015.

[50] Mehdi Marani, Morteza Soltani, Mina Bahadori, Masoumeh Soleimani, and Atajahangir Moshayedi. The role of biometric in banking: A review. EAI Endorsed Transactions on AI and Robotics, 2(1), 2023.

[51] Isabel Marcin and Andreas Nicklisch. Testing the endowment effect for default rules. Review of Law & Economics, 13(2), 2017.

[52] Mara Mather, Nina Mazar, Marissa A Gorlick, Nichole R Lighthall, Jessica Burgeno, Andrej Schoeke, and Dan Ariely. Risk preferences and aging: The “certainty effect” in older adults’ decision making. Psychology and aging, 27(4):801, 2012.

[53] Arunesh Mathur, Gunes Acar, Michael J Friedman, Elena Lucherini, Jonathan Mayer, Marshini Chetty, and Arvind Narayanan. Dark patterns at scale: Findings from a crawl of 11k shopping websites. Proceedings of the ACM on HumanComputer Interaction, 3(CSCW):1–32, 2019.

[54] Arunesh Mathur, Jonathan Mayer, and Mihir Kshirsagar. What makes a dark pattern... dark? design attributes, normative considerations, and measurement methods. arXiv preprint arXiv:2101.04843, 2021.

[55] D Harrison McKnight, Vivek Choudhury, and Charles Kacmar. Developing and validating trust measures for ecommerce: An integrative typology. Information systems research, 13(3):334– 359, 2002.

[56] Andrew L Mendelson and Zizi Papacharissi. Look at us: Collective narcissism in college student facebook photo galleries. The networked self: Identity, community and culture on social network sites, 1974:1–37, 2010.

[57] Miriam J Metzger. Effects of site, vendor, and consumer characteristics on web site trust and disclosure. Communication Research, 33(3):155–179, 2006.

[58] Mehrdad Mohammadi, Mahrou Samizadeh, Shaheen Pouya, and Raheleh Arabahmadi. Examining the mediating effect of knowledge management on the relationship between organizational culture and organizational performance. Journal of Soft Computing and Decision Analytics, 1(1):63–79, 2023.

[59] Bengt Muthén and Linda Muthén. Mplus. Chapman and Hall/CRC, 2017.

[60] Barbara M Newman and Philip R Newman. Development through life: A psychosocial approach. Cengage Learning, 2017.

[61] Helen Nissenbaum. Privacy as contextual integrity. Wash. L. Rev., 79:119, 2004.

[62] Xinru Page and Marco Marabelli. Changes in social media behavior during life periods of uncertainty. In Proceedings of the International AAAI Conference on Web and Social Media, volume 11, 2017.

[63] Leysia Palen and Paul Dourish. Unpacking" privacy" for a networked world. In Proceedings of the SIGCHI conference on Human factors in computing systems, pages 129–136, 2003.

[64] Yong Jin Park. Digital literacy and privacy behavior online. Communication Research, 40(2):215–236, 2013.

[65] Chris Rose. The security implications of ubiquitous social media. International Journal of Management & Information Systems (IJMIS), 15(1), 2011.

[66] Alexander J Rothman and Peter Salovey. Shaping perceptions to motivate healthy behavior: the role of message framing. Psychological bulletin, 121(1):3, 1997.

[67] Matthew Rueben, Frank J Bernieri, Cindy M Grimm, and William D Smart. Framing effects on privacy concerns about a home telepresence robot. In Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, pages 435– 444, 2017.

[68] Paul Russo and Oded Nov. Photo tagging over time: A longitudinal study of the role of attention, network density, and motivations. In Proceedings of the International AAAI Conference on Web and Social Media, volume 4, 2010.

[69] Sonam Samat and Alessandro Acquisti. Format vs. content: the impact of risk and presentation on disclosure decisions. In Thirteenth Symposium on Usable Privacy and Security ({SOUPS} 2017), pages 377–384, 2017.

[70] William Samuelson and Richard Zeckhauser. Status quo bias in decision making. Journal of risk and uncertainty, 1(1):7– 59, 1988.

[71] Hu Shuijing and Jiang Tao. An empirical study on digital privacy risk of senior citizens. In 2017 International Conference on Robots & Intelligent System (ICRIS), pages 19–24. IEEE, 2017.

[72] Michael Siegrist and George Cvetkovich. Better negative than positive? evidence of a bias for negative information about possible health dangers. Risk analysis, 21(1):199–206, 2001.

[73] H Jeff Smith, Tamara Dinev, and Heng Xu. Information privacy research: an interdisciplinary review. MIS quarterly, pages 989– 1015, 2011.

[74] M Soleimani, F Mahmudi, and MH Naderi. Some results on the maximal graph of commutative rings. Advanced Studies: EuroTbilisi Mathematical Journal, 16(supp1):21–26, 2023.

[75] Masoumeh Soleimani, Zahra Forouzanfar, Morteza Soltani, and Majid Jafari Harandi. Imbalanced multiclass medical data classification based on learning automata and neural network. EAI Endorsed Transactions on AI and Robotics, 2, 2023.

