Three frameworks while suggesting clients:
- Responsible data practices
- What is the source of the training data?
- What has been done to reduce bias in the data?
- How might the data we're using perpetuate historic bias?
- What opportunities exist to prevent biased decision-making?
- Boundaries on safe and appropriate use and
- Who is the target population for this tool?
- What are their main goals and incentives?
- What is the most responsible way to achieve these goals?
- Robust transparency
- How did the tool arrive at its output?
- What other ways do we have of testing fairness?
- Can decision makers easily understand the input-analysis-output process?
- Have you engaged with a broad range of stakeholders?
Ethical data organization can be divided into three parts:
- Prioritizing privacy
- Conduct a privacy audit
- During a privacy audit, you build a comprehensive understanding of:
- what data your organization has,
- how it was collected,
- how it's stored, and
- how it's administered.
- Create a training curriculum for employees.
- Reducing bias and
- Who are the end users
- Is the input data set diverse enough?
- Consult who interpreted the data
- Promoting transparency
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