AI Panic!

We have been trying to model our successors robot servants to resemble human beings physically and psychically for a while now. While the psychical development is taking its first steps out of its literal infancy, the physical resemblance has still a long way to go. It has to cross the uncanny valley:

The uncanny valley is a hypothesis that when robots and other facsimiles of humans look and act almost, but not entirely, like actual humans, it causes a response of revulsion among human observers. The “valley” in question is a dip in a proposed graph of the positivity of human reaction as a function of a robot’s lifelikeness.

This valley is the major hurdle towards believable and likeable humanoid model, be it robots, 3D animations or game avatars.

A common bail-out here is to depict characteristics generally considered humanoid by transmuting or exaggerating these features. Comics and the typical Pixar CGI movies are a very good example. The suspension of disbelief is the key factor here: We accept that comic-like depictions are there to interpret reality and show us a filtered, deliberately unrealistic image of the plot. It is very easy for our imagination to fill in the gaps and to ignore physical inaccuracies.

This gets much harder when we try to be as realistic as possible by using correct proportions, complex shading and detailed textures. The movie Beowulf almost perfectly falls into this category: It is completely CGI, but uses real actors and tries to simulate reality. While still-images still look alright, it is the animations where it goes downhill. The trailer has some examples in it, especially the horse animations look wrong, which is much more obvious in the actual movie (while technically not directly a humanoid animation, the galloping horses still add to the feeling that something is wrong with the depicted “reality”).

While not directly concerned with the uncanny valley, some military robots are quite creepy in my opinion. For example the Boston Dynamics “Big Dog”, which somehow looks like two soldiers bending over and pushing against each other. In a sense, it is the opposite to Beowulf: The movement, especially when it tries to regain its balance or slips on ice, looks quite natural, but the visual appearance (and sound) is really disturbing.

Scientists from the MIT are trying - but not quite managing - to avoid the valley with a robot using the comic-approach. They have developed the Nexi, a what they call MDS robot - mobile, dexterous, social. Both the pictures of this robot and the video of Nexi talking and gesticulating look a bit creepy, the robot reminds me of Jigsaw from the movie Saw.

They say that the “purpose of this platform is to support research and education goals in human-robot interaction, teaming, and social learning.”

The antipathy the uncanny valley introduces leads to a potential problem when regarding this social aspect of human-robot interaction: Once humans start to enhance themselves with transhuman enhancements, for example improved eye-sight, nanobots that increase the IQ or prostheses that work better than their natural counterparts, there may be a sudden rift between enhanced and “normal” humans, caused by the antipathy mentioned above. This hypothesis was introduced by Jamais Cascio, who further states that once such technologies gain further distance from human norms, “transhuman” individuals would cease to be judged on human levels and instead be regarded as separate entities altogether (this point is what has been dubbed “posthuman“), and it is here that acceptance would rise once again out of the uncanny valley.

I think the idea of the uncanny valley makes it harder for malicious AIs to undermine human civilisation, as fear of robots is more easily sparked with the help of uncanny-valley-antipathy (AI Panic -1%). However, the concept might be known to an intelligence, and thus we might see robots that does not look like human beings at all - or worse, like our childhood Disney-heroes!

London-based charity Landmine Action wants autonomous robots capable of killing people banned under the same kind of treaty that has outlawed landmines in over 150 countries. According to the New Scientist it is the first time a high profile non-governmental organisation has campaigned against such a technology. This campaign follows the reasoning of Noel Sharkey, who condemned these automation plans earlier this year.

As I’ve written before, the robots in use by the military nowadays (and the next years) are almost fully automatic, but so far the trigger has still to be pulled by a human soldier. However, it is only a question of time until the software is strong enough so that this decision will be made entirely by the machine. And once the software is in place, there will be no ethical opposition - at least in the US Department of Defence, who wants them in future to work without supervision.

A reaction to this news article comes from Wired, where the idea of danger through war robots is dismissed:

But to argue as if this is in the here or now, or even in the next decade, is just plain silly. The Pentagon has not only never advocated taking the man-out-the-loop of targeting decisions for drones or robots, its current policies and procedures would prohibit such a move (some might argue that international law already prohibits autonomous armed drones). [...] Unless and until those policies are drastically altered, it’s safe to say we are safe from renegade Terminators.

