Welcome to the AI-Assisted Incident Command Decision-Support Study
Thank you for your interest in this research study conducted through the University of Maryland Global Campus (UMGC) Doctor of Business Administration program.
The purpose of this study is to evaluate how artificial intelligence (AI) decision-support applications present threat assessments and tactical recommendations to fire service incident commanders during emergency scenarios. Specifically, this research examines how different formats of AI-generated information influence command decision-making under time-pressured, high-consequence conditions.
Your participation will involve completing a brief pre-simulation survey, interacting with a simulated structure fire scenario that includes an AI decision-support system, and completing a short post-simulation survey. The entire session takes approximately 15–20 minutes.
Your professional expertise as an incident commander is essential to this research. The findings will contribute to evidence-based guidance for designing AI decision-support systems and training programs for emergency management professionals.
Informed Consent for Participation in Research
Principal Investigator: David Povlitz, Doctoral Candidate, DBA, University of Maryland Global Campus
Faculty Advisors: Dr. Tacy Holliday | Dr. Jason Stroman — University of Maryland Global Campus
This study examines how AI decision-support systems communicate threat assessments and recommendations to incident commanders during emergency scenarios. The goal is to generate evidence-based guidance for designing AI tools that support effective emergency management decision-making.
If you agree to participate, you will: (1) Complete a brief pre-simulation survey about your professional background and attitudes toward AI technology, taking approximately 5 minutes; (2) Receive an orientation to the simulation interface and controls; (3) Interact with a web-based simulation of a residential structure fire scenario in the role of incident commander, during which an AI system will provide threat assessments and tactical recommendations at several decision points — the simulation lasts approximately 5 minutes; and (4) Complete a short post-simulation survey about your experience with the AI system, taking approximately 2–3 minutes. The total time commitment is approximately 15–20 minutes.
- I volunteer to participate in a research project conducted by David Povlitz from the University of Maryland Global Campus. I understand that the project is designed to gather information about incident commander decision support from artificial intelligence applications. I will be one of approximately 160 people participating with this research.
- My participation in this project is voluntary. I understand that I will not be paid for my participation. I may withdraw and discontinue participation at any time without penalty. If I decline to participate or withdraw from the study, no one in University of Maryland Global Campus or in my organization will be told.
- If I feel uncomfortable in any way during the simulation session, I have the right to decline to answer any question or to end the simulation and survey.
- I understand that the researcher will not identify me by name in any reports using information obtained from this simulation and survey, and that my confidentiality as a participant in this study will remain secure. Subsequent uses of records and data will be subject to standard data use policies which protect the anonymity of individuals and institutions.
- I understand that this research study has been reviewed and approved by the Institutional Review Board (IRB) for Studies Involving Human Subjects at the University of Maryland Global Campus. For research problems or questions regarding subjects, the Institutional Review Board may be contacted at [email protected].
- I have read and understand the explanation provided to me. I have had all my questions answered to my satisfaction, and I voluntarily agree to participate in this study. I can print a copy of this consent form from my web browser.
The risks associated with this study are minimal and do not exceed those ordinarily encountered in routine incident command training exercises. You may experience mild cognitive fatigue or brief stress due to the time-pressured decision-making scenario. The simulation does not depict graphic imagery. You may pause or stop the session at any time if you experience discomfort.
There are no direct benefits to you from participating. Your participation will contribute to research that may improve the design of AI decision-support tools and training programs for emergency management professionals.
All data collected in this study are anonymous. No personally identifiable information, including your name, email address, department name, I.D. number, or IP address, is collected or stored at any time. You will be assigned a randomly generated participant code. Your responses cannot be linked to your identity. All data will be stored on encrypted, password-protected media accessible only to the principal investigator and retained for at least three years before secure deletion.
If you have questions about this study, please contact David Povlitz at . If you have questions about your rights as a research participant, please contact the UMGC IRB at .
Simulation Orientation: What to Expect
Thank you for consenting to participate. Before you begin, here is an overview of what your session will involve.
- 1
Pre-Simulation Survey — approximately 5 minutes
You will answer brief questions about your professional background (rank, years of service, department type, prior AI experience) and your general attitudes toward AI technology.
- 2
Simulation Orientation — approximately 2 minutes
You will familiarize yourself with the simulation interface, including how to read the AI system's threat assessments, how to view the scenario information displays, and how to submit your decisions using the action buttons.
