  One objection to conventional AI ethics is that it slows innovation. This
presentation responds by reconfiguring ethics as an innovation accelerator. The
critical elements develop from a contrast between Stability AI's Diffusion and
OpenAI's Dall-E. By analyzing the divergent values underlying their opposed
strategies for development and deployment, five conceptions are identified as
common to acceleration ethics. Uncertainty is understood as positive and
encouraging, rather than discouraging. Innovation is conceived as intrinsically
valuable, instead of worthwhile only as mediated by social effects. AI problems
are solved by more AI, not less. Permissions and restrictions governing AI
emerge from a decentralized process, instead of a unified authority. The work
of ethics is embedded in AI development and application, instead of functioning
from outside. Together, these attitudes and practices remake ethics as
provoking rather than restraining artificial intelligence.
