February 26, 2024

The government is investing in AI research, but federally funded researchers are facing a problem with datasets that contain dangerous or illegal content. These datasets, often collected from the open web, can contain illicit imagery, such as child sexual abuse material. This poses ethical, legal, and practical challenges as federal agencies push for more AI research. The National Science Foundation highlighted the need for a National Artificial Intelligence Research Resource after a major Stanford report uncovered illegal content in a popular dataset used by researchers and AI systems. Removing and detecting harmful content in datasets is a complex issue, especially as the Biden administration prioritizes AI research. The presence of illegal material in AI datasets raises legal concerns and can have long-term impacts. The incident with the LAION-5B dataset has led to calls for alternative resources and tools for AI development. Using open web databases presents the risk of encountering dangerous content, and researchers and government agencies must find ways to mitigate this risk. Federal agencies like NSF, DOE, and IARPA are working to address these concerns by reviewing datasets and research programs. The use of tainted datasets by federally funded researchers is a real risk, as shown by the LAION-5B incident. Proper precautions, ethical considerations, and legal compliance are crucial in AI research, and the implementation of the National Institute of Standards and Technology’s Risk Management Framework is being recommended to address these issues.

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