Generative AI is a type of Artificial Intelligence (AI) that produces content. That could be a story, an image, or an audio file, and is a shift from traditional AI usage, which is focused on completing a task based on predefined rules. Generative AI utilizes existing data to produce this new content based on a prompt such as "write a blog post on government use of generative AI." Disclaimer: generative AI was not used in the creation of this blog post.
Balancing Act of Generative AI
Like traditional AI, generative AI holds great promise for automating highly manual tasks in many areas of government. A recent report found that three-fourths of agency leaders said their agencies have already begun establishing teams to assess the impact of generative AI and are planning to implement initial applications in the coming months.
However, the ethics of utilizing and altering existing content as well as the veracity of newly created content are key concerns slowing generative AI adoption. The same report found the top concerns about generative AI were lack of controls to ensure ethical/responsible information generation, a lack of ability to verify/explain generated output, and potential abuse/distortion of government-generated content in the public domain. But even with those concerns, the report found that 71% of respondents believe that the potential advantages of employing generative AI in their agency's operations outweigh the perceived risks.
Generative AI in Action
Agencies across government are establishing enterprise-level teams or offices devoted to developing AI policies and resources while simultaneously utilizing the technology for a variety of projects. The AI.gov website includes details on more than 700 artificial intelligence use cases among federal agencies, with the Department of Energy and Health and Human Services being the most prolific users of AI in government today.
The applications of generative AI are vast. To make its use more real, we wanted to highlight a couple distinct use cases currently being explored.
- Crisis response - The speed of generative AI makes it valuable in emergency response as it can quickly synthesize information from multiple sources and present a coherent report. It holds the promise to be used for faster, more accurate early warnings, decision support, and community communication of information like first aid advice, latest health warnings, road closures, and more. Generative AI can also be used before a crisis to create training and simulations for first responders and communication staff. Finally, it can support post-event analysis by quickly pulling important data to create reports on response effectiveness.
- Healthcare - AI can help healthcare providers supply educational content to patients. Human intervention is, of course, critical to double-checking the content coming out of AI systems for accuracy and applicability. Legislation has been proposed to fund more research into how to use generative AI to improve patient care and incentivize its use.
- Citizen service - The initial use of generative AI in government was in the area of citizen service in the form of chat bots that delivered answers to common questions. As technology and people's comfort with AI have progressed, there are other ways generative AI can support citizen service. The state of Utah is using it to automate its process for purchasing rights of way, which is incredibly tedious and involves repetitively describing plots of land.
- Budgeting - Generative AI can help streamline creating budget requests and provide the needed documentation to back up those requests. For example, a local government could use generative AI to analyze historical spending on infrastructure to predict future requirements and distribute resources more optimally.
To learn more about generative AI and stay on top of its evolution in government check out these resources from GovEvents and GovWhitePapers.
- Decoding the Digital Future: A Comprehensive Guide to ML, AI, and Gen AI Technologies (November 1, 2023; webcast) - In the evolving tech landscape, terms like machine learning, artificial intelligence, and Generative AI are often tossed around. But what exactly do they mean, and how do they compare to one another?
- Introduction to Responsible AI in Practice (November 2, 2023; Reston, VA) - This event is a high-level exploration of recommended best practices for responsible AI usage across different areas of focus: Fairness, Interpretability, Privacy, and Safety.
- Amplifying Federal Efficiency with AI-Powered Intelligent Document Processing (November 7, 2023; webcast) - Technological advancements now empower agencies to streamline data processing and extract valuable insights from their document repositories, enhancing efficiency, and accuracy. This event explores the application, benefits, and features of intelligent document processing bolstered by artificial intelligence.
- The Future of Federal Agencies: Empowering Workforces with Easy-to-Use Automated Tools for Responsible AI (November 8, 2023; webcast) - In the era of rapid innovation, Federal agencies must harness the transformative power of AI and Machine Learning to augment human capabilities and drive decision-making. But with the ever-evolving nature of these technologies, it's no easy task to keep up!
- GovAI Summit 2023 (December 4-6, 2023; Arlington, VA) - Learn practical applications and the opportunities of AI in the public sector across .mil, .gov, .edu, and .org. Speakers will present real use cases and explore the art of the possible and the challenges with getting there.
- AI: More a Pot of Gold than a Pothole (February 9, 2024; webcast) - Generative AI offers the potential for advancements in speed of delivery for improved and new services to constituents, customers, and employees alike. This event will review the risks and benefits of utilizing AI, outline the potential strategy for AI to identify new services and opportunities for agencies to meet their mission, and detail the steps agencies can take to protect employees and constituents from potential risks of AI.
- Generative Artificial Intelligence and Copyright Law (white paper) - This paper explores questions that courts and the U.S. Copyright Office have begun to confront regarding whether the outputs of generative AI programs are entitled to copyright protection, as well as how training and using these programs might infringe copyrights in other works.
- Adding Structure to AI Harm (white paper) - Harms from the use of artificial intelligence systems ("AI harms") are varied and widespread. Monitoring and examining these harms (AI harm analyses) are a critical step towards mitigating risks from AI.