Is it ethical to work on general-purpose robots given the risk of cyberhacking?
If there were millions+ of general-purpose robots deployed in the world, and someone were able to hack / take control of a large fraction of them, they could easily create a repressive state. Despite the feasiblity of this danger, I have found very little discussion online.
TLDR: For this reason, was wondering if anyone happens to know: i) what the mainstream AI safety community’s view on this issue is — i.e., whether the cyberhacking of general-purpose robots is considered a serious risk—and if so, whether it is ethical to work on general-purpose robotics; or ii) any good online discussions that examine this specific issue?
How inevitable are most accessible hard-tech startups?
(For context, I’m an undergraduate considering entering the hard-tech startup space. One concern I have is whether some of these startups are highly inevitable, and therefore whether my marginal impact as a founder would be essentially negligible.)
Question: For many hard-tech startups that do not require extremely sophisticated technology, if the first inventor had not existed, how much later would someone else likely have done something similar?
By “hard tech that does not require extremely sophisticated technology,” I mean physical products that could be created in a typical local makerspace (i.e. without specialized nanotechnology, advanced fabrication methods, etc.). For example, smart thermostats and basic robotics would fall into this category.
I would like to believe the answer is often “years later,” but I can also imagine the delay being only a few days to a month, because i) many hard-tech founders are actively looking for startup ideas; ii) many of the underlying problems are already well known; and iii) if the technology is relatively accessible, it seems especially likely that multiple people would try to solve the same problem around the same time.
Is this intuition correct? I’m looking specifically for rigorous quantitative analyses that try to estimate the “delay” for accessible hard-tech startups, not one-and-off anecdotes. If anybody knows of any rigorous analyses, it would be deeply appreciated.
Is it ethical to work on general-purpose robots given the risk of cyberhacking?
If there were millions+ of general-purpose robots deployed in the world, and someone were able to hack / take control of a large fraction of them, they could easily create a repressive state. Despite the feasiblity of this danger, I have found very little discussion online.
TLDR: For this reason, was wondering if anyone happens to know: i) what the mainstream AI safety community’s view on this issue is — i.e., whether the cyberhacking of general-purpose robots is considered a serious risk—and if so, whether it is ethical to work on general-purpose robotics; or ii) any good online discussions that examine this specific issue?
How inevitable are most accessible hard-tech startups?
(For context, I’m an undergraduate considering entering the hard-tech startup space. One concern I have is whether some of these startups are highly inevitable, and therefore whether my marginal impact as a founder would be essentially negligible.)
Question: For many hard-tech startups that do not require extremely sophisticated technology, if the first inventor had not existed, how much later would someone else likely have done something similar?
By “hard tech that does not require extremely sophisticated technology,” I mean physical products that could be created in a typical local makerspace (i.e. without specialized nanotechnology, advanced fabrication methods, etc.). For example, smart thermostats and basic robotics would fall into this category.
I would like to believe the answer is often “years later,” but I can also imagine the delay being only a few days to a month, because i) many hard-tech founders are actively looking for startup ideas; ii) many of the underlying problems are already well known; and iii) if the technology is relatively accessible, it seems especially likely that multiple people would try to solve the same problem around the same time.
Is this intuition correct? I’m looking specifically for rigorous quantitative analyses that try to estimate the “delay” for accessible hard-tech startups, not one-and-off anecdotes. If anybody knows of any rigorous analyses, it would be deeply appreciated.