"We need a pony. And the moon on a stick. By next Thursday."
antipope.org
antipope.org
It really surprises me that we think there's a realistic path to the singularity and that we obsessed about it. Human-like AI is a dead field, or at least dead as far we can tell. We're not even sure how to build it because conceptually we don't even have a grasp on consciousness or cognition.
Then there's the false assumption that we can get to this level before doing things like, say, solving all mental health issues and that it can magically be scaled to super-human speeds. For all we know cognition happens at a certain speed and any attempts past that are troublesome. Look at how easily we suffer from mania and other issues when our natural limiters go haywire.
Singularity prediction is almost a cargo cult. Its weird that so many take it seriously.
The reason it's popular is that it plays to some deep eschatological anxieties shared by many people -- and it strikes resonant echoes with Christian millennialism, making it an easy memetic poisoned chalice for anyone who has consciously rejected knee-jerk Christian doctrine but not actually re-evaluated all their composite assumptions and beliefs to drink from.
Becoming a science fiction cliche does not reduce the probability of an event occurring.
Edit: retracting the following:
>The reason it's popular is that it plays to some deep eschatological anxieties shared by many people.
This is probably true, but that's not an argument against the feasibility of AI or the extent of its implications. You're saying, "These projections "rhyme" with those of a low-status group, therefore they can't be true."
No, that's not his argument for why it's not true, it's his argument for why the singularity concept persists when it seems that otherwise non-religious people would reject it.
Some of his arguments against an imminent singularity:
http://www.antipope.org/charlie/blog-static/2011/06/reality-...
http://www.antipope.org/charlie/blog-static/2014/02/the-sing...
The entire low level ongoing effort to build a flying car (Terrafugia, Moller, etc) is basically driven by no market and no common sense, but a whole lot of Jetsons.
A separate effort which actually makes a bit more sense and has more of a market is the iTec Maverick [1] - more of a flying dune buggy using a parasail as the "wing", but targeting a wholly different market (the Transition is aimed at wealthy pilots in wealthy countries with streets, airports, etc, whereas the Maverick is - in part - aimed at villagers living in remote jungles, far removed from civilization).
--------------------
I think I'd like to see some statistics on that.
Edit: No really, I'm serious. Actual data on the commonality of some SF idea and the measured likelihood of it would be very cool.
But there are a few clear standouts. 6. The patently obvious design flaws in a vehicle or weapon system go uncorrected during the entire life cycle of the system in question.
The original humvee had issues with passenger armor back in 2004 - they could have been purchased with the armor but weren't.
13, Computers, when shot, explode as if they had been stuffed full of Roman candles.
The videos of laptop batteries catching fire are pretty sparkly. Not sure how that would actually interact with a gunshot.
25, On-board computers always know exactly how long it will take for the malfunction to blow up the ship.
The Tesla roadster battery stories seem to give warning and force drivers to stop and get out.
31. A robot that can't climb stairs is deployed in an area where stairs are common.
Roomba?
At the very least, we can make an existential argument about sci-fi cliches actually being accurate. I couldn't think of a good way to get historical science fiction cliches. But the thing about the future is it's unknown. some of Jules Verne's stuff worked out, like submarines and travel to the moon, and other stuff didn't, like time travel.
I guess the rational response to "the singularity" is to stick a number on the likelihood of that actually happening - and then getting on with your life.
I think you're thinking about the future in a funny way, you should give Nassim Nicholas Taleb's The Black Swan a read.
Which is probably more a statement about its lack of novelty than anything else.
That seems as if it can get pretty close to the singularity, and answers a lot of questions about what a super intelligent being's motivations would be.
Sounds like we can get the "Captain America" singularity - everyone gets a genius-level IQ, but nothing further.
Which has the major upside of meaning we'll never have to deal with the Vile Offspring.
By the way, the final component to Rapture of the Nerds didn't seem to have a very good "exam", as I can't imagine the Galactic Authority would never have come up with any way to analyze minds, for instance a sample of human minds, and thus infer the chance that we can coexist as a species without having to run trillions of parallel copies performing very expensive simulations. Hilarious book, other than that, though; it really reminded me how much of a total nerd I am that I understood every single damn word without having to google.
http://www.antipope.org/charlie/blog-static/2011/06/reality-...
