A good starting point for sharing ethical values across organisations is to subscribe to a code of conduct. You can create one specific for your situation, or you can refer to a general governance framework.
General governance frameworks that you may want to refer to include:
- Google Responsible AI
- Microsoft AI principles
- European Commission High-Level Expert Group - Ethical guidelines for trustworthy AI
These frameworks set high-level objectives for concerns such as security, privacy, and fairness. They can be complemented or refined for your specific situation.
Defining or subscribing to a code of conduct helps to build trust with users and enhances the auditability of your development process and your applications.
The values set by a code of conduct can be refined into a set of concrete governance objectives. The governance objectives appropriate for a given machine learning application depend on factors such as:
- the type of data being processed: for example, when personal information is processed, privacy objectives are relevant
- the usage context: for example, when used for autonomous driving, safety objectives are relevant
- the organisational context: for example, a government agency may require usage of open data and non-proprietary machine learning algorithms
- Decide Trade-Offs through Defined Team Process
- Have Your Application Audited
- Employ Interpretable Models When Possible
- Ethics Guidelines for Trustworthy AI
- Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims