The state of South Dakota Bureau of Information and Telecommunications (BIT) designed guidelines for the responsible use of AI-generated content in state government agencies, emphasizing the need for proofing, editing, fact-checking, and using AI-generated content as a starting point, not the finished product.
South Dakota Bureau of Information and Telecommunications
This research explores how software engineers are able to work with generative machine learning models. The results explore the benefits of generative code models and the challenges software engineers face when working with their outputs. The authors also argue for the need for intelligent user interfaces that help software engineers effectively work with generative code models.
The Electronic Privacy Information Center (EPIC) emphasizes the necessity of adopting broad regulatory definitions for automated decision-making systems (ADS) to ensure comprehensive oversight and protection against potential harms.
In this interview, Code for America staff members share how client success, data science, and qualitative research teams work together to consider the responsible deployment of artificial intelligence (AI) in responding to clients who seek assistance with three products.
Companies have been developing and using artificial intelligence (AI) for decades. But we've seen exponential growth since OpenAI released their version of a large language model (LLM), ChatGPT, in 2022. Open-source versions of these tools can help agencies optimize their processes and surpass current levels of data analysis, all in a secure environment that won’t risk exposing sensitive information.
A catalogue to help teams design trustworthy services that work for people. Categories including informing decisions, signing into services, giving and removing consent, and doing security checks.
To help policy makers, regulators, legislators and others characterize AI systems deployed in specific contexts, the OECD has developed a user-friendly tool to evaluate AI systems from a policy perspective.
Organisation for Economic Co-operation and Development (OECD)
This academic paper examines predictive optimization, a category of decision-making algorithms that use machine learning (ML) to predict future outcomes of interest about individuals. Through this examination, the authors explore how predictive optimization can raise concerns that make its use illegitimate and challenge claims about predictive optimization's accuracy, efficiency, and fairness.
This playbook provides federal agencies with guidance on implementing AI in a way that is ethical, transparent, and aligned with public trust principles.
U.S. Department of Health and Human Services (HHS)
This report investigates how D.C. government agencies use automated decision-making (ADM) systems and highlights their risks to privacy, fairness, and accountability in public services.
