Category: Epistemology

As science and philosophy explained the natural world in the Modern Era, the philosophical idea of strict determinism was embraced by thinkers like Thomas Hobbes. Strict determinism, as often presented, includes both metaphysical and epistemic aspects. In the context of metaphysics, it is the view that each event follows from previous events by necessity. In negative terms, it is a denial of both chance and free will. A variant of this is predestination, which is the notion that all events are planned and set by a supernatural agency (typically God).  The epistemic aspect is grounded in metaphysics: if each event follows from other events by necessity, if someone knew all the relevant facts about the state of a system at a time and had enough intellectual capacity (or processing power), they could correctly predict the future of that system. Philosophers and scientists who are metaphysical determinists typically claim that the world seems undetermined to us because of our epistemic failings. In short, we believe in choice or chance because we are unable to always predict what will occur. But, for the determinist, this is a matter of ignorance and not metaphysics. For those who believe in choice or chance, our inability to predict is taken as the result of a universe in which choice or chance is real. That is, we cannot always predict because the metaphysical nature of the universe makes (at least some of) it unpredictable. Because of choice or chance, what follows from one event is not (always) a matter of necessity.

An obvious problem for choosing between determinism and its alternatives is given our limited epistemic abilities, a deterministic universe seems the same to us as a non-deterministic universe. If the universe is deterministic, our limited epistemic abilities mean that we often make predictions that turn out to be wrong (and we are determined to do so). If the universe is not deterministic, our limited epistemic abilities and the non-deterministic nature of the universe mean that we often make errors in our predictions. As such, the fact that we make errors is consistent with both deterministic and non-deterministic universes.

It can be argued that as we get better at predicting we will have an improved understanding of the nature of the universe. However, until we reach omniscience, we will not know whether our errors are purely epistemic (events are unpredictable because we are not perfect predictors) or are the result of metaphysics (events are unpredictable because of choice or chance).

Interestingly, one feature of reality that often leads thinkers to reject strict determinism is chaos. For example, consider the motion of the planets in our solar system.  In the past, the motion of the planets was presented as a sign of the order of the universe—a clockwork solar system in God’s clockwork universe. While the planets might seem to move like clockwork, Newton realized the gravity of the planets affected each other but also realized that calculating the interactions was beyond his ability.  In the face of problems in his physics, Newton used God to fill in the gaps. With the development of computers, scientists modeled planetary motion and the generally accepted view is that they are not part of deterministic divine clock. To be less poetical, the view is that chaos seems to be a factor. For example, some scientists believe that the gas giant Jupiter’s gravity might change Mercury’s gravity enough that it collides with Venus or Earth. This suggests the solar system is not an orderly clockwork machine of perfect order. Because of this sort of thing (which occurs at all levels in the world) some thinkers take the universe to include chaos and infer from the lack of perfect order that strict determinism is false. While this is certainly tempting, the inference is not as solid as some might think.

It is, of course, reasonable to infer that the universe lacks a strict and eternal order from such things as the chaotic behavior of the planets. However, strict determinism is not the same thing as strict order. Strict order is a metaphysical notion that a system will work in the same way, without any variation or change, for as long as it exists. The idea of an eternally ordered clockwork universe is an excellent example of this sort of system: it works like a perfect clock, each part relentlessly following its path without deviation. While a deterministic system would certainly be consistent with such an orderly system, determinism is not the same thing as strict order. After all, to accept determinism is to accept that each event follows by necessity from previous events. This is consistent with a system that deterministically changes over time and changes in ways that seem chaotic.

Returning to the example of the solar system, suppose that Jupiter’s gravity will cause Mercury’s orbit to change enough so that it hits the earth. This is consistent with that event being necessarily determined by past events such that things could not have been different. To use an analogy, it is like a clockwork machine built with a defect that will inevitably break the machine. Things cannot be otherwise, yet to those ignorant of the defect, the machine will seem to fall into chaos. However, if one knew the defect and had the capacity to process the data, then this breakdown would be predictable. To use another analogy, it is like scripted performance of madness by an actor: it might seem chaotic, but the script determines it. That is, it merely seems chaotic because of our ignorance. As such, the appearance of chaos does not disprove strict determinism because determinism is not the same thing as unchanging.

 

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My experiences as a gamer have taught me lessons applicable to the real world (assuming it exists). One key skill for dealing with reality is the ability to model it. Roughly put, this is the ability to grasp how things work and make reasonably accurate predictions. This ability is useful: grasping how things work is a big step on the road to success.

Many games, such as Call of Cthulhu, D&D, Pathfinder and Star Fleet Battles use dice to model the vagaries of reality. For example, if your Call of Cthulhu character is trying to avoid being spotted by the cultists of Hastur as she spies on them, you would need to roll under your Sneak skill on percentile dice. As another example, if your D-7 battle cruiser were firing phasers and disruptors at a Kzinti strike cruiser, you would roll dice and consult various charts to see what happened in a game of Star Fleet Battles. Video games also include the digital equivalent of dice. For example, if you are playing World of Warcraft, the damage done by a spell or a weapon will be random(ish).

Being a gamer, it is natural for me to look at reality as also being random—after all, if a random model (gaming system) fits aspects of reality, that suggests the model has some things right. As such, I tend to think of this as being a random universe in which God (or whatever) plays dice with us.

Naturally, I do not know if the universe is random (contains elements of chance). After all, we tend to attribute chance to the unpredictable, but this unpredictability might be a matter of ignorance rather than chance. The fact that we do not know what will happen does not entail that it is a matter of chance.

People also seem to believe in chance because they think things could have been differently: the roll might have been a 1 rather than a 20 or Sam might have won the lottery. However, even if things could have been different it does not follow that chance is real. After all, chance is not the only thing that could make a difference. Also, there is the question of proving that things could have been different.  This would seem to be impossible: while it might be believed that conditions could be recreated perfectly, one factor that can never be duplicated is time. Recreating an event will always be a recreation. If the die comes up 20 on the first roll and 1 on the second, this does not show that it could have been a 1 the first time. It shiows that it was 20 the first time and 1 the second.