To completely ignore the threat by robots with weapons and justifying this ignorance by saying that these robots are still science fiction and it will take decades until these robots appear seems a bit strange to me, especially as Wired itself has reported about existing armed robots before. It is exactly this ignorance and belief that everything is so far away that allows organisations like the military to push these developments without any opposition.

Furthermore, I think it is a little blue-eyed to think that the control of weapons mounted on otherwise fully automated robots will remain in human hands just because the Pentagon does not admit of having plans that say otherwise. By arguing that international law might already prohibit autonomous armed drones and at the same time clearly seeing that these very drones are being used by the U.S. Army in Iraq right now, Wired maneuvers itself on very thin ice. I don’t think it can support the arguments that promises, laws and policies are sufficient enough to protect us from a - what Wired deems nonexistant - danger. And heck, what is so bad about protesting against future dangers as opposed to only trying to fight seeing the effects of existing weapons like landmines in hindsight?

I think it is about time that more voices are raised against automating war machinery, and the Landmine Action has taken a step in the right direction. If it will be heard by the military - and the U.S. Army is without doubt on the forefront of research towards this automation - is a completely different matter. So far, I think the chances are still slim, to specify I say it lowers the AI Panic Level by -0.1%.

The march towards learning, fully functional AI systems has taken another step. A cognitive AI system with the intelligence level of a puppy has been created to learn and perform simple tasks through a robotic arm.

Sure, a puppy is (often) quite stupid, but that achievement should not be underestimated, especially as the researchers at the EU-funded COSPAL project claim that this level of cognition and learning goes beyond the current state of the art.  They combine artificial neural networks (ANNs) to control low-level motor actions and a classical rule-based system to combine these actions to form a plan.

Although this advancement of AI potentially is a step towards a fully aware system, i.e., an AI system that is able to reason and learn from all its surrounding world information (for example through a common sense knowledge database), it is not an unexpected development nor something close to self-awareness, as Michael Felsberg from the research team at Linköping University explains:

In human terms, our robot is probably like a two or three year old child, and it will take a long time for the technology to progress into the equivalent of adulthood. I don’t think we will see it in our lifetimes.

His pessimism shows that Artificial General Intelligence is still quite far out, and while I think he might be overestimating the time-span for it (alas, the Singularity is scheduled earlier than after our lifetimes), he’s still one of the researchers on the forefront of AI research, and thus I think it is safe to say that we will still have to wait quite a while before smart enough AIs appear that could be dangerous (AI Panic -2%).

(Via PhysOrg.com)

If you think that artificial intelligences that actively attack and try to kill its human counterparts are just a hypothetical idea that might never come to reality, you might be mistaken.

The gaming industry has been training gruesome robots, mighty automated armies and deadly opponents for years now. So one might wonder, how dangerous are these algorithms really?

I was inspired to write a bit about this topic by a comment from Horus Aha on last weeks article about Ray Kurzweil’s talk on the Future in Gaming at the Games Developer Conference:

Lots of investment in making game AI’s that are basically sociopathic killers explicitly designed to effectively compete against humans. This applies in 1st person shooters, but also to other genres. The games are networked and it is possible that the AI’s in these games may learn how to game-the-game by finding ways to compete with players outside of game environments. Why not? I don’t think anybody would have taken warnings about “gold-farming” seriously until it was already a reality.

Now, is this fear justified? Are we really endangered by computer game AI?

No.

AI in the entertainment industry is incredibly dumb. The are a couple of reasons for that. Probably the most important is that the game developers do not want an intelligence that can out-reason humans and win all the time: The goal is making an AI that plays to lose, not to win. It is a well-known psychological fact that an opponent that almost beats but eventually loses against the player is most enjoyable for him (There was a good presentation about that from Soren Johnson at this year’s GDC called Playing to Lose: AI and “CIVILIZATION”).

But don’t we need a proper AI to be able to figure out how to achieve this? When you look at the concepts of AI in games and talk to game developers it quickly becomes clear that they don’t even try to make a learning or guessing AI: They cheat! Faking intelligence is a lot easier than actually achieving proper reasoning. In almost all games with incomplete information, i.e., a fog of war or hidden objects, the AI is given full information and only pretends to not know where you are and what you do. And if you see a really smart manoeuvre from the enemy troops (or your virtual team-mates) it is hard-coded or pre-scripted very often. I attended the AI roundtable talks at the GDC in San Francisco two weeks ago and almost none of the attending developers (who worked on Bioshock, Halo3, The Sims, Command & Conquer etc.) has used any of the “proper” academic AI algorithms like neural networks or genetic algorithms.

