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.
Concerns over risks from generative artificial intelligence systems have increased significantly over the past year, driven in large part by the advent of increasingly capable large language models. But, how do AI developers attempt to control the outputs of these models? This primer outlines four commonly used techniques and explains why this objective is so challenging.
Center for Security and Emerging Technology (CSET)
This news release highlights Pennsylvania’s first-in-the-nation Generative AI pilot under Governor Shapiro, showcasing its positive impact on state employees and commitment to responsible, ethical AI use.
DSN Spotlights are short-form project profiles that feature exciting work happening across our network of digital government practitioners. Spotlights celebrate our members’ stories, lift up actionable takeaways for other practitioners, and put the resources + examples we host in the Digital Government Hub in context.Â
This video shows you how to get started with using Generative AI tools, including Bard, Bing, and ChatGPT, in your work as public sector professionals.
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.
What exactly are the differences between generative AI, large language models, and foundation models? This post aims to clarify what each of these three terms mean, how they overlap, and how they differ.
Center for Security and Emerging Technology (CSET)
This is the summary version of a report that documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
This report documents four experiments exploring if AI can be used to expedite the translation of SNAP and Medicaid policies into software code for implementation in public benefits eligibility and enrollment systems under a Rules as Code approach.
This report on the use of Generative AI in State government presents an initial analysis of the potential benefits to individuals, communities, government and State government workers, while also exploring potential risks.