It is titled "Three arguments against the singularity" from June 22, 2011
reminded me of Jack Williamson's With Folded Hands scenario (from 1947, http://en.wikipedia.org/wiki/With_Folded_Hands )
Oh god - domination by the mediocre AI bureaucrat sounds worse than the AI overlord.
Human-level AI is possible.
Human-level AI will likely be practical this century.
Once AI is sufficiently advanced, it will be capable of AI research.
Most terminal goals would lead to intelligence enhancement as a sub goal, as any system with a goal would be better able to pursue it if more intelligent. Therefore, most AIs will devote resources to increasing their intelligence.
Assuming humans are not near the maximum possible intellectual level, super-human AI will likely be developed soon after an AI is created that is as smart as the smartest human.
This means the future will not be controlled by humans, as we will no longer be the smartest things in town.
Unless we can predict the goals of the AI, we should consider the future unpredictable after the point of its creation, as our models of the future rely on human-shaped agents with human goals and capabilities. With these assumptions broken, we have a sort of singularity, a breakdown of our models of the future.
It's quite conjunctive, but this all seems pretty reasonable to me - and it's worth spending resources studying.
How does a difference in the level of intelligence of a particular entity compare to the effective intelligence of having lots of less intelligent entities? Having lots of people means that you can apply intelligence towards a lot of tasks, but perhaps all of them together will never come up with something that a greater intelligence could come up with.
Thinking about it, it seems to me that you have to apply it against an actual difficult task. Take a task like "build a power-producing fusion reactor" that nobody knows how to do yet. Would we be able to figure out how to do that faster if there was some superior intelligence applied to it? Or does the huge number of engineering problems associated with building such a thing respond better to a large number of more ordinary intelligence?
Sorry for reviving old thread.
edit: And the collective is significantly more intelligent than the individual (for some but definitely not all reasonable definitions of intelligent and collective).
Only in the sense that Stalin or Pinochet was a productive citizen. Powerful people can mobilize others to their own ends without those ends being at all good or moral for everyone who is not so mobilized.
From agrarians to victors of ww2 in ~20 years is pretty impressive by any measure.
> Human-level AI will likely be practical this century.
Both are unknown.
Well we exist, so we know human-level intelligence can be implemented in physics. So we certainly know AI is possible.
In fact, I think it is quite clear that we are capable of designing systems that are more intelligent than an unaided human (or even group of humans). One of the first such systems were writing. I also tentatively claim that new means of recording and arranging knowledge (which we do today by means of computers) is another step towards superhuman intellect in the strictest sense of "more than mere human".
I think it is an open question what will come out of our playing with genes directly. I certainly expect we'll able to produce some change in the human condition, I hope some of that change will be for the "objectively" better. I have no idea if it will directly impact our intelligence.
"Designing" isn't necessary for creating (OTOH, whether we can artificial select for it and avoid selecting for dead ends may be an issue.)
Btw, Crystal Nights by Greg Egan is a fascinating short story: http://ttapress.com/553/crystal-nights-by-greg-egan/
We have no mean to know. Maybe the subjective experience is an inherent part of our intelligence, and not just a side effect. And I do not see any way of applying the scientific method to the subjective experience.
Nethertheless, I really hope that the future will prove me wrong.
Further, beyond the task of software improvement, the task of improving hardware is itself already heavily software-mediated when performed by humans, and will likely be a prime candidate for applying pre-AGI AI.
There are likely other ways to attack the problem, such as not focusing on hardware improvements per-se, but instead on the cycle time for getting the improvements deployed (eg. somehow eliminating or cutting the size/cost/construction time of new Fabs).
Given how far away from that goal we are now, after 85 previous years of research, I would not hold my breath for reaching that goal in the next 85 years.
