|June 26th, 2017|
|giving, airisk [html]|
What I'm planning to spend the next few days on is getting a better understanding of where this difference comes from. I think I'm in a good position to do this: I'm close to both groups, have some technical background as a programmer, and have some time. I see two ways this could go:
If after looking into it more I still think AI risk is not a valuable place to be working, I may be able to convince others of this. Since 80000 Hours and other EAs are currently suggesting a lot of people go into this field, if it turns out we're overvaluing it then those people could work on other things.
If I change my mind and start thinking AI risk is something we should be working on, I may convince some of my friends in machine learning. It's also likely that something in this direction would be close enough to my skills to be a good career fit and I should consider working on it.
Rough plan: read a bunch of stuff to get background, talk to a lot of people, write things up. Things I'm planning to read:
- 80000 Hours' Artificial intelligence and the 'control problem'
- WaitButWhy's The AI Revolution: The Road to Superintelligence
- Nick Bostrom's Superintelligence
- Dario Amodei and others' Concrete Problems in AI Safety
- Eliezer Yudkowsky's AI Alignment: Why It's Hard, and Where to Start
- Paul Christiano's Three impacts of machine intelligence and Technical and social approaches to AI safety [EDIT: also Prosaic AI alignment]
- Scott Alexander's AI Researchers on AI Risk and No Time Like the Present for AI Safety Work
- EDIT: also Holden Karnofsky's Some Background on Our Views Regarding Advanced Artificial Intelligence and Potential Risks from Advanced Artificial Intelligence: The Philanthropic Opportunity
- EDIT: also Luke Muehlhauser's What Do We Know about AI Timelines? and Replies to people who argue against worrying about long-term AI safety risks today
- EDIT: also Kaj Sotala and Roman Yampolskiy's Responses to catastrophic AGI risk: a survey
- EDIT: also Dario Amodei and others' Learning from Human Preferences
- EDIT: also Brian Tomasik's Artificial Intelligence and Its Implications for Future Suffering
- Maybe some of 80000 Hours' AI safety syllabus as it looks relevant.
- Maciej Ceglowski's Superintelligence: The Idea That Eats Smart People
- EDIT: also Ernest Davis' Ethical Guidelines for A Superintelligence
The list above is entirely people who think AI risk should be prioritized, aside from the Ceglowski post at the end, so I'm especially interested to read (if they exist) pieces where machine learning experts talk about why they don't think AI risk is a high priority. I'm also interested in other general AI risk background reading, and suggestions of people to talk to.