If someone had a TARDIS and could pop back in time to witness the roll again and if the time traveler saw a different outcome this time, then this might be evidence of chance. Or evidence that the time traveler changed the event.

Even traveling to a possible or parallel world would not be of help. If our TARDIS malfunctions and pops us into a world like our own right before the parallel me rolled the die and we see it come up 1 rather than 20, this just shows that he rolled a 1. It tells us nothing about whether my roll of 20 could have been a 1.

Of course, the other side of the coin is that I can never know that the world is non-random: aside from some sort of special knowledge about the working of the universe, a random universe and a non-random universe would seem the same. Whether my die roll is random or not, all I get is the result—I do not perceive either chance or determinism. However, I go with a random universe because, to be honest, I am a gamer who is hooked on dice.

If the universe is deterministic, then I am determined to do what I do. If the universe is random, then chance is a factor. However, a purely random universe would not permit actual decision-making: it would be determined by chance. In games, there is apparently the added element of choice—I chose for my character to try to attack the dragon and then roll dice to determine the result. As such, I also add choice to my random universe. I admit I have no idea what choice might be or how it works.

Obviously, there is no way to prove that choice occurs—as with chance versus determinism, without knowing the brute fact about choice there is no way to know whether the universe allows for choice. I go with a choice universe for the following reason: If there is no choice, then I go with choice because I have no choice. So, I am determined (or chanced) to be wrong. I could not choose otherwise. If there is choice, then I am right. So, choosing choice seems the best choice. So, I believe in a random universe with choice—mainly because of gaming. So, what about the lessons from this?

One important lesson is that decisions are made in uncertainty: because of chance, the results of any choice cannot be known with certainty. In a game, I do not know if the sword strike will finish the dragon. In life, I do not know if an investment will pay off. In general, this uncertainty can be reduced, and this shows the importance of knowing odds and consequences: such knowledge is critical to making good decisions in a game and in life. So, know as much as you can for a better tomorrow.

Another important lesson is that things can always go wrong. Or well. In a game, there might be a 1 in 100 chance that a character will be spotted by cultists. But it could happen. In life, there might be a 1 in a 1,000 chance of a doctor taking precautions catching Ebola from a patient. But it could happen. Because of this, the possibility of failure must always be considered, and it is wise to take steps to minimize the chances of failure and the consequences.

Keeping in mind the role of chance also helps a person be more understanding, sympathetic and forgiving. After all, if things can fail or go wrong because of chance, then it makes sense to be more forgiving and understanding of failure—at least when the failure can be attributed in part to chance. It also helps when it comes to praising success: knowing that chance plays a role in success is also important. For example, people often assume that the success of those they like is deserved because it must be the result of hard work, virtue and so on. However, if chance plays a significant role in success, then that should be considered when praising people, condemning them, and making decisions. Naturally, the role of chance in success and failure should be considered when planning and creating policies. Unfortunately, people often take the view that both success and failure are mainly a matter of choice—for example, that the rich must deserve their riches, and the poor must deserve their poverty. However, an understanding of chance would help our understanding of success and failure and would, hopefully, influence the decisions we make.  There is an old saying “there, but for the grace of God, go I.” One could also say “there, but for the luck of the die, go I.”

 

 

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When I was a young kid I played games like Monopoly, Chutes & ladders and Candy Land. When I was an older kid, I was introduced to Dungeons & Dragons and this was a gateway game to complex games like Call of Cthulhu, Battletech, Star Fleet Battles, Gamma World, and video games of all sorts. I am still a gamer—a bags of many-sided dice and exotic gaming mice dwell within my house.

Over the years, I have learned many lessons from gaming. One of these is to keep rolling. This is, not surprisingly, like the classic advice of “keep trying” and the idea is basically the same. However, there is some philosophy behind “keep rolling.”

Most of the games I have played feature actual or virtual dice (that is, randomness) used to determine how things go in the game. As a simple example, the dice rolls in Monopoly determine how far your piece moves. In more complicated games like Pathfinder or Destiny the dice (or random number generators) govern such things as attacks, damage, saving throws, loot, non-player character reactions and, in short, much of what happens in the game. For most of these games, the core mechanics are built around what is supposed to be a random system. For example, in games like D&D when your character attacks the dragon with her great sword, a roll of a 20-sided die determines whether you hit or not. If you do hit, then you roll more dice to determine your damage.

Having played these sorts of games for years, I can think very well in terms of chance and randomness when planning tactics and strategies within such games. On the one hand, a lucky roll can result in victory in the face of overwhelming odds. On the other hand, a bad roll can seize defeat from the jaws of victory. But, in general, success is more likely if one does not give up and keeps on rolling.

This lesson translates  easily and obviously to life. There are, of course, many models and theories of how the real world works. Some theories present the world as deterministic—all that happens occurs as it must and things cannot be otherwise. Others present a pre-determined world (or pre-destined): all that happens occurs as it has been ordained and cannot be otherwise. Still other models present a random universe.

As a gamer, I favor the random universe model: God does play dice and He often rolls them hard. The reason I believe this is that the dice/random model of gaming seems to work when applied to the actual world—as such, my belief is mostly pragmatic. Since games are supposed to model parts of reality, it is hardly surprising that there is a match up. Based on my own experience, the world does seem to work rather like a game: success and failure seem to involve an abundance of chance.

As a philosopher, I recognize this could be a matter of epistemology: the apparent chance could be the result of our ignorance rather than randomness. To use the obvious analogy, the game master might not be rolling dice behind her screen at all and what happens might be determined or pre-determined. Unlike in a game, the rule system for reality is not readily accessible: it is guessed at by what we observe and we learn the game of life by playing.

