Algorithmic Consumer Duty of Care: Reconstructing Digital Platform Responsibility under Indonesian Consumer Protection Law

Novia Larasati Hidayat; Eko Galih Kusuma

Authors

Novia Larasati Hidayat Universitas Padjadjaran Author
Eko Galih Kusuma Universitas Padjadjaran Author

Keywords:

Algorithmic consumer duty of care, Algorithmic opacity, Dark patterns, Consumer vulnerability, Digital platform responsibility

Abstract

Purpose – This study examines whether algorithmic opacity, dark-pattern exposure, and substantive algorithmic transparency shape consumer vulnerability and support for proactive platform responsibility, and develops Algorithmic Consumer Duty of Care as a preventive framework for Indonesian consumer protection law.

Methodology – A quantitative cross-sectional survey of 412 Indonesian digital-platform consumers was analyzed using PLS-SEM, including measurement-model assessment, structural-path analysis, predictive relevance, and mediation testing.

Findings – Algorithmic opacity and dark-pattern exposure increased perceived consumer vulnerability, whereas substantive algorithmic transparency reduced it. Consumer vulnerability strongly increased support for proactive platform responsibility and significantly mediated all three algorithmic relationships, with dark-pattern exposure producing the strongest positive effect.

Implications – The findings support preventive platform obligations involving algorithmic risk assessment, meaningful transparency, restrictions on manipulative interface design, auditability, user control, and effective redress within Indonesian digital consumer protection.

Originality – The study integrates behavioral, technological, and legal perspectives in one empirical model and introduces Algorithmic Consumer Duty of Care as an autonomy-oriented and risk-based framework for platform accountability.

References

Abbott, R., Sin, R., Pedersen, C., Harris, T., Beck, T., Nilsson, S., Dong, T., Wang, Y., & Li, Y. (2023). The role of dark pattern stimuli and personality in online impulse shopping: An application of S-O-R theory. Journal of Consumer Behaviour, 22(6), 1311–1329.https://doi.org/10.1002/cb.2208

Afifah, N. (2024). Tanggung jawab hukum platform e-commerce terhadap keamanan data pribadi pengguna: Analisis berdasarkan UU PDP 2022. Jurnal Legalitas, 2(1), 29–38.https://doi.org/10.58819/jle.v2i1.165

Bitzer, T., Wiener, M., & Cram, W. A. (2023). Algorithmic transparency: Concepts, antecedents, and consequences: A review and research framework. Communications of the Association for Information Systems, 52, 293–331.https://doi.org/10.17705/1CAIS.05214

Brenncke, M. (2024). A theory of exploitation for consumer law: Online choice architectures, dark patterns, and autonomy violations. Journal of Consumer Policy, 47(1), 127–164.https://doi.org/10.1007/s10603-023-09554-7

Calaza, T. (2024). Caught in the web: How e-commerce plays with consumer minds. Brazilian Journal of Law, Technology and Innovation, 2(2), 54–70.https://doi.org/10.59224/bjlti.v2i2.54-70

Capone, V., Lo Presti, L., & Maggiore, G. (2025). Digital consumer vulnerability: A new theoretical framework through a systematic literature review. Micro & Macro Marketing, 2, 243–268.https://doi.org/10.1431/114639

de Elizalde, F. (2025). Fragmenting consumer law through data protection and digital market regulations: The DMA, the DSA, the GDPR, and EU consumer law. Journal of Consumer Policy, 48(3), 355–389.https://doi.org/10.1007/s10603-025-09584-3

Di Porto, F., & Egberts, A. (2024). The collective welfare dimension of dark patterns regulation. European Law Journal, 29(1–2), 114–141.https://doi.org/10.1111/eulj.12478

Duivenvoorde, B., & Goanta, C. (2023). The regulation of digital advertising under the DSA: A critical assessment. Computer Law & Security Review, 51, 105870.https://doi.org/10.1016/j.clsr.2023.105870

Durovic, M., & Poon, J. (2023). Consumer vulnerability, digital fairness, and the European rules on unfair contract terms: What can be learnt from the case law against TikTok and Meta? Journal of Consumer Policy, 46(4), 419–443.https://doi.org/10.1007/s10603-023-09546-7

