Author: Michael LaBossiere

The right to vote is part of the foundation of democracy and this includes the right to have one’s vote count. One part of protecting this right is preventing voter fraud. Fraud can rob legitimate voters of their right to decide the election. Another part is preventing voter suppression because it can rob people of their votes.

Republicans profess to be very worried about voter and election fraud (by Democrats) and have enacted laws aimed they claim will reducing such fraud. In response, Democrats claim these laws are aimed at voter suppression. Each side accuses the other of having wicked political motives. Many Democrats see Republicans as trying to disenfranchise voters who tend to vote for Democrats. The Republicans counter, without evidence, that Democrats support fraud because it is in their favor. While these beliefs might be sincere, sincerity is irrelevant to truth. What matters are the reasons and evidence that support the belief. As such, I will look at the available evidence and endeavor to sort out the matter.

One point of contention is the extent of voter fraud. One longstanding Republican talking point is that voter fraud is widespread.  For example, on April 7, 2014 Dick Morris claimed that over 1 million people voted twice in 2012. If this was true, then it would be a very serious matter: widespread voter fraud could change the results of elections and rob voters of their right to decide. Democrats admit fraud does occur but at such a miniscule level that it has no effect on election outcomes and does not warrant the measures favored by the Republicans.

Settling this matter requires looking at the available facts.  Dick Morris’ claim (which made the rounds as a conservative talking point), is false. But the fact that Morris was astoundingly wrong does not prove that voter fraud is not widespread. However, the facts do. Despite years of searching for fraud, the Republicans have not found any evidence (other their own efforts to overturn the 2020 election).

Republicans argue for voter ID laws by claiming they will prevent fraud. However, past investigations of voter fraud has shown only 31 credible cases out of one billion ballots. As such, this sort of fraud does occur—but only at an incredibly low rate.

In general, significant (let alone widespread) voter fraud does not occur although the myth is widespread. Republican claims about voter fraud are based on a myth and shows the lack of foundation for their claims and proposals regarding the matter. And yet they persist in their fairy tales of fraud.

It might be argued that while voter fraud is insignificant, it still must be countered by laws and policy changes, such as requiring voter IDs and eliminating early voting.  This has some appeal. To use an analogy, even if only a fraction of 1% of students cheated, then professors should still take some effort to prevent that cheating for the sake of academic integrity. Unless, of course, the measures used to counter that cheating did more harm than the cheating. The same would seem to apply to measures to counter voter fraud.

A key moral issue here is whether it is more important to prevent fraud or to prevent disenfranchisement. This is analogous to the moral concern about guilt in the legal system. In the United States, there is (supposed to be) a presumption of innocence on the moral grounds that it is better that a guilty person goes free than an innocent person be unjustly punished. In the case of voting, should it be accepted that it is better that a legitimate voter be denied her vote rather than an illegitimate voter be allowed to get away with fraud? Or is it better that an illegitimate voter gets away with fraud then to deny a legitimate voter her right to vote?

My moral conviction is that it is more important to prevent disenfranchisement and this should be given greater weight than fraud prevention. To avoid a straw man attack, I must say I am against fraud and favor rational safeguards against it. However, given the minuscule rates of fraud if attempts to reduce it result in disenfranchisement, then I would oppose such attempts on moral grounds. Naturally, others take a different view and believe it is worth disenfranchising voters in an (alleged) attempt to reduce the minuscule rates of fraud to even more miniscule levels.

Returning to the matter of facts, one  important concern is whether the laws and policies in question result in voter suppression. If they do not, even if they do nothing to counter voter fraud, then they might be tolerable (assuming they do not come with other costs).

