Publishers aren't interested in a book's credibility except insofar as it affects its ability to drive sales. Self-publishing or vanity publishing isn't evidence of inaccuracy or lack of intellectual integrity; it's evidence of being boring, niche, poorly written, or otherwise of limited potential. That's definitely not good news but it doesn't qualify as "Dark Arts" by any means.
(Things are a little different in the academic press, but I don't think that applies here.)
Normal publishers filter books for many aspects that would lead a reader to not want to read the book. While it's true that not much filtering is done on accuracy and integrity, the aspects that the books are filtered on are still ones that typical readers care about. Relying on the user's lack of knowledge of the publisher to make him think such filtering has been done, when it has not, is dark arts, deceptive, or whatever other term for bad things you like to use.
In other words, "I'm not tricking a user into reading an inaccurate book, I'm just tricking the user into reading a boring and poorly written book" isn't an excuse.
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!