Fagan, P. (2024). Clicks and tricks: The dark art of online persuasion. Current Opinion in Psychology, 58, 101844.https://doi.org/10.1016/j.copsyc.2024.101844

Fassiaux, S. (2023). Preserving consumer autonomy through European Union regulation of artificial intelligence: A long-term approach. European Journal of Risk Regulation, 14(4), 710–730.https://doi.org/10.1017/err.2023.58

Hacker, P. (2023). The European AI liability directives: Critique of a half-hearted approach and lessons for the future. Computer Law & Security Review, 51, 105871.https://doi.org/10.1016/j.clsr.2023.105871

Hair, J. F., Sarstedt, M., Ringle, C. M., Sharma, P. N., & Liengaard, B. D. (2024). Going beyond the untold facts in PLS-SEM and moving forward. European Journal of Marketing, 58(13), 81–106.https://doi.org/10.1108/EJM-08-2023-0645

Hayati, A. N. (2024). The issue of dark patterns in digital platforms: The challenge for Indonesia's consumer protection law. Asian Journal of Law and Society, 11(4), 453–465.https://doi.org/10.1017/als.2024.24

Judijanto, L., Basri, T. S., Khulaili Harsya, R. M., Vandika, A. Y., & Utama, A. S. (2024). Kajian hukum dampak kecerdasan buatan terhadap perlindungan privasi data dalam hukum siber Indonesia. Sanskara Hukum dan HAM, 3(2), 68–76.https://doi.org/10.58812/shh.v3i02.498

Khaerudin, A., Rosalia, O., Firayani, & Nasim, A. S. (2025). Responsibility of e-commerce platforms to consumers for illegal products in Indonesia. Leges Privatae, 1(5), 40–47.https://doi.org/10.62872/ebwg8t95

Kim, K. K., Kim, W. G., & Lee, M. (2023). Impact of dark patterns on consumers' perceived fairness and attitude: Moderating effects of types of dark patterns, social proof, and moral identity. Tourism Management, 98, 104763.https://doi.org/10.1016/j.tourman.2023.104763

Koh, W. C., & Seah, Y. Z. (2023). Unintended consumption: The effects of four e-commerce dark patterns. Cleaner and Responsible Consumption, 11, 100145.https://doi.org/10.1016/j.clrc.2023.100145

Lechevalier, F., & Potel Saville, M. (2025). Fairness by design: Combatting deceptive AI-driven interfaces. Cambridge Forum on AI: Law and Governance, 1, e31.https://doi.org/10.1017/cfl.2025.10018

Li, Y., Deng, X., Hu, X., & Liu, J. (2024). The effects of e-commerce recommendation system transparency on consumer trust: Exploring parallel multiple mediators and a moderator. Journal of Theoretical and Applied Electronic Commerce Research, 19(4), 2630–2649.https://doi.org/10.3390/jtaer19040126

Liu, Y., & Sun, X. (2024). Towards more legitimate algorithms: A model of algorithmic ethical perception, legitimacy, and continuous usage intentions of e-commerce platforms. Computers in Human Behavior, 150, 108006.https://doi.org/10.1016/j.chb.2023.108006

Maharani, R., & Prakoso, A. L. (2024). Perlindungan data pribadi konsumen oleh penyelenggara sistem elektronik dalam transaksi digital. Jurnal USM Law Review, 7(1), 333–347.https://doi.org/10.26623/julr.v7i1.8705

Mende, M., Bradford, T. W., Roggeveen, A. L., Scott, M. L., & Zavala, M. (2024). Consumer vulnerability dynamics and marketing: Conceptual foundations and future research opportunities. Journal of the Academy of Marketing Science, 52, 1301–1322.https://doi.org/10.1007/s11747-024-01039-4

Mourali, M., Novakowski, D., Pogacar, R., & Brigden, N. (2025). Post hoc explanations improve consumer responses to algorithmic decisions. Journal of Business Research, 186, 114981.https://doi.org/10.1016/j.jbusres.2024.114981