There are some exceptions, for example Black & White uses a simple reinforcement learning algorithm to make the creature learn from your actions. F.E.A.R. is an often cited example of real planning in a game, however, the used algorithm is really simple and some argue that the resulting behaviour could have been achieved with pre-written scripts just as well.

So there’s no real, potentially dangerous, intelligence in games at all. This is why the AI Panic Level drops by -5%, the “sociopathic killers” will not be able to escape the virtual world of computer games for a long time. If at all, they will become smart only by developments outside the games industry, for example academic research.

This post has nothing directly to do with Artificial Intelligence, but astronomy is one of my other big interests and I thought I’d share the interesting topic of the most powerful explosions in the universe with you.

When someone asks what the biggest, most energetic events in the universe are, Gamma Ray Bursts are a good bet. These incredibly powerful explosions happen when the core of a very massive, fast rotating star collapses to form a black hole and surrounding matter of the outer hulls of the dying star fall towards the black hole. Due to the fast rotation and the acceleration towards the hole, the matter heats up and powers a powerful jet of gamma radiation that blasts outward through the “poles” of the rotating system (see illustration below). At least, that is what the most popular theory of GRBs says, the whole thing is still poorly understood.

The power these bursts have is incredible: If one would happen 6000 light years away from earth, it might cause a mass extinction (according to the History Channel, so take it with a grain of salt!). Also, just some seconds within the beam might cause a lot (some say 30-50%) of earth’s ozone layer to disappear. The whole ozone layer damage we saw in the last decades had only about 5% of the layer disappearing! So, we’d rather not have a GRB happen near us.

The likelihood of such a burst striking earth very slim. GRBs are very rare events, and if a burst happens, the jets are very concentrated and thin. However, the odds are not zero.

Now, there is a binary star system called WR 104 about 8000 light years away from us near the center of the milkyway. After all the introduction about gamma ray bursts and lethal explosions and stuff, it is no coincidence I bring this system up:

The brighter of the two stars might, just maybe kinda possibly, be ready to go GRB on us. It’s not at all clear if it can, and there is reason to believe it can’t (young stars like this one tend to have characteristics that make it very hard for them to form an actual GRB). Also, even if it does blow up that way, the beams are a double-edged sword; yes, they pack an unbelievable punch, but they’re narrow. A GRB would have to be aimed precisely at us to damage us, and the odds of that are pretty low.

Except that for WR 104, it’s possible the star does have us in its sights.

That’s an excerpt from an article Phil Plait wrote about WR 104 in his excellent blog BadAstronomy.com. Phil goes on to say that there are a lot of other variables like the distance, matter between us and the star, the time it will explode and so on which decrease the probability of the star being a direct danger to us substantially. So most likely, nothing is going to happen, and if something happens, it probably won’t affect us at all.

Alas, a Gamma Ray Burst that hits us would most likely mean the end of most life on the planet, and with it the development of an universal AI (thus justifying this astronomy article here, phew!). Therefore such an catastrophic astronomical event (and that includes hits by asteroids, attacks by extraterrestrial lifeforms and so on) decreases the AI Panic Level by -0.1%. Actually I think the danger of these events is still lower, but I don’t want to go into hundredths of percents, and therefore rounded it up.

I hope you bore with me here and don’t find astronomy too boring, I certainly don’t!

At the “Up Experience” conference in Houston, Steve Wozniak had a very pessimistic view on how smart robots are and how long it will take them to become intelligent. In an interview with the Houston Chronicle, he said:

“I don’t think we’re close. I don’t think we’ve gone one step. [...] I think we understand a bare amount of what the mind does.”

A robot that could simulate human life would have to be around for eight or so years before it could have a child’s understanding, he noted.

Steve Wozniak sees the day robots become intelligent (which is, in his eyes, be able to get him a cup of coffee) still far away in the future. Although this opinion could be classified into Kurzweils “linear thinking” category, Wozniak is undeniably an expert in the technology sector. Therefore the AI Panic Level will be reduced by -1%.

Harvard scientists are now trying to map the brain on a neuron level resolution. They hope to use the ‘wiring diagram’, a map of every single neuron and its connections to understand processes of how neurons connect to neighbours, how they select which connections to cut and how the brain works in general.

