Apart from they both need a fair amount of computer science to predict their capabilities and dangers?
I recently shifted to believing that pure mathematics is more relevant for FAI than computer science.
Call your research institute something like the Institute for the prevention of Advanced Computational Threats, and have separate divisions for robotics and FAI. Gain the trust of the average scientist/technology aware person by doing a good job on robotics and they are more likely to trust you when it comes to FAI.
In FAI, the central question is what a program wants (which is a certain kind of question about what the program means), and not what a program does.
Computer science will tell lots about what which programs can do how, and how to construct a program that does what you need, but less about what a program means (the sort of computer science that does is already a fair distance towards mathematics). This is also a problem with statistics/machine learning, and the reason they are not particularly useful for FAI: they teach certain tools, and how these tools work, but understanding they provide isn’t portable enough.
Mathematical logic, on the other hand, contains lots of wisdom in the right direction: what kinds of mathematical structures can be defined how, which structures a given definition defines, what concepts are definable, and so on. And to understands the concepts themselves one needs to go further.
Unfortunately, I can’t give a good positive argument for the importance of math; that would require a useful insight (arrived at through use of mathematical tools). At the least, I can attest finding a lot of confusion in my past thinking about FAI as a result of each “level up” in understanding of mathematics, and that counts for something.
I recently shifted to believing that pure mathematics is more relevant for FAI than computer science.
A truly devious plan.
That’s interesting. What’s your line of thought?
In FAI, the central question is what a program wants (which is a certain kind of question about what the program means), and not what a program does.
Computer science will tell lots about what which programs can do how, and how to construct a program that does what you need, but less about what a program means (the sort of computer science that does is already a fair distance towards mathematics). This is also a problem with statistics/machine learning, and the reason they are not particularly useful for FAI: they teach certain tools, and how these tools work, but understanding they provide isn’t portable enough.
Mathematical logic, on the other hand, contains lots of wisdom in the right direction: what kinds of mathematical structures can be defined how, which structures a given definition defines, what concepts are definable, and so on. And to understands the concepts themselves one needs to go further.
Unfortunately, I can’t give a good positive argument for the importance of math; that would require a useful insight (arrived at through use of mathematical tools). At the least, I can attest finding a lot of confusion in my past thinking about FAI as a result of each “level up” in understanding of mathematics, and that counts for something.