IBM: Mind reading is less than five years away. For real.
news.cnet.com
news.cnet.com
Something like moving a cursor around by thinking about it, or thinking about making a call and having it happened requires a hell of a lot of bits of information to be produced by the brain computer interface. With the current state of the art we can distinguish between something like 2-6 classes of thoughts sort-of reliably, and even then it's typically about thinking of particular movements, not "call mom".
Importantly, what most people look for in the signal (the feature in machine learning terms) are changes in signal variance. And there are methods to detect these changes that are in some sense mathematically optimal (which is to say they can be still be improved a little bit, but there won't be any revolutionary new discoveries.) There may be other features to look for, but we wont be getting much better at detecting changes in signal variance.
Some methods can report results like a 94% accuracy over a binary classification problem. Such a result may seem "close to perfect", but it is averaged over several subjects, and likely varies between for example 100% and 70%. For the people with 70% accuracy, the distinguishing features of their signals are hidden for various reasons. And this is for getting one bit of information out of the device. Seems like such a device would need to work for everyone to be commercially successful.
In computer vision we have our own brains to prove that the problems can be solved. For EEG based brain computer interfaces, such proofs don't exist. There are certain things you probably can't detect from an EEG signal, meaning the distinguishing information probably isn't there at all. I'm easily willing to bet IBM money that who I would like to call can not be inferred from the electrical activity on my scalp. (Seriously IBM, let's go on longbets.org and do this.)
If I read the blog post correctly the claim is not passive mind reading. The claim is that the user has some training to issue the sorts of thought commands that can be reliably picked up. If I think "call mom" it doesn't do anything. But if I think "Up Up Down Down Left Right Left Right" maybe it can interpret that correctly as my preassigned shorthand for "call mom".
So I think they are actually describing a "call mom" scenario, and I strongly doubt that the information to detect that is at all present in an EEG signal.
Be more precise. If you can distinguish two classes, you can convey anything through EEG, however slowly (think 'bits'). With error, use error-correcting codes and you can get relatively high accuracy.
Pedantics aside, I agree in sentiment. Even with invasive techniques we can only roughly decode movement.
It seems to me that if you can map patterns for four directions, you should also be able to map patterns for 50 different phone book entries and several verbs.
When I say detecting movement, I mean things like imagining moving a hand, a foot or a tongue. These movements use distinct areas of the brain so you can distinguish between them by looking at where on the scalp the change occurred. This is done in ways that are known to be close to perfect.
However, you probably couldn't use scalp location if you wanted to distinguish "call mom" from "call John", as they would presumably activate the same area of the brain. There are of course other things one could look at, and I obviously can't prove that it can't be done. But at the same time I have never seen any kind of positive result for an EEG classification task at this level of detail.
Secondly, I am not sure one can learn to almost unconsciously think about certain movements of bodily parts. Chances are this will keep requiring too much apof one's attention.
Thirdly, I think temporal resolution will be awful. Even if you can learn to think about say 3 movements simultaneously, I doubt you will get this above a byte per second of bandwidth. Written text is around a bit/character, so that would likely be way below slow speech.
Most of this is opinion/guessing, so feel free to correct things.
So you couldn't distinguish individual fingers with todays technology. If it was ever to be done, I'd expect that it would be done with the same algorithms as we use today, but with much denser electrodes. If I were to bet, I'd bet that this would be physically impossible, but I'm not as confident as I am with saying we wont be able to detect who I want to call.
[1] http://en.wikipedia.org/wiki/File:Human_motor_cortex_topogra...
And I work in a lab that does BMI work, and we couldn't do the "call mom" command in the sentiment of lars, even though we use more spatially precise recordings (multi-electrode chronically implanted arrays). So I'm with that. OTOH we can do some cool things like control a computer cursor or tv remote with motor commands like "left-up" etc. Subjects reported that after a while they would cease to "translate" thoughts from movement commands into "BMI" commands like "change channel". It stands to reason they might be able to do the phone-book thing in that case.
Of course, few people find it worthwhile to get chronically implanted electrodes placed in their motor cortex, soooo.
(Of course, this is highly domain-specific and not very convenient. But it does seem possible.)
But what is to me implausible about thinking "phone Mom" and having my computer do it for me is that this scenario envisions an unusually high degree of usability that no consumer-facing software writers have ever achieved. Right now, on a BRAND NEW computer system using mostly application programs recommended by Hacker News readers (for example, I am using Chrome to Web browse), I can't count on my computer doing what I want even if I have my hands on the keyboard or a hand on my mouse. User-interface design appears to be HARD--or at least, it is rarely done right--so I am very doubtful that in five years or even twenty-five years I'll be able to use a computer that really does what I think.
This would take the "butt-dialing" phenomenon to disturbing new levels.
http://www.youtube.com/watch?v=Uyrd0uOuyms
Even giving directions via thought is tricky.
[1] http://asmarterplanet.com/blog/2011/12/the-next-5-in-5-our-f...
The only thing biometric data is really good for is keeping track of people when they don't want to be tracked or want to hide their identity. For example, it would be a useful means of tracking and identifiying people in a prison or a border checkpoint.
"Mind reading" already exists kindof sortof maybe good enough to cnet to write an article about.
This is at the top of my Christmas list: http://emotiv.com/
In fact, here is a comparison of consumer Brain Computer Interfaces: http://en.wikipedia.org/wiki/Comparison_of_consumer_brain%E2...
the first thing I ever saw along these lines: recreating a cat's vision from brain sensors (1999)
On the technical side, it does seem to be the best current option for consumer EEG, though most of these devices are actually strongly influenced by, if not heavily reliant on, facial muscle movements.
Also there was a rather restrictive licence on the out-of-the-box software, which is not very productive for a hardware company.
