Emergency & Acute Care AI Risk Research Volunteer Triage, Rapid Decision-Making, Disaster Response & Global Emergency Systems (Remote)

Already, 1 in 10 patients are harmed during their medical care. Our 501c3 nonprofit works to ensure AI improves patient care rather than putting it at greater risk.We host a variety of remote volunteer opportunities. From researching the use of AI in diagnostics to creating patient education tools, and from liaising with industry to investigative journalism - BRITE Institute offers diverse ways to use your skills to save lives.,About The InitiativeThe BRITE Institute is expanding a structured AI Safety and Risk Framework initiative focused on identifying, analyzing, and documenting AI failure modes in healthcare and other high-risk environments.As artificial intelligence becomes increasingly integrated into emergency care, triage systems, crisis response, patient monitoring, diagnostics, resource allocation, EMR systems, and operational decision-making, there is an urgent need for contributors who understand high-pressure healthcare environments.This initiative is building a scalable AI safety research and intelligence framework designed to help identify where AI systems may fail in emergency, acute care, disaster response, remote, underserved, unstable, or globally distributed healthcare environments.This work is especially important because AI systems may perform differently whenTime is limitedPatient information is incompleteResources are scarceInfrastructure is unstableClinical teams are under pressureCommunication systems are disruptedPatients are medically complexCare is delivered in emergency, disaster, battlefield, or remote settingsThis is a unique opportunity to contribute to meaningful work at the intersection ofEmergency medicineAcute carePatient safetyDisaster responseBattlefield and austere medicineRemote and underserved healthcareGlobal emergency response systemsAI/MLClinical operationsRisk managementEmerging technologyThe project operates through a standardized research workflow and collaborative system.Volunteer Roles AvailableWe are seeking contributors from a wide range of emergency, acute care, crisis response, and healthcare backgrounds, includingEmergency physiciansEmergency department nursesTrauma nursesEMTsParamedicsFlight medicsMilitary medicsCombat medicsDisaster response professionalsHumanitarian healthcare workersCrisis response volunteersUrgent care cliniciansCritical care cliniciansTrauma care professionalsMedical studentsNursing studentsPre-med studentsPhysician assistantsNurse practitionersPublic health emergency response professionalsRemote healthcare workersRural healthcare professionalsGlobal health professionalsField medicine professionalsHealthcare operatorsClinical researchersAllied health professionalsHealth system operations professionalsThis is a fully remote and unpaid volunteer opportunity.What You Will DoContributors may assist withIdentifying emergency and acute care AI failure modesEvaluating how AI failures may impact triage, diagnosis, treatment, escalation, and patient safetyReviewing emergency care, disaster response, and crisis deployment scenariosAssessing operational realism in high-pressure clinical environmentsIdentifying AI risks in remote, rural, underserved, unstable, or resource-limited settingsEvaluating how AI systems may fail when data is incomplete, delayed, biased, or unavailableReviewing risks related to rapid clinical decision-makingIdentifying unsafe deployment conditions and edge casesAnalyzing trust, adoption, overreliance, underuse, and clinician judgment risksSupporting publication-oriented research outputsContributing to mitigation strategy developmentHelping ensure AI systems reflect real-world emergency and crisis care environmentsEntering finalized findings into standardized project systemsSpecial Focus AreasThis role is especially designed to attract contributors who understand healthcare delivery in complex or high-risk environments, includingEmergency Department and Acute CareTriageTrauma careUrgent diagnosisRapid patient deteriorationCritical decision-makingED overcrowdingHandoff failuresAlert fatigueTime-sensitive escalationDisaster Response and Crisis MedicineMass casualty eventsNatural disastersPublic health emergenciesEmergency logisticsResource allocationField operationsCrisis coordinationDisrupted communication systemsRemote and Underserved RegionsRural healthcareLimited access to specialistsLimited diagnostic toolsTransportation delaysInfrastructure gapsScarce resourcesDelayed follow-up carePopulation-specific health risksUnstable and War-Torn EnvironmentsBattlefield medicineAustere care settingsConflict zonesHumanitarian responseLimited suppliesSecurity risksDisrupted health systemsHigh-pressure field decision-makingGlobally Distributed Emergency Response SystemsCross-border