There are two things holding back AI (which from a singularity-standpoint just means "a machine capable of general problem-solving", and not "a machine possessing the ineffable characteristics of human consciousness"). First, we don't know how. Second, we might not have the computational capacity.
While we still don't know how, the bar is getting lower and lower as time goes on. Increasing computational capacity means that we can start with worse and worse initial versions of a general intelligence. Maybe a really special genius could write a general problem solver which ran on a 386 (even if it lacked the self awareness to feel the pain of running on a 386). Maybe we're too dumb to ever write a general problem solver even if we had an infinately fast computer with unlimited memory.
But even if programmers have made no progress since the 1960s, we are definitely not in the same position.
That depends on who is saying it. I've noticed that when actual researchers say, "We hope this will provide a treatment for reticularly homicidal brain-worms within 5 years", they mean they have no idea if or when any such practical material benefits will appear. If they say, "We will be able to get effectively unlimited amounts of energy from russet potatos within 20 years," they mean they don't believe it's ever going to happen.
If the difficulty is exponential, as I rather expect it to be (in my own completely unfounded opinion), then lowering the bar a given amount doesn't help much. And as far as increasing computational capacity goes, we're already deep into the realm where communication costs outweigh actual computational costs, which makes it a whole different ball game going forward.
If you want a further speculation, I suspect that modern statistical methods like those behind th' Goog, self-driving cars, and what-not will not get too much closer to a super intelligence than conventional heuristic search. They're capable of doing a lot of things easily, that only humans could do heretofore, but they're not actually more powerful. So, "a machine capable of general problem-solving" is easily conceivable in the same sense that you are capable of general problem solving, but I can't see a singularity on the other side of that.
Now we know the real motivation behind pretty much every sci-fi storyline involving AI revolts.
So, having a look at wikipedia, we find: "Inspired by Babbage's difference engine plans, Per Georg Scheutz built several difference engines from 1855 onwards, one of which was sold to the British government in 1859." -- that's very convenient. We can cheat a little, and say that in 1929, there'd been about 86 years worth of research into computing -- and so by extension, achieving AI by 2100 is a greater feat than the NSAs new data center was as seen from 1929?
Perhaps. Makes for some interesting thought experiments.
For example, I work in aging and, to a lesser extent, neuroscience. I have had many private conversations with researchers who will candidly say that the long-term goal of their work is lifespan extension or cognitive enhancement. Yet, for the purposes of grant and paper-writing, you'd never write such a thing; it would sound too speculative.
I'm not in AI, but I strongly suspect the same thing is going on there. There are probably a lot of AI researchers who want to see human-level or higher general AI happen, and are working on it, but simply can't say so in public. We know it's possible, since we have an existence proof in the human brain.
I think it was Scientific American or another such magazine that ran a story, maybe a month and a half ago, in which they interviewed a whole bunch of real theoretical and computational neuroscientists about mind uploading. A not-that-small portion of these admitted that when they are in private, have had a drink or two, and are ready to admit things they would never say in a grant application, they are definitely trying to achieve whole-brain emulation.
Hell, it's basically the implicit point of the Human Brain Project, or whatever those initiatives are called by the US and EU governments this past year.
> You are right that you won't see many researchers publicly talking about human-level AI, or framing their research in terms of the search for general AI. But that doesn't mean the field is "dead".
Indeed. What instead happened is that actual humanlike cognition has been steadily broken down into subproblems and each subproblem is being formalized and worked-on separately. There are a few papers on optimal utility-maximizing agents for general environments, but those tend to require "until the stars burn out" levels of FLOPs to work anyway.
So actually, AI is going to work, but by the time it does, it won't be called AI. In fact, the researchers who'll create it would look at you funny for calling it AI. They do and will have lots of academic jargon used for specifying exactly what their algorithms do and how they do it, so much so that only when their algorithm kills all humans will anyone actually admit it was artificial intelligence ;-).
I think it was Scientific American or another such
magazine that ran a story, [...] real theoretical and
computational neuroscientists [...] admit things they
would never say in a grant application, they are
definitely trying to achieve whole-brain emulation.