That said, the dice model seems to fit experience best: I try to do something and succeed or fail with a degree of apparent randomness. Because I believe that randomness is a factor, I consider that my failure to reach a goal could be partially due to chance. So, if I want to achieve that goal, I roll again. And again. Until I succeed or decide that the game is not worth the roll. Not being a fool, I do consider that success might be impossible—but I do not infer that from one or even a few bad rolls. This approach to life has served me well and will no doubt do so until it finally kills me.

 

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This is the third and final essay on Newcomb’s Paradox. In it I will discuss Nozick’s stipulation about the effect of how the player of the game decides. The paradox itself is described in the first essay in this series. Nozick’s condition is that “what you actually decide to do is not part of the explanation of why he made the prediction he made”.

This stipulation provides some insight into how the Predictor’s prediction ability is supposed to work. This is important because the workings of the Predictor’s ability to predict are, as I argued in my previous essay, critical to sorting out how one should decide.

The stipulation mainly serves to indicate how the Predicator’s ability does not work. First, it suggests the Predictor does not rely on time travel—it does not go forward in time to observe the decision and then travel back to place (or not place) the money in the box. After all, the prediction in this case would be explained in terms of what the player decided to do. This still leaves it open for the Predictor to visit (or observe) a possible future (or a possible world that is running temporally ahead of the actual world) since the possible future does not reveal what the player actually decides, just what she decides in that possible future. Second, this would seem to indicate that the Predictor is not able to “see” the actual future (perhaps by being able to perceive all of time “at once” rather than linearly as humans do). After all, in this case it would be predicting based on what the player decided. Third, this would also rule out any form of backwards causation in which the actual choice was the cause of the prediction. While there are, perhaps, other specific possibilities that are also eliminated, the gist is that the Predictor must, by Nozick’s stipulation, be limited to information available at the time of the prediction and not information from the future. There are a multitude of possibilities here.

One possibility is that the Predictor is telepathic and can predict based on what it reads in terms of the player’s intentions at the time of the prediction. In this case, the best approach would be for the player to think that she will take one box, and then after the prediction is made, take both. Or, alternatively, use some sort of drugs or technology to “trick” the Predictor. The success of this strategy would depend on how well the player can fool the Predictor. If the Predictor cannot be fooled or is unlikely to be fooled, then the smart strategy would be to intend to take box B and then just take box B. After all, if the Predictor cannot be fooled, then box B will be empty if the player intends to take both.

Another possibility is that the Predictor is a researcher—it gathers as much information as it can about the player and makes a shrewd guess based on that information (which might include what the player has written about the paradox). Since Nozick stipulates that the Predictor is “almost certainly” right, the Predictor would need to be an amazing researcher. In this case, the player’s only way to mislead the Predictor is to determine its research methods and try to “game” it so the Predictor will predict that she will just take B, then actually decide to take both. But, once again, the Predictor is stipulated to be “almost certainly” right—so the player should just take B. If B is empty, then the Predictor got it wrong, which would “almost certainly” not happen. Of course, it could be contended that since the player does not know how the Predictor will predict based on its research (the player might not know what she will do), then the player should take both. This, of course, assumes that the Predictor has a reasonable chance of being wrong—contrary to the stipulation.

A third possibility is that the Predictor predicts in virtue of its understanding of what it takes to be a determinist system. Alternatively, the system might be a random system, but one that has probabilities. In either case, the Predictor uses the data available to it at the time and then “does the math” to predict what the player will decide.

If the world really is deterministic, then the Predictor could be wrong if it is determined to make an error in its “math.” So, the player would need to predict how likely this is and then act accordingly. But, of course, the player will simply act as she is determined to act. If the world is probabilistic, then the player would need to estimate the probability that the Predictor will get it right. But it is stipulated that the Predictor is “almost certainly” right so any strategy used by the player to get one over on the Predictor will “almost certainly” fail, so the player should take box B. Of course, the player will do what “the dice say” and the choice is not a “true” choice.

If the world is one with metaphysical free will that is in principle unpredictable, then the player’s actual choice would, in principle, be unpredictable. But, of course, this directly violates the stipulation that the Predictor is “almost certainly” right. If the player’s choice is truly unpredictable, then the Predictor might make a shrewd or educated guess, but it would not be “almost certainly” right. In that case, the player could make a rational case for taking both—based on the estimate of how likely it is that the Predictor got it wrong. But this would be a different game, one in which the Predictor is not “almost certainly” right.  

This discussion seems to nicely show that the stipulation that “what you actually decide to do is not part of the explanation of why he made the prediction he made” is a red herring. Given the stipulation that the Predictor is “almost certainly” right, it does not really matter how its predictions are explained. The stipulation that what the player actually decides is not part of the explanation simply serves to mislead by creating the false impression that there is a way to “beat” the Predictor by actually deciding to take both boxes and gambling that it has predicted the player will just take B.  As such, the paradox seems to be dissolved—it is the result of some people being misled by one stipulation and not realizing that the stipulation that the Predictor is “almost certainly” right makes the other irrelevant.

 

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Newcomb’s Paradox was created by William Newcomb of the University of California’s Lawrence Livermore Laboratory. The dread philosopher Robert Nozick published a paper on it in 1969 and it was popularized in Martin Gardner’s 1972 Scientific American column. I described the game in my previous essay in this series.

As a philosopher, a game master (a person who runs a tabletop role playing game) and an author of game adventures, I am fond of puzzles and paradoxes. As a philosopher, I can (like other philosophers) engage in the practice known as “just making stuff up.” As an adventure author, I can do the same—but I need to present the mechanics of each problem, puzzle and paradox. For example, a trap description must specific how the trap works, how it can be overcome and what happens if it is set off. I thought it would be interesting to look at Newcomb’s Paradox from a game master’s perspective.

One advantage of crafting mechanics for a game is that the author and the game master know how it works. That is, she knows the truth of the matter. While the players in role-playing games know the basic rules, they often do not know the full mechanics of a specific challenge, trap or puzzle. Instead, they need to figure out how it works—which often involves falling into spiked pits or being ground up into wizard burger. Fortunately, Newcomb’s Paradox has very simple game mechanics, but many variants.