health responseInternational emergency coordinationGlobal health deploymentsField data collectionMulti-site response systemsVariable infrastructure across regionsCommunication and documentation gapsIdeal Candidate ProfileWe are looking for contributors who areDetail-orientedHighly organizedReliable and responsiveAble to follow directions and guidanceComfortable following structured workflowsAble to work independentlyAdaptable to evolving research processesComfortable reviewing healthcare-related scenariosAble to think critically under complex conditionsInterested in patient safety, emergency care, and responsible AI deploymentCapable of producing high-quality work within standardized systemsStrong Candidates Are Comfortable WithEmergency care environmentsAcute care workflowsTriage and prioritizationPatient safety risk analysisDisaster response or crisis operationsResource-limited healthcare settingsRemote or underserved healthcare deliveryField medicine or humanitarian responseHealthcare operationsResearch-intensive workDocumentation accuracyCollaborative systemsIterative feedbackStructured templatesShared research systemsMaintaining consistency across standardized workflowsPrior AI Experience Is Helpful But Not Required.The strongest candidates will be able to apply their emergency, clinical, operational, humanitarian, field, or crisis-response experience to identify where AI systems may fail in real-world high-pressure healthcare environments.Why Emergency, Crisis & Field Experience MattersAI systems do not only fail in controlled hospital environments. They may also fail when healthcare is delivered under pressure, with limited information, limited time, limited staff, unstable infrastructure, or high patient volume.Contributors with emergency, acute care, disaster response, battlefield medicine, remote care, or global health experience can help identify risks that purely technical reviewers may miss, includingWhat happens when seconds matterHow triage decisions are made under pressureHow incomplete information affects patient safetyHow resource scarcity changes clinical decision-makingHow AI tools may fail during surge conditionsHow emergency teams respond to alerts, recommendations, and uncertaintyHow unstable environments affect documentation, monitoring, and follow-upHow globally distributed systems may create inconsistent AI performanceHow trust, usability, and adoption influence emergency care outcomesThis role is especially valuable for people who understand the practical realities of emergency medicine, field care, crisis response, and high-stakes healthcare delivery.Important NotesThis initiative is fast-moving, systems-oriented, and research intensive.Contributors should be comfortable withLearning new workflows quicklyOperating within standardized systemsReceiving structured feedbackContributing consistently within collaborative research environmentsMeeting deadlinesUsing collaborative digital tools and remote workflowsMaintaining professionalism and accuracyRemote collaboration may includeSlackZoomGoogle MeetGoogle DocsShared spreadsheetsResearch templatesStructured data entry systemsBecause this work may contribute to future publications, policy frameworks, healthcare AI safety guidance, and advanced AI safety initiatives, the following are extremely importantProfessionalismReliabilityOperational awarenessConfidentialityAttention to detailClear communicationConsistent follow-throughWhat You’ll GainVolunteers may gainExposure to emerging AI safety researchInterdisciplinary emergency care and AI experiencePublication-oriented collaborationOperational and systems-thinking experienceExperience analyzing emergency, disaster, field, and crisis-response AI risksExperience working alongside technical AI contributors and researchersHands-on exposure to the rapidly growing AI/ML ecosystem impacting healthcare globallyOpportunities to help shape safer and more clinically grounded AI systemsExperience contributing to a framework relevant to high-risk and resource-limited healthcare settingsThis is an opportunity to help bridge the gap between real-world emergency care, global crisis response, and the future of AI-driven healthcare systems.Additional InformationEstimated commitment approximately 8–15 hours per weekWork may include structured research, documentation, and standardized data entryThis is a merit-based and experience-based volunteer opportunityApplicants should be prepared to submit relevant work samples, research examples, writing samples, healthcare experience, emergency response experience, field experience, military medical experience, humanitarian experience, or related professional backgroundSelected candidates may also be asked to complete a short skills-based assessment aligned with the responsibilities outlined in this position descriptionRemote Volunteer Unpaid Flexible Hours