欧美高清

Publications

Derbyshire James, Dhami Mandeep, , Onkal Dilek, Aven Terje

Risk Analysis Vol 45, pp. 3737-3757 (2025)

Peters Joshua, , , , , Kikkert Peter,

Proceedings of the 22nd ISCRAM Conference ISCRAM 2025 (2025)

, , , Kikkert Peter, ,

Proceedings of the 22nd ISCRAM Conference ISCRAM 2025 (2025)

Dhami Mandeep K, , De Werd Peter, Hadzhieva Velichka, Wicke Lars

Cognitive Research: Principles and Implications Vol 9 (2024)

, Dhami Mandeep K

Journal of Empirical Legal Studies Vol 21, pp. 208-239 (2024)

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Arctic Science Summit Week (2024)

Professional Activities

Speaker

18/5/2025

Participant

12/3/2025

Organiser

24/6/2024

Chair

23/4/2024

Chair

28/4/2023

Projects

Weaver, Beth (Principal Investigator) Belton, Ian (Co-investigator) Dong, Feng (Co-investigator) Gillon, Fern Rebecca Louise (Researcher) Heron, Gavin (Co-investigator) Lagnado, David (Co-investigator) Sanna, Greta (Researcher)

Through interactive workshops, interdisciplinary collaboration, and structured practitioner engagement, we can influence how JSW鈥檚 interpret, trust, and act upon information when conducting risk assessments; strengthen AI literacy among practitioners; augment their critical thinking using causal modalities; support responsible and ethical use of AI. This addresses an urgent unmet need for improved professional critical thinking, AI literacy, practical/policy guidance in responsible use of AI, and critical awareness and trust in adoption of AI technologies.

Project partners are South Lanarkshire HSCP (SLHSCP), a 欧美高清 Strategic partner, and Social Work Scotland (SWS), a National Professional body. While SLHSCP will directly participate in the workshops they will be key to local impact. SWS are instrumental to achieving national impact across social work and social care.

15-Jan-2025 - 15-Jan-2026

Belton, Ian (Principal Investigator) Rudman, Archie John (Researcher) Quigley, John (Co-investigator) Walls, Lesley (Co-investigator) Howick, Susan (Co-investigator)

The NNSAR project was focused on enhancing the Search and Rescue (SAR) system in the Canadian Arctic regions of Nunavut and Nunavik, where SAR responders 鈥� mostly volunteers 鈥� provide 24/7 response capabilities in challenging conditions with limited resources. Their services are essential for community safety and well-being. The NNSAR team has developed a novel quantitative risk model to support decision-making around the strategic allocation of resources for SAR operations.

To improve the management of SAR operations, and to maximise the impact of the NNSAR model, we have identified a need for more and better SAR data. At present, Emergency Management Organizations (EMOs) must allocate resources and seek government funding based on limited and/or anecdotal evidence only. This impact project plans to address the identified data gap in two ways.
First, we will work with Kativik Civil Security (KCS), the Nunavik EMO, to develop a rigorous process for the collection, analysis and reporting of SAR data. Those data will allow KCS to make evidence-based policy decisions to better support SAR in Nunavik and enable us to develop the NNSAR model into one with broad applicability across diverse SAR environments.

Second, we aim to extend the reach of our impact to Scotland. As in Nunavik, Scottish mountain rescue relies on a committed group of volunteers operating in a challenging environment. The two SAR systems share many features, notably growing caseloads that are increasing the strain on responders and the system as a whole. The data available in Scotland are much more detailed than in Nunavik but are currently underutilised. We will form a new partnership with Mountaineering Scotland to:
1. Apply the NNSAR model to existing Scottish mountain rescue data 鈥� this can both improve the model and provide useful insights for Scotland, which will translate back to Canada; and

2. Apply learning from the novel Nunavik SAR data collection process to enhance data collection within Scotland.

The outcomes of this project will include enhanced SAR in Nunavik and Scotland, stronger relationships with external partners, and the construction of a risk model with wide application to emergency management operations across the world.

02-Jan-2025 - 31-Jan-2025

El Raoui, Hanane (Principal Investigator) Belton, Ian (Co-investigator) Elawady, Mohamed (Co-investigator) Nguyen, Le Khanh Ngan (Co-investigator) Thompson, Nathan (Co-investigator)

01-Jan-2023 - 31-Jan-2024

Belton, Ian (Co-investigator)

01-Jan-2023 - 31-Jan-2028

Belton, Ian (Co-investigator) Bolger, Fergus (Principal Investigator) Crawford, Megan Michelle (Co-investigator) Hamlin, Iain (Co-investigator) MacDonald, Alice (Co-investigator) Rowe, Gene (Principal Investigator) Sissons, Aileen (Co-investigator) Taylor Browne L奴ka, Courtney (Co-investigator) Vasilichi, Alexandrina (Co-investigator) Wright, George (Principal Investigator)

BARD was a 23-month project funded by the US Government Intelligence Advanced Research Projects Activity (IARPA) and formed part of the larger Crowdsourcing Evidence, Argumentation, Thinking and Evaluation 鈥� 鈥淐REATE鈥� 鈥� program. In BARD, we designed and produced Graphical User Interfaces (GUIs) to assist in the construction of Causal Bayesian Networks (CBNs) as the underlying engines for the analysis of arguments and evidence. BARD thus allows analysts to build and test competing or complementary arguments, and to examine the impact of different pieces of evidence, in an intuitive environment. BARD makes use of the Delphi technique 鈥� an iterative survey method that minimizes negative effects of cognitive and social biases 鈥� to manage the interaction between users.

In addition to the Delphi Team based in 欧美高清, BARD also consisted of teams based in London (UCL and Birkbeck) 鈥� who are experts on the psychology of causal reasoning 鈥� and in Melbourne, Australia (Monash University) 鈥� who are expert in CBNs and software engineering.

IARPA - https://www.iarpa.gov/
CREATE - https://www.iarpa.gov/index.php/research-programs/create

01-Jan-2017 - 30-Jan-2018