Consumer opt-in on data used by Gen AI

I had previously written two Linkedin posts, over a year ago, on the importance of creating ‘opt-in’ systems where consumers are asked what type of advertising and how often they'd like to see ads, linked with compensation. It’s the ultimate licensing agreement:? Consumers would OPT-IN for data collection, including what data they approve to be collected, AND they’d be rewarded with a personalized experience and financially every time their data generates advertising dollars to the social networks (that captured the data). Rewarded or not, and though users might be willing to share personal data for personalized services, with the growth of Generative AI and its (one of them) use to offer better consumer experiences, it has brought additional concerns regarding ethics, governance, and the risks of AI information misuse.

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To top it off, imagine a future where consumers are opting-in to sharing their data with AI networks for the benefit of improved experiences and monetary gain, what happens when they no longer want to do so?? In a recent article by research scientists at 谷歌 , ‘fully erasing the influence of the data requested to be deleted is challenging since, aside from simply deleting it from databases where it’s stored, it also requires erasing the influence of that data on other artifacts such as trained machine learning models’ and ‘it may still be possible to infer whether that individual's data was used to train a model’.

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For businesses that are seeing the importance of using Gen AI to acquire the right consumers, at the right time, keeping them the longest, and potentially compensating them for their data, it will not be an easy task.? I’ve found this recent Harvard Business Review article on How to Prepare for a Gen AI Future You Can’t Predict by Amy Webb , to be very informative and thought provoking, where she says ‘the single best thing organizations can do right now — during this period of what feels like a soul-crushing amount of change and uncertainty — is to methodically plan for the future. That requires knowing generative AI’s limitations as well as its strengths and adopting a culture of continual evaluation and improvement. It also means getting past clever product demos to much more mundane, pragmatic conversations about the trajectory of development, how data are being used, and the practical ways in which companies can use emerging (AI) tools’.

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Personally, I’m excited with the prognostic of Gen AI as a tool to enhance consumer experiences (among other things not discussed in this article, like increased productivity, time and cost savings, creativity amplification, data synthesis, enhanced knowledge, and adaptive learning to name a few), and though the road is definitely unknown and likely bumpy, I do believe that companies that are able to openly collect consumer data (via opt-in), rewarding consumers for it and with that, train their AI systems to deliver solutions to consumers’ problems, will definitely stay ahead.? It’s what I like to call win – win – win: Consumers win since their expectations are met (though likely surpassed), AI systems win as they evolve and deliver continuous experience enhancements, and companies win potentially devoted consumers, translating to exponential growth!