The story in Wired explains that the researchers are working on mice brain only, because storing the data of a human brain would need “hundreds of petabytes of information, or about the total amount of storage in Google’s data centers“. Additionally, the work required to map the brain is immense, they’ve already built a brain-slicing and photographing robot (shown above).

While a full map of all neurons in a brain might lead to some new insights, for example more accurate clustering of brain regions and statistical data about synapse connections, I very much doubt that this will lead to understanding how the brain works on a bigger scale: Intelligence, Consciousness or just why this big lump of neurons keeps us alive at all are very hard to answer with just a map of connections between cells.

It is like looking at a movie-file with a hex-editor and trying to understand what the plot is. We are still a long way from understanding the brain, it is not likely that artificial intelligence can be derived from this human intelligence analysis: Panic Level adjusted by -0.5%.

Two AI Pioneers. Two Bizarre Suicides. What Really Happened? That’s what Wired wrote some days ago and I just stumbled over.

Chris McKinstry and Pushpinder Singh were both researchers working on common sense knowledge databases that were designed to help instill background knowledge into AI systems. Although they both gathered a lot of entries into their systems, the databases haven’t yet produced remarkable output nor AI systems working with it.

We don’t really know why they both committed suicides in early 2006, but their deaths are likely to be connected, seeing that they are only a month apart and happened under similar circumstances (they taped a bag around their heads and filled it with gas). However, their suicides might have nothing to do with their AI projects, as McKinstry was a very eccentric, attention seeking personality, and Singh had searious health problems that clouded his thoughts.

I wondered if it was appropriate to assign a panic value to this story. The loss of two smart AI researchers working on the task of making common sense knowledge available for AI systems certainly throws the field back a bit and probably delays the development of an understanding AI. As I’m looking at the potential dangers of such an AI in this blog, this leeds to less panic. Of course it is questionable to connect the deaths of two researchers with a state of less panic, whatever that panic might be. And I want to make clear that I don’t think their deaths helped to save the world or were in any other way useful for anything.

However, I do give it a AI Panic Level of -1%, not because McKinstry and Singh are not longer amongst us, but two bright minds stopped working on the forefront of AI research. Of course stopping all research cannot and will not be the answer to the threat of hostile AIs, but from the viewpoint of this blog, it does delay their emergence.

Until recently, the term “artificial life” referred almost exclusively to computer programs, or maybe robots, but the progress being made by synthetic biologists building real cells out of real biological material means that the field is on the cusp of a major step forward, and that this conference has the potential to be a real breakthrough event.

Although this sounds quite impressive, it is not likely to be happening. The announcement of the ALIFE XI conference at Southampton later this year is full of optimism and non-achievement at the same time: Scientists get ‘closer’ to new forms of life, and they try to understand living systems. With the movement to biological cells the focus of the research shifts from a generalising, top-down approach to a bottom-up method: it is a very long way from a living cell to an organism that is remotely capable of what a robot or a computer is today. The state of the art in ALife research is quite far from (and not really focused on) the creation of intelligence. Long way to go still: AI Panic Level drops by -0.1%.

The US company DIAGNOS has made a deal with US Gold to use its technologies in the search for natural gold and silver reserves in Mexico. US Gold is paying $230,000 CDN for this service and will get some juicy bonuses if some precious metals are actually found. The “AI” behind the technology DIAGNOS applies, however, is quite a straight forward approach, in which maps (satellite images, topography, geology, etc.) are weighted and combined into a “prospectivity map”.

This technology might be used to dig holes, but is not ground breaking on the AI side. Statistical learning has been around in for quite a while now and there is lots of research on it. However, it is nice to see some of that research actually applied for useful activities, like exploiting natural resources. The slow speed in which actual AI research results are adopted by commercial companies (possibly with the exception of computer vision, i.e., face recognition) can be linked to the often difficult to understand algorithms and almost always impossible to predict outcomes of them. This inherent complexity of AI algorithms (especially of those that aspire world domination!) prevents fast adaptation by the industry and thus limits research to academia somewhat.The algorithms used by DIAGNOS are no exception of that. There is no danger of them (or any other similar algorithm for that matter) becoming conscious, thus no need to panic: As an example of state of the art applied AI, it shows how far we still are from doomsday events, therefore the AI Panic Level changes by -0.1%.