For example, if I'm researching image correlation techniques, which have applications in machine vision, which has applications in obstacle detection and tracking, which has applications in self driving cars, I could tell a journalist that I'm working on image processing techniques with potential applications in self driving cars.
Is that me admitting things I would never say in a grant application, that I'm trying to achieve self-driving cars? Or am I working on exactly what my grant application says, but I've simplified it and added context because I know Scientific American isn't going to be publishing articles about efficient convolving and fast fourier transforms any time soon?
On the other hand, my real-world observations say that for many scientists, the burning dream heating their blood and getting them up in the morning to deal with all the bullshit is... careerist ego-stroking.
So on further reflection, ugh.
Of course they are trying.
They were also trying in 1956: "We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer."
http://en.wikipedia.org/wiki/Dartmouth_Conference
The history of AI research is full of totally unfounded optimism that has failed every time. (I mean the kind of research that promises significant advances towards human level AI. Of course AI research has produced methods that have useful applications.)
Gaaah, I'm trying to remember the link to some short story that Someone (we all know who) wrote about a man fretting over his JRPG party members seeming to be conscious. The author's afterword said that he expected seemingly-conscious video game characters to show up "six months before the Singularity". I currently expect seemingly conscious video-game characters - which are actually just very stylish fakes with really good NLP - many decades before anyone manages to produce a self-improving agent.
Absolutely not.
But I think it's too far in the future, that it is totally pointless for us, in 2014, to worry about it.
I view the singularity crowd as a bunch of medieval alchemists, after they have seen gunpowder, worrying about mutually assured destruction of the whole world, after someone scales their firecrackers to a size capable of destroying whole countries.
Yes, coming to 1950's we did reach nuclear weapons with end-the-world capability.
But it would have been quite pointless for (al)chemist, or philosophers, in the 1400's, or even in the 1700's, to start worrying about this threat.
No, I don't think so.
I just think the way looks very long, even given our current acceleration rate. Plus, this field has a very strong track record of blatant overestimations.
I apologize but being ambiguous. I don't think they are the same. But I see the same totally unfounded optimism in both the people who expect AGI to happen relatively soon, and in the people who expect WBE to happen relatively soon.
Like, in the next 50–100 years.
That is the historical nature of artificial intelligence: it's only AI until you know how to do it reasonably well.
So yes, they are very much aware of it. I think many aging researchers have a love/hate relationship with SENS, in that they share its goals in theory, but are afraid its ambitious public claims will draw disrepute (and associated loss of funding) upon the field.
You have to remember that we are mostly funded by the NIH, whose mandate is to treat disease, and aging is not widely considered a disease. So we have to frame our discourse accordingly.
But still, you have to be a bit more subtle with grant reviewers than that. "Age-associated disease" is a common catchphrase. For best results, the emphasis has to be on the disease rather than on the aging (even you happen to believe, as I do, that aging is a common root of many diseases).
The current optimism around A.I. is the result not of real advances in the field, but the very useful outcomes that arise from doing pattern matching and machine learning on big data sets. When people can type "weather today" into Google and get a little card that shows the weather in Philadelphia today, it's hard not to be impressed, not realizing that these tricks don't bring us closer to "real A.I."
As a counter-example, take something very simple like search-and-replace. Word processors have had this function for decades, and it hasn't gotten any better. How long will it be before I can tell my word processor to replace all occurrences of {singular proper noun phrase} with {plural proper noun} and shoot it off to my boss without double-checking each replacement?
I think what we have learned in the interim is not just that "machine-learning" style approaches are successful at specific tasks, but also that a statistical, data-driven, "bottom-up" approach is going to need to be an integral part of any eventual general AI solution. Whether we will need to explicitly design the high-level cognitive elements, or whether they will emerge from properly constructed low-level elements, remains an open question.
Another very important advance since the 70s/80s is the widespread realization that every major aspect of cognition is essentially probabilistic. People have realized that a search for "exact" or "optimal" solutions to problems with the complexity seen in the real world is a futile task because of the high dimensionality of these problems.
