Harnessing the power of AI for public sector organizations
The buzz around AI has reached a fever pitch in recent months. Much of it has centered on potential enterprise applications. But those in the public sector should be thinking of how AI will affect them, not only because public sector organizations are vital to the functioning of communities, but also because AI has significant and under-explored potential to transform them.
Whether you are a K-12 school district or a local government council, you should begin thinking about how AI will impact your role in the coming months and years.
One of the chief applications of generative artificial intelligence (GAI) in these industries will be strategic thinking and policymaking. Naturally, these functions won’t be delegated entirely to GAI, but their efficiency cannot be overstated. Their ability to find and store reams of data, recall them instantly, and synthesize them to extract insights will skyrocket productivity in the public sector.
In this article, we’ll explore some of the possible applications of AI, and in particular, large language models (LLMs), as well as identifying a few key considerations when evaluating and using AI.
AI in K-12 education
GAI and LLMs hold immense promise for transforming K-12 education. These technologies can augment and streamline administrative tasks, enabling educators to focus more on fostering student engagement and personalized learning experiences. This includes time-intensive tasks like grading, scheduling, managing student records, and handling routine inquiries — tasks that require administrative energy but are more-or-less adjacent to the actual important work of teaching itself.
With GAI's data analysis capabilities, educational institutions can gather insights into student performance and identify areas for improvement, thus tailoring curriculum to meet individual needs. Moreover, LLMs can act as virtual mentors, providing real-time answers to student queries and enabling teachers to deliver enriched educational content. With their limitless ability to understand and synthesize data, LLMs can also support teachers by providing access to a vast repository of educational content and resources.
GAI's analytical abilities could also include parameters such as student performance, attendance records, teacher evaluations, and budgetary information. By processing this data, school boards can gain valuable insights into the effectiveness of existing policies and identify areas that need improvement. It can also pinpoint trends and patterns that might have otherwise gone unnoticed.
Moreover, GAI can use predictive analytics to forecast the potential impact of different policy options. For example, it can simulate how changes in curriculum, school schedules, or resource allocation may affect student outcomes, attendance rates, or budget utilization. This helps the school board make informed decisions based on evidence rather than intuition.
Embracing GAI and LLMs in K-12 education will empower stakeholders to make data-driven, strategic decisions that elevate learning outcomes for the next generation of leaders.
AI in local government
The integration of GAI and LLMs into local government has the potential to revolutionize public service delivery. These technologies can streamline bureaucratic processes, expedite decision-making, and improve citizen engagement. GAI's predictive analytics can anticipate community needs, enabling officials to allocate resources strategically and address issues proactively. Furthermore, LLMs can analyze vast amounts of legislative and regulatory information, allowing policymakers to make more well-informed choices that align with the community's interests.
GAI can analyze vast amounts of data from various sources, including government databases, public records, surveys, and social media. By processing this data, GAI can extract valuable insights, identify patterns, and provide data-driven recommendations to inform policy-making decisions. It can also analyze policies and practices implemented in other equivalent state and local governments. By summarizing best practices from these entities, it can provide valuable information to local governments, helping them understand what has worked elsewhere and what they could potentially implement to improve their own operations.
As for citizen engagement, GAI can be invaluable in analyzing public feedback captured from multiple channels, such as social media, emails, public forums, and surveys. It can summarize and categorize the feedback to provide decision-makers with a comprehensive view of what the community is saying and what it wants. This real-time, full-scope feedback would help in understanding public sentiment and making policy-making more participatory and truly democratic.
By harnessing GAI and LLMs, local governments can implement efficient and strategic governance, enhancing the quality of life for their constituents.
Key considerations for AI in the public sector
While there are many possibilities for AI use, public sector organizations should also have guardrails in place as exploration and rollout occur. To maximize the benefits of AI, public sector organizations should pay attention to these key considerations:
Data quality
An important best practice pertains to data. LLMs are only as good as the data pools they’re trained on. Non-corporate entities such as educational institutions, local governments, and nonprofits often lack this all-important data, as they don't always have the infrastructure to capture it comprehensively. These organizations can begin by building better data infrastructure, as well as training data literacy across the board by everyone in their organizations including partners and other key stakeholders.
Data privacy
The importance of data in computer programs like AI and language models also has a direct connection to privacy concerns. The public sector of course handles public data — or in the case of K-12, the data of minors.
Organizations therefore need to ensure that they’re adhering to privacy best practices, as well as the relevant laws and regulations governing that privacy. Compliance is complicated by the fact that no LLM is custom-fit to educational or governmental use cases — therefore, the specific privacy concerns of these industries will have to be customized from whatever off-the-shelf GAI solutions are adopted.
Policy considerations
Apart from data, the other single most important consideration in maximizing AI is developing strong policy. Policy amounts to the guardrails and directives that govern an AI's deployment throughout a given organization.
These parameters focus an AI's productivity, determine its ethical framework, and the limits of what it is permitted to do. Not only does policy circumscribe an AI's framework, it also delimits what an organization will or will not do with AI. For example, a local government would need to carefully determine the degree of transparency it wishes to adopt with respect to its constituents in how it uses AI.
Start small
As with any new technology, it's best for public sector leaders interested in GAI to begin with small pilot projects. These projects will allow organizations to start small in closed environments with a smaller degree of risk exposure. It will also allow organizations to build necessary literacy with GAI and its core abilities as well as policymaking capacity to govern its broader application across an organization.
Small experiments should be carefully designed, so that their learning can be applied broadly to the organization on the whole, and not simply relegated to a small area of learning. As the applications of GAI are broad and likely revolutionary, the public sector must strike the appropriate balance between beginning modestly, while retaining bold and far-reaching goals.
A public board playbook for digital governance
AI is just one of the digital technologies completely transforming modern governance for public boards of nonprofits and mission-driven organizations.
A new Diligent executive guide gives public boards in education and government a definitive playbook for navigating governance in the digital era — including how to leverage new tools like GAI to enhance board operations and make smarter, faster decisions; and how to incorporate digital communication tools to connect with digital-native communities, all while staying on the right side of tightening data security regulations.
Download the digital governance playbook here.
