Responsible artificial intelligence in Africa: Towards policy learning

Paul Plantinga, Kristophina Shilongo, Oarabile Mudongo, Angelique Umubyeyi, Michael Gastrow and Gabriella Razzano

No jyhae, SocArXiv from Center for Open Science

Abstract: Several African countries are developing artificial intelligence (AI) strategies and ethics frameworks with the goal of accelerating responsible AI development and adoption. However, many of these governance actions are emerging without consideration for their suitability to local contexts, including whether the proposed policies are feasible to implement and what their impact may be on regulatory outcomes. In response, we suggest that there is a need for more explicit policy learning, by looking at existing governance capabilities and experiences related to algorithms, automation, data and digital technology in other countries and in adjacent sectors. From such learning it will be possible to identify where existing capabilities may be adapted or strengthened to address current AI-related opportunities and risks. This paper explores the potential for learning by analysing existing policy and legislation in twelve African countries across three main areas: strategy and multi-stakeholder engagement, human dignity and autonomy, and sector-specific governance. The findings point to a variety of existing capabilities that could be relevant to responsible AI; from existing model management procedures used in banking and air quality assessment, to efforts aimed at enhancing public sector skills and transparency around public-private partnerships, and the way in which existing electronic transactions legislation addresses accountability and human oversight. All of these point to the benefit of wider engagement on how existing governance mechanisms are working, and on where AI-specific adjustments or new instruments may be needed.

Date: 2023-09-26
New Economics Papers: this item is included in nep-afr, nep-ain, nep-cmp and nep-ict
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:jyhae

DOI: 10.31219/osf.io/jyhae

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