Eva Tanya Banerjee
Affiliation: KTH Royal Institute of Technology
 EECS School of Electrical Engineering and Computer Science
Sweden  
Correspondence: etba@kth.se 

Cite This Source

Banerjee, E. T. (2025). Choice overload and surveillance: A critique of Amazon’s interaction design and its ethical implications. Confluence: Journal for Interdisciplinary Studies, Volume IX, 36-43.

In 2023, Amazon’s sales hit nearly 575 billion U.S. dollars (Coppola, 2025) in net sales revenue worldwide and became one of the most valuable brands worldwide as of 2024 (Faria, 2025). Amazon’s e-commerce derives its ethos and work goals from four main principles: “customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking.”(About Us | Amazon, n.d.)(Routson, 2010) A large amount of emphasis has been placed on Amazon’s goal to be the world’s most customer-centric company by providing customers with the lowest prices for goods and the ability to order and receive goods in the comfort of their home(About Us | Amazon, n.d.). As of November 2024, Amazon has over 310 million users around the world, with 9.7 million sellers worldwide and 1.9 million actively selling on the platform. Furthermore, approximately 92% of online shoppers have purchased an item from Amazon, 89% of whom prefer Amazon to any other website for purchasing products (Yaqub, 2025). However, the question that has often been researched and critiqued in previous studies is how Amazon makes money. However, going into the details of this cost cycle lies outside the scope of this interaction critique. In the Attention Economy (Center for Humane Technology, n.d.), these numbers are prime real estate for tech giants that use principles of persuasive technology(Fogg, 2002) to commoditise their users by manipulating data points that signify user motivation, ability and triggers to keep the user engaged and returning to the technology..

In the fields of Human-Computer Interaction (HCI) and interaction design, interaction critiques have emerged as valuable tools for constructing knowledge through interpretation, contextualization, interrelatedness, and critical questioning. These critiques contribute to an ongoing dialogue among practitioners, scholars, and the broader public (Bardzell et al., 2010). Positioned within this tradition, my commentary offers a critical reading of Amazon. Through this lens, I examine how Amazon’s design influences user behaviour, decision-making, and broader societal values. First, I explore how Amazon diminishes users’ ability to exercise agency by overwhelming them with options, drawing on American psychologist Barry Schwartz’s Paradox of Choice theory to show how the platform induces uncertainty and choice paralysis. Second, I consider how the collection and use of user data shape personalised experiences that further constrain what users see and choose. Finally, I reflect on the implications of these mechanisms for users’ sense of self and their capacity to participate in collective action, particularly in the context of urgent global issues such as climate change. I argue that Amazon’s interface not only disrupts individual autonomy but may also erode shared ethical values, contributing to a weakening of community-oriented decision-making.

How Excessive Options Impair User Decision-Making and Fosters Uncertainty
In Schwartz’s theory, he argues that while choice improves the quality of our lives, it can become excessive, leading to freedom being experienced as a kind of “misery-inducing tyranny” (“The Paradox of Choice,” 2015, 121-138). Additionally, Iyengar and Leppar’s 2000 study titled ‘When Choice is Demotivating: Can One Desire Too Much of a Good Thing?’ indicated how students faced with a small array of choices were more satisfied than those faced with a large array, hence suggesting that people find a large number of options paralysing rather than liberating (Iyenagar and Lepper, 2000). Before this, Simon argued that in situations where there is an explosion of choice, individuals will often “satisfice” (Simon, 1955)(Simon, 1956), referring to the act of choosing the first option to surpass the absolute
threshold of acceptability rather than trying to “optimize” and find the best possible choice.
This can be observed in user consumption trends and choices made on Amazon. Amazon not only promises multiple options or sellers of the same good but also caters to various user desirabilities such as the price of the good, the delivery time, and the product reviews. The vast variety of products with individual differences and customizability further contributes to the difficulty in decision-making, but also the number of options present on the screen can further confuse the user into a decision dilemma termed by Schwartz as “choice overload” (“The Paradox of Choice,” 2015, 121-138). This choice overload can result in users not only feeling exhausted but also pressured by the need to find the best option available in the variety of choices available to them(Simon, 1955). This furthers the potential for users to experience regret due to the fear of choosing suboptimally. For instance, while reviewing the website for Christmas tree reviews without applying any filters, it became evident that the website’s layout and placement of components reinforced a tailored sense of opportunity cost(Villeneuve, 2023). Specifically, the more expensive tree appeared to promise better reviews compared to the cheaper one, potentially motivating users to purchase the more expensive option. However, this is not the only issue with the layout. Upon closer examination, as seen in Fig. 1, it becomes apparent that the website also promotes or incentivises products with very few reviews by offering a price slash, appealing to users through perceived value.

