No AI tools, including GovEagle, are immune from:
Bias when asked to make sensitive decisions
Hallucinations (making up information) when asked about specific facts
To use the tool effectively, users should remain in control of high-level decisions, and, as much as possible, use the tool as a focused assistant for tedious work.
Understanding Hallucinations and Bias
Hallucinations often arise when, without realizing it, you ask the tool to perform a task that it cannot complete without making hidden (and sometimes invalid) assumptions. GovEagle is more likely than many tools to seek clarification when it doesn't have enough information to complete a task accurately, but it will always prioritize your request over these general guidelines.
Bias works similarly. When the tool lacks specific information to answer your question, it is more likely to fall back on behaviors and patterns generalized across its training data. This is often undesirable for decision-making use cases.
Both hallucinations and bias often boil down to a lack of information.
The most effective way to avoid these issues is to structure your requests so they don't require the tool to make assumptions or fill in gaps with generic content, and they don't give the tool control over decisions where bias is likely to arise. When you're specific about what you want and where the information should come from, you get more accurate, verifiable, and useful responses.
Key Principles
Be specific. The more specific your request, the less room there is for the tool to fill in gaps with assumptions or generalizations.
Always have GovEagle specify its sources. Ask for citations and review the source documents directly. This makes it easy to verify that the information is accurate and relevant.
Don't delegate sensitive decisions to the tool. Use GovEagle to help you gather and synthesize information quickly, but make the important decisions yourself. The tool should inform your judgment, not replace it.
Do delegate specific tasks. Specific, well-defined tasks – especially tedious or repetitive work, like searching for something, making specific edits, or writing to an outline – are usually a great fit.
Provide context and constraints. Reference specific documents, past performance examples, or requirements to ground the AI's responses in your actual capabilities.
Examples
Example 1: Evaluating Candidates
Instead of:
Who should we hire?
Consider:
List all resumes in the resume folder meeting the "5 years of experience" criteria from the RFP and provide direct quotes supporting each candidate's qualifications.
By giving the tool a specific task with clear criteria, you remove ambiguity and ensure responses are grounded in actual resume content. You'll get citations linking directly to source documents that you can review yourself to make the hiring decision.
Example 2: Writing Technical Approaches
Instead of:
Write a section explaining how we will deliver this project.
Consider:
Draft an approach section that references our delivery methodology from [name of past performance] and addresses each requirement explicitly.
This grounds the response in both the RFP requirements and your proven capabilities, rather than generic project management language.
Example 3: Addressing Requirements
Instead of:
Add all our capabilities to meet the requirements in the PWS.
Consider:
Map each requirement in PWS Section 3 to specific capabilities from our capability statements in the [company capabilities folder]. For any requirements without a direct match, flag them for my review.
This creates a traceable connection between requirements and your documented capabilities, while surfacing gaps that need your attention.
Example 4: Writing Requirement Responses
Instead of:
Write a paragraph for this requirement.
Consider one of these approaches:
When you have a specific example in mind:
Use the XYZ capability we demonstrated in [name of past performance] to address requirements A, B, and C. Include specific metrics from that project.
When you want the tool to explore your content library:
Step 1: Search our past performance library for examples where we successfully delivered [specific capability] and present your findings for my review.
Step 2: [After reviewing results] Use the [specific project names] examples to draft a response showing how we'll apply that experience to meet this requirement.
By breaking this into steps, you maintain control. You review what GovEagle finds, select what's relevant, and then direct it on what to include.
When you want GovEagle to suggest best practices:
This is a novel requirement for our team. Suggest industry best practices for [specific capability], and I'll review whether they align with our approach.
Being explicit about which approach you want helps GovEagle provide the most appropriate response. GovEagle can be very effective at using general knowledge, and there are times when you will want to use this capability. However, you should be aware that when sources are less clear or when the AI is drawing on general knowledge rather than specific documents, there is a higher risk of bias or hallucinations.