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Sacrificing Innovation in Artificial Intelligence on the Altar of Regulation: Nigeria as a Case Study

Authors: Joel Odili; Oreoluwa Onafowokan; Adeyemi Adefidipe;

Sacrificing Innovation in Artificial Intelligence on the Altar of Regulation: Nigeria as a Case Study

Abstract

The introduction of Artificial Intelligence (AI) was welcomed by state and non-state actors because of the possibilities that could be actualised with the use of this ‘new system’. Just like the internet, the introduction of AI to the global landscape was not intended to be used to perpetrate ills or to violate the rights of persons. However, scars left from the unscrupulous use of technological innovations have raised fears from various quarters that this new system may fall into the wrong hands, causing greater evil than the intended good. These fears, though legitimate, have formed the basis for the formulation of restrictive regulations which in turn have hampered innovation in AI. To this end, this paper sets out to argue in favour of the innovations that can be developed from AI systems and the need for this system to be given full expression before the lawmakers can step in to formulate laws geared towards curtailing the potential mischief that may characterise the use of AI systems, rather than addressing merely perceived issues.

Keywords

Algorithm, Artificial Intelligence, Innovation

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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