Beyond the promise: implementing ethical AI
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OPINION PAPER
Beyond the promise: implementing ethical AI Ray Eitel‑Porter1 Received: 31 August 2020 / Revised: 31 August 2020 / Accepted: 3 September 2020 © The Author(s) 2020
Abstract Artificial Intelligence (AI) applications can and do have unintended negative consequences for businesses if not implemented with care. Specifically, faulty or biased AI applications risk compliance and governance breaches and damage to the corporate brand. These issues commonly arise from a number of pitfalls associated with AI development, which include rushed development, a lack of technical understanding, and improper quality assurance, among other factors. To mitigate these risks, a growing number of organisations are working on ethical AI principles and frameworks. However, ethical AI principles alone are not sufficient for ensuring responsible AI use in enterprises. Businesses also require strong, mandated governance controls including tools for managing processes and creating associated audit trails to enforce their principles. Businesses that implement strong governance frameworks, overseen by an ethics board and strengthened with appropriate training, will reduce the risks associated with AI. When applied to AI modelling, the governance will also make it easier for businesses to bring their AI deployments to scale. Keywords AI · Ethics · Responsible AI · Ethical AI · AI principles · Data governance
1 Introduction Ethical AI, also known as responsible AI, is the practice of using AI with good intention to empower employees and businesses, and fairly impact customers and society. Responsible AI enables companies to engender trust and scale AI with confidence. Around the world, a growing number of organisations are working on ethical AI principles and frameworks. These include academia-led programmes, such as The Institute for Ethical AI and Machine Learning, trade union-led schemes, such as UNI Global Union, and business-led initiatives, such as Microsoft’s responsible AI guidelines [1–3]. These and other such initiatives reflect a growing acknowledgement that AI applications can and do have unintended negative consequences if not implemented carefully. More broadly, ethical AI is part of a wider responsible business agenda, whereby organisations are increasingly prioritising good governance and a respect for the societal and environmental concerns of customers [4]. * Ray Eitel‑Porter ray.eitel‑[email protected] 1
Although ethical principles are a necessary precondition for responsible AI, they are not sufficient. Ethical standards only have value when put into practice. In this paper, I argue that responsible AI also requires strong, mandated governance controls including tools for managing processes and creating associated audit trails. I also argue that good governance helps businesses scale their AI tools and extract full value from their AI applications and services. For the purposes of this paper, I focus solely on the trust, fairness, and privacy elements of AI deployments. Although related, this paper does
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