Request for Information (RFI): Community Influence on Human Judgment During Information Processing Tasks
🏛 Dept of the Army -- Materiel Command (DOD-AMC)
✓ Free, no account · Source: Grants.gov · Last verified Jul 16, 2026
Can you apply?
This grant is for organizations and researchers interested in studying human judgment and decision-making. The Army Research Laboratory is seeking information on theories and models related to collective influences on judgment during information processing tasks. This is a Request for Information (RFI) for planning purposes only—not a binding solicitation or procurement. Respondents should note that the Army is under no obligation to acknowledge receipt or provide feedback, and no contract will be awarded based on responses.
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Program description
This is a Request for Information (RFI) issued solely for information and planning purposes and does not constitute a solicitation. Respondents are advised that the Army Research Lab (ARL) is under no obligation to acknowledge receipt of the information received or provide feedback to respondents with respect to any information submitted under this RFI.
Responses to this notice are not offers and cannot be accepted by the Government to form a binding contract. Respondents are solely responsible for all expenses associated with responding to this RFI. ARL will not provide reimbursement for costs incurred in responding to this RFI. It is the respondent’s responsibility to ensure that the submitted material has been approved for public release by the information owner.
The Government does not intend to award a contract on the basis of this RFI or to otherwise pay for the information solicited, nor is the Government obligated to issue a solicitation based on responses received. Neither proprietary nor classified concepts or information should be included in the submittal.
The Army Research Laboratory (ARL) is seeking information on interdisciplinary theories and models for collective influences on human judgment during information processing tasks and prior to collective decision making. This RFI is issued for planning purposes only, and it does not constitute a formal solicitation for proposals or suggest the procurement of any material, data sets, etc. The following sections of this announcement contain details on the specific scientific areas of interest, along with instructions for the submission of responses.
Background and Scope:
During information processing tasks, the formation of judgments on the utility of information from a wide variety of sources by analysts (working alone or in teams) is influenced by (a) other people in their networks, (b) the available information they consume, (c) potential interactions with virtual agents, and (d) their own internal predispositions based on background, training, and values. These analysts’ capabilities and performance on such tasks can be expanded and augmented through intelligent systems or information agents leveraging technologies such as Large Language Models (LLMs) or through additional information gained from social media and social networking platforms. However, such human-agent teaming approaches can lead to the emergence of new biases and challenges surrounding the reliability of such judgments made to accept/reject each piece of information being processed. These phenomena reside at the conscious and subconscious levels, further expounding the challenges to understand their impact on judgment formation.
This RFI seeks to elicit interdisciplinary perspectives on the judgment formation process in the context of analysts being embedded in larger communities and inundated with algorithmically driven information.
Who can apply
Eligible applicants
How to apply
Application links
Key dates & requirements
Required documents
- Response letter or document addressing the research topics
- Any supporting materials (non-proprietary and public-release approved)
- Organization contact information
Program contact
- 👤 Dr. Edward T. Palazzolo Program Manager: Social and Cognitive Networks Humans in Complex Systems DEVCOM ARL Army Research Office Dr. Robert St. Amant Program Manager: Knowledge Systems Military Information Sciences DEVCOM ARL Army Research Office
- 📧 ARL-CIHJ-RFI@army.mil
- 📞 Contact By Email
Funding track record
Recent awards under CFDA 12.431 from the last 3 years — real organizations that won funding through this same program.
Top 10 Largest Recent Awards
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$213,594,079
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$88,655,689
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$54,356,555
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$49,736,421
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$48,908,501
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$43,820,967
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$38,292,265
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$34,850,000
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$31,526,562
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$27,457,336
Top States by Funding
- MD 10 awards $367.6M
- MA 13 awards $197.8M
- CA 11 awards $189.5M
- TX 6 awards $129.2M
- PA 9 awards $126.4M
Source: USAspending.gov — federal spending transparency. Data covers last 3 years.
Funding history
Annual funding for this program — Federal obligations (CFDA 12.431). How funding has trended year over year.
| 2024 | $764,057,529 | |
| 2025 | $750,782,726 | |
| 2026 est. | $800,000,000 |
FAQ
Is this a formal solicitation for proposals?
No, this is a Request for Information (RFI) issued for planning purposes only. The Army is not obligated to issue a solicitation based on responses received.
Will respondents be reimbursed for costs?
No. Respondents are solely responsible for all expenses associated with responding to this RFI.
What type of information is being sought?
The Army Research Laboratory seeks interdisciplinary theories and models on how collective influences affect human judgment during information processing tasks, including effects from social networks, information sources, virtual agents, and personal predispositions.
Can I submit proprietary or classified information?
No. Proprietary and classified concepts or information should not be included in submissions. Ensure submitted material is approved for public release.
What is the deadline and next steps?
The deadline is January 17, 2024. This RFI is for information gathering only; responses do not constitute offers and may lead to future formal solicitations.
💡 Tips for applicants
- Submit information on interdisciplinary theories and models relevant to human judgment in team-based information processing contexts.
- Address how collective influences from social networks, information agents, and LLMs affect judgment formation and reliability.
- Keep submissions clear and non-proprietary; ensure any submitted material is approved for public release.
- Note that this is an RFI for planning purposes only—responses will not result in immediate contracts or payments.
- Consider including perspectives on both conscious and subconscious factors influencing judgment in algorithmically driven information environments.
⚠️ Common mistakes
Submitting proprietary or classified information will disqualify your response. Many respondents waste effort expecting reimbursement or an immediate contract award. Not ensuring material is approved for public release before submission will cause rejection.
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