AI, Big Tech and privacy—how to navigate legal and ethical use of consumer data

Companies such as Google, Meta, Apple, and Microsoft are enhancing their generative AI chatbots and broader AI capabilities by leveraging consumer data to create more personalized experiences. Though these advancements promise transformative innovation, they also raise important considerations about data privacy, ethical use of data, compliance and user consent. Amid this tension, the message to big tech companies is clear: Prioritize consumer privacy in AI development or face repercussions from both users and lawmakers. Balancing hyper-personalization and transparency While some may appreciate tailored discounts and new streaming recommendations from favorite brands and platforms, they might not fully realize that AI is leveraging their individual data to do so. In this era of advanced personalization and limited AI regulation, companies must prioritize clear and honest communication, going beyond the minimum to be hyper-transparent while providing clear notice and choice from the onset. Check out the latest Ad Age events and award programs Much of the broader debate around AI focuses on ensuring the transparency and fairness of AI decision-making, but an equally important concern is the protection of individual privacy rights, including the collection and use of personal information to train and develop AI systems. Over the last five years, “privacy rights” have received significant attention from state and federal regulators and consumer advocates. Consumer data has become highly regulated in the blink of an eye. Nevertheless, nightmare projections have not materialized, and both regulation and the industry are adapting as all participants come to understand real risks versus misconceptions. Privacy in the use cases of AI will likely develop similarly. Do the right thing It's simple: If there's hesitation about being fully transparent, data shouldn't be collected. If there's a reluctance to explain clearly how data will be used, it shouldn’t be requested in the first place. The underlying principle is to just do the right thing. Consent and choice must be clear and leave no room for doubt. Prior to collection, organizations should transparently communicate what data will be collected, how it will be used and for how long it will be retained. Consent should be freely given and choice treated as an ongoing option. For instance, if a user consents to data collection for personalized recommendations but not for AI training, this choice must be respected. Ensuring consumers are aware of how their data will be used from the outset reduces the likelihood of later dissatisfaction and erosion of consumer trust. The challenge with AI personalization is that if companies fail to manage data transparency and user choice properly, they risk having to scrap entire models and start over, causing significant operational and financial setbacks. To avoid this, companies must be proactive in offering opt-out mechanisms and ensuring that consumers fully understand their personalized data rights. With innovation comes regulation While there is not yet a comprehensive federal AI law in the U.S., existing privacy and consumer rights legislation, such as Section 5 of the FTC Act and the Fair Credit Reporting Act, provide some regulatory guidance. In the absence of federal action, state regulations, both narrow (Colorado, Utah) and sweeping (California's Senate Bill 1047) have begun to take shape. This process lays the foundation for responsible AI use, though in the early days it can create uncertainty for companies navigating new rules. Today’s conservative approach is not necessarily permanent, but a step toward an effective balance of cultural expectations and subsequent regulation and interpretation. NextGen Marketing Summit Join us for a crash course on Gen Z, DTC marketing and the creator economy Register today Training, assessment and governance essentials To navigate changing regulations, organizations need a governance structure to prioritize the ethical use of data in AI chatbots used for personalized consumer experiences. Companies could aim to implement a few key steps. Ongoing training and education for all stakeholders involved in data handling and AI development are essential for fostering a culture of transparency and accountability. Training programs should encompass understanding data types, relevant legal requirements, the importance of data protection and ethical considerations. Before deploying AI features, companies should also conduct thorough privacy impact assessments, both to evaluate potential risks to consumers (such as data breaches, misuse and unfair treatment) and to ensure compliance with legal requirements in many states. This proactive analysis helps in understanding and mitigating possible harms. Additionally, establishing an updated governance framework is vital for overseeing AI development and deployment. This includes forming internal committees to review plans and audit findings, implementing controls and reporting to the board or regulatory bodies to ensure adherence and effectiveness. Companies must champion transparency, uphold ethical data practices and stay agile in a shifting regulatory environment. By doing so, they can unlock AI's full potential while earning and preserving consumer trust. A-List & Creativity Awards Enter for a chance to be recognized as the best in advertising Submit your entry here

AI, Big Tech and privacy—how to navigate legal and ethical use of consumer data

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