LinkedIn recently introduced a privacy setting that allows users to opt out of having their data used to train generative AI models. This update to LinkedIn’s privacy policy is crucial for businesses to understand, as it highlights how user data is being utilized for AI training purposes. LinkedIn stated, “We may use your personal data to improve, develop, and provide products and services, develop and train artificial intelligence (AI) models, and gain insights with the help of AI.” This data is used for features such as writing assistance and post recommendations.
To prevent their data from being used in future AI training, users need to navigate to the Data Privacy tab in their account settings and turn off the toggle labeled “Use my data for training content creation AI models.” It is important to note that opting out means user data won’t be used for training models going forward, but past training using that data cannot be undone. Additionally, LinkedIn clarified that it does not train models on data from users who live in the EU, EEA, or Switzerland, likely due to stricter privacy regulations in those regions.
While this new setting specifically addresses data used to train generative AI models, LinkedIn has other machine learning tools that utilize user data for personalization and moderation. Opting out of those requires a separate process. Privacy activists have raised concerns over LinkedIn’s decision to opt users into training these AI models by default. Mariano delli Santi, legal and policy officer at the Open Rights Group, stated, “The opt-out model proves once again to be wholly inadequate to protect our rights: the public cannot be expected to monitor and chase every single online company that decides to use our data to train AI. Opt-in consent isn’t only legally mandated, but a common-sense requirement.”
LinkedIn’s move follows similar actions by other tech companies, such as Meta, which recently admitted to having scraped non-private user data for model training dating back to 2007. As the demand for data to train generative AI models grows, businesses must recognize the importance of data privacy and the need to regularly review and update their settings to maintain control over their personal information.
For business leaders, the implications are clear. Ensuring data privacy is not only a compliance issue but also a matter of maintaining trust with users and clients. Companies must be proactive in managing their data policies and consider the potential backlash from users who feel their privacy has been compromised. Monitoring these developments closely will be essential for staying ahead in the competitive landscape where data ethics are increasingly under scrutiny.