On a purely physical level, this is hard to believe. We don't have precise models of consciousness and reasoning, but the general ones (bayesian reasoning, decision theories, etc) are speed-agnostic. It's hard to imagine one that isn't.
> Look at how easily we suffer from mania and other issues when our natural limiters go haywire.
Sure, our hardware sucks. Plus, that's even more the reason to worry about the singularity - if a very fast ai can think and plan, but suffers from mania, that's not a very good outcome. UFAI is an area of concern for many.
We don't need to understand consciousness or cognition to create optimization processes that end up hurting (or killing) humanity.
It surprises me how many people seem ignorant of this fact.
And these are evolving through selective pressures as well. And not generally in the pro-humanity direction, more in the "preserve self at all costs" direction.
Yes, we've noticed. Those are evil, too.
Instead, it means that something will become so intelligent that it will be different in kind, in somewhat the same way that we are so different from gravel that gravel cannot hope to understand our behavior.
An optimization process that ends up killing all of us is bad, but it's not a singularity.
An even better theistic analogy for the singularity is the return of Jesus. Just wait till he comes and rights all the wrongs and banishes death and knows everything about everyone who ever lived and makes a paradise on earth for the true believers ... wait was I talking about the singularity or Jesus again?
(note that I'm not (intentionally) making fun of either subject, but trying to focus on the crude search and replace aspect of the analogy)
Certainly, Julius Caesar or Crassus could have afforded a Roman era hot air balloon or hang glider or glider aircraft if this false analogy hadn't stood in the way of development. Performance would have been somewhat lower than modern material craft, but probably not as bad as you think. There were several decades of modest performance aircraft before titanium, synthetic fabrics, and carbon fiber.
AI workers might be more successful in the long run if they focus on making a useful martian brain, not clone humans in silicon.
AI has been a diverse field for a long time, with many different paths -- both with direct biological inspiration (often not human -- including, e.g., insect-inspired approaches) and without are common. Its not an exclusive "human or not human" modelling choice.
Stone > Bronze > Steel > Silicon > Software >
It's the "geek rapture" version that's more fantastic and extremely unlikely.
If I had to guess, I would put the next phase at "integration" or "control." In that once we have functional, reliable libraries and virtual instruments, the logical next step is to integrate the high-level control of such into our physiologies. Alternatively, I could see "space" being an age we expand into, drawing our resources increasingly from space and broadening the scope of our potential that way. I'd like to see these happen in parallel if possible.
Things like new forms of quantum logic/algorithms, artificial atoms, metamaterials, even subvocal tools (moving us from graphical user interfaces towards thought-based user interfaces), are more 0+1 to me.
Not studying that would be cargo culture.
Even if the latter is true, its largely irrelevant to the former. Human-like AI might be one route to a singularity, but not required for it; most of the singularity predictions that I've seen are more centered more around humans rapidly (and at an ever-accelerating pace) becoming proportionately less of the "processing power" involved in the systems where they are the central intelligence, rather than human-like AI per se.
Why do you think "human-like" AI is a requirement for a singularity to occur?
Isn't it much more likely to emerge simply as a side-effect from continued exponential technological progress and the ever increasing network density?
Maybe try to look at it with less anthropocentrism, perhaps consider how we have evolved from shouting to the internet in a mere few thousand years?
Do you think we'll still be using our eyes and hands to interface with the network, in another thousand years from now?
But only those beings who have the capacity of experiencing surprise.
See, I can make up predictions too.
One was an acquaintance of mine, who had lived down the hall from the kid in a college dorm. As he recounted it, the conversation went in part like this:
Secret Service guys: Did he seem like the sort of person who would do something like this? Acquaintance: No, really pretty serious. Now, I might think it was funny to do something like that. [Smiles, chuckles.] SSg: [Silence, no smiles, no chuckles]
Let's face it, they aren't paid to have a sense of humor.
I suspect it is a bit edgy being the one just behind the president...
And we all know that could never happen.
As more and more data about us is collected, about what we say/type vs. what we actually do, this has the potential to become more accurate over time.
