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Spinoza: Building an AI Ethics Framework From First Principles

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

..

  1. Many AI ethics approaches are academic – these sound great in theory but are hard to implement
  2. 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
  3. 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

  1. Identify existing infrastructure that a data and AI ethics program can leverage.
  2. Create a data and AI ethical risk framework that is tailored to your industry
  3. Change how you think about ethics by taking cues from the successes in health care.
  4. Optimize guidance and tools for product managers.
  5. Build organizational awareness.
  6. Formally and informally incentivize employees to play a role in identifying AI ethical risks.
  7. 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

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Tags: dsc_ai, dsc_ethics

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