Good point, but the fact that humans are consequentialists (at least partly) doesn't seem to make the problem much easier. Suppose we replace Yvain's blue-minimizer robot with a simple consequentialist robot that has the same behavior (let's say it models the world as a 2D grid of cells that have intrinsic color, it always predicts that any blue cell that it shoots at will turn some other color, and its utility function assigns negative utility to the existence of blue cells). What does this robot "actually want", given that the world is not really a 2D grid of cells that have intrinsic color?

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steven0461's comment notwithstanding, I can take a guess at what the robot actually wants. I think it wants to take the action that will minimize the number of blue cells existing in the world, according to the robot's current model of the world. That rule for choosing actions probably doesn't correspond to any coherent utility function over the real world, but that's not really a surprise.

The interesting question that you probably meant to ask is whether the robot's utility function over its model of the world can be converted to a utility function over t... (read more)

15steven04619yWho cares about the question what the robot "actually wants"? Certainly not the robot. Humans care about the question what they "actually want", but that's because they have additional structure that this robot lacks. But with humans, you're not limited to just looking at what they do on auto-pilot; instead, you can just ask the aforementioned structure when you run into problems like this. For example, if you asked me what I really wanted under some weird ontology change, I could say, "I have some guesses, but I don't really know; I would like to defer to a smarter version of me". That's how I understand preference extrapolation: not as something that looks at what your behavior suggests that you're trying to do and then does it better, but as something that poses the question of what you want to some system you'd like to answer the question for you. It looks to me like there's a mistaken tendency among many people here, including some very smart people, to say that I'd be irrational to let my stated preferences deviate from my revealed preferences; that just because I seem to be trying to do something (in some sense like: when my behavior isn't being controlled much by the output of moral philosophy, I can be modeled as a relatively good fit to a robot with some particular utility function), that's a reason for me to do it even if I decide that I don't want to. But rational utility maximizers get to be indifferent to whatever the heck they want, including their own preferences [], so it's hard for me to see why the underdeterminedness of the true preferences of robots like this should bother me at all. Insert standard low confidence about me posting claims on complicated topics that others seem to disagree with.
1Vladimir_Nesov9y(Reading this comment [] first might be helpful.) To answer your thought experiment. It doesn't matter what the agent thinks it's acting based on, we look at it from the outside instead (but using a particular definition/dependence that specifies the agent), and ask how its action depends on the dependence of the actual future on its actual action. Agent's misconceptions don't enter this question. If the misconceptions are great, it'll turn out that the dependence of actual future on agent's action doesn't control its action, or controls it in some unexpected way. Alternatively, we could say that it's not the actual future that is morally relevant for the agent, but some other strange fact, in which case the agent could be said to be optimizing a world that is not ours. From yet another perspective, the role of the action could be played by something else, but then it's not clear why we are considering such a model and talking about this particular actual agent at the same time.

The Blue-Minimizing Robot

by Scott Alexander 3 min read4th Jul 2011161 comments


Imagine a robot with a turret-mounted camera and laser. Each moment, it is programmed to move forward a certain distance and perform a sweep with its camera. As it sweeps, the robot continuously analyzes the average RGB value of the pixels in the camera image; if the blue component passes a certain threshold, the robot stops, fires its laser at the part of the world corresponding to the blue area in the camera image, and then continues on its way.

Watching the robot's behavior, we would conclude that this is a robot that destroys blue objects. Maybe it is a surgical robot that destroys cancer cells marked by a blue dye; maybe it was built by the Department of Homeland Security to fight a group of terrorists who wear blue uniforms. Whatever. The point is that we would analyze this robot in terms of its goals, and in those terms we would be tempted to call this robot a blue-minimizer: a machine that exists solely to reduce the amount of blue objects in the world.

Suppose the robot had human level intelligence in some side module, but no access to its own source code; that it could learn about itself only through observing its own actions. The robot might come to the same conclusions we did: that it is a blue-minimizer, set upon a holy quest to rid the world of the scourge of blue objects.

But now stick the robot in a room with a hologram projector. The hologram projector (which is itself gray) projects a hologram of a blue object five meters in front of it. The robot's camera detects the projector, but its RGB value is harmless and the robot does not fire. Then the robot's camera detects the blue hologram and zaps it. We arrange for the robot to enter this room several times, and each time it ignores the projector and zaps the hologram, without effect.

Here the robot is failing at its goal of being a blue-minimizer. The right way to reduce the amount of blue in the universe is to destroy the projector; instead its beams flit harmlessly through the hologram.

Again, give the robot human level intelligence. Teach it exactly what a hologram projector is and how it works. Now what happens? Exactly the same thing - the robot executes its code, which says to scan the room until its camera registers blue, then shoot its laser.

In fact, there are many ways to subvert this robot. What if we put a lens over its camera which inverts the image, so that white appears as black, red as green, blue as yellow, and so on? The robot will not shoot us with its laser to prevent such a violation (unless we happen to be wearing blue clothes when we approach) - its entire program was detailed in the first paragraph, and there's nothing about resisting lens alterations. Nor will the robot correct itself and shoot only at objects that appear yellow - its entire program was detailed in the first paragraph, and there's nothing about correcting its program for new lenses. The robot will continue to zap objects that register a blue RGB value; but now it'll be shooting at anything that is yellow.

The human-level intelligence version of the robot will notice its vision has been inverted. It will know it is shooting yellow objects. It will know it is failing at its original goal of blue-minimization. And maybe if it had previously decided it was on a holy quest to rid the world of blue, it will be deeply horrified and ashamed of its actions. It will wonder why it has suddenly started to deviate from this quest, and why it just can't work up the will to destroy blue objects anymore.

The robot goes to Quirinus Quirrell, who explains that robots don't really care about minimizing the color blue. They only care about status and power, and pretend to care about minimizing blue in order to impress potential allies.

The robot goes to Robin Hanson, who explains that there are really multiple agents within the robot. One of them wants to minimize the color blue, the other wants to minimize the color yellow. Maybe the two of them can make peace, and agree to minimize yellow one day and blue the next?

The robot goes to Anna Salamon, who explains that robots are not automatically strategic, and that if it wants to achieve its goal it will have to learn special techniques to keep focus on it.

I think all of these explanations hold part of the puzzle, but that the most fundamental explanation is that the mistake began as soon as we started calling it a "blue-minimizing robot". This is not because its utility function doesn't exactly correspond to blue-minimization: even if we try to assign it a ponderous function like "minimize the color represented as blue within your current visual system, except in the case of holograms" it will be a case of overfitting a curve. The robot is not maximizing or minimizing anything. It does exactly what it says in its program: find something that appears blue and shoot it with a laser. If its human handlers (or itself) want to interpret that as goal directed behavior, well, that's their problem.

It may be that the robot was created to achieve a specific goal. It may be that the Department of Homeland Security programmed it to attack blue-uniformed terrorists who had no access to hologram projectors or inversion lenses. But to assign the goal of "blue minimization" to the robot is a confusion of levels: this was a goal of the Department of Homeland Security, which became a lost purpose as soon as it was represented in the form of code.

The robot is a behavior-executor, not a utility-maximizer.

In the rest of this sequence, I want to expand upon this idea. I'll start by discussing some of the foundations of behaviorism, one of the earliest theories to treat people as behavior-executors. I'll go into some of the implications for the "easy problem" of consciousness and philosophy of mind. I'll very briefly discuss the philosophical debate around eliminativism and a few eliminativist schools. Then I'll go into why we feel like we have goals and preferences and what to do about them.