Facial and voice-tone analysis, analysis of our peers' responses to what we say/write, analysis of our actual movements/purchases compared to what we say/write ("I'm so going along to that Nickelback concert at the weekend...!") etc., combined with leading brains in stats and ML lead me to think this problem could be tractable to some extent in the future. Scary :-/
If something like this comes to be, and is deployed 'wholesale', it has the potential to influence our behaviour, and over generations, alter our definition of 'sarcasm' by what we are able to get away with saying. Insidious!
That said I hope Charlie is right and that humans can game the system significantly that it is a non-starter.
I was brought up in a family that used sarcasm heavily and "turning it down" on the Internet has been a real challenge. Sometimes I still fail (something I believe is obviously sarcastic is misread).
My daughter (13) observing this suddenly chimed in: "I think you're caught in a sarcasm trap."
She claims to have invented the term on the spot.
My 13 year old knows it's sometimes not possible for humans to detect sarcasm, much less a computer program. It's a shame that the secret service doesn't too.
(I would venture to say that more people struggle with sarcasm than not. It often requires shared culture/experience to detect if it's not delivered in an obvious tone.)
Also, your daughter is much more perceptive than the vast majority of the people I know.
Moe: Hey is Curly back from Vacation yet?
Larry: I saw a Red Lamborghini in the parking lot.
Moe: Cool
NLP is hard
An AI could form _a number of_ inferences and then use a knowledge base to choose a likely candidate. In fact: I feel like IBM's Watson gave us a little preview of what an AI's "thought process" might be like.
If the system knows Curly drives a red lambo, and that it is a rare car in this area, and that Curly usually only parks in the parking lot when he's around, and etc. etc. etc.
He was outlining that the difference is: humans do not need the context.
I do not know who Curly is, and I still got what car he drives just by reading the three-line dialog.
I inferred that too, but it doesn't mean that it is correct.
Not saying that parsing natural language is easy, just not sure this is such a terribly hard example (for a system that's prepared to cheat and/or appear stupid/gullible).
Eg, parse both the above and the below correctly with the same parser:
Ann: Have you seen my dragon?
Dad: I think he is playing with the bear in your room.
Ann: Ok.
They also host excited discussions of linguistic technologies like Siri or Watson.
Here we have a government agency attempting to push the envelope of technology in hopes of reducing their over-reactions. Seems like the sort of thing that would be greeted warmly but, nope, apparently not.
So, while the minor impulse (reduce overreach) is right, the major impulse (automated justice) is still very wrong.
"phrase used widely by teenagers and young adults in the mid 90s as it was made popular by the comedy geniuses Stew Lee & Richard Herring. they used it mostly in the second series of their hit tv & radio show 'Fist of Fun'.[1] It means basically to want everything, if you want the moon on a stick then you want everything, including things you can't have."[2]
[1] https://www.youtube.com/watch?v=ERDUbAv8Qz0
[2] http://www.urbandictionary.com/define.php?term=moon%20on%20a...
(That was, btw, sarcasm. Normally I don't like it, but it seemed appropriate here.)
That would also be a plausible spinoff.
But, with the NSA databases, any government solution will have that shared context, right? (I can't tell if I'm being sarcastic...)
1. http://onlinelibrary.wiley.com/doi/10.1111/j.1467-8624.1990....
I'm pretty sure the secret service could be convinced to proceed on that maxim.
This might be an interesting way to detect / work around / operationally neutralize the theorized sarcasm detector, as it should be easy to make a google-verifiable sarcastic comment thats ridiculously out of line for most mouth breathing humans WRT CS or quantum mechanics or math in general.
What does this mean to the hypothetical algo: "If P=NP then I'm killing Heisenbergs cat". (edited to add, I hope the algo tries to prove P=NP or crashes when it thinks about it)
Even more fun way to hack with the hypothetical AI, tag something obscure in wikipedia with your site as an external source, then use that obscure reference in a theoretical threat against the prez and log the accesses to your site and research your site accesses accordingly.
