Responsible use of Generative AI in disaster management

About the Project

Project Details

The impact of disasters and crises affects an increasing number of vulnerable people every year. These people require assistance to satisfy basic needs and to reduce suffering but operating under uncertain conditions is extremely challenging for humanitarian organisations. One of the key challenges is the management of information. Disaster situations are surrounded by dynamic environments with changing priorities and limited resources, often managed with limited, out-of-date and unreliable information. A global review of disaster initiatives of the UN highlighted that the use of information, technology and applied research can be essential to tackle disaster risk reduction. The primary objective is to improve the capture, extraction, analysis and actionability of information. Generative AI (GenAI) can manage vast amounts of information and produce novel and meaningful content, thereby transforming the way we work and make decisions. There are multiple exciting applications in disaster management, whether for situation and needs analysis in combination with other tools such as social media, image analysis or drones, or for supporting search and rescue. Current pilot applications in humanitarian organisations include chatbots for information dissemination, voice transcription for remote data collection, and large language models (LLMs) for situation analysis. However, these applications are still working around the edges of disaster response. In fact, the use of AI and LLMs to assist the disaster management process is currently understudied. Those applications, however, need to be carefully approached. Concerns about transparency, privacy and ethical issues about the use of real-time data are further complicated by the limited understanding of the limitations of GenAI. For instance, ChatGPT has shown inconsistencies in response in activities of sensitive nature, limited accuracy of responses, and difficulty processing complex context-dependent queries in specialized disaster scenarios. The use of social media and open-source information, which needs to be filtered, the reliance on patter recognition over specialized knowledge, and the potential of hallucination make adoption in disaster management a complex process. Considering the potential and vulnerabilities of GenAI, there is a need to explore the readiness for adoption and the operational practices of disaster management organisations to mitigate potential problems (e.g. shadow AI) and promote successful implementation. The purpose of this project is to analyse the organisational adoption of Gen AI for disaster management. It defines critical elements to develop a framework for responsible implementation in the area. The outputs of this research will be: i) a map of different GenAI tools and their fit with disaster response activities, ii) a validated framework incorporating the key requirements for responsible implementation of GenAI in disaster management, iii) and a validated self-assessment questionnaire for the adoption of GenAI in disaster management organisations. The successful student will have knowledge about Disaster Management, Artificial Intelligence and technology adoption. The first year will be focused on literature review and taking the Research Methods Course, with data collection and analysis starting in year 2. The final 4 months of the project will allow the student to write-up the dissertation for submission. The outcomes will provide opportunities for conference presentations and journal publications.

Person Specification

The successful applicant should hold, or expect to achieve:

A First or Upper Second Class Honours undergraduate degree, and a Masters degree with Merit or Distinction, both in relevant subjects.

Qualifications from overseas institutions will be considered, but performance must be equivalent to that described above, and the University reserves the right to ascertain this equivalence according to its own criteria.

Desirable / Essential Skills or Experience

Experience in Artificial Intelligence and technology adoption. Applicants with knowledge about technology and the human/organisational impact are encouraged to apply

Desirable characteristics

Additional factors that may be considered include:

• Distinction in the MSc or BSc dissertation.
• Evidence of research experience (e.g. publications, research assistantships, etc.).
• Professional experience relevant to the proposed research (working on disaster management and/or Artificial Intelligence).
• Evidence of qualitative, quantitative or mixed-method designs
• Excellent communication skills to engage with practitioners

Submitting an application

We can only consider applications that are complete and have all supporting documents. Applications that do not provide all the relevant documents will be automatically rejected.Your application must include:

1. English language copies of the transcripts and certificates for all your higher education degrees, including any Bachelor degrees.
2. A Research Statement detailing your understanding of the research area, how you would approach the project, and a brief review of relevant literature. Be sure to use the title of the research project you are applying for. There is no set format or word count.
3. A personal statement which outlines any further information which you think is relevant to your application, such as your personal suitability for research, career aspirations, possible future research interests, and further description of relevant employment experience.
4. A Curriculum Vitae (Resume) which details your education and work history.
5. Two academic refereeswho can discuss your suitability for independent research. References must be on headed paper, signed and dated no more than 2 years old. At least one reference should be from your most recent University. You can submit your references at a later date if necessary.
6. Evidence that you meet the English Language requirements. If you do not currently meet the language requirements, you can submit this at a later stage.
7. A copy of your passport. Where relevant, include evidence of settled or pre-settled status.

Contact Information

For enquiries about this project, contact s.khorana@aston.ac.uk

Location

This position will be based on the Aston Campus in Birmingham, UK. The successful candidate will need to be located within a reasonable distance of the campus, and will be expected to visit in person regularly.

Interviews

Interviews will be conducted online via Microsoft Teams. If you are shortlisted, you will be contacted directly with details of the interview.

Funding Notes

This project covers all tuition fees.

Please note that the successful candidate will be responsible for living expenses, and any costs relating to moving to Birmingham and/or visiting the Aston campus. International students must meet the financial requirements for the visa, flights, and NHS Surcharge. Applicants should be confident that they can meet these costs before applying.

Further information can be found here: Financial Requirements | Aston University