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Unpacking Dark Patterns: Understanding Dark Patterns and Their Implications for Consumer Protection in the Digital

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Unpacking Dark Patterns: Understanding Dark Patterns and Their Implications for Consumer Protection in the Digital UNPACKING DARK PATTERNS: UNDERSTANDING DARK PATTERNS AND THEIR IMPLICATIONS FOR CONSUMER PROTECTION IN THE DIGITAL ECONOMY *Beni Chugh & **Pranjal Jain ABSTRACT This paper examines the increasing use of dark patterns in digital interfaces and the concerns they raise for consumer protection. Dark patterns are user-interfaces that confuse, coerce, or manipulate users into making a decision that does not reflect their underlying preferences. By exploiting users’ cognitive biases and reinforcing users’ information asymmetry, dark patterns impair their decision-making abilities. They coerce users into disregarding their preferences and acting against their best interests. This can cause significant harm in rapidly digitizing economies and societies. Dark patterns are already being used to steer users to sign up for financial products they may not need. They are also influencing citizens’ political choices and interfering with democratic processes. These incursions into users’ autonomy significantly disenfranchise and disempower them in the digital economy. Further, emerging research suggests that users with lower levels of education and earning lower levels of income are more vulnerable to dark patterns. These findings are crucial for jurisdictions such as India where the use of the internet is fast expanding to rural parts, and there is a rise in first-generation users of the internet. Here we analyze the use of dark patterns in digital interfaces and the influence they exert on users’ decision making. It distinguishes dark patterns from persuasive advertisements and sets out a list of common dark patterns to examine their adverse consequences for consumers. It advocates for regulatory intervention to arrest the proliferation of dark patterns on the internet and remedy the power imbalance they have already wrought. It concludes with some open questions that India must contend with when regulating dark patterns. * Beni Chugh, Research Manager, Future of Finance Initiative at Dvara Research. ** Pranjal Jain, Co-founder of theUXWhale, Alumnus of Dvara Research. PAGE | 1 2021 RGNUL STUDENT RESEARCH REVIEW Vol. 7(1) I. INTRODUCTION TO DARK PATTERNS Until recently it was common for travel portals to bundle travel insurance with travel tickets. They used pre-checked boxes to default the user into buying the insurance cover, even when the user had shown no active interest in purchasing the product or understanding it. Exhibit 1 demonstrates a screenshot of a transaction, typical of travel portals in India until recently. Exhibit 1: Use of pre-checked buttons to bundle insurance cover with travel tickets | Source: MoneyControl1 This use of pre-checked buttons to bundle travel cover with travel tickets is a classic example of a ‘dark pattern’. Dark patterns are “user interfaces that make it difficult for users to express their actual preferences or that manipulate users into taking actions that do not comport with their preferences or expectations”.2 The term ‘dark pattern’ was coined by Harry Brignull in 2010, who defined it as interface designs that “trick users into doing things that they might not want to do, but which benefit the business in question”.3 Dark patterns use the design of the interface to influence users to make choices they would not have made if 1 Explained: Here is why airlines, portals can no longer mis-sell you travel insurance from Oct 1, Moneycontrol, available at https://www.moneycontrol.com/news/business/economy/explained-here-is-why- airlines-portals-can-no-longer-mis-sell-you-travel-insurance-from-oct-1-4492451.html, last seen on 23/12/2020. 2 Stigler Committee on Digital Platforms, Final Report, Stigler Committee, available at https://research.chicagobooth.edu/-/media/research/stigler/pdfs/digital-platforms--- committee-report---stigler-center.pdf?la=en, last seen on 23/12/2020 3 H, Brignull, Dark Patterns: inside the interfaces designed to trick you, The Verge, available at https://www.theverge.com/2013/8/29/4640308/dark-patterns-inside-the-interfaces- designed-to-trick-you, last seen on 23/12/2020. PAGE | 2 UNPACKING DARK PATTERNS: UNDERSTANDING DARK PATTERNS AND THEIR IMPLICATIONS FOR CONSUMER PROTECTION IN DIGITAL ECONOMY the user interface did not distort the information presented to the user or limit the user from acting on that information. In the example above, the use of pre-checked boxes assumes that the user’s default preference will be to purchase an add-on financial service. Users are expected to expend costly time and attention to uncheck the box and opt out of the default purchase. This default setting is unfair and taps into users’ cognitive limitations. Users are known to be less likely to opt-out of existing defaults as they are beset by several cognitive biases and severe cognitive inertia, that keep them from questioning default options.4 Research from other jurisdictions suggests that when travel insurance covers travel tickets, even those users who did not intend to