Amazon's 'Look Inside' shows the Kindle version, using whatever typesetting Amazon chooses; the PDF is better typeset. The main cost is researching the different options for making it available as a paperback and then verifying that research, which probably costs several hours of staff time, and our operations staff are currently doing higher-value work. If somebody I trust has already analyzed the options recently, and found the best choice or shown that it doesn't matter much, then it should only take Alex 1-2 hours of his time to make the paperback available, which is probably worth it.
This sounds like bad instrumental rationality. If your current option is "don't publish it in paperback at all", and you are presented with an option you would be willing to take, publishing at a certain quality, if that quality was the best quality, then the fact that there may be better options you haven't explored should never return your "best choice to make" to "don't publish it in paperback at all." Your only viable candidates should be: "Publish using a suboptimal option" and "Do verified research about what is the best option and then do that."
As they say, "The perfect is the enemy of the good."
We're pleased to announce the release of "Smarter Than Us: The Rise of Machine Intelligence", commissioned by MIRI and written by Oxford University’s Stuart Armstrong, and available in EPUB, MOBI, PDF, and from the Amazon and Apple ebook stores.
Can we instruct AIs to steer the future as we desire? What goals should we program into them? It turns out this question is difficult to answer! Philosophers have tried for thousands of years to define an ideal world, but there remains no consensus. The prospect of goal-driven, smarter-than-human AI gives moral philosophy a new urgency. The future could be filled with joy, art, compassion, and beings living worthwhile and wonderful lives—but only if we’re able to precisely define what a “good” world is, and skilled enough to describe it perfectly to a computer program.
AIs, like computers, will do what we say—which is not necessarily what we mean. Such precision requires encoding the entire system of human values for an AI: explaining them to a mind that is alien to us, defining every ambiguous term, clarifying every edge case. Moreover, our values are fragile: in some cases, if we mis-define a single piece of the puzzle—say, consciousness—we end up with roughly 0% of the value we intended to reap, instead of 99% of the value.
Though an understanding of the problem is only beginning to spread, researchers from fields ranging from philosophy to computer science to economics are working together to conceive and test solutions. Are we up to the challenge?
Special thanks to all those at the FHI, MIRI and Less Wrong who helped with this work, and those who voted on the name!