Fig.1 Amazon Christmas tree listing from amazon.se, captured on July 2, 2025.

Such demonstrations do not indicate that users will choose the cheaper tree, but rather how the variety of fluctuating options makes users feel growingly helpless(Seligman, 1975) because they think that any decision made will result in opportunity costs. This fosters uncertainty(Chen and Cheng, 2015) in users, making it a determinant for companies that not only results in continuous monitoring of the page and products but also fosters user fatigue, self-blame and choice paralysis- leaving users feeling “debilitated rather than liberated” (“The Paradox of Choice,” 2015, 121-138).

Amazon’s Surveillance Capitalism
Coined by Zuboff in the book Age of Surveillance Capitalism, the conceptualisation of Surveillance Capitalism enables us to shed light on the fear around how human experiences are being treated as raw materials to help build behavioural databases that are then sold for predictions and make surveillance capitalists immensely profit from the trade of their digital monitoring (Zuboff, 2023). While academics in the field of digital ethics and HCI have grown critical of these market strategies, Amazon’s business practices indicate a rapid normalisation and even the encouragement to use tools that worm their way in not only through their website and targeted ads but also through the products manufactured by the company. For instance, the interactive ecosystem through Alexa and Echo devices has been proven to collect and partake in the non-consensual collection of user data (West, 2019). For example, in 2019, The New York Times published an article titled “Amazon’s Alexa Never Stops Listening to You. Should You Worry?” highlighted how the author’s interaction with the Echo device was akin to their relationship with a pet dog. However, one major criticism revolves around the algorithmic improvements enabling Alexa to recognise individual voices. This raises particular concerns for individuals with children, as it means their voices could be recorded without consent, amplifying fears surrounding the ethics of interactive technology.

But contrary to the aforementioned users, some often perceive their personalized feeds as a sign that the platform understands their preferences (Kant, 2020). It may result in ease of shopping and conversational assistance with purchasing tasks, data used for personalisation and data collected for data mining appear ambiguous or opaque. This impression is shaped by recommendation algorithms that rely on extensive data collection. However, research shows that obtaining informed user consent for data collection and processing is complex. In response, Amazon has implemented subtle design strategies such as pre-selected options or opaque privacy settings that facilitate data acquisition without requiring users to provide explicit or fully informed consent (Tene & Polonetsky, 2013). Moreover, it prompts critical questions about the extent to which privacy-invasive technology is being domesticated(Neville, 2021) and how large conglomerates like Amazon are not only utilising such data for their purposes but also packaging and selling it to other companies. Furthermore, something apparent through the course of all e-commerce platforms, but even more predominant on the Amazon website, is the Prime membership promises that the platform provides. Due to the expansive product and service infrastructure (Jenkins, 2018) and the convenience associated with ordering goods easily, fast deliveries and low prices are concomitant factors to nudge members to keep using the service. The data collected by users that on the surface appear to be necessary to deliver packages and complete tasks can then appear to help machines trained to feed recommender systems. Furthermore, the convenience offered by Prime masks the underlying aspects of how users’ frequency of engagement with the platform multiplies the data set and also furthers the ability to make inferences about non-users that share similar user demographics, locations, etc.

