Spinoza’s ethics was the first attempt to apply Euclidean thinking to philosophy to create a system of ethics from first principles.
Could we apply the same first principles thinking to formulating AI ethics?
Last week, I spoke at an online event for legal professionals about AI Ethics. AI ethics is a very important topic but it is also a subject like Privacy i.e. there is a lot of heat but little light. By that I mean, everyone has a view on AI ethics but there are very few pragmatic approaches on AI ethics.
So, I was trying to present a set of pragmatic ideas for AI ethics.
I proposed that every organization should create its own AI ethics framework from first principles because
..
- Many AI ethics approaches are academic – these sound great in theory but are hard to implement
- Many companies internally take the opposite approach try to define ethics only on the problems they currently have but could ignore ethics problems that may arise downstream
- There are AI ethics approaches from countries and large vendors but they cannot be applied as-is
Hence, the suggestion that every company could create its own AI ethics by adapting an existing framework to their needs and undertaking a first-principles approach for their organization
Firstly, you could start with a general ethics framework for example by the Alan Turing Institute which provide the principles and priorities for a legal framework
- Human dignity
- Human freedom & autonomy
- Prevention of harm
- Non-discrimination, gender equality, fairness & diversity
- Data protection and the right to privacy
- Accountability and responsibility
- Democracy
- Rule of law
This represents a top-down approach
Now, the HBR document How to create an AI ethics framework suggests a bottom-up approach based on the following steps
- Identify existing infrastructure that a data and AI ethics program can leverage.
- Create a data and AI ethical risk framework that is tailored to your industry
- Change how you think about ethics by taking cues from the successes in health care.
- Optimize guidance and tools for product managers.
- Build organizational awareness.
- Formally and informally incentivize employees to play a role in identifying AI ethical risks.
- Monitor impacts and engage stakeholders.
Hence, it may be not so difficult to create an AI ethics framework tailored to your organization from first principles by taking both a top-down and bottom-up approach – much like Spinoza.
Image source: wikipedia
