On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services
It addresses practical implementation issues for AI developers in financial services, but is incremental as it surveys existing problems without proposing new solutions.
The paper surveys the practical challenges in developing fair and ethical AI solutions in financial services, highlighting gaps between high-level principles and deployed applications to foster industry-wide discussions.
Artificial intelligence (AI) continues to find more numerous and more critical applications in the financial services industry, giving rise to fair and ethical AI as an industry-wide objective. While many ethical principles and guidelines have been published in recent years, they fall short of addressing the serious challenges that model developers face when building ethical AI solutions. We survey the practical and overarching issues surrounding model development, from design and implementation complexities, to the shortage of tools, and the lack of organizational constructs. We show how practical considerations reveal the gaps between high-level principles and concrete, deployed AI applications, with the aim of starting industry-wide conversations toward solution approaches.