Summary: The sea of Artificial Intelligence (AI) development is ceaselessly churning. As it advances, the question of how our data fuels its growth has risen to the forefront. Companies have already harvested a significant amount of personal and public data from the web to train AI models. Amid rising concerns, however, measures to give individuals greater control over their data are emerging. Today we’ll explore these new mechanics of data control, discuss how they are embodied in current companies’ practices, and unveil some layers cloaked by ambiguity.
Data Control and AI-Fueled Companies
Many of us are beginning to ask how companies are using our data to train AI models, including language models and image creators. It’s essential to understand that some companies have already scraped the web, meaning your data could already be a part of their systems. As a result, several companies have begun to offer individuals and businesses the option to opt-out of having their data used in AI training or sold for such purposes.
The Challenge of Opting Out
However, finding these opt-out options can be far from straightforward. You may encounter them buried deep within a website, or they may demand a considerable amount of effort to complete. Furthermore, companies typically opt users in by default, as they bank on the fact most people aren’t actively seeking to remove their data from AI systems. Education and awareness are key to reversing this.
Privacy Laws and Technical Removal
Numerous copyright and privacy laws govern our data’s use and distribution. In parallel, technical methods exist to extract data from AI systems, but these aren’t so well known. As we navigate through these complex landscapes, it’s vital to understand what data these companies have scraped, and how it is being used.
The Companies’ Approach
A roster of companies, including Adobe, Amazon, Google, Microsoft, and OpenAI, provides specific instructions for opting out. While this is a positive move, we cannot overlook the opaque nature of these processes nor the ambiguity surrounding the specific data used.
Conclusion: Understanding this arena of data control is critical for professionals like lawyers, doctors, and consultants dealing with sensitive information. As AI continues to shape our professional and personal landscapes, ensuring transparency and control over our data must remain our shared priority.
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Featured Image courtesy of Unsplash and Markus Spiske (FXFz-sW0uwo)
