This week, I attended  the launch of a new report from MMC Ventures which discusses the ethical challenges of training AI models, drawing parallels be

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2024-11-29 18:30:08

This week, I attended the launch of a new report from MMC Ventures which discusses the ethical challenges of training AI models, drawing parallels between the data gathering practices of today and the Napster-to-Spotify transition that occurred over two decades ago in the music industry. The report examines the perspectives of three stakeholders: content creators, data rights holders, and AI developers, highlighting the need for fair compensation and efficient rights management.

The authors - Advika Jalan and Charlotte Barttelot - do a good job exploring technological solutions like AI data marketplaces and watermarking to address these issues, advocating for a shift towards licensing agreements and improved data discoverability. They also emphasize the importance of standardization in data formats and consent management to encourage ethical AI development.

One thing that the report does well is look at how the dynamics between data and AI models play out during the entire lifecycle, making the observation that, as we move from pre-training and fine-tuning to inferencing, the value of individual data points increases because the difference it makes to the outcomes is greater.

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