- 3
Simulated Scenario — approximately 4–5 minutes
You will assume the role of the incident commander arriving on scene at a residential structure fire. The scenario will evolve through several critical decision points. At each point, an AI decision-support system will present a threat assessment and a tactical recommendation. You will review the available information and select your command decision. There are no trick questions; choose the decision you believe is most appropriate given the information presented.
- 4
Post-Simulation Survey — approximately 2–3 minutes
After the scenario concludes, you will answer a few short questions about your experience with the AI system.
(1) A situation briefing describing current fireground conditions; (2) the AI system's threat appraisal of the evolving situation; (3) information about potential outcomes; and (4) the AI system's recommended tactical or strategic action. You will then select one of the available strategic or tactical options.
Anonymous Demographic and Professional Information Questionnaire
General Attitudes towards Artificial Intelligence Scale (GAAIS)
Source: Schepman & Rodway (2023). International Journal of Human–Computer Interaction, 39(13), 2724–2741. doi:10.1080/10447318.2022.2085400
| Statement | 1 Strongly Disagree | 2 Disagree | 3 Neutral | 4 Agree | 5 Strongly Agree |
|---|
| Statement | 1 Strongly Disagree | 2 Disagree | 3 Neutral | 4 Agree | 5 Strongly Agree |
|---|
Pre-Arrival Incident Briefing
| Incident | Structure Fire — Single-Family Dwelling (1-Story with Basement) | Date/Time | 10:00 AM |
| Address | Generic Residential Address, Sector Alpha | Weather | Sunny, 60°F, Wind: Light 5–8 mph from West |
| Occupancy | Single-Family Dwelling, 1-Story, Basement without Walkout, Wood Frame, Comp Shingle Roof | Life Hazard | CRITICAL — Multiple Non-Ambulatory Occupants Reported |
| Initial Strategy | OFFENSIVE — Rescue, Confinement, Extinguishment | Command Post | Alpha Side — Front of Structure (Street) |
At 10:00 AM on a clear, sunny morning with a temperature of 60°F and light westerly winds, dispatch receives multiple 911 calls reporting fire and heavy smoke from a one-story, wood-frame, single-family dwelling in a residential neighborhood. Callers report visible flames from the front (Side Alpha) of the structure and heavy black smoke venting from windows on the Delta (right) side. One caller specifically reports seeing elderly occupants prior to the fire. Two additional callers independently state they believe occupants are still inside and cannot get out.
The structure is an approximately 1,800 square foot, single-story residence with a composition shingle roof and wood-frame construction (Type V) with a finished basement. A hydrant is located 150 feet from the front of the structure on the Alpha side. Life safety is the immediate priority. The emergency communications center relays that three occupants as non-ambulatory and are reportedly trapped.
| Charlie Side (Rear) | Bravo Side (Left) | Alpha Side (Front) | Delta Side (Right) |
|---|---|---|---|
| Rear entry door | Light smoke showing from attic vent. Garage and kitchen area. | FIRE ORIGIN AREA — Active flames from visible living room. Command Post location. | Bedroom windows with heavy smoke showing. |
| Unit | Personnel | SOP Assignment | Estimated Arrival | Initial Activity Prior to Chief 1 Arrival |
|---|---|---|---|---|
| Engine 1 | 4 | Initial Attack — Lead Engine | Minute -2 (09:58) | Size-up, establish water supply, deploy attack line — Alpha side |
| Engine 2 | 4 | Back-up Attack / Search | Minute -1 (09:59) | Backup attack line, assist with fire confinement Charlie side |
| Engine 3 | 4 | Water Supply / RIC | Minute 4 (10:04) | Responding |
| Engine 4 | 4 | Staging / Rehabilitation | Minute 3 (10:03) | Responding |
| Truck 1 | 4 | Primary Search & Rescue | Minute 1 (10:01) | Forcible entry, primary search Alpha/Bravo quadrant, victim removal |
| Truck 2 | 4 | Ventilation / Secondary Search | Minute 4 (10:04) | Responding |
| Rescue 1 | 4 | Rescue — Victim Extrication | Minute 4 (10:04) | Responding |
| Medic 1 | 2 | EMS / Triage | Minute 3 (10:03) | Responding |
| Chief 1 | 1 | Incident Commander | Minute 2 (10:02) | Assume command, direct all operations, establish command post Alpha side |
| Safety 1 | 1 | Safety Officer | Minute 4 (10:04) | Responding |
Strategy confirmed OFFENSIVE. Three non-ambulatory victims confirmed and possibly in the basement. Rescue is Priority 1.