Perhaps by careful, fast, automated wikipedia edits if you can make changes faster than the generic spider can figure out what to look at, you could theoretically SWAT people using the sarcasm detector. So if you posted in 2011, "Obama's going to get Wisconsin in 2012" as in electoral college votes, by proper automated wikipedia editing you could turn that into a SWATting incident by editing "Wisconsin" to be a military grade nerve gas before the sarcasm detector accesses it. Who cares if your automated edit gets reverted in 5 minutes if the men in black are already carrying M16s in the van on the way to the SWATting victim's house by the time its reverted...
So that's actually a pretty high bar in those areas that humans have traditionally much better at than computers.
(Or were you being sarcastic?)
Somehow I feel like the people that are serious about this level of criminal activity, and capable of actually accomplishing it, aren't first announcing their intentions on twitter.
More than one mass murderer has talked publicly about what they're planning online. And two guys that planned to assassinate Obama in 2008 were caught because they bragged to a friend about what they were doing: http://en.wikipedia.org/wiki/Barack_Obama_assassination_plot...
Obviously you won't catch everybody, but I don't think the idea of getting tipped off about a potential assassination plan based on posts online is totally far fetched.
As a culture we've been pretty effective lately at electing miserable disappointing failures to public office. This seems a relatively uncontroversial observation, and note I'm careful not to name any names so as to not appear biased toward one side or the other of the one coin we've been dealt.
Precondition 2 is everyone has social media accounts where they say stuff no one cares about, constantly. The CB radio of this decade.
Precondition 3 is anyone planning an assassination is smart enough to self censor and say nothing about the entire topic.
Given the above preconditions, the only rational conclusion is 99.9% of the population will continually be whining and complaining, and you can focus your attentions on the 0.1% who are at least considering doing something bad enough to self censor.
So the thought experiment is Obama comes to visit a city and the guy who gets a SS visit is the only guy in the whole city who's not rambling on in social media about "Kenya" or "Can't believe I wasted my vote on him" or writing racial slurs or "he broke every campaign promise" or whatever.
The "disappointing" incumbent is merely a printed-paper face on the front of a machine. Which some loons choose to use for target practice. Resulting in the existence of a vast reactionary bureaucracy dedicated to extirpating threats to printed-paper faces.
Somehow I feel like the people that are serious about this
level of criminal activity, and capable of actually
accomplishing it, aren't first announcing their intentions
on twitter.
Once the assassin has been identified, if they had a tweet from a month ago saying "I am going to assassinate the president in a month" you can bet that will be on the front page of every newspaper, making you look like an idiot.
And if your anti-embarrassment system should prevent a real assassination, so much the better.
By that same logic, are you still an idiot if instead of a tweet, it was a facebook public post? How about a facebook post marked only visible to your friends? Or in an email to your brother's wife's third cousin?
I'm not a big fan of slippery slopes, but this one looks a bit lubricated.
So tweets are in and public facebook messages are in, but private facebook messages and e-mails are out.
And let me add that anyone that's stupid enough to try to troll/game this system deserves all the consequences of their actions.
edit: Remembering Bayes: Given a threat on someone the SS is charged w/ protecting, what is the probability it is not actionable?
It seems "Ability to sarcasm and false positives" is just one of the large list of 22 reqs. The list also includes:
• Compatibility with Internet Explorer 8;
That was sarcasm.
http://en.wikipedia.org/wiki/Twitter_Joke_Trial
Also, self-linkingly, the problem is that people don't tend to broadcast their violent intentions very reliably:
(I suppose that's timely with the Tianamen Square anniversary)
Better would be to argue that it is not only hard for humans to determine between sarcasm and genuine speech, we have no idea of how it would be done well. It is not a problem which is dominated by our limited abilities, it is dominated by imperfect knowledge (the inability to know the internal thoughts of another person). This same limitation seems to apply to any automated solution which only had access to the public speech (text, tweet, etc.). Therein lies the intractable difficulty.
However, consider if we had a device that could read minds. Maybe some model is built that can accurately translate brain waves, or the input of subdermal probes into thoughts and intentions. Then it would be much simpler to write a program that could detect sarcasm. It might still need the physical presence of the author, but again there may be a creative solution to that.
