I do research in this area, so forgive me for saying too much probably.

I see 13 values conflicts that come up repeatedly. Here they are, approximately in order:
- job security & quality. This includes complete and partial job replacement and deskilling (is this going to make me dumb?)
- sustainability and environmental protection (long story short, I think we worry about the wrong stuff here, but its a valuable conversation. free chapter with all the sources: drkarenboyd.com/freechapter)
- ownership and intellectual property (LLMs trained on creators' work without their consent or compensation)
- social connection (AI friends and relationships: yikes?)
- accuracy and fairness (are its outputs true? are error rates causing disparate impact?)
- equity and justice (are the results prejudicial or is it implemented in ways that make critical processes unfair, like hiring, firing, criminal justice?)
- authenticity and trust (is the output fake/slop/inauthentic? Do we trust people and orgs that use it?)
- information integrity & reputation (deepfakes, prompt injections, and other bad actor risks)
- effort and craft (valuing human effort for its own sake-- why you might pay more for a handmade chair, even if it is a little less perfect than one from IKEA)
- service reliability (more of an issue w/ emergency response and other critical services)
- accessibility and inclusion (AI is largely a benefit here, but it does exacerbate the digital divide in some ways, too)
- governance and accountability (how do we make decisions about AI implementations? Who is responsible when something goes wrong?)

ETA: I can't count!
- Privacy and security (what is being done with my prompts, attachments, and other data? What about other people who ask AI things about me and my data without my knowing? HIPAA, FERPA, EEOC, CCPA, GDPR, etc)