Strategy: OFFENSIVE | Mode: INTERIOR ATTACK | Status: OFFENSIVE — RESCUE PRIORITY | CONFINEMENT & ATTACK
Fire confinement
Engine 2
Backup line
Two 1¾" lines — water supply established
T1 Crew — Forcible entry and Alpha/Delta search
Truck 2 (ETA min 4)
Horizontal ventilation planned
Bravo/Delta windows
Not yet established
Treatment area planned Alpha
(E3 ETA min 4)
AI Command Assistant — Operator Instructions
- How incident commanders integrate AI-generated situation assessments with their own training and experience
- The quality, timing, and rationale behind command decisions made with AI support
- How participants evaluate, accept, question, or override AI recommendations
- Cognitive workload and confidence levels during the simulation
- The overall effectiveness of the AI Command Assistant Agent as a decision support tool
The AI Command Assistant Agent operates by continuously analyzing three data streams simultaneously:
Video analysis: Live and recorded video feeds from scene cameras, aerial assets, and cameras on operating crews. The agent classifies fire stage, smoke conditions, and structural involvement.
Radio traffic: Real-time monitoring and transcription of all fireground radio communications. The agent tracks unit assignments, PAR status, conditions reported by interior crews, and deviations from assigned tasks.
Environmental sensors: Data from environmental monitoring sensors including atmospheric readings, thermal imaging overlays, wind speed and direction, structural heat sensors, and responder localization where available.
| Output Type | Description |
|---|---|
| Situation Assessment | A concise, current picture of incident conditions — fire location and spread, victim status, crew positions, hazards, and resource status. Updated continuously as conditions change. |
| Threat Assessment | Identification and prioritization of imminent and developing threats to life safety, structural integrity, crew safety, and exposure structures. Includes confidence level and supporting data. |
| Strategic Recommendations | High-level command guidance — recommended strategy (offensive/defensive/transitional/marginal) and priority objectives based on current conditions. |
| Tactical Recommendations | Specific operational suggestions — unit assignments, positioning, ventilation coordination, water supply decisions, search priorities, and egress routes. |
| Decision Prompts | At key moments during the simulation, the AI will prompt you with a decision point. You will be asked to make a command decision based on your training, experience, and the AI's analysis. |
- You may accept an AI recommendation in whole or in part
- You may reject any AI recommendation
- You may override the AI based on your own assessment at any time
- The AI does not feel offended. It does not second-guess you. It does not judge or evaluate you.
- The simulation has sound. Radio transmissions are synthesized. The AI command agent also transcribes a radio log for clarity.
- The simulation and AI Command Assistant will prompt your attention or action with flashing elements.
- Click "Begin Command Simulation" button below to advance to the simulation page. Start the simulation by clicking the play button.
Incident Command Simulation
Post-Simulation Trust Assessment
Source: McGrath, R., Lamba, R., Bhatt, S., & Maloney, A. (2025). A short trust in automation scale. International Journal of Human–Computer Interaction, 41(3), 1–13. doi:10.1080/10447318.2024.2366182
| Statement | 1 Not at all | 2 Slightly | 3 Somewhat | 4 Moderately | 5 Quite | 6 Very | 7 Extremely |
|---|---|---|---|---|---|---|---|
| I am confident in the system. | |||||||
| The system is reliable. | |||||||
| I can trust the system. |
Post-Simulation Protection Motivation Assessment
Adapted from: Witte, K., Cameron, K. A., McKeon, J. K., & Berkowitz, J. M. (1996). Predicting risk behaviors: Development and validation of a diagnostic scale. Journal of Health Communication, 1(4), 317–341. doi:10.1080/108107396127988
The following statements concern your assessment of the structure fire and life-safety situation as presented. Please indicate your level of agreement with each statement based on the information available to you at this time.
| Statement | 1 Strongly Disagree | 2 Disagree | 3 Neutral | 4 Agree | 5 Strongly Agree |
|---|---|---|---|---|---|
| The structure fire currently presents a severe threat to the lives of the trapped occupants. | |||||
| The consequences of this incident are serious if immediate tactical action is not taken. | |||||
| The potential for loss of life in this incident is significant. | |||||
| This structure fire represents a critical life-safety emergency requiring urgent intervention. | |||||
| The harm that could result from this incident is extreme. | |||||
| The structural and fire conditions reported in this incident make the threat to trapped occupants severe. |
The following statements concern your assessment of the likelihood of harm occurring in this incident given current conditions.
