1. How is ASCI leveraging AI to monitor the rapidly growing digital advertising landscape more effectively?
In a recent media interaction, Manisha Kapoor, CEO and Secretary General of the Advertising Standards Council of India (ASCI), emphasized the importance of collaborating with technology partners to develop AI tools specifically tailored to India’s advertising landscape. She highlighted the need for AI integration to effectively address the unique challenges of the Indian market. Kapoor’s statement reflects a forward-thinking approach towards incorporating AI to enhance transparency and accountability in India’s dynamic advertising ecosystem.
If ASCI encodes its advertising policies and guidelines into AI-based models, it could be a pathbreaking move and a game changer. The integration of AI models trained on Indian advertisements and ASCI’s guidelines would enable advertisers to pre-test their content for compliance before it goes live. This initiative is particularly beneficial for smaller advertisers, many of whom lack in-house compliance teams or dedicated marketing heads. By using AI to analyze ads against ASCI’s standards, SMEs can ensure compliant advertising at a lower cost, with greater expertise and accuracy. This proactive approach will not only help reduce the incidence of misleading ads but also foster a more transparent and trustworthy advertising environment across digital platforms.
2. What percentage of problematic ads are found online, and why is digital media particularly challenging to regulate?
As per a recent press release by ASCI on May 22, 2024, 8,229 ads were scrutinized. Of these, 85%were found on digital platforms, highlighting that the compliance rate for digital ads remains low at 75%, compared to 97% for print and TV. According to ASCI’s Annual Complaints Report, sector-specific violations are particularly prevalent, with the healthcare sector leading, accounting for 19% of the ads scrutinized in 2023-24. This is followed by illegal offshore betting (17%), personal care (13%), conventional education (12%), food and beverage (10%), and realty (7%).
It becomes significantly challenging to regulate digital media due to various factors, such as the obsolescence of existing laws with advancements in technology. For example, with generative AI tools, advertisers can automate the creation of original content, including text, images, articles, and marketing collaterals—while the regulatory framework around AI-generated content is still evolving. Another challenge is the existence of diverse digital platforms, which feature a wide variety of content, creating compliance issues due to the borderless nature of the digital ecosystem and the complexities of cross-jurisdictional enforcement.
3. What are some of the potential challenges or limitations of AI in monitoring digital ads, including concerns over accuracy and biases?
AI systems may struggle to detect subtle violations, such as misleading claims hidden within creative visuals or nuanced language. Biases in AI, often stemming from incomplete or skewed datasets, can lead to unfair targeting, with certain industries or regions being disproportionately flagged.
Moreover, AI can have difficulty understanding complex content, like influencer promotions or native advertising, making it hard to differentiate between genuine content and sponsored material. Advertisers also use sophisticated tactics, such as cloaking or blending ads with organic posts, which can evade AI detection. Additionally, the fast-evolving nature of digital advertising poses a challenge, as AI systems must be constantly updated to keep up with new trends and platforms. False positives and negatives further undermine the system’s effectiveness, with compliant ads being wrongly flagged or problematic ones slipping through. Lastly, there are ethical concerns regarding the transparency of AI decisions and the potential for reinforcing biases, making human oversight crucial for accurate and fair ad monitoring.
4. How will AI-powered monitoring help protect consumers from misleading or harmful messaging, particularly in sectors like healthcare and finance?
In healthcare, AI can detect exaggerated claims about treatments or products, while in finance, it flags ads promoting unsuitable products that don’t consider factors like age, income, appropriateness, or that promise unrealistic returns. With real-time content analysis, AI identifies patterns of non-compliance and ensures false claims are flagged quickly. AI can enhance compliance practices in these sectors while also ensuring transparency and trustworthiness.
Advances in natural language processing (NLP) allow AI to assess the context of ads, ensuring they comply with regulations and ethical standards. This is crucial in both healthcare and finance, where misinformation can have serious consequences. AI’s scalability ensures broad monitoring across digital platforms, automating compliance checks for financial disclaimers and health claims. By minimizing human error and monitoring hyper-targeted ads, AI offers an effective system to safeguard consumers from harmful or misleading content in these high-risk industries.