Just because it is hard for humans doesn't mean we can't make it easy using our tools. That is one of the prime characteristics of our species.
If humans can't yet detect sarcasm accurately, that is evidence that it will be near impossible to do it programmatically.
Edit: I'm not saying to not try. Clark's first law says we should always try things, even the crazy stuff. (as you can tell I like my eponymous laws).
No human is ever given enough time. If you're not done in a hundred years (tops) -- you'll never get done.
It's an interesting thought that a program that has access to a "Total Intelligence Awareness" feed, might actually have more context than any one human has (and can possibly have) -- and by extension be better at detecting sarcasm.
>> No human is ever given enough time.
>
> You have missed the point it seems. The actual amount of time is
> irrelevant. If a program can get an answer given some input, so
> can a human (given infinite time).
We do absolutely know that humans are fallible, so even if a human has enough time, and enough paper -- there is no guarantee that a human can duplicate the effort of a machine in following an algorithm.
You are assuming both the human and machine are given the same input (perhaps you think of only looking at the tweet in isolation). This might be how a human would intuitively try to determine if a given tweet is sarcastic. The machine might be able to look at and review the authors entire corpus of written statements, the authors movements in the past 20 years, analyse all tv programs and other writings the author has ever referenced along with an exhaustive study of all events in the authors life --- In short --- a human might not have "enough time" to "figure it out with pencil and paper" in the same way the machine can.
So, I agree with your initial point: If we cannot define what it means to tell if something is sarcasm or not (do we for instance care what the author meant, or only how the author was perceived? Can we be certain that the author knows if he/she is being sarcastic?) --- then how can a we program a machine to tell the difference?
On the other hand, if we can agree on some rules for what we might more likely consider to be sarcastic, it isn't entirely impossible that that algorithm can use so much data to draw its conclusions, that it would in effect be impossible for a human to verify -- because a human doesn't have infinite time. Or in other words: it's not inconceivable that we could create a system, that ends up being better at telling sarcasm from honest opinion than humans are. But it is likely that such a system would come to its decision in a very different way than a human would.
The rule is one method to determine if a program is theoretically possible or not.
For example, writing a program to determine if a given piece of code contains an infinite loop is impossible.
Read up on Computability and Decidability for more examples of things that are impossible to write programs for.
I do agree (with you and Pope) that sarcasm might be indeterminable in the general case. Now, if a computer system that has superhuman domain knowledge of the author can tell if a tweet is sarcastic, but a human can not -- is the tweet then, in fact, sarcastic? I'd say that's an open question.
Also, the example I gave is a simple solution: mind reading is a trivial solution to sarcasm detection, and it is not inconceivable from our current point of technology.
Well enough to protect the president, or well enough to perpetuate the taxpayer->government->university financial cycle by making something that kinda sorta works but could get better with uint8_t more years and uint32_t more dollars‽
http://www.youtube.com/watch?v=-fNvi6xG-5Y
from about 1:00
I think what we're all half-expecting, is that they'll define the output of the program to be true; thereby a) ensuring the program is 100% correct, and b) In the event of real threats (as identified by the program) have actionable intelligence.
Almost, but not quite, the same as banning sarcasm on the Internet.
"I went to a presentation from a sentiment analysis business last year. They were discussing how they were using it on the firehose feed of everything from twitter. Rather than assassinations, they were more interested in marketing, branding, and the impact on stock prices (there are apparently some iiiiiiinteresting correlations).
The thing that entertained me was they said they had to special-case content coming from the UK — because our levels of sarcasm/irony were skewing their results.
I think it was the most patriotic moment of my life <sniff> ;-)"
> ...the real target is the autonomous exercise of professional judgement.
http://www.cs.huji.ac.il/~oren/papers/sarcasmAmazonICWSM10.p...
This is beginning to read like a Stross book plot and maybe he's pissed because yet again he's scooped where the world is getting weirder faster than his plots are getting weird, like happened with the halting state series (as I recall). The laundry series is still safe from this danger, at least as far as we know...