Skip to content

Main Insight

Between May and August 2021, The Future Society collaborated with the bank Société Générale, its 16 branches in Africa, and the civic tech Bluenove to up-skill Société Générale employees’ understanding about the risks and benefits linked to the adoption of AI in the banking sector. The three workshops organised throughout the summer cumulated in the

Leveraging Responsible AI in the Banking Sector in Africa 

October 21, 2021

In 2021, The Future Society collaborated with Bluenove, Société Générale, and its 16 branches in Africa (Algeria, Benin, Equatorial Guinea, Congo, Cameroon, Ivory Coast, Ghana, Guinea Conakry, Mauritania, Morocco, Madagascar, Mozambique, Senegal, Tchad, Togo and Tunisia) to train local collaborators about the opportunities and risks linked to the adoption of AI, especially in the banking sector.

We organized a series of three workshops to raise employees’ awareness, and debate trade-offs across specific use cases: 

  • The first workshop introduced local collaborators to the concept of responsible AI, and to existing corporate guidelines. Kenyan researcher Kathleen Siminyu, from the Mozilla Foundation, notably highlighted the possibility of using natural language processing tools to translate local dialects, and thus increase financial literacy and inclusion in the region. 

 

  • The second workshop focused on the ethical challenges raised by the use of algorithmic prediction for credit lending. Shameek Kundu, Head of Financial Services and Chief Strategy Officer at Truera, notably highlighted six benefits to deploying machine learning in the banking sector: 1) More effective risk management, 2) Operational efficiency through greater automation, 3) Better customer experience, 4) Higher top-line from existing businesses, 5) New business models, 6) Better internal decision-making. 

 

  • The third workshop analyzed the potential impact of facial recognition technologies (FRT) in the banking sector. Lofred Madzou, AI Lead at the World Economic Forum, emphasised the risks of fraud and identity theft when deploying FRT without safeguards.

The insights gathered during these fruitful conversations cumulated in the production of a manifesto for the responsible adoption of AI and data in the banking sector, which should be soon publicly released. 

Related resources

Heavy is the Head that Wears the Crown

Heavy is the Head that Wears the Crown

In this blueprint, we explain why a tiered approach makes sense in the EU AI Act and how to build a risk-based tiered regulatory regime for GPAI – the technicalities involved, which requirements should be imposed on their corresponding tiers, and how to enforce them.

Giving Agency to the AI Act

Giving Agency to the AI Act

Earlier this year, we conducted research comparing different institutional models for an EU-level body to oversee the implementation and enforcement of the AI Act. We're pleased to share our memo: Giving Agency to the AI Act.

Response to NIST Generative AI Public Working Group Request for Resources

Response to NIST Generative AI Public Working Group Request for Resources

TFS submitted a list of clauses to govern the development of general-purpose AI systems (GPAIS) to the U.S. NIST Generative AI Public Working Group (NIST GAI-PWG).

Response to U.S. OSTP Request for Information on National Priorities for AI

Response to U.S. OSTP Request for Information on National Priorities for AI

Our response put forward national priorities focused on security standards, measurement and evaluation frameworks, and an industry-wide code of conduct for GPAIS development.

Strengthening the AI operating environment

Strengthening the AI operating environment

In a paper published at the International Workshop on Artificial Intelligence and Intelligent Assistance for Legal Professionals in the Digital Workplace (Legal AIIA), Dr. Bruce Hedin and Samuel Curtis present an argument for distributed competence as a means to mitigate risks posed by AI systems.

Response to U.S. NTIA AI Accountability Policy Request for Comment

Response to U.S. NTIA AI Accountability Policy Request for Comment

Our response emphasized the need for scrutiny in the design and development of general-purpose AI systems (GPAIS). We encourage the implementation of third-party assessments and audits, contestability tools for impacted persons, and a horizontal regulatory approach toward GPAIS.