How to Lessen the Burden of Freedom of Information Act Requests

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It is essential to lessen the FOIA burden on government agencies.

The Freedom of Information Act, or FOIA, is a win for free speech and transparency. But what happens when you fail to deliver a timely response to the request? You may not realize how grueling and stressful the processes involved in sourcing the requested information is, particularly given the explosion of data growth and hoarding in the federal government. 

Even though many government agencies have digitized their FOIA request data sourcing and response processes, it hasn’t resulted in any significant increase in response time, nor has it lessened FOIA request burdens. So, what does this tell you?

The advantages of digitizing FOIA request data search, sourcing and response time haven’t been fully realized. Instead, the mandate for digital records has only increased the load on federal agencies. 

Pathways to Lessening the Burden

It is essential to lessen the FOIA burden on government agencies. Using a framework that includes automated thematic analysis, aspects of machine learning, natural language processing and statistical clustering will allow agencies to manage FOIA requests more effectively.

Agencies can overhaul their approach in four steps:

  • Create a Data Asset Inventory: Analyze information at rest in its original location to ensure that only necessary information is curated into intuitive data clusters. This builds an inventory of metadata facets as well as the relevant in-file data for effective targeted pre-search without exhausting agency resources.  
  • Data Cleansing: The cleaning process involves determining what data constitutes as high-value or sensitive from that of lesser value.
  • Modeling and Auto-categorization: Modeling typically involves the agency subject matter experts sorting out the collected information inventory by applying the various policies and rules involved in their dispensation, depending on the type of FOIA request received. 
  • Reporting: A final report will then be delivered. The key is working smarter with the FOIA request process, not against it.

When taking these steps, it’s important to note that search isn’t enough. A typical data search within a large agency can bring up 200,000 to 2 million results with tens of terabytes of unstructured/semi-structured data. It is very easy to get overwhelmed by such a massive number of results. As a reviewer, this does not help you optimize the response time. Artificial intelligence can play a role in automating and increasing the efficiency of FOIA processes, however, is still limited in its capabilities. Identifying the correct datasets to train AI models appropriately is more time-consuming and resource-intensive than effective. 

But agencies can start at the ground level bringing FOIA into policy review. Reviewing agency directives and policies that contain approved information management controls and reporting requirements that may need to involve a FOIA program review against any business products generated as the policy is executed is a good place to begin. Listing these business products as “exempt” or “responsive” helps to prepare the offices responsible for executing policy requirements.

As unmanaged data organization systems lead to heavy backlogs, agencies can lessen the load by creating  a lightweight metadata index of thematic properties. Developing an index involving mapped data with obtained and available core associated metadata leads to more effective and efficient decisions. But agencies should avoid retaining a full-text index, which is resource-intensive and not scalable.

Auto-categorization is the best approach to lessening the burden in conjunction with human subject matter experts. This should be implemented alongside policy agnostic data modeling tools against an inventory of high-value, pre-discovered metadata facets to discover relevant, responsive records for the incoming request quickly. 

Although agencies are awash in data, by reviewing and curating your data, FOIA requests can be handled much more efficiently. 

Tom Jacobs is a senior federal sales executive and James Jones is a senior federal sales engineer at ActiveNav.

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