The organization’s mission and relevant goals for the AI technology are understood.
About
Socio-technical AI risks emerge from the interplay between technical development decisions and how a system is used, who operates it, and the social context into which it is deployed. Addressing these risks is complex and requires a commitment to understanding how contextual factors may interact with AI lifecycle actions. One such contextual factor is how organizational mission and identified system purpose create incentives within AI system design, development, and deployment tasks that may result in positive and negative impacts. By establishing comprehensive and explicit enumeration of AI system purpose and expectations, organizations can identify and manage these types of risks and benefits.
Actions
Reconcile documented concerns about system context of use or purpose against the organization’s stated values, mission statements, social responsibility commitments, and AI principles.
Reconsider the design, implementation strategy, or deployment of AI systems with potential impacts that do not reflect institutional values.
Transparency and Documentation
Organizations can document the following:
What goals and objectives does the entity expect to achieve by designing, developing, and/or deploying the AI system?
To what extent are the model outputs consistent with the entity’s values and principles to foster public trust and equity?
To what extent are the metrics consistent with system goals, objectives, and constraints, including ethical and compliance considerations?