(I've heard a few people make similar complaints to yours, which is really really saddening to me. Regardless I'm still going to buy one and see what I can do with it :))
Broadly speaking, there are two kinds of tasks that can be easily accomplished; anything involving moving limbs, or simple, low degree of freedom tasks (like moving a computer cursor). After months and months of training, a person can be trained to manipulate numerous degrees with pretty good reliability (i.e., move a robotic arm, AND control the mechanical pincer at the end), but this type of work doesn't generalize to other types of thought. We're nowhere near being able to extract sentences or words or being able to determine what complex scene is being viewed simply using brain activity patterns.
1) P300 - This refers to a predictable change in the EEG signal that happens around 300 milliseconds after something you were expecting happens. For example, if I am looking for a particular letter to flash amongst a grid of letters all randomly flashing, a P300 will be triggered when the letter I want flashes.
2) SSVEP - This stands for steady state visually evoked potential. This approach uses EEG signals recorded from over the visual cortex, which responds to constantly flickering stimuli. Given a few seconds, the power of the frequency of the attended stimulus increases in the EEG, which can then be detected and used to make a decision.
3) SMR - This stands for sensorimotor rhythms, and is an approach that looks for changes in EEG activity over the motor cortex. Successful approaches have been able to identify when you imagine clenching your left or right fists, or pushing down on your foot. Unlike the other two, this does not require external stimuli.
SMR is the most like what we consider mind reading, as the user is initiating the signal while the other two infer what a person is looking at. It is limited to only 2-3 degrees of freedom at the moment, however, and is the hardest signal to work with. It is susceptible to external factors such as the current environment and mental state, and not everyone seems to be able to generate the needed signals. SSVEP, while lacking the wow factor of SMR, is much easier to work with and is a much more stable signal.
Disclosure: I work in this area. Here's a flashy NSF video highlighting our lab: http://www.nsf.gov/news/special_reports/science_nation/brain...
Now taking it a step further I can't even imagine how out of control a computer would be based on someone's mind. Our minds randomly fire off thoughts non-stop - its actually incredibly hard to concentrate on one deliberate thing for a long time (if you've ever tried meditation you realize this very quickly). How a computer could filter actions for it and actions that are just the randomness of the brain seems like it would be incredibly difficult in that there really isn't a definitive line there at all.
It doesn't help, of course, that I'm currently reading this book: http://www.amazon.com/Conspiracy-Against-Human-Race-Contriva...
The luddite in me wishes that science will never be able to fully pick apart the human psyche. Here's to having an inscrutable ghost in the machine to keep us from being mere deterministic flesh-bots...
There have been other times in history that scientists had the idea that science was almost complete, that there were just a few things left to sort out and we'd understand it all (such as around 1900 with mathematics).
We may think we are very near and then discover something new and then find out a lot of new questions around the mind and consciousness. I don't think we're quite there yet.
However I'm sure "shallow AI" (and maybe "shallow mindreading") will become more and more important in the near future. Which is what IBM is focusing on.
BTW: Thanks for the pointer. That book looks very interesting.
I'm actually not so happy about posting that link. For me, it states things that I had already mostly figured out on my own previously. For others, it might zap a lot of Sanity Points.
I would say Ligotti is a very unique writer, in that he's deeply immersed in existentialist philosophy, neuroscience, cognitive psychology, AND lovecraftian horror. It makes for a very... disturbing cocktail.
Of course, everyone on HN is seemingly a Nietzschean overman who can take these kinds of things in stride. Me, not so much :p
Also, if the "basic tenets of existence" (whatever you consider those to be) can be torn down by looking at them critically, shouldn't they be? (Perhaps.)
Should we look at Cthulhu just because we can? :p
It would be interesting to see some calculations how much could be gained that way.
But the really interesting thing in energy in the next 5 years is going to be price drops in storage. We could conceivably see the first lithium-air batteries for cars, which will finally get costs down to within striking distance of petrol. I also suspect we'll start seeing widespread grid storage installations - possibly using sodium-sulphur batteries to absorb and redistribute inputs from distributed renewable sources. The 2-way grid is the next big story in energy.
This isn't just sophistry, but shows there are two problems, 1. to transmit information into and out of a mind; 2. to transform the information into a form that can be understood by another. A common language if you will.
This has analogues in relational databases, where the internal physical storage representation is transformed into a logical representation of relations, from which yet other relations may be transformed; and in integrating heterogeneous web services, where the particular XML or JSON format is the common language and the classes of the programs at the ends are the representation within each mind.
There's no reason to think that the internal representation within each of our minds is terribly similar. It will have some common characteristics, but will likely differ as much as different human languages - or as much as other parts of ourselves, such as our fingerprints. Otherwise, everyone would communicate with that, instead of inventing common languages.
How would we communicate with it? By directly linking our brains together? I don't see why it would have a direct translation into sounds.
See Poe's detective Auguste Dupin, in, for example, "Murders in the Rue Morgue."
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http://www.ted.com/talks/tan_le_a_headset_that_reads_your_br...
So, to summarize in shell-like syntax, you can redirect your output to /dev/null, as in
$ me > /dev/null
but you can't sensibly use a pipe like so:
$ me | /dev/null
This has been a message from your friendly neighborhood Unix fundamentalism/literalism chapter.
$ sudo cp /bin/cat /dev/null
$ echo test | /dev/null
test
(this doesn't actually work)Imagine writing code by thinking only?
But you could imagine an MRI machine that works with lower strength fields and better sensor technology. Imagining one is a far cry from being able to build one though and I don't see this happening in the near future (if at all).
I think this prediction (like most of IBM's predictions about the future) is strong on marketing and very weak on science.