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Microsoft is exploring a way to credit contributors to AI training data
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Quick takeaways
- Microsoft's research project aims to enhance the transparency of AI training processes by recognizing the contributions of specific datasets.
- The podcast highlights ongoing legal challenges faced by AI companies over copyright issues, emphasizing the need for ethical data practices.
Deep dives
Microsoft's Training Time Provenance Project
Microsoft is initiating a research project aimed at assessing the influence of specific training examples on the outputs generated by AI models. This initiative, noted in a job listing for a research intern, seeks to make the processes of model training more transparent by estimating the contributions of particular datasets, including images and texts. The lack of clarity in current neural network architectures has raised concerns, and this research could provide a framework for recognizing and compensating those who contribute valuable data, addressing issues of data dignity as highlighted by technologist Jaron Lanier. For instance, if an AI model generates a creative work based on numerous influencers, this project could facilitate acknowledgment and payment to those key contributors, effectively connecting them to their impact in the creation process.
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