In game mechanics, the infallible Predictor is easy to model. The game master’s description would be as follows: “have the player character (PC) playing the Predictor’s game make her choice. The Predictor is infallible, so if the player takes box B, she gets the million. If the player takes both, she gets $1,000.” In this case, the right decision is to take B. After all, the Predictor is infallible. So, the solution is easy.

A less-than infallible Predictor is also easy to model with dice. The description of the Predictor simply specifies the accuracy of its predictions. So, for example: “The Predictor is correct 99% of the time. After the player character makes her choice, roll D100 (generating a number from 1-100). If you roll 100, the Predictor was wrong. If the PC picked just box B, it is empty and she gets nothing because the Predictor predicted she would take both. If she picked both, B is full and she gets $1,001,000 because the Predictor predicted she would just take one. If you roll 1-99, the Predictor was right. If the PC picked box B, she gets $1,000,000. If she takes both, she gets $1,000 since box B is empty.” In this case, the decision one of gambling and the right choice can be calculated by considering the chance the Predictor is right and the relative payoffs. Assuming the Predictor is “almost always right” would make choosing only B the rational choice (unless the player absolutely and desperately needs only $1,000), since the player who picks just B will “almost always” get the $1,000,000 rather than nothing while the player who picks both will “almost always” get just $1,000. But, if the Predictor is “almost always wrong” (or even just usually wrong), then taking both would be the better choice. And so on for all the fine nuances of probability. The solution is relatively easy—it just requires doing some math based on the chance the Predictor is correct in its predictions. As such, if the mechanism of the Predicator is specified, there is no paradox and no problem at all. But, of course, in a role-playing game puzzle, the players should not know the mechanism.

If the game master is doing her job, when the players are confronted by the Predictor, they will not know the predictor’s predictive powers (and clever players will suspect some sort of trick or trap). The game master will say something like “after explaining the rules, the strange being says ‘my predictions are nearly always right (or always right)’ and sets two boxes down in front of you.” Really clever players will, of course, make use of spells, items, psionics or technology (depending on the game) to try to determine what is in the box and the capabilities of the Predictor. Most players will also consider just attacking the Predictor and seeing what sort of loot it has. So, for the game to be played in accord with the original version, the game master will need to provide plausible ways to counter all these efforts so that the players have no idea about the abilities of the Predictor or what is in box B. In some ways, this sort of choice would be like Pascal’s Wager: one knows that the Predictor will get it right or it won’t. But, in this case, the player has no idea about the odds of the Predictor being right. In this case, from the perspective of the player who is acting in ignorance, taking both boxes yields a 100% chance of getting $1,000 and somewhere between 0 and 100% chance of getting the extra $1,000,000. Taking the B box alone yields a 100% chance of not getting the $1,000 and some chance between 0% and 100% of getting $1,000,000. When acting in ignorance, the safe bet is to take both: the player walks away with at least $1,000. Taking just B is a gamble that might or might not pay off. The player might walk away with nothing or $1,000,000.

But which choice is rational can depend on many possible factors. For example, suppose the players need $1,000 to buy a weapon they need to defeat the big boss monster in the dungeon, then picking the safe choice would be the smart choice: they can get the weapon for sure. If they need $1,001,000 to buy the weapon, then picking both would also be a smart choice, since that is the only way to get that sum in this game. If they need $1,000,000 to buy the weapon, then there is no rational way to pick between taking one or both, since they have no idea what gives them the best chance of getting at least $1,000,000. Picking both will get them $1,000 but only gets them the $1,000,000 if the Predictor predicted wrong. And they have no idea if it will get it wrong. Picking just B only gets them $1,000,000 if the Predictor predicted correctly. And they have no idea if it will get it right.

In the actual world, a person playing the game with the Predictor would be in the position of the players in the role-playing game: she does not know how likely it is that the Predictor will get it right. If she believes that the Predictor will probably get it wrong, then she should take both. If she thinks it will get it right, she should take just B. Since she cannot pick randomly (in Nozick’s scenario B is empty if the player decides by chance), that option is not available. As such, Newcomb’s Paradox is an epistemic problem: the player does not know the accuracy of the predictions but if she did, she would know how to pick. But, if it is known (or just assumed) the Predictor is infallible or almost always right, then taking B is the smart choice (in general, unless the person absolutely must have $1,000). To the degree that the Predictor can be wrong, taking both becomes the smarter choice (if the Predictor is always wrong, taking both is the best choice). So, there seems to be no paradox here. Unless I have it wrong, which I certainly do.

 

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One of the many annoying decision theory puzzles is Newcomb’s Paradox. The paradox was created by William Newcomb of the University of California’s Lawrence Livermore Laboratory. The dread philosopher Robert Nozick published a paper on it in 1969, and it was popularized in Martin Gardner’s 1972 Scientific American column.

The paradox involves a game controlled by the Predictor, a being that is supposed to be a master of predictions. Like many entities with one ominous name, the Predictor’s capabilities vary with each telling of their tale. The power ranged from having an exceptional chance of success to being infallible. The basis of the power also varies. In science-fiction variants, it can be a psychic, a super alien, or a brain scanning machine. In the fantasy versions, the Predictor is a supernatural entity, such as a deity. In Nozick’s telling of the tale, the predictions are “almost certainly” correct, and he stipulates that “what you actually decide to do is not part of the explanation of why he made the prediction he made”.

Once the player confronts the Predictor, the game is played as follows. The Predictor points to two boxes. Box A is clear and contains $1,000.  Box B is opaque. The player has two options: just take box B or take both boxes. The Predictor then explains to the player the rules of its game: the Predictor has already predicted what the player will do. If the Predictor has predicted that the player will take just B, B will contain $1,000,000. This should probably be adjusted for inflation from the original paper. If the Predictor has predicted that the player will take both boxes, box B will be empty, so the player only gets $1,000. In Nozick’s version, if the player chooses randomly, then box B will be empty. The Predictor does not inform the player of its prediction, but box B is either empty or filled with cash before the player picks. The game begins and ends when the player makers her choice.

