Extending AI governance to competition and energy policy.

Global AI frameworks need to reflect global principles and standards for the responsible and ethical use of AI technology, while also taking into account the unique needs and challenges of different regions. In this policy brief we argue that the  African experience offers a valuable case study for understanding how local contexts can inform and influence the development of global AI governance frameworks. 

We are already witnessing anti-competitive behaviour by so-called big tech companies, particularly on the African continent. These companies are using their competitive advantage to squeeze out competition and hold the market share. 

Beyond this, there are important ethical considerations around the development and use of data-driven AI technologies, which inherit and reinforce the biases that exist in the data. This can and already does lead to discriminatory outcomes and economic exclusion for marginalised groups.

There are also concerns about the high energy demands on AI systems. To effectively deploy these technologies, African countries need more energy capacity than they are currently producing. A key consideration is how AI can support  Africa’s transition to a sustainable low-carbon economy, away from fossil fuels.  

Key recommendations in this report include:

  • AI frameworks should prioritise inclusion in AI development and establish measures to detect and mitigate anti-competitive practices. This involves clear antitrust laws and enforcement mechanisms to prevent AI companies from engaging in monopolistic behaviour. 
  • Lowering barriers to entry for new AI players and ensuring that smaller companies have access to the necessary data to compete.
  • AI frameworks should also require diverse and representative datasets, regular fairness audits, and mitigation strategies.
  • AI governance should include energy policies that align effectively with Africa’s decarbonisation efforts to cater for the insufficient power supplies in the continent.
  • Prioritise cost-effective, socially and gender-inclusive, sustainable AI and renewable energy provision in Africa.

Adopting governing priorities like these can help create sustainable, economically sound policies that work for the most vulnerable. Using the African perspective as a case study can serve as a valuable example of how localised regulations can inform and influence the development of global AI governance frameworks. 

Only by adopting a nuanced and context-specific approach can we ensure that AI is developed and deployed in a way that benefits everyone, including the most vulnerable, rather than exacerbating existing inequalities and divisions.