The authors of this paper explore the current integration of AI Ethics in AI-based monitoring tools & systems for wildlife conservation in South Africa. A framework that guides stakeholders on the implementation of AI ethics in Wildlife monitoring AI systems is designed and proposed to help minimize AI ethical concerns in data, algorithms, legal aspects and human-AI interactions.
Title: Integrating AI ethics in wildlife conservation AI systems in South Africa: a review, challenges, and future research agenda.
Authors: Irene Nandutu, Marcellin Atemkeng, Patrice Okouma
Journal: AI & Society: Journal of Knowledge, Culture and Communication
Citation: Nandutu, I., Atemkeng, M. & Okouma, P. Integrating AI ethics in wildlife conservation AI systems in South Africa: a review, challenges, and future research agenda. AI & Soc (2021). https://doi.org/10.1007/s00146-021-01285-y
Open Access: No (Credentials required)
With the increased use of Artifcial Intelligence (AI) in wildlife conservation, issues around whether AI-based monitoring tools in wildlife conservation comply with standards regarding AI Ethics are on the rise. This review aims to summarise current debates and identify gaps as well as suggest future research by investigating (1) current AI Ethics and AI Ethics issues in wildlife conservation, (2) Initiatives Stakeholders in AI for wildlife conservation should consider integrating AI Ethics in wildlife conservation. We fnd that the existing literature weakly focuses on AI Ethics and AI Ethics in wildlife conservation while at the same time ignores AI Ethics integration in AI systems for wildlife conservation. This paper formulates an ethically aligned AI system framework and discusses pre-eminent on-demand AI systems in wildlife conservation. The proposed framework uses agile software life cycle methodology to implement guidelines towards the ethical upgrade of any existing AI system or the development of any new ethically aligned AI system. The guidelines enforce, among others, the minimisation of intentional harm and bias, diversity in data collection, design compliance, auditing of all activities in the framework and ease of code inspection. This framework will inform AI developers, users, conservationists, and policymakers on what to consider when integrating AI Ethics into AI-based systems for wildlife conservation.
Keywords : Wildlife conservation concerns, Human–wildlife conficts, AI Ethics , AI in wildlife conservation, AI Ethics integration, Artifcial intelligence
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