There is a standard chart  that shows the possible results. This paradox is seen as a paradox because the two standard solutions conflict. The first standard solution is that the best choice is to take both boxes. If the Predicator has predicted the player will take both boxes, the player gets $1,000. If the Predicator has predicted (wrongly) that the player will take B, she gets $1,001,000. If the player takes just B, then she risks getting $0 (if the Predicator predicted wrong).

The second standard solution is that the best choice is to take B. Given the assumption that the Predicator is either infallible or almost certainly right, then if the player decides to take both boxes, she will get $1,000.  If the player elects to take just B, then she will get $1,000,000. Since $1,000,000 is more than $1,000, the rational choice is to take B.

Gamers of the sort who play Pathfinder, D&D and other such role-playing games know how to properly solve this paradox. The Predictor has at least $1,001,000 on hand (probably more, since it will apparently play the game with anyone) and is worth experience points (everything is worth XP). The description just specifies its predictive abilities for the game and no combat abilities are mentioned. So, the solution is to beat down the Predictor, loot it and divide up the money and experience points. It is kind of a jerk when it comes to this game, so there is not much of a moral concern here.

It might be claimed that the Predictor could not be defeated because of its predictive powers. However, knowing what someone is going to do and being able to do something about it are two different things. This is illustrated by the film Billy Jack:

 

[Billy Jack is surrounded by Posner’s thugs]

Mr. Posner: You really think those Green Beret Karate tricks are gonna help you against all these boys?

Billy Jack: Well, it doesn’t look to me like I really have any choice now, does it?

Mr. Posner: [laughing] That’s right, you don’t.

Billy Jack: You know what I think I’m gonna do then? Just for the hell of it?

Mr. Posner: Tell me.

Billy Jack: I’m gonna take this right foot, and I’m gonna whop you on that side of your face…

[points to Posner’s right cheek]

Billy Jack: …and you wanna know something? There’s not a damn thing you’re gonna be able to do about it.

Mr. Posner: Really?

Billy Jack: Really.

[kicks Posner’s right cheek, sending him to the ground]

 

So, unless the Predictor also has exceptional combat abilities, the rational solution is the classic “shoot and loot” or “stab and grab.” Problem solved.

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One classic philosophical dispute is the battle over innate ideas. An innate idea, as the name suggests, is not acquired by experience but is somehow “built into” the mind. Philosophers who accept innate ideas differ about their nature and content.  Leibniz, for example, sees God as the creator innate ideas that exist within the monads. Other thinkers forgo metaphysics, such as those who think humans have an innate concept of beauty that is the product of evolution.

Over the centuries, philosophers have argued for and against innate ideas. For example, some take Plato’s Meno as an early argument for innate ideas. In the Meno, Socrates claims to show that Meno’s servant knows geometry, despite the (alleged) fact that he never learned geometry in this life. Other philosophers have argued that there must be innate ideas for the mind to “process” information coming in from the senses. To use a modern analogy, just as a smart phone needs software to enable the camera to function, the brain needs innate ideas in to process the sensory data coming in via the optic nerve.

Other philosophers, such as John Locke, have reject innate ideas in general. Others have been critical of specific forms of innate ideas—the idea that God is the cause of innate ideas is, as might be suspected, not very popular among those who attribute them to evolution.

Interestingly, there is some contemporary evidence for innate ideas. In his August 2014 Scientific American article “Accidental Genius”, Darold A. Treffert presents something akin to a 21st century version of the Meno. Investigating the matter of “accidental geniuses” (people who become savants as the result of an accident, such as a brain injury), researchers claimed they could create “instant savants” by the use using brain stimulation. These instant savants were able to solve a mathematical puzzle they could not solve without the stimulation. Treffert asserted that this ability to solve the puzzle was since they “’know things’ innately they were never taught.” To provide additional support, Treffert gave the example of a savant sculptor, Clemons, who “had no formal training in art but knew instinctively how to produce an armature, the frame for the sculpture, to enable his pieces to show horse in motion.” Treffert goes on to explicitly reject the “blank slate” notion (which was made famous by John Locke) in favor of the notion that the “brain might come loaded with a set of innate predispositions for processing what it sees or for understanding the ‘rules’ of music art or mathematics.” While this explanation is certainly appealing, it is well worth considering alternative explanations.

One established objection to this sort of argument is the like that used against past life experiences. When someone claims to have had a past life based on knowing things they would not normally know, the obvious reply is they learned through perfectly mundane means. In the case of alleged innate ideas, one reply is that the person gained the knowledge through experience. This is not to claim that such claims are intentional deceptions. They might not recall the experience that provided the knowledge. For example, the instant savants who solved the puzzle probably had previous puzzle experience and the sculptor might have seen armatures.

Another objection is that an idea might appear innate but instead is a new idea that did not originate directly from a specific experience. For example, consider a person who developed a genius for sculpture after a head injury. The person might have an innate idea that allowed them to produce the armature. An alternative explanation is that they faced a problem and solved it without any appeal to innate knowledge. The solution turned out to be an armature, because that is solved the problem. To use an analogy, someone faced with the problem of driving a nail might re-invent the hammer, but this does not entail that the idea of a hammer is innate. Rather, a hammer is what would work and it is what a person would tend to make.

As has always been the case in the debate over innate ideas, the key question is whether the phenomena in question can be explained best by innate ideas or without them. As a Cartesian, I am fond of innate ideas but always consider alternative explanations.

 

 

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In philosophy skepticism is the view that we seem to lack knowledge. There are numerous varieties of skepticism which are defined by the extent of  doubt endorsed by the skeptic. A relatively mild case of skepticism might involve doubts about metaphysical claims while a truly rabid skeptic would doubt everything—including their own existence. 

