Creating Transparency and Fairness in Automated Decision Systems for Administrative Agencies
Summary
Artificial intelligence is increasingly being used to make decisions about human welfare. Automated decision systems (ADS) administer U.S. social benefits programs—such as unemployment and disability benefits—across local, state, and Federal governments. While ADS have the potential to enable large gains in efficiency, they also run a high risk of reinforcing the class- and race-based inequities of the status quo. Additionally, the use of these systems is not transparent, often leaving individuals with no meaningful recourse after a decision has been made. Individuals may not even know that ADS played a role in the decision-making process.
The Federal Government should take immediate action to promote the transparency and accountability of automated decision systems. Agencies must build internal technical capacity as well as data cultures centered around transparency, accountability, and fairness. The White House should require that agencies using ADS undertake a notice-and-comment process to disclose information about these systems to the public. Finally, in the long-term, Congress must pass comprehensive legislation to implement a single, national standard regulating the use of ADS across sectors and use cases.
In anticipation of future known and unknown health security threats, including new pandemics, biothreats, and climate-related health emergencies, our answers need to be much faster, cheaper, and less disruptive to other operations.
To unlock the full potential of artificial intelligence within the Department of Health and Human Services, an AI Corps should be established, embedding specialized AI experts within each of the department’s 10 agencies.
The U.S. government should establish a public-private National Exposome Project (NEP) to generate benchmark human exposure levels for the ~80,000 chemicals to which Americans are regularly exposed.
The federal government is responsible for ensuring the safety and privacy of the processing of personally identifiable information within commercially available information used for the development and deployment of artificial intelligence systems