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Why Pandemics and Climate Change Are Hard to Understand and Make Decision-Making Difficult
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Raymond Bond ,
Ana Caraban
Interacting with Computers
Swansea University Author:
Alan Dix
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© The Author(s) 2023. Published by Oxford University Press on behalf of The British Computer Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
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DOI (Published version): 10.1093/iwc/iwad043
Abstract
This paper draws on diverse psychological, behavioural and numerical literature to understand some of the challenges we all face in making sense of large-scale phenomena and use this to create a roadmap for HCI responses. This body of knowledge offers tools and principles that can help HCI researche...
| Published in: | Interacting with Computers |
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| ISSN: | 0953-5438 1873-7951 |
| Published: |
Oxford University Press (OUP)
2023
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa63274 |
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| Abstract: |
This paper draws on diverse psychological, behavioural and numerical literature to understand some of the challenges we all face in making sense of large-scale phenomena and use this to create a roadmap for HCI responses. This body of knowledge offers tools and principles that can help HCI researchers deliver value now, but also highlights challenges for future HCI research. The paper is framed by looking at patterns and information that highlight some of the common misunderstandings that arise – not just for politicians and the general public but also for many in the academic community. This paper does not have all the answers to this, but we hope it provides some and, perhaps more importantly, raises questions that we need to address as scientific and technical communities. |
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| Keywords: |
Decision making, covid, HCI, statistics, numerosity, data, cognitive bias, numeracy |
| College: |
Faculty of Science and Engineering |
| Funders: |
This research was (partly funded) by the UKRI EPSRC Not-Equal Network+, Social Justice through the Digital Economy, EP/R044929/1. |