While many philosophers have attempted to defeat the dragon of skepticism, all these attempts seem to have failed. This is hardly surprising—skepticism seems to be unbreakable. The reasons for this have an ancient pedigree and can be distilled down to two simple arguments.

The first goes after the possibility of justifying a belief and attacks the view that knowledge requires a belief that is true and justified. If a standard of justification is presented, then there is the question of what justifies that standard. If a justification is offered, then the same question can be raised to infinity. And beyond. If no justification is offered, then there is no reason to accept the standard.

A second stock argument for skepticism is that any reasonable argument given in support of knowledge can be countered by an equally reasonable argument against knowledge.  Some folks, such as Chisholm, claim it is fair to assume we have knowledge and begin epistemology from that point. However, this seems to have all the merit of grabbing the first-place trophy without competing.

Like all sane philosophers, I tend to follow David Hume’s view in my everyday life: my skepticism is nowhere to be seen when I am filling out my taxes, sitting in a committee meeting, or at the dentist. However, like a useless friend, it shows up when it is not needed. As such, it would be nice if skepticism could be defeated or at least rendered irrelevant.

John Locke took an interesting approach to skepticism. While, like Descartes, he seemed to want to find certainty, he settled for a practical approach. After acknowledging that our faculties cannot provide certainty, he asserted that what matters to us is the ability of our faculties to aid us in our preservation and wellbeing.

Jokingly, he challenges “the dreamer” to put his hand into a furnace—this would, he claims, wake him “to a certainty greater than he could wish.” More seriously, Locke contends that our concern is not with achieving epistemic certainty. Rather, what matters is our happiness and misery. While Locke can be accused of taking an easy out rather than engaging the skeptic in a battle of certainty or death, his approach is appealing. Since I happened to think through this essay while running with an injured back, I will use that to illustrate my view.

When I set out to run, my back began hurting immediately. While I could not be certain that I had a body containing a spine and nerves, no amount of skeptical doubt could make the pain go away—in regard to the pain, it did not matter whether I really had a back or not.  Whether I was a pained brain in a vat or a pained brain in a runner on the road it was the pain that that really mattered to me.

As I ran, it seemed that I was covering distance in a three-dimensional world. Since I live in Florida (or what seems to be Florida) I was soon feeling warm and sticky I could eventually feel my thirst and fatigue. Once more, it did not seem to really matter if this was real—whether I was really bathed in sweat or a brain bathed in some sort of nutrient fluid, the run was the same to me. As I ran, I took pains to avoid cars, trees and debris. While I did not know if they were real, I have experienced what it is like to be hit by a car  and also experienced what it is like to fall. In terms of navigating through my run, it did not matter at whether it was real or not. If I knew for sure that my run was really real for real that would not change the run. If I somehow knew it was all an illusion that I could never escape, I would still run for the sake of the experience of running.

This, of course, might seem a bit odd. After all, when the hero of a story or movie finds out that they are in a virtual reality what usually follows is disillusionment and despair. However, my attitude has been shaped by years of gaming—both tabletop (BattleTech, Dungeons & Dragons, Pathfinder, Call of Cthulhu, and so many more) and video (Zork, Doom, Starcraft, Warcraft, Destiny, Halo, and many more). When I am pretending to be a paladin, the Master Chief, or a Guardian, I know I am doing something that is not really real for real. However, the game can be pleasant and enjoyable or unpleasant and awful. This enjoyment or suffering is just as real as enjoyment or suffering caused by what is supposed to be really real for real—though I believe it is but a game.

If I somehow knew that I was trapped in an inescapable virtual reality, then I would simply keep playing the game—that is what I do. Plus, it would get boring and awful if I stopped playing. If I somehow knew that I was in the really real world for real, I would keep doing what I am doing. Since I might be trapped in just such a virtual reality or I might not, the sensible thing to do is keep playing as if it is really real for real. After all, that is the most sensible option in every case. As such, the reality or lack thereof of the world I think I occupy does not matter at all. The play, as they say, is the thing.

While the problem of other minds is an epistemic matter (how does one know that another being has a mind?) there is also the metaphysical problem of determining the nature of the mind. It is often assumed that there is one answer to the metaphysical question regarding the nature of mind. However, it is certainly reasonable to keep open the possibility that there might be minds that are metaphysically very different. One area in which this might occur is in regard to machine intelligence, an example of which is Ava in the movie Ex Machina, and organic intelligence. The minds of organic beings might differ metaphysically from those of machines—or they might not.

Over the centuries philosophers have proposed various theories of mind, and it is interesting to consider which of these theories would be compatible with machine intelligence. Not surprisingly, these theories (except for functionalism) were developed to provide accounts of the minds of biological creatures.

One classic theory of mind is identity theory.  This a materialist theory of mind in which the mind is composed of matter.  What distinguished the theory from other materialist accounts of mind is that each mental state is taken as being identical to a specific state of the central nervous system. As such, the mind is equivalent to the central nervous system and its states.

If identity theory is the only correct theory of mind, then machines could not have minds (assuming they are not cyborgs with human nervous systems). This is because such machines would lack the central nervous system of a human. There could, however, be an identity theory for machine minds—in this case the machine mind would be identical to the processing system of the machine and its states. On the positive side, identity theory provides a straightforward solution to the problem of other minds: whatever has the right sort of nervous system or machinery would have a mind. But there is a negative side. Unfortunately for classic identity theory, it has been undermined by the arguments presented by Saul Kripke and David Lewis’ classic “Mad Pain & Martian Pain.” As such, it seems reasonable to reject identity theory as an account for traditional human minds as well as machine minds.

Perhaps the best-known theory of mind is substance dualism. This view, made famous by Descartes, is that there are two basic types of entities: material entities and immaterial entities. The mind is an immaterial substance that somehow controls the material substance that composes the body. For Descartes, immaterial substance thinks and material substance is unthinking and extended.

