I remember reading about Cyc when I was a kid, thinking it was pretty cool. I remember reading breathless articles with emotional quotes from the system where it asked existential questions like "am I alive?". I grew up with Sci-Fi, Video Games and Anime where the protagonist had an AI that did all sort of wonderful things for them. I'm by default a fan of the Cyc project and cheer a little whenever I see anything about Cyc.

So this is not meant to take anything away from the folks who work on (Open)Cyc, but I think it's time to ask some hard questions about this kind of AI approach:

Cyc (open or otherwise) is about 30 years old and has yet to demonstrate any sort of serious advancement over other, much lower friction approaches (actually it's hard to find utility at all). My personal feeling is that it represents a failed approach. This is not the same as a failure, it was a very important experiment that tried to answer the question (paraphrasing the WP article), "is it possible to craft an AI that can perform human-like reasoning using an ontology of common sense knowledge?" I think after 30 years the result has been an interesting curiosity, but the answer is a pretty strong "no".

There are more important questions though. Let's say that OpenCyc represents 30% of the state goal -- and since the goal from the WP page is a bit nebulous let's refine it and say 30% to the reasoning capacity of a 6-8 year old human child (6-8YOHC). And let's say that miracle upon miracles, Cyc is able to move closer to that goal at a steady 1% per year...and after 70 more years Cyc is now as smart as a 6-8YOHC. Is this desirable? I mean, is this a good thing to have? I don't mean this question to come from a source of deep philosophy or moralistic questions...but have you ever tried to get a 6-8YOHC to do any task more complex then follow a few simple instructions with lots of supervision (even getting personality and desires of the child out of the way)? A digital 6-8YOHC measured just on intelligence might, just might, be smart enough to follow a simple question like "find me news articles about the Libor scandal". But is that worthwhile? Is 100 years of R&D to achieve this useful?

The approach in the past was to not tackle the general purpose problems the Cyc was always meant to but to focus the approach on specific problem sets and build "expert systems". This is apparently what the (limited) list of use-cases Cyc is being applied towards is. This again means that Cyc has failed. "Common sense" knowledge means "general purpose" a 6-8YOHC knows as much about terrorism or biomedicine as it does about car engines...in other words it should perform equally well on any of those things because none of those things are "common sense". "It's hot outside so I shouldn't wear a winter coat" is a common sense thing.

So what are we left with? We're back to ontologies and various flavors of knowledge management and reasoning systems, all of which in my experience are faddish cover terms for the kind of AI research which just didn't go anywhere and haven't demonstrated much more than adding an interesting aside to what were already pretty darn good search results in my favorite search engine when I go to hunt down showtimes for a movie I want to see.

The number of dead, dying and useless Semantic Graph projects that are out in the world are astonishing. The lack of any real useful tools built with them is even more astonishing. And I don't mean tools that let you inspect the Knowledge Base (very exciting stuff like e.g. "is President Obama in the Knowledge Base? What is he connected to?") which I guess are useful sort of search engines in some contexts where the information is impossibly well curated (e.g. wikipedia). But I mean things like automated teachers, digital accurate diagnosticians, AIs that write good Pop Songs and hold interviews with the entertainment press, anything that might represent intelligence. It seems like whenever some of the pieces of these things show up (WP, Khan Academy, etc.) they are eschewing the direction that Semantic Research is taking us and going with a lower friction, higher payoff route. Why isn't there an AI that can suck in WP and Project Gutenberg and then generate and give me Khan academy lessons for K-12? Or at the very least provide NPCs in a game that are capable of having at least a 6-8YOHC level of conversation.

The answer has always been "wait till we add more objects/entities/facts/assertions/things/stuff/etc.". This is a bad answer, and unfortunately is the one that challengers to this approach get served back to them. Feeding "stuff" into a model and waiting for the spark of life to kick in just doesn't seem to be cutting it. There are ontologies with literally billions of things in them that are nothing more than strangely structured databases with odd query interfaces.

I'm a fan of Cyc, and it feels like it makes sense, and I'd love to be proven wrong, but I'm forced to lump it and similar approaches into yet another dustbin of evolutionary dead ends along with atomic powered cars and dinosaurs. I'm afraid Cory Doctorow was right http://www.well.com/~doctorow/metacrap.htm

I'd love to know for example that Cyc, as the most mature common sense reasoning system was the "go to" when Google started building the voice search in Jelly Bean and the Google Semantic Search and every few months we'll just be blown away by what's happening when we turn over a 30% 6-8YOHC on nearly every bit of human knowledge ever collected and it'll start doing really really useful amazing stuff for us instead of saving me a few smudges on my screen when I want to set an appointment or look up how tall Brad Pitt is.

I hate to turn this into a vent, but I just feel so...crestfallen...at the seemingly limitless lack of serious progress in the entire field (not just Cyc) despite what are probably millions of man years put into it.

The final hard question then is...is this kind of approach the right one?