The problems that lie at the intersections of surveillance capitalism and decision-making impairment
While at a cursory glance, these problems appear to have a resolution, a large amount of the onus rests on users to act cautiously and be vigilant, which can result in user fatigue, growing distrust and helplessness while interacting more with technologies. This not only reduces technology to be viewed as a source of profit but also takes away from how many technologies and designers are attempting to design for social and ethical good. However, the main challenge that the occurrence of such problems can cause is the further marginalisation of marginalised communities and the lack of focus on a major goal of the discipline of user experience, which is to support user safety and, in turn, promote community welfare (Grundgeiger et al., 2021). Such interactions often leave users feeling overwhelmed, leading to a sense of numbness and apathy toward their choices. In recent years, users of platforms like Shein, Temu, and Amazon have frequently reported feelings of guilt about using these platforms. They explain that while these platforms are convenient and affordable, they lack the resources to find suitable alternatives. As highlighted in D’Ignazio and Klein’s article on data feminism, narratives around big data and data science have become increasingly white, male, and techno-heroic (D’Ignazio & Klein, 2020). Data ethics, however, does not solely call for the development of more ethical e-commerce platforms. Instead, it emphasises the need to hold companies like Amazon accountable by implementing checks and balances that safeguard user sentiments and needs, both now and in the future.

Finally, the intersection of decision fatigue and surveillance capitalism in Amazon’s interaction design raises critical questions about the ethical boundaries of persuasive technologies as well. While Amazon’s interface is optimised to foster continuous engagement, it does so at the expense of user autonomy. Rather than merely presenting itself as a customer-centric platform, Amazon’s practices reveal a calculated approach towards commodifying user behaviour and encouraging opaque data practices. However, it is possible to circumvent this by engaging in UX disciplines that prioritise user well-being. It is in these circumstances that the convergence of skills and collaborations between industry and academia can be most valuable, as it provides UX professionals with a sense of psychological safety and fosters connections beyond corporate barriers, implementing soft-resistance tactics (Wong, 2021). By critically examining these dimensions, interaction design researchers can offer pathways to reimagine e-commerce interfaces that prioritise transparency, reduce decision-making fatigue, and promote ethical alignment with broader societal goals.

Conclusion

In this article, I attempted to critically examine Amazon’s interaction design and its implications for user decision-making, privacy, and societal ethics. By leveraging Schwartz’s Paradox of Choice theory, I aimed to establish causal linkages between the theory and how Amazon’s expansive product offerings can impair user agency, leading to choice paralysis, uncertainty and regret. Furthermore, I attempted to shed light on the implications of surveillance capitalism by detailing how Amazon’s data collection practices not only compromise user privacy but also perpetuate patterns of exploitation under the guise of personalisation and convenience. Finally, I have extrapolated these connections to help support my argument on how these intersections create an interaction paradigm that prioritises profit over user welfare, perpetuating fatigue, distrust, and apathy among its users. By addressing these challenges, interaction design can play a pivotal role in reshaping e-commerce platforms to prioritise transparency, reduce decision fatigue, and align with the psychological safety of users and data ethics. The responsibility lies not only in advancing user-centred practices but also in holding corporations accountable to ensure technology serves as a tool for empowerment rather than exploitation.

References

About Us | Amazon. (n.d.). About Amazon. https://www.aboutamazon.com/about-us

Bardzell, J., Bolter, J., & Löwgren, J. (2010). Interaction criticism: three readings of an interaction design, and what they get us. Interactions, 17(2), 32 – 37. https://doi.org/10.1145/1699775.1699783

Center for Humane Technology. (n.d.). Persuasive Technology. Center for Humane Technology. https://www.humanetech.com/youth/persuasive-technology

Chen, Y., & Cheng, M. (2015). How Do Designers Deal With Uncertainty. Lund University School of Economics and Management. https://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=7370184&fileOId=7370196

Coppola, D. (2025, February 24). Amazon – statistics & facts. Statista. https://www.statista.com/topics/846/amazon/#topic

Overview D’Ignazio, C., & Klein, L. F. (2020). What Gets Counted Counts. In Data Feminism (pp. 97-123). MIT Press. https://doi.org/10.1080/2325548X.2022.2072592

Faria, J. (2025, September 11). Most valuable brands worldwide 2025. Statista. https://www.statista.com/statistics/264875/brand-value-of-the-25-most-valuable-brands/

Fogg, B. J. (n.d.). Persuasive technology: using computers to change what we think and do. Ubiquity, 2002(December), 89-120. https://doi.org/10.1145/764008.763957