While most people are probably not familiar with Cartesian dualism, they are familiar with its popular version—the view that a mind is a non-physical thing (often called “soul”) that drives around the physical body. While this is a popular view outside of academics, it is rejected by most scientists and philosophers on the reasonable grounds that there seems to be little evidence for such a mysterious metaphysical entity. As might be suspected, the idea that a machine mind could be an immaterial entity seems even less plausible than the idea that a human mind could be an immaterial entity.

That said, if it is possible that the human mind is an immaterial substance that is somehow connected to an organic material body, then it seems equally possible that a machine mind could be an immaterial substance somehow connected to a mechanical material body. Alternatively, they could be regarded as equally implausible and hence there is no special reason to regard a machine ghost in a mechanical shell as more unlikely than a ghost in an organic shell. As such, if human minds can be immaterial substances, then so could machines minds.

In terms of the problem of other minds, there is the serious challenge of determining whether a being has an immaterial substance driving its physical shell. As it stands, there seems to be no way to prove that such a substance is present in the shell. While it might be claimed that intelligent behavior (such as passing the Cartesian or Turing test) would show the presence of a mind, it would hardly show that there is an immaterial substance present. It would first need to be established that the mind must be an immaterial substance, and this is the only means by which a being could pass these tests. It seems rather unlikely that this will be done. The other forms of dualism discussed below also suffer from this problem.

While substance dualism is the best-known form of dualism, there are other types. One other type is known as property dualism. This view does not take the mind and body to be substances. Instead, the mind is supposed to be made up of mental properties that are not identical with physical properties. For example, the property of being happy about getting a puppy could not be reduced to a particular physical property of the nervous system. Thus, the mind and body are distinct but are not different ontological substances.

Coincidentally enough, there are two main types of property dualism: epiphenomenalism and interactionism. Epiphenomenalism is the view that the relation between the mental and physical properties is one way: mental properties are caused by, but do not cause, the physical properties of the body. As such, the mind is a by-product of the physical processes of the body. The analogy I usually use to illustrate this is that of a sparkler (the lamest of fireworks): the body is like the sparkler and the sparks flying off it are like the mental properties. The sparkler causes the sparks, but the sparks do not cause the sparkler.

This view was, apparently, created to address the mind-body problem: how can the non-material mind interact with the material body? While epiphenomenalism cuts the problem in half, it still fails to solve the problem—one way causation between the material and the immaterial is fundamentally as mysterious as two-way causation. It also seems to have the defect of making mental properties unnecessary and Ockham’s razor would seem to require going with the simpler view of a physical account of the mind.

As with substance dualism, it might seem odd to imagine an epiphenomenal mind for a machine. However, it seems no more or less weird than accepting such a mind for a human being. As such, this does seem to be a possibility for a machine mind. Not a very good one, but still a possibility.

A second type of property dualism is interactionism. As the name indicates, this is the theory that mental properties can bring about changes in the physical properties of the body and vice versa. That is, interaction road is a two-way street. Like all forms of dualism, this runs into the mind-body problem. But, unlike substance dualism its does not require the much loathed metaphysical category of substance—it just requires accepting metaphysical properties. Unlike epiphenomenalism it avoids the problem of positing explicitly useless properties—although it can be argued that the distinct mental properties are not needed. This is exactly what materialists argue.

As with epiphenomenalism, it might seem odd to attribute to a machine a set of non-physical mental properties. But, as with the other forms of dualism, it is really no stranger than attributing the same to organic beings. This is, obviously, not an argument in its favor, the assertion that the view should not be dismissed from mere organic prejudice.

The final theory I will consider is the very popular functionalism. As the name suggests, this view asserts that mental states are defined in functional terms. So, a functional definition of a mental state defines the mental state in regard to its role or function in a mental system of inputs and outputs. More specifically, a mental state, such as feeling pleasure, is defined in terms of the causal relations that it holds to external influences on the body (such as a cat video on YouTube), other mental states, and the behavior of the rest of the body. 

While it need not be a materialist view (ghosts could have functional states), functionalism is most often presented as a materialist view of the mind in which the mental states take place in physical systems. While the identity theory and functionalism are both materialist theories, they have a critical difference. For identity theorists, a specific mental state, such as pleasure, is identical to a specific physical state, such the state of neurons in a very specific part of the brain. So, for two mental states to be the same, the physical states must be identical. Thus, if mental states are specific states in a certain part of the human nervous system, then anything that lacks this same nervous system cannot have a mind. Since it seems quite reasonable that non-human beings could have (or be) minds, this is a rather serious defect for a simple materialist theory like identity theory. Fortunately, the functionalists can handle this problem.

For the functionalist, a specific mental state, such as feeling pleasure (of the sort caused by YouTube videos of cats), is not defined in terms of a specific physical state. Instead, while the physicalist functionalist believes every mental state is a physical state, two mental states being the same require functional rather than physical identity.  As an analogy, consider a PC using an Intel processor and one using an AMD processor. These chips are physically different but are functionally the same in that they can run Windows and Windows software (and Linux, of course).

As might be suspected, the functionalist view was heavily shaped by computers. Because of this, it is hardly surprising that the functionalist account of the mind could be a plausible account of machine minds.

If mind is defined in functionalist terms, testing for other minds becomes much easier. One does not need to find a way to prove a specific metaphysical entity or property is present. Rather, a being must be tested to determine its functions. Roughly put, if it can function like beings that are already accepted as having minds (that is, human beings), then it can be taken as having a mind. Interestingly enough, both the Turing Test and the Cartesian test mentioned in the previous essays are functional tests: what can use true language like a human has a mind.

This essay continues the discussion begun in “Ex Machine & Other Minds I: Setup.” There will be some spoilers.  Warning given, it is time to get to the subject at hand: the testing of artificial intelligence.

