Our Process for Ethical AI
Governance by Design
At Sonder Scheme, we have designed a broad yet comprehensive AI governance process:
- Stage 1: Learn and set scope
- Stage 2: Ethical AI design standards
- Stage 3: AI project risk assessment
- Stage 4: Implementation
In the first stage, we help level set; educating and training everyone. We define current company values in an AI- relevant way help teams set accountabilities at the right level in the company.
The second stage is setting ethical design standards that will guide development. Design standards include:
- User need, why AI?
- Data collection
- Optimizing algorithms
- Fairness
- Mental model design
- Explainability and transparency
- Trust, context and intent
- Feedback and control
- Error testing and design for failure
The third stage is to assess risk. With more than 140 criteria across 9 risk categories, our risk screen runs vertically from high-level decisions to the details of AI development.
- Management
- Team
- Design
- Data, Analysis, Build, Operate
- Explainability
- Fairness and Inclusion
- Safety
- Compliance & Competition
- Accountability
- Safety
We’ve wrapped this up into a flexible and customizable tool for evaluating AI risks and setting key aspects of governance review such as standards and thresholds.
The fourth phase concerns learning: both of humans and machines. Our implementation stage embeds AI governance design across the organization.
- Risk (re)assessment process
- Data management, archiving &
- traceability
- Exception management
- Dashboard and reporting
- Failure and crisis management
- Learning cycle review
As AI diffuses through our entire economy and across all societies, there are few areas of corporate governance that are more important than governance for AI.
