Ethical AI: Principles versus practice
In recent years numerous companies, governments, NGOs and academic institutions have developed and publicised their AI ethics principles.
Whilst there may be a developing (Western) global consensus on ethical AI, there remains a significant implementation and accountability gap between aspirational principles and practice. At present, the operationalization of ethics principles in AI product development and deployment remains largely unaccounted for (both legally and professionally).
Consequently, there have several examples of corporations acting in direct contradiction of their own ethics principles.
The AI NOW institute’s 2019 report details the following two examples:
These examples, amongst others, demonstrate that while there continues to be a lack of legal accountability concerning a corporation’s violation of their own ethics principles, the most effective vehicle for change occurs when there is public pressure from workers, journalists, and policymakers to ensure ethical AI. For example, while Facebook publicises its own internal ethics process, the various controversies the company has recently faced demonstrate that public pressure and organized workers appear to be far better at ensuring ethical AI than the company’s principles are. Whilst the articulation of ethical principles is valuable, they cannot guarantee ethical AI.
There is much work to be done, globally, in order to realise the operationalization of ethics principles in AI product design, development and deployment.
AI Now 2019 Report. New York: AI Now Institute, 2019, https://ainowinstitute.org/AI_Now_2019_Report.html