[76] Masoumeh Soleimani, Fatemeh Mahmudi, and Mohammad Hasan Naderi. On the maximal graph of a commutative ring. Mathematics Interdisciplinary Research, 2021.

[77] Masoumeh Soleimani and Mohamad Hasan Naderi. on power graph of some finite rings. Mathematics Interdisciplinary Research, 8(2):161–173, 2023.

[78] Sarah Spiekermann, Alessandro Acquisti, Rainer Böhme, and KaiLung Hui. The challenges of personal data markets and privacy. Electronic markets, 25(2):161–167, 2015.

[79] Sarah Spiekermann, Jens Grossklags, and Bettina Berendt. Eprivacy in 2nd generation e-commerce: privacy preferences versus actual behavior. In Proceedings of the 3rd ACM conference on Electronic Commerce, pages 38–47, 2001.

[80] Stoyan R Stoyanov, Leanne Hides, David J Kavanagh, Oksana Zelenko, Dian Tjondronegoro, and Madhavan Mani. Mobile app rating scale: a new tool for assessing the quality of health mobile apps. JMIR mHealth and uHealth, 3(1):e27, 2015.

[81] Fred Stutzman and Jacob Kramer-Duffield. Friends only: examining a privacy-enhancing behavior in facebook. In Proceedings of the SIGCHI conference on human factors in computing systems, pages 1553–1562, 2010.

[82] Mart Tacken, Fiorella Marcellini, Heidrun Mollenkopf, Isto Ruoppila, and Zsuzsa Szeman. Use and acceptance of new technology by older people. findings of the international mobilate survey:‘enhancing mobility in later life’. Gerontechnology, 3(3):126–137, 2005.

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

[84] Shalini Talwar, Amandeep Dhir, Puneet Kaur, Nida Zafar, and Melfi Alrasheedy. Why do people share fake news? associations between the dark side of social media use and fake news sharing behavior. Journal of Retailing and Consumer Services, 51:72–82, 2019.

[85] Lihong Tang, Wanlun Ma, Marthie Grobler, Weizhi Meng, Yu Wang, and Sheng Wen. Faces are protected as privacy: An automatic tagging framework against unpermitted photo sharing in social media. IEEE Access, 7:75556–75567, 2019.

[86] Jiang Tao and Hu Shuijing. The elderly and the big data how older adults deal with digital privacy. In 2016 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS), pages 285–288. IEEE, 2016.

[87] Zeynep Tufekci. Can you see me now? audience and disclosure regulation in online social network sites. Bulletin of Science, Technology & Society, 28(1):20–36, 2008.

[88] Amos Tversky and Daniel Kahneman. Rational choice and the framing of decisions. In Multiple criteria decision making and risk analysis using microcomputers, pages 81–126. Springer, 1989.

[89] Amos Tversky and Daniel Kahneman. Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and uncertainty, 5(4):297–323, 1992.

[90] Evert Van den Broeck, Karolien Poels, and Michel Walrave. Older and wiser? facebook use, privacy concern, and privacy protection in the life stages of emerging, young, and middle adulthood. Social Media+ Society, 1(2):2056305115616149, 2015.

[91] Eka Dyar Wahyuni and Arif Djunaidy. Fake review detection from a product review using modified method of iterative computation framework. In MATEC web of conferences, volume 58, page 03003. EDP Sciences, 2016.

[92] Pei-Shan Wei and Hsi-Peng Lu. An examination of the celebrity endorsements and online customer reviews influence female consumers’ shopping behavior. Computers in Human Behavior, 29(1):193–201, 2013.

[93] Marc G Weinberger and William R Dillon. The effects of unfavorable product rating information. ACR North American Advances, 1980.

[94] Pamela Wisniewski, AKM Islam, Heather Richter Lipford, and David C Wilson. Framing and measuring multidimensional interpersonal privacy preferences of social networking site users. Communications of the Association for information systems, 38(1):10, 2016.

[95] Pamela Wisniewski, Heng Xu, Heather Lipford, and Emmanuel Bello-Ogunu. F acebook apps and tagging: The trade-off between personal privacy and engaging with friends. Journal of the Association for Information Science and Technology, 66(9):1883–1896, 2015.

[96] Darrell A Worthy, Marissa A Gorlick, Jennifer L Pacheco, David M Schnyer, and W Todd Maddox. With age comes wisdom: Decision making in younger and older adults. Psychological science, 22(11):1375–1380, 2011.

[97] Heng Xu and Sumeet Gupta. The effects of privacy concerns and personal innovativeness on potential and experienced customers’ adoption of location-based services. Electronic Markets, 19(2- 3):137–149, 2009.

[98] Eva-Maria Zeissig, Chantal Lidynia, Luisa Vervier, Andera Gadeib, and Martina Ziefle. Online privacy perceptions of older adults. In International Conference on Human Aspects of IT for the Aged Population, pages 181–200. Springer, 2017.