Strategies for Designing Responsibly within a Capitalist Enterprise

The "ethics vs. business" framing is counterproductive: The paper argues that responsible AI research often treats ethics and business as opposing forces, but this dichotomy prevents practical implementation. Instead, the authors advocate for an "ethics and business" approach that recognizes enterprises must create value to survive and operate at scale.

Current responsible AI research has limited real-world adoption: Despite advances in HCI and responsible AI research, industry implementation remains minimal, suggesting that academic contributions may not adequately account for how companies actually operate and make decisions.

Ideation is proposed as a practical bridge strategy: The paper identifies ideation—the process of generating multiple design alternatives—as a concrete method for creating solutions that satisfy both ethical requirements and business objectives, making responsible AI more feasible to implement.

Responsible design requires understanding capitalist enterprise constraints: To achieve meaningful impact, responsible AI researchers need to design with full awareness of how capitalist enterprises function, including their need for profitability and value creation, rather than treating these as obstacles to ethics.

Expanding the "space of responsible design" requires alignment with business realities: By reframing responsible AI to work within (rather than against) enterprise economics, the authors argue we can actually increase the amount of ethically sound AI that gets built and deployed in practice.