AI Technology in Veteran Benefits Administration: Pros and Cons
This paper examines the application of artificial intelligence (AI) in public administration, with particular focus on improving performance and efficiency in settings such as the Veteran Benefits Administration. Drawing on Dhasarathy, Jain, and Khan (2019), the paper describes what AI is and how machine learning algorithms work, outlines the goals of AI adoption including equitable decision-making and predictive equality, identifies implementation challenges such as algorithm stability and change resistance, and analyzes how AI affects organizational culture. The paper concludes by weighing the pros and cons of integrating AI into public administration workflows, emphasizing that AI is a tool to enhance—not replace—human decision-making.
- Introduction: AI's growing role in public administration
- Summary of the Technology: How machine learning algorithms support decision-making
- Goals of AI in Public Administration: Equity, predictive equality, and stable decisions
- Implementation Challenges: Technical hurdles and employee resistance to change
- Organizational Culture and Change Management: Overcoming resistance through communication and vision
- Pros and Cons of AI Adoption: Benefits of efficiency weighed against creativity loss
- Conclusion: AI as a tool to enhance, not replace, administrators
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What makes this paper effective
- Uses a clear, logical structure that moves from definition to goals, challenges, culture, and evaluation — making the argument easy to follow.
- Grounds abstract concepts in concrete examples, such as child welfare programs, tax audits, and scholarship allocation, to illustrate how AI applies in real public-sector contexts.
- Balances optimism about AI's potential with honest acknowledgment of its limitations, including programmer quality and the risk of eliminating human creativity from decision-making.
- Incorporates change management theory (Kotter's 8-step model) to connect the technology topic to organizational behavior literature.
Key academic technique demonstrated
The paper demonstrates effective use of a single anchor source (Dhasarathy et al., 2019) to structure a multi-faceted argument. Rather than simply summarizing the source, the student extends its ideas across distinct analytical categories — goals, challenges, culture, pros and cons — showing how one authoritative reference can anchor an organized, original discussion.
Structure breakdown
The paper follows a six-part structure: an introduction framing the topic, a technology summary defining AI and machine learning, a goals section outlining desired outcomes, a challenges section addressing technical and human obstacles, an organizational culture section connecting AI adoption to change management, a pros-and-cons evaluation, and a conclusion synthesizing all themes. Each section builds on the previous one to form a cohesive argument.
Introduction
The use of artificial intelligence (AI) in public administration is a concept that is growing around the world. As Dhasarathy, Jain, and Khan (2019) show, AI can help governments solve complex public-sector issues in more effective and efficient ways. This paper describes AI technology, the goals of its usage, challenges faced with its implementation, how it impacts organizational culture, and the pros and cons of adopting AI methods in public administration.
Summary of the Technology
AI is a technology that essentially allows a machine to learn how to address new problems based on information collected and analyzed by algorithms over time. AI can be used to help public administrators make decisions and improve their performance. Some examples of the ways in which AI can be used include sorting through infrastructure data to find information on specific issues, or sifting through health and social-service data to develop a program for addressing child welfare in the community (Dhasarathy et al., 2019). To make AI work, programmers must be skilled in writing algorithms, and public administrators must know what they want the program to do once it is written.
Goals of AI in Public Administration
The goals of using AI are to create a more equitable and fair community through effective decision-making, and to achieve predictive equality via the application of "a set of nuanced debiasing practices used in the field of data science" (Dhasarathy et al., 2019, p. 4). Another goal is to achieve stability in decision-making. The use of AI removes the risk of bias, instability, and uncertainty, and allows for all relevant information to be brought together so as to facilitate the decision-making process most effectively.
Goals in practical terms can range from deciding which people will receive rehabilitation treatment to deciding where to focus tax audits, or which students should receive scholarships and grants based on the probability that they will graduate and use the money effectively (Dhasarathy et al., 2019).
Conclusion
AI is a new and emerging technology that can help public administrators sort and sift through data and make predictions about which courses of action are likely to have the best results. AI depends upon programming tools and computer code that can read, interpret, and project information to facilitate the decision-making process of public administrators. It can help administrators improve their own work and create a fairer, more equitable environment for all. However, it can also encounter challenges from workers who feel undervalued because so much emphasis is being placed on a computer program rather than on their own expertise. To overcome this obstacle, workers should be made to understand that AI and machine learning are tools to help them in the decision-making process — not tools to replace them. At the end of the day, public administrators are still needed; computers simply help.
References
Dhasarathy, A., Jain, S., & Khan, N. (2019). When governments turn to AI: Algorithms, trade-offs, and trust. Public Sector Practice, January.
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