The epidemic of COVID-19 has highlighted the critical need for government agencies to improve data access in order to save time, money, and lives. The past year and a half has also served as a reminder that data is constantly changing—whether it comes from a state’s centralized repository of health records or a military jet that generates one terabyte of data per hour—and that it must be readily available and up-to-date in order for key decision-makers to analyze it appropriately.
Artificial intelligence and machine learning will become more important in the public sector, allowing agencies to make better, faster, and more accurate judgments. In today’s world, open-data and open-source approaches are also the most effective way to ensure data is current and freely accessible.
Data and AI are a top priority for the government, but there are challenges to overcome.
The federal government is clearly keen on updating its data analytics and warehousing capabilities, with the Biden administration forming the National AI Research Resource Task Force and the Department of Defense announcing a data plan. Last year, the government promised a $1 billion investment in AI research and development. Better focus on cloud, analytics, and AI may result in increased operational efficiency. According to a Deloitte analysis, data-driven automation may save government agencies $41 billion each year.
However, because the AI technology landscape is vast, complex, and ever-changing, keeping up with all conceivable solutions to identify which is optimal for a given application is difficult. The main stumbling block is the data itself: The process of gaining actionable insights and obtaining a unified perspective of organizational data is frequently hampered by data silos. It can also be difficult to find and scale individuals with the necessary capabilities to implement robust AI solutions.
Time and Life-Saving Methodologies
Federal agencies can use open data or open-source ways to handle some of these innovative issues with much-needed agility and the most efficient way to ensure data is up to date.
According to a recent survey, governments at all levels are seeing the advantages of open solutions, which include cheaper costs, improved confidence, increased transparency, and reduced vendor lock-in. An open-data model also promotes collaboration, allowing government departments to handle similar issues without having to reinvent the wheel.
Open-Source Adoption Obstacles
While open-source solutions can help agencies in a variety of ways, there are a few roadblocks to adoption. Many agencies are dealing with out-of-date legacy systems that are sometimes disconnected, resulting in data silos, or they may lack the technical expertise to integrate open-source tools or run software.
Another issue to consider while choosing open solutions is data security. To decrease the danger of data exposure, only publish the code, not the data that goes with it. Implementing “supported” open-source software that has been reviewed and maintained by a vendor can also provide data security assurance, as the government will be alerted when a vulnerability is discovered and the flaw will be addressed quickly.
Federal agencies may use open-source software to find more efficient and long-term solutions, enhancing collaboration, lowering expenses, and ultimately saving lives. In the future, it’s difficult to see how federal agencies that need to exchange data with other government agencies, nations, and the general public could adopt closed source solutions, since data is often held in a proprietary format. The missing puzzle piece in the gridlocked information-sharing puzzle is prioritizing transparency.