Multi-AI Complex Systems in Humanitarian Response

TL;DR

This paper explores the emergence and challenges of multi-AI systems in humanitarian response, emphasizing the need for better understanding, assessment, and trustworthiness of interconnected AI decision-making entities.

Contribution

It introduces the concept of multi-AI complex systems in humanitarian response, highlighting their potential behaviors and proposing initial considerations for their assessment and management.

Findings

Multi-AI systems can arise even in simple humanitarian scenarios.

Such systems may exhibit emergent and erratic behaviors.

Understanding and designing for trustworthiness is crucial.

Abstract

AI is being increasingly used to aid response efforts to humanitarian emergencies at multiple levels of decision-making. Such AI systems are generally understood to be stand-alone tools for decision support, with ethical assessments, guidelines and frameworks applied to them through this lens. However, as the prevalence of AI increases in this domain, such systems will begin to encounter each other through information flow networks created by interacting decision-making entities, leading to multi-AI complex systems which are often ill understood. In this paper we describe how these multi-AI systems can arise, even in relatively simple real-world humanitarian response scenarios, and lead to potentially emergent and erratic erroneous behavior. We discuss how we can better work towards more trustworthy multi-AI systems by exploring some of the associated challenges and opportunities, and how we can design better mechanisms to understand and assess such systems. This paper is designed to be a first exposition on this topic in the field of humanitarian response, raising awareness, exploring the possible landscape of this domain, and providing a starting point for future work within the wider community.