But the evidence shows the laws allegedly aimed at preventing voter fraud serve as voter suppression measures, mostly aimed at minority voters. Keith Bentele and Erin E. O’Brien published a study entitled “Jim Crow 2.0? Why States Consider and Adopt Restrictive Voter Access Policies.” Based on their analysis of the data, they concluded “the Republican Party has engaged in strategic demobilization efforts in response to changing demographics, shifting electoral fortunes, and an internal rightward ideological drift among the party faithful.” The full study, from the journal Perspectives on Politics, is available here. Since this is a factual matter, those who disagree with these findings can counter this by providing an analysis of equal or greater credibility based on supported facts. Since the 2013 study, Republicans have increased their efforts to fight “fraud” and Trump has made it clear he wants Republicans to do anything they can to ensure Republican victories through such means as redistricting and various strategies that are obviously aimed at voter suppression.

It is a talking point among Republicans that most professors are tools of the Democrats and academic experts should not be trusted. While this has been an effective ad homimen, what is needed is evidence and arguments countering the claims.  If professors are tools of the Democrats and academic experts are not to be trusted, then it should be easy to provide credible, objective evidence and analysis showing that they are in error.

One of the best-known methods proposed to counter voter fraud is the voter ID law. While, as shown above, the sort of fraud that would be prevented by these laws almost never occurs, it serves to disenfranchise voters. As would be suspected, Hispanic and African-American voters are more likely than white Americans to lack the ID required by these laws.

Another approach is to make it harder for citizens to register. One example is restrictions on voter registration drives—Hispanics and African-Americans register to vote at twice the rate of whites via drives. It is not clear how these methods would reduce fraud. The restrictions mostly do not seem to be aimed at making it harder for people to register fraudulently—just to make it more inconvenient to register at all.

A third tactic is to reduce the available early voting times and eliminate weekend and evening voting. This would seem to have no effect on fraud but seems aimed at minority voting patterns. In 2008 70% of African-American voters in North Carolina cast their ballots early.  Minority voters are more likely than white voters to vote on weekends and in the evening. For example, 56% of the 2008 weekend voters in Cuyahoga County in Ohio were black.

A fourth tactic is to make it harder for people with past convictions to regain their voting rights. This impacts African Americans the most. This tactic does not prevent fraud—it merely denies people the right to vote.

The laws and policies allegedly aimed at voter fraud would not reduce the existing fraud (which is already miniscule) and the only effect would be to suppress voting. As such, these laws and proposals fail to protect the rights of voters and instead are a violation of that basic right. In short, they are either a misguided and failed effort to prevent fraud or a wicked and potentially successful effort to suppress voters in favor of Republican victories. Either way, these laws and policies are a violation of a fundamental right of American democracy.

 

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 While most Americans do not vote, there is still in question of how a voter should vote. While I have opinions about the candidates and issues in the upcoming election in my adopted state of Florida, this essay is not aimed at convincing you to vote as I will. Rather, my goal is to discuss how you should vote in general.

The answer to the question of how you should vote is easy: if you are rational, then you should vote in your rational self-interest. In the case of a candidate, you should vote for the candidate you believe will act in your self-interest. In the case of such things as ballot measures, you should vote for or against based on how you believe it will impact your self-interest. So, roughly put, you should vote for what you think is best for you.

While this is obvious advice, it does bring up two often overlooked concerns. The first is the determining what is actually in your self-interest. The second is determining whether your decision is in your self-interest. In the case of a candidate, the concern is whether the candidate will act in your self-interest. In the case of things like ballot measures, the question is whether the measure will be advantageous to your interests or not.

It might be thought that a person knows what is in her self-interest. Unfortunately, people can be wrong about this. In most cases people assume that if they want or like something, then it is in their self-interest. But what a person likes or wants might not be what is best for them. For example, a person might like the idea of cutting school funding without considering how it will impact her family and community. In contrast, what people do not want, or dislike is often assumed to be against their self-interest. But what a person dislikes or does not want might not be bad for her. For example, a person might dislike the idea of an increased minimum wage and vote against it without considering whether it would be in their self-interest or not. The take-away is that a person needs to look beyond what they like or dislike, want or do not want to determine their actual self-interest.

