Reinforcing data bias in crisis information management: The case of the Yemen humanitarian response

Paulus, David; Vries, G. de; Janssen, Marijn; Walle, Bartel Van de

doi:10.1016/j.ijinfomgt.2023.102663

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2024

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Cited by 7 publications

References 41 publications

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Examining Infrastructure Pipelines Information for Their Relevance in Construction Organizations’ Strategic Decision-Making

Moshood,

Rotimi,

Shahzad

2024

Lecture Notes in Civil Engineering

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Examining Infrastructure Pipelines Information for Their Relevance in Construction Organizations’ Strategic Decision-Making

Moshood,

Rotimi,

Shahzad

2024

Lecture Notes in Civil Engineering

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AI for crisis decisions

Comes

2024

Ethics Inf Technol

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Increasingly, our cities are confronted with crises. Fuelled by climate change and a loss of biodiversity, increasing inequalities and fragmentation, challenges range from social unrest and outbursts of violence to heatwaves, torrential rainfall, or epidemics. As crises require rapid interventions that overwhelm human decision-making capacity, AI has been portrayed as a potential avenue to support or even automate decision-making. In this paper, I analyse the specific challenges of AI in urban crisis management as an example and test case for many super wicked decision problems. These super wicked problems are characterised by a coincidence of great complexity and urgency. I will argue that from this combination, specific challenges arise that are only partially covered in the current guidelines and standards around trustworthy or human-centered AI. By following a decision-centric perspective, I argue that to solve urgent crisis problems, the context, capacities, and networks need to be addressed. AI for crisis response needs to follow dedicated design principles that ensure (i) human control in complex social networks, where many humans interact with AI; (ii) principled design that considers core principles of crisis response such as solidarity and humanity; (iii) designing for the most vulnerable. As such this paper is meant to inspire researchers, AI developers and practitioners in the space of AI for (urban) crisis response – and other urgent and complex problems that urban planners are confronted with.

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Precision epidemiology at the nexus of mathematics and nanotechnology: Unraveling the dance of viral dynamics

Aljabali,

Obeid,

El-Tanani

et al. 2024

Gene

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Reinforcing data bias in crisis information management: The case of the Yemen humanitarian response

Cited by 7 publications

References 41 publications

Examining Infrastructure Pipelines Information for Their Relevance in Construction Organizations’ Strategic Decision-Making

Examining Infrastructure Pipelines Information for Their Relevance in Construction Organizations’ Strategic Decision-Making

AI for crisis decisions

Precision epidemiology at the nexus of mathematics and nanotechnology: Unraveling the dance of viral dynamics

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