Frank, R. (n.d.). Top 10 people most likely to reach trillionaire status. CNBC. Retrieved November 5, 2025, from https://www.cnbc.com/2024/09/06/top-10-people-most-likely-to-reach-trillionaire-status.html

Grundgeiger, T., Hurtienne, J., & Happel, O. (2021). Why and How to Approach User Experience in Safety-Critical Domains: The Example of Health Care. Human Factors, 63(5), 821-832. https://doi.org/10.1177/0018720819887575

Hookway, B. (2014). Interface. MIT Press. Iyenagar, S. S., & Lepper, M. R. (2000). When choice is demotivating: Can one desire too much of a good thing? Journal of Personality and Social Psychology, 79(6), 995–1006. https://doi.org/10.1037//0022-3514.79.6.995

Jenkins, T. (2018). Third-Wave HCI Perspectives on the Internet of Things. In M. Filimowicz (Ed.), New Directions in Third Wave Human-Computer Interaction: Volume 1 – Technologies (pp. 145–161). Springer International Publishing. https://doi.org/10.1007/978-3-319-73356-2_9

Kant, T. (2020). Making it Personal: Algorithmic Personalization, Identity, and Everyday Life. Oxford University Press. Neville, S. J. (2021).

The domestication of privacy-invasive technology on YouTube: Unboxing the Amazon Echo with the online warm expert. Convergence, 27(5), 1288-1307. https://doi.org/10.1177/1354856520970729

Oxfam. (2023, November 20). Top 5 ways billionaires are driving climate change. Oxfam. https://www.oxfamamerica.org/explore/stories/top-5-ways-billionaires-are-driving-climate-change/

The Paradox of Choice. (2015). In S. Joseph (Ed.), Positive Psychology in Practice: Promoting Human Flourishing in Work, Health, Education, and Everyday Life (pp. 121-138). Wiley. https://learning.oreilly.com/library/view/positive-psychology-in/9781118757253/c08.xhtml#c08_level
1_1

Routson, J. (2010, October 01). Jeff Bezos Makes Magic Out of Online Retailing. Stanford Graduate School of Business. https://www.gsb.stanford.edu/insights/jeff-bezos-makes-magic-out-online-retailing

Seligman, M. E.P. (1975). Helplessness: On Depression, Development, and Death. W. H. Freeman. Simon, H. A. (1955). A Behavioral Model of Rational Choice. The Quarterly Journal of Economics, 69(1), 99–118. https://doi.org/10.2307/1884852

Simon, H. A. (1956). Rational choice and the structure of the environment. Psychological Review, 63(2), 129–138. https://psycnet.apa.org/doi/10.1037/h0042769

Tene, O., & Polonetsky, J. (2013). Big Data for All: Privacy and User Control in the Age of Analytics. Northwestern Journal of Technology and Intellectual Property, 11(5), 239-273.

Villeneuve, L. (2023). John Stuart Mill and the art of consumption. The European Journal of the History of Economic Thought, 31(1), 40-58. https://doi.org/10.1080/09672567.2023.2238856

Wealth Inequality Initiative. (n.d.). About wealth inequality. Wealth Inequality Initiative. https://www.wealth-inequality.net/wealth-inequality-today

West, E. (2019). Surveillance & Society. Amazon: Surveillance as a Service, 17(1), 27-33. https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/13008/8472

Wong, R. Y. (2021). Tactics of Soft Resistance in User Experience Professionals’ Values Work. Proc. ACM Hum.-Comput. Interact., 5(CSCW2), 1 – 28. https://doi.org/10.1145/3479499

Yaqub, M. (2025, July 30). Amazon Statistics: The Ultimate Numbers Must Know in 2025. Business Dasher. https://www.contimod.com/amazon-statistics/#:~:text=Amazon%20User%20Statistics&text=Amazon%20h as%20over%20310%20million%20active%20users%20worldwide%2C%20with%2080,at%20least%20onc e%20a%20month.

Zuboff, S. (2023). The Age of Surveillance Capitalism. In Social Theory Re-Wired (pp. 203-213). Routledge. https://doi.org/10.4324/9781003320609-27