It is natural to think that of what is in a person’s self interest in selfish terms. That is, in terms of what seems to benefit only the person without considering its effect on others. While this is one way to look at self-interest, it is worth considering what might seem to be in a person’s selfish interest could be against her self-interest. For example, a business owner might see paying taxes to fund public education as being against her self-interest because it seems to have no direct, selfish benefit to her. However, having educated fellow citizens would seem to be in her self-interest and even in her selfish interest. Having the state pay for the education of her workers is advantageous to her—even if she has to contribute a little through her taxes. As another example, a person might see paying taxes for public health programs and medical aid to foreign countries as against her self-interest because she has her own medical coverage and does not travel to those countries. However, as has been shown with Ebola, public and world health is in her interest—unless she lives in total isolation. As such, even the selfish should consider whether their selfishness in a matter is actually in their self-interest.

It is also worth considering a view of self-interest that is more altruistic. That is, that a person’s interest is not just in her individual advantages but also in the general good. For this sort of person, providing for the common defense and securing the general welfare would be in her self-interest because her self-interest goes beyond just herself.

So, a person should sort out her self-interest and consider that it might not just be a matter of what she likes, wants or sees as in her selfish advantage. The next step is to determine which candidate is most likely to act in her self-interest and which vote on a ballot measure is most likely to serve her self-interest.

Political candidates, obviously enough, try to convince their target voters that they will act in their interest. Those backing ballot measures also do their best to convince voters that voting a certain way is in their self-interest. However, the evidence shows that most politicians do not act in the interest of the majority of those who voted for them. Researchers at Princeton and Northwestern conducted a study, “Testing Theories of American Politics: Elites, Interest Groups, and Average Citizens”, to determine whether politicians acted based on the preferences of the majority. The researchers examined about 1,800 policies and matched them against the preferences expressed by three classes: the average American (50th income percentile), the affluent American (the 90th percentile of income) and the large special interest groups.

The results are hardly surprising: “The central point that emerges from our research is that economic elites and organized groups representing business interests have substantial independent impacts on US government policy, while mass-based interest groups and average citizens have little or no independent influence.” This suggests that voters are bad at selecting candidates who will act in their interest. Or, to be fair and balanced, perhaps there are few  candidates who will do so.

It can be countered that the study just shows that politicians generally act contrary to the preferences of the majority but not that they act contrary to their self-interest. After all, I made the point that what people want (prefer) might not be what is in their self-interest. But, on the face of it, unless what is in the interest of the majority is that the affluent get their way, then it seems that the politicians voters choose generally do not act in the best interest of the voters. This would suggest that voters should pick different candidates and that better people should run for office.

 

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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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As I have written in other essays, the Dungeons & Dragons alignment system is surprisingly useful for categorizing people in the real world. This time I will look at chaotic evil.

In fantasy games, players often encounter chaotic evil foes—these include classic enemies ranging from the lowly goblin to the terrifyingly powerful demon lord. Chaotic evil foes are usually good choices for those who write adventures—no matter what alignment the party happens to be, almost no one has a problem with killing chaotic evil creatures. Especially other chaotic evil creatures. Fortunately, chaotic evil is not as common in the actual world as it is in game world. In the game system, chaotic evil is defined as follows:

 

A chaotic evil character is driven entirely by her own anger and needs. She is thoughtless in her actions and acts on whims, regardless of the suffering it causes others.

In many ways, a chaotic evil character is pinned down by her inherent nature to be unpredictable. She is like a spreading fire, a coming storm, an untested sword blade. An extreme chaotic evil character tends to find similarly minded individuals to be with—not out of any need for company, but because there is a familiarity in this chaos, and she relishes the opportunity to be true to her nature with others who share that delight.