buy the cover, end up buying it. Even more worryingly, a sizeable proportion of buyers remains unaware that they purchased the cover, implying that they may never actually benefit from the insurance.5 Recognizing that pre-checked boxes disempower users by leveraging their cognitive biases, the Insurance and Regulatory Development Authority of India (“IRDAI”) has prohibited travel portals in India from using them for selling travel insurance. IRDAI has directed travel insurance companies to “ensure that any portal or App providing the travel insurance coverage shall not pre- select the option of buying the travel cover as a default option”.6 The regulator further emphasized that prospective buyers of insurance products should be allowed to make an “informed choice” before buying them. This regulatory 4 General Insurance Add-Ons Market Study – Remedies: banning opt-out selling across financial services and supporting informed decision-making for add-on buyers, Financial Conduct Authority, UK, available at https://www.fca.org.uk/publication/policy/policy-statement-15-22-general- insurance-add-ons.pdf, last seen on 23/12/2020; E.J. Johnson, S. Bellman & G.L. Lohse, Defaults, Framing and Privacy: Why Opting In-Opting Out, 13 Marketing Letters 5, (2002), available at https://www0.gsb.columbia.edu/mygsb/faculty/research/pubfiles/1173/defaults_fram ing_and_privacy.pdf, last seen on 23/12/2020; Consumer Rights Directive, Brussels: European Commission, available at https://ec.europa.eu/info/policies/consumers/consumer-protection_en, last seen 23/12/2020. 5 General insurance add-ons: Provisional findings of the market study and proposed remedies, Financial Conduct Authority, available at https://www.fca.org.uk/publication/market- studies/ms14-01.pdf. 6 Circular on Travel Insurance Products and operational matters, IRDAI, available at https://www.irdai.gov.in/ADMINCMS/cms/whatsNew_Layout.aspx?page=PageNo39 13&fl, last seen on 23/12/2020. PAGE | 3 2021 RGNUL STUDENT RESEARCH REVIEW Vol. 7(1) intervention shines a light on the increasing use of dark patterns and the questions it raises for consumer protection in the digital economy. II. EFFECT OF DARK PATTERNS ON USERS’ DECISION-MAKING ABILITIES Dark patterns differ from other marketing strategies in the effect they have on users’ preferences. Their objective is to make consumers disregard their own preferences and act in a manner inconsistent with them. They are designed to be manipulative rather than persuasive,7 to encourage users to make decisions they would not have made if not for their influence. This is in sharp contrast to persuasive marketing efforts that influence users to revise their preferences.8 This is evident in the example of the bundling of travel insurance cover with the travel ticket. The travel portal does not introduce the buyers to the product or convince them of its utility to influence their preferences. Instead, it resorts to directly adding the travel cover to the buyer’s purchase, regardless of their preferences. A growing body of scholarship is investigating the effects of dark patterns on the decision-making process of users by drawing on Tversky & Kahneman’s Dual Process Theory.9Kahneman & Tversky’s research suggests that humans have two modes of thinking: System 1 thinking and System 2 thinking. System 1 thinking is prompt, unconscious, automatic, less laborious, and less rational. System 2 thinking tends to be more conscious, rational and laborious. Researchers suggest that dark patterns appeal to System 1 of the human brain, encouraging users to make impulsive decisions that could serve the interests of the providers better than the interests of the users.10 7 Supra 2. 8 J. Luguri & L. Strahilevitz, Shining a light on Dark Patterns, University of Chicago Coase- Sandor Institute for Law & Economics Research Paper No. 879 (2019), available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3431205, last seen 23/12/2020. 9 A. Tversky & D. Kahneman, Judgment under Uncertainty: Heuristics and Biases, 185 Science 1124, 1131 (1974). 10 C. Bösch et al., Tales from the Dark Side: Privacy Dark Strategies and Privacy Dark Patterns, 2016 Proceedings on Privacy Enhancing Technologies, 237–254 (2016); J. Luguri & L. Strahilevitz, Shining a light on Dark Patterns, University of Chicago Coase-Sandor Institute for Law & Economics Research Paper No. 879 (2019), available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3431205, last seen 23/12/2020. PAGE | 4 UNPACKING DARK PATTERNS: UNDERSTANDING DARK PATTERNS AND THEIR IMPLICATIONS FOR CONSUMER PROTECTION IN DIGITAL ECONOMY Users’ decisions are influenced by the way information is presented to them. Features of the design interface such as the language in which information is presented, the functional hierarchy including the placement of the information, the font type, size and color used to present the information, influence the users’ decisions. Digital interfaces and accompanying choice architecture can be used to exploit users’ cognitive vulnerabilities. The choice architecture is informed by a deep understanding of the users’ behavioral biases, their bounded rationality, cognitive inertia and the constraints on the time and attention of users when they make decisions.
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