Creating an Immutable ‘Family Tree’ for AI Training Data

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The race for every company to embrace AI has them combining myriad and often inconsistently documented datasets in their training, raising legal and ethical questions about where the data actually originated.

MIT’s Data Provenance Initiative audit of more than 1,800 datasets found that companies can’t reliably track where their AI training data comes from. In fact, the researchers have concluded that authenticity, as well as consent practices and provenance, are broken in AI, leaving companies without the training data transparency



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Creating an Immutable ‘Family Tree’ for AI Training Data


The race for every company to embrace AI has them combining myriad and often inconsistently documented datasets in their training, raising legal and ethical questions about where the data actually originated.

MIT’s Data Provenance Initiative audit of more than 1,800 datasets found that companies can’t reliably track where their AI training data comes from. In fact, the researchers have concluded that authenticity, as well as consent practices and provenance, are broken in AI, leaving companies without the training data transparency



Source link

Disclaimer

We strive to uphold the highest ethical standards in all of our reporting and coverage. We StartupNews.fyi want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.

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