Views on AI aren't binary -- they're plural

The "AI Ethics vs. AI Safety" divide is a false binary. The paper argues that framing responsible AI work as two opposing camps misrepresents how the field actually operates. In reality, these communities have overlapping concerns and goals rather than fundamental opposition.

AI discourse is more complex and plural than a simple two-sided debate. Rather than people falling neatly into "ethics" or "safety" camps, the paper demonstrates that views on AI responsibility exist on a spectrum with multiple dimensions, making any binary framework inaccurate and oversimplified.

Framing disagreements as "us vs. them" is counterproductive. The paper warns that treating different approaches to responsible AI as opposing sides can create unnecessary conflict within the community of people trying to develop and govern AI responsibly, potentially undermining collaborative progress.

The lessons extend beyond ethics and safety debates. The paper notes that the same false binary problem appears in other AI tensions, such as between "accelerationist" perspectives (favoring rapid AI development) and more cautious stances, suggesting this is a broader pattern in how AI discourse gets framed.

Individuals can actively help bridge divides in AI governance. The paper provides concrete suggestions for how people working on AI can avoid contributing to polarization and instead foster more nuanced, collaborative approaches to responsible AI development.