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How do we embed values throughout AI workflows?

AI corporate-ethics

Issue: Values-based design

## BackgroundEthics are often treated as an impediment to innovation, even among those who ostensibly support ethical design practices. In industries that reward rapid innovation in particular, it is necessary to develop ethical design practices that integrate effectively with existing engineering workflows. Those who advocate for ethical design within a company should be seen as innovators seeking the best outcomes for the company, end users, and society. Leaders can facilitate that mindset by promoting an organizational structure that supports the integration of dialogue about ethics throughout product life cycles.A/IS design processes often present moments where ethical consequences can be highlighted. There are no universally prescribed models for this because organizations vary significantly in structure and culture. In some organizations, design team meetings may be brief and informal. In others, the meetings may be lengthy and structured. The transition points between discovery, prototyping, release, and revisions are natural contexts for conducting such reviews. Iterative review processes are also advisable, in part because changes to risk profiles over time Companies should study design processes to identify situations where engineers and researchers can be encouraged to raise and resolve questions of ethics and foster a proactive environment to realize ethically aligned design. Achieving a distributed responsibility for ethics requires that all people involved in product design are encouraged to notice and respond to ethical concerns. Organizations should consider how they can best encourage and facilitate deliberations among peers.

## RecommendationsOrganizations should identify points for formal review during product development. These reviews can focus on “red flags” that have been identified in advance as indicators of risk. For example, if the datasets involve minors or focus on users from protected classes, then it may require additional justification or alterations to the research or development protocols.can illustrate needs or opportunities for improving the final product.

## Further Resources

Overarching Principles Merit and Integrity
Principles Merit and Integrity
Sources IEEE
Title How do we embed values throughout AI workflows?