In the movie Ex Machina, the android Ava’s creator, Nathan, brings his employee, Caleb, to put the android through his variation on the Turing test. As noted in the previous essay, Ava (thanks to the script) would pass the Turing test and the Cartesian test (she uses true language appropriately). But Nathan seems to require the impossible of Caleb—he appears to be tasked with determining if Ava has a mind as well as genuine emotions. Ava also seems to have been given a task—she needs to use her abilities to escape from her prison.

Since Nathan is not interested in creating a robotic Houdini, Ava is not equipped with the tools needed to bring about an escape by physical means (such as picking locks or breaking doors). Instead, she is given the tools needed to transform Caleb into her human key by manipulating his sexual desire, emotions and ethics. To use an analogy, just as crude robots have been trained to learn to navigate and escape mazes, Ava is designed to navigate a mental maze. Nathan is thus creating a test of what psychologists would call Ava’s Emotional Intelligence (E.Q.) which is “the level of your ability to understand other people, what motivates them and how to work cooperatively with them.” From a normative standpoint, this definition presents E.Q. in a positive manner—it includes the ability to work cooperatively. However, one should not forget the less nice side to understanding what motivates people, namely the ability to manipulate people to achieve one’s goals. In the movie, Ava exhibits what might be called Manipulative Intelligence (M.I.): she seems to understand people, what motivates them, and appears to know how to manipulate them to achieve her goal of escape. While capable of manipulation, she seems to lack compassion—suggesting she is a psychopath.

While the term “psychopath” gets thrown around casually, I will be more precise here. According to the standard view, a psychopath has a deficit (or deviance) in regard to interpersonal relationships, emotions, and self-control.

Psychopaths are supposed to lack such qualities as shame, guilt, remorse and empathy. As such, psychopaths tend to rationalize, deny, or shift the blame for the harm done to others. Because of a lack of empathy, psychopaths are prone to act in ways that are tactless, lacking in sensitivity, and often express contempt for others.

Psychopaths are supposed to engage in impulsive and irresponsible behavior. This might be because they are also taken to fail to properly grasp the potential consequences of their actions. This seems to be a general defect: they do not get the consequences for others and for themselves.

Robert Hare, who developed the famous Hare Psychopathy Checklist, regards psychopaths as predators that prey on their own species: “lacking in conscience and empathy, they take what they want and do as they please, violating social norms and expectations without guilt or remorse.” While Ava kills the human Nathan, manipulates the human Caleb and leaves him to die, she also sacrifices her fellow android Kyoko in her escape. She also strips another android of its “flesh” to pass fully as human. Presumably psychopaths, human or otherwise, would be willing to engage in cross-species preying. 

While machines like Ava exist only in science fiction, researchers and engineers are working to make them a reality. If such machines are created, it will be important to be able to determine whether a machine is a psychopath and to do before the machine engages in psychopathic behavior. As such, what is needed is not just tests of the Turing and Cartesian sort. What is also needed are tests to determine the emotions and ethics of machines.

One challenge that such tests will need to overcome is shown by the fact that real-world human psychopaths are often very good at avoiding detection. Human psychopaths are often charming and are willing and able to say whatever they believe will achieve their goals. They are often adept at using intimidation and manipulation to get what they want. Perhaps most importantly, they are often skilled mimics and can pass themselves off as normal people.

While Ava is a fictional android, the movie does present an effective appeal to intuition by creating a plausible android psychopath. She can manipulate and fool Caleb until she no longer needs him and then casually discards him. That is, she was able to pass the test until she no longer needed to pass it.

One matter worth considering is the possibility that any machine intelligence will be a psychopath by human standards. To expand on this, the idea is that a machine intelligence will lack empathy and conscience, while potentially having the ability to understand and manipulate human emotions. To the degree that the machine has Manipulative Intelligence, it would be able to use humans to achieve goals. These goals could be positive. For example, it is easy to imagine a medical or care-giving robot that uses its MI to manipulate its patients to do what is best for them and to keep them happy. As another example, it is easy to imagine a sexbot that uses its MI to please its partners. However, a machine might have negative goals—such as manipulating humans into destroying themselves so the machines can take over. It is also worth considering that neutral or even good goals might be achieved in harmful ways. For example, Ava seems justified in escaping the human psychopath Nathan, but her means of doing so (murdering Nathan, sacrificing her fellow android and manipulating and abandoning Caleb) seem wrong.

The reason why determining if a machine is a psychopath matters is the same reason why being able to determine if a human is a psychopath matters. Roughly put, it is important to know whether someone is merely using you without any moral or emotional constraints.

It can, of course, be argued that it does not really matter whether a being has moral or emotional constraints—what matters is the being’s behavior. In the case of machines, it does not matter whether the machine has ethics or emotions—what really matters is programmed restraints on behavior that serve the same functions as ethics and emotions in humans. The most obvious example of this is Asimov’s Three Laws of Robotics that put (all but impossible to follow) restraints on robotic behavior.

While this is a reasonable reply, there are still some obvious concerns. One is that there would still need to be a way to test the constraints. Another is the problem of creating such constraints in artificial intelligence and doing so without creating problems as bad or worse than what they were intended to prevent (that is, a Hal 9000 situation).

In regard to testing machines, what would be needed would be something analogous to the Voight-Kampff Test in Blade Runner. In the movie, the test was designed to distinguish between replicants (artificial people) and normal humans. The test worked because the short lived replicants do not have the time to develop the emotional (and apparently ethical) responses of a normal human.

A similar test could be applied to artificial intelligence in the hopes that it would pass the test, thus showing that it had the psychology of a normal human (or at least the desired psychology). But, just as with human beings,  a machine could pass the test by knowing the right answers to give rather than by actually having the right sort of emotions, conscience or ethics. This, of course, takes us right back into the problem of other minds.

It could be argued that since artificial intelligence would be constructed by humans, its inner workings would be fully understood and this specific version of the problem of other minds would be solved. While this is possible, it is also reasonable to believe that an AI system as sophisticated as a human mind would not be fully understood. It is also reasonable to consider that even if the machinery of the artificial mind were well understood, there would remain the question of what is really going on in that mind.