In light of the increasing use of dark patterns, the Central Consumer Protection Authority (CCPA) has issued an advisory urging e-commerce platforms to identify and eliminate such practices through self-audits to be conducted within three months.
Based on the self-audit reports, platforms are encouraged to furnish self-declarations affirming they do not engage in any dark pattern practices. The advisory reiterates the need to comply with the Guidelines for Prevention and Regulation of Dark Patterns, 2023, which apply to (i) all platforms, systematically offering goods or services in India, (ii) advertisers, and (iii) sellers.
Annexed to the Guidelines is an illustrative list of 13 prohibited practices such as false urgency, basket sneaking, subscription traps, and drip pricing.
The CCPA has also issued notices to certain e-commerce platforms found in violation of the Guidelines. Platforms have been cautioned against deploying deceptive design interfaces that mislead consumers or manipulate their decision-making.
According to the press release dated June 7, the Department of Consumer Affairs has set up a working group to identify dark pattern violations and share findings with the Department on a regular basis.
Last month, a high-level stakeholder meeting was convened to address the issue. The meeting noted a recent spike in consumer complaints, and major e-commerce companies were directed to conduct regular internal audits.
Globally, several major platforms have come under fire for using dark patterns. Trials and complaints have highlighted issues such as forced subscriptions, hidden costs, and misleading interface design, adding momentum to regulatory action worldwide. For instance, Amazon is facing trial over its Prime subscription practices, and Uber has been accused of charging users for its Uber One subscription service without consent and making cancellations difficult. A pan-European consumer group has also filed a complaint with the European Commission against Shein, citing practices such as confirm-shaming, nagging, and artificial scarcity prompts like ‘low stock.’