Ning, X., Lu, Y., Li, W., & Gupta, S. (2024). How transparency affects algorithmic advice utilization: The mediating roles of trusting beliefs. Decision Support Systems, 183, 114273.https://doi.org/10.1016/j.dss.2024.114273

Ostinelli, M., Bonezzi, A., & Lisjak, M. (2025). Unintended effects of algorithmic transparency: The mere prospect of an explanation can foster the illusion of understanding how an algorithm works. Journal of Consumer Psychology, 35(2), 203–219.https://doi.org/10.1002/jcpy.1416

Park, K., & Yoon, H. Y. (2024). Beyond the code: The impact of AI algorithm transparency signaling on user trust and relational satisfaction. Public Relations Review, 50(5), 102507.https://doi.org/10.1016/j.pubrev.2024.102507

Prihartanto, Y., Arifin, F., Maarif, I., & Kwarteng, A. H. (2025). From legal formalism to algorithmic justice: Rethinking consumer protection in the digital economy. Supremasi Hukum: Jurnal Kajian Ilmu Hukum, 14(1), 65–88.https://doi.org/10.14421/gqmmwr98

Quinelato, P. D. (2024). Consumer manipulation through behavioral advertising: Regulatory proposal by the Data Services Act. Brazilian Journal of Law, Technology and Innovation, 2(1), 1–24.https://doi.org/10.59224/bjlti.v2i1.1-24

Rott, P. (2025). Digital fairness and the burden of proof. Journal of Consumer Policy, 48(3), 297–314.https://doi.org/10.1007/s10603-025-09583-4

Sa'adah, B. L. N., Sukarmi, & Dewantara, R. (2024). Establishing a personal data protection agency for e-commerce in Indonesia: Legal framework and implementation challenges. Invest Journal of Sharia & Economic Law, 4(2), 292–316.https://doi.org/10.21154/invest.v4i2.10031

Schuett, J. (2024). Risk management in the Artificial Intelligence Act. European Journal of Risk Regulation, 15(2), 367–385.https://doi.org/10.1017/err.2023.1

Singh, V., Vishvakarma, N. K., & Kumar, V. (2024). Unveiling digital manipulation and persuasion in e-commerce: A systematic literature review of dark patterns and digital nudging. Journal of Internet Commerce, 23(2), 144–171.https://doi.org/10.1080/15332861.2024.2330813

Stewart, K., Perren, R., Chambers, C., & Zulauf, R. (2024). In tech we rely: How technology dependence fuels consumer vulnerability. Journal of Consumer Affairs, 58(4), 905–945.https://doi.org/10.1111/joca.12610

Turillazzi, A., Taddeo, M., & Floridi, L. (2023). The digital services act: An analysis of its ethical, legal, and social implications. Law, Innovation and Technology, 15(1), 83–106.https://doi.org/10.1080/17579961.2023.2184136

Uceng, A., & Hanifah, A. M. Z. (2024). Dark patterns and consumer decision making in emerging markets: Experimental evidence from Indonesia. Data: Journal of Information Systems and Management, 2(3), 180–192.https://doi.org/10.61978/data.v2i3.919

Waseem, D., Chen, S., Xia, Z., Rana, N. P., Potdar, B., & Tran, K. T. (2024). Consumer vulnerability: Understanding transparency and control in the online environment. Internet Research, 34(6), 1992–2030.https://doi.org/10.1108/INTR-01-2023-0056

Witte, J., Kenning, P., & Brock, C. (2025). Dark patterns in online retailing: An analysis based on information manipulation theory. European Journal of Marketing, 59(13), 596–624.https://doi.org/10.1108/EJM-04-2023-0302

Yulianingsih, S., & Putra, R. K. (2024). Analisis yuridis tentang perlindungan konsumen pada e-commerce di Indonesia: Pendekatan yuridis-normatif. Hakim: Jurnal Ilmu Hukum dan Sosial, 2(4), 842–856.https://doi.org/10.51903/hakim.v2i4.2204

Zac, A., Huang, Y.-C., von Moltke, A., Decker, C., & Ezrachi, A. (2025). Dark patterns and consumer vulnerability. Behavioural Public Policy, 1–50.https://doi.org/10.1017/bpp.2024.49