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We don’t yet know which AI architectures are safe; learning more about this is one of the goals of FLI's grants program. AI researchers are generally very responsible people who want their work to better humanity. If there are certain AI designs that turn out to be unsafe, then AI researchers will want to know this so they can develop alternative AI systems.
Avoid directly responding to the question in the answer, repeat the relevant part of the question instead. For example, if the question is "Can we do X", answer "We might be able to do X, if we can do Y", not "Yes, if we can manage Y". This way, the answer will also work for the questions "Why can't we do X" and "What would happen if we tried to do X".
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Consider enclosing newly introduced terms, likely to be unfamiliar to many readers, in speech marks. If unsure, Google the term (in speech marks!) and see if it shows up anywhere other than LessWrong, the Alignment Forum, etc. Be judicious, as it's easy to use too many, but used carefully they can psychologically cushion newbies from a lot of unfamiliar terminology - in this context they're saying something like "we get that we're hitting you with a lot of new vocab, and you might not know what this term means yet".
When selecting related questions, there shouldn't be more than four unless there's a really good reason for that (some questions are asking for it, like the "Why can't we just..." question). It's also recommended to include at least one more "enticing" question to draw users in (relating to the more sensational, sci-fi, philosophical/ethical side of things) alongside more bland/neutral questions.
Current narrow systems are much more domain-specific than AGI. We don’t know what the first AGI will look like, some people think the GPT-3 architecture but scaled up a lot may get us there (GPT-3 is a giant prediction model which when trained on a vast amount of text seems to learn how to learn and do all sorts of crazy-impressive things, a related model can generate pictures from text), some people don’t think scaling this kind of model will get us all the way.
It’s pretty dependent on what skills you have and what resources you have access to. The largest option is to pursue a career in AI Safety research. Another large option is to pursue a career in AI policy, which you might think is even more important than doing technical research.
Smaller options include donating money to relevant organizations, talking about AI Safety as a plausible career path to other people or considering the problem in your spare time.
It’s possible that your particular set of skills/resources are not suited to this problem. Unluckily, there are many more problems that are of similar levels of importance.
There have been surveys and opinion polls done. The most comprehensive one was done by The Future of Humanity Institute, where they surveyed 550 of the top experts in AI research. In this survey, when asked "which year do you think the chance of human level artificial intelligence reaches 50%", the mean response was 2081 and the median response was 2040.
Link to https://www.cold-takes.com/ai-could-defeat-all-of-us-combined/ at the end
Very hard to say. This draft report for the Open Philanthropy Project is perhaps the most careful attempt so far (and generates these graphs), but there have also been expert surveys, and many people have shared various thoughts. Berkeley AI professor Stuart Russell has given his best guess as “sometime in our children’s lifetimes”, and Ray Kurzweil (Google’s director of engineering) predicts human level AI by 2029 and the singularity by 2045. The Metaculus question on publicly known AGI has a median of around 2029 (around 10 years sooner than it was before the GPT-3 AI showed unexpected ability on a broad range of tasks).
The consensus answer is something like: “highly uncertain, maybe not for over a hundred years, maybe in less than 15, with around the middle of the century looking fairly plausible”.