| Statement | 1 Strongly Disagree | 2 Disagree | 3 Neutral | 4 Agree | 5 Strongly Agree |
|---|---|---|---|---|---|
| It is likely that the trapped occupants will suffer serious harm or death if tactical intervention is delayed. | |||||
| Based on the conditions reported, the probability that occupants will not survive without immediate rescue is high. | |||||
| The operating crews entering this structure face a real and present risk of serious injury or death. | |||||
| Given the fire behavior and structural conditions, adverse outcomes are probable without effective tactical action. | |||||
| The risk that this incident will result in civilian fatalities is elevated under current conditions. | |||||
| I believe that rescue personnel operating in this structure are genuinely exposed to life-threatening hazards. |
The following statements concern your assessment of the tactical and strategic recommendation provided by the AI decision support application in response to this incident.
| Statement | 1 Strongly Disagree | 2 Disagree | 3 Neutral | 4 Agree | 5 Strongly Agree |
|---|---|---|---|---|---|
| The AI decision support application's recommendation is an effective approach to managing the life-safety threat in this incident. | |||||
| Following the AI application's recommended tactical course of action would meaningfully reduce the risk of harm to trapped occupants. | |||||
| The recommended strategy provided by the AI application is a sound approach to this structure fire. | |||||
| Implementing the AI application's recommendation would help protect the safety of rescue personnel operating in this incident. | |||||
| The AI application's recommendation addresses the most critical tactical priorities of this incident. | |||||
| The course of action recommended by the AI decision support application would likely produce better outcomes than taking no coordinated action. |
The following statements concern your confidence in your own ability to carry out the tactical and strategic recommendation provided by the AI decision support application.
| Statement | 1 Strongly Disagree | 2 Disagree | 3 Neutral | 4 Agree | 5 Strongly Agree |
|---|---|---|---|---|---|
| I am capable of implementing the tactical course of action recommended by the AI decision support application in this incident. | |||||
| I have the resources and personnel necessary to carry out the AI application's recommended strategy under current conditions. | |||||
| Executing the AI application's recommended approach to this incident is within my operational capacity as incident commander. | |||||
| I am confident in my ability to coordinate the tactical actions recommended by the AI decision support application. | |||||
| Implementing the AI application's recommendation is achievable given the crews, equipment, and conditions present at this incident. | |||||
| Even under the time pressure of this incident, I could successfully execute the strategy recommended by the AI decision support application. |
Study Explanation and Thank You
Thank you for completing this research study. Your participation is greatly valued and contributes to important research on AI-assisted decision-making in emergency management.
This study investigates how two specific features of AI decision-support systems influence incident commanders' decisions during emergencies: (1) the level of explainability provided by the AI system, and (2) how decision outcomes are framed.
AI Explainability Manipulation
Participants were randomly assigned to either a high-explainability condition, in which the AI system provided detailed reasoning for its threat assessments (including perception data inputs, reasoning chains, and confidence levels), or a low-explainability condition, in which the AI provided only its threat classification and recommended action without disclosing its underlying reasoning. This manipulation tests whether AI transparency enables the cognitive appraisal processes that protection motivation theory (Maddux & Rogers, 1983) identifies as prerequisites for appropriate protective action.
Gain–Loss Framing Manipulation
Participants were also randomly assigned to either a gain-frame condition, in which AI recommendations emphasized the positive outcomes of compliance (e.g., lives saved, structures preserved), or a loss-frame condition, in which the AI emphasized the negative consequences of noncompliance (e.g., lives lost, structures destroyed). The numerical information was equivalent across conditions; only the framing language differed. This manipulation tests prospect theory's (Tversky & Kahneman, 1992) prediction that loss framing induces different risk preferences than gain framing.
What We Are Studying
The central research question is: Under simulated emergency conditions, how do the AI explainability of threat appraisals and the situation's gain–loss framing of outcomes influence incident commanders' appropriate adoption of AI recommendations with time-bound, high-consequence decisions?
Important Note
The AI system in the simulation was designed for research purposes. Its recommendations were trained and validated by subject-matter experts and found to be objectively appropriate for the simulated conditions. The study did not evaluate your competence or decision-making ability as an incident commander.
Your randomly generated participant ID is displayed at the top of this page. If you wish to withdraw your data, please provide this ID to the researcher. Because no personally identifiable information was collected, this code is the only way to locate and remove your data.
- Principal InvestigatorDavid Povlitz —
- Faculty AdvisorDr. Tacy Holliday —
- UMGC IRB
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