To Do: Develop Shared Pools of High-Quality, App-Specific Training and Validation Data
Recommendation
The White House should direct federal agencies to support the development of shared pools of high-quality, application-specific training and validation data in key areas of public interest.
Details
It can take large pools of data to “train” AI systems, but it can be difficult and costly to amass this training data. Federal agencies overseeing sectors where AI applications could advance key public interests, such as in agriculture, education, public safety, and law enforcement, should gather and share this data to spur the development of these valuable AI applications. For example, NIST should work with law enforcement agencies, civil society, and other stakeholders to develop shared, representative datasets of faces that can serve as an unbiased resource for organizations developing facial recognition technology.
Keep reading:
▪ Joshua New, “Why the United States Needs a National Artificial Intelligence Strategy and What It Should Look Like” (Center for Data Innovation, December 2018), https://www.datainnovation.org/2018/12/why-the-united-states-needs-a-national-artificial-intelligence-strategy-and-what-it-should-look-like/.