 

The chaotic evil person differs from the lawful evil person in their view of law. While they are both evil, the lawful evil person is committed to order, tradition and hierarchy. As such, lawful evil types can create, lead and live in organized states (and all real-world states have lawful evil aspects). They can get along with others. In contrast, chaotic evil types have no commitment to order, tradition or hierarchy. But they can be compelled. For example, if the threat of punishment is sufficient, a chaotic evil type will obey those with greater power. Chaotic evil types do like order, tradition and hierarchy in the same way that arsonists like things that burn—without these things, the chaotic evil type would have much less to destroy.

Lawful evil types do often find chaotic evil types useful for specific tasks, although those wise about evil are aware of the dangers of using such tools. For example, a well-organized terrorist group or corporation might have lawful evil leadership. However, they will find many uses for the chaotic evil types. A lawful evil type is generally not likely to strap on an explosive vest and run into a crowd, but a chaotic evil person might. Lawful evil types also sometimes need people to create chaos so that they can then impose more order—the chaotic evil are the right people for this job. But, as noted, chaotic evil people can get out of hand—they are not constrained by order or even rational selfishness. This is why the smart lawful evil types do their best to see to it that the chaotic evil types do not outlive their usefulness.

The chaotic evil person differs from the neutral evil person in terms of their view of chaos. While the chaotic evil and neutral evil are both selfish and care nothing for others, the neutral evil person tends to be more rational and calculating in her selfishness. A neutral evil person can have excellent self-control and conceal her true nature to achieve her selfish and evil ends. Chaotic evil types lack that self-control and find it hard to conceal their true nature—that takes a discipline that the chaotic, by their nature, lack. President Trump provides an excellent real-world example of a chaotic evil person, although his followers might envision him as awful good.

The neutral evil see society as having instrumental value for them—but their selfishness means that they will take actions that can destroy society. The chaotic evil person sees no value in society other than as presenting a target rich environment for their evil. In our world, chaotic evil types tend to be those who commit horrific crimes, endeavor to corrupt and destroy nations, or engage in acts of brutal terror.

While chaotic evil types are chaotic and evil, they can take up the mantle of a cause and purport to be acting for some greater good. However, their actions disprove their claims about their alleged commitment to anything good. They might take up a religious or political cause to assuage whatever shreds of conscience they might still retain—or do so as part of their chaotic game.

In an orderly society that does not need the chaotic evil people to do evil tasks, smarter chaotic evil types try to hide from the authorities—though their nature drives them to commit evil. Those that are less clever commit their misdeeds and are quickly caught. The cleverer might never be caught and become legends. Fortunately for the chaotic evil (and unfortunately for everyone else), they have plenty of opportunities to act on their alignment. There are always organizations that are happy to have them and there are always places where they can act in accord with their true natures—often with the support and blessings of the authority. In the end, though many are willing to make use of their morality, no rational person wants the chaotic evil around.

 

 

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As noted in other essays I’ve written on the subject, it is often useful to look at the actual world in terms of the D&D alignment system. In this essay, I will look at the alignment that many players find the most annoying: lawful good (or, as some call it, “awful good”).

Pathfinder, which is a version of the D20 D&D system, presents the alignment as follows:

 

A lawful good character believes in honor. A code or faith that she has unshakable belief in likely guides her. She would rather die than betray that faith, and the most extreme followers of this alignment are willing (sometimes even happy) to become martyrs.

A lawful good character at the extreme end of the lawful-chaotic spectrum can seem pitiless. She may become obsessive about delivering justice, thinking nothing of dedicating herself to chasing a wicked dragon across the world or pursuing a devil into Hell. She can come across as a taskmaster, bent upon her aims without swerving, and may see others who are less committed as weak. Though she may seem austere, even harsh, she is always consistent, working from her doctrine or faith. Hers is a world of order, and she obeys superiors and finds it almost impossible to believe there’s any bad in them. She may be more easily duped by such imposters, but in the end she will see justice is done—by her own hand if necessary.

 

In the fantasy worlds of role-playing games, the exemplar of the lawful good alignment is the classic paladin. Played properly, a paladin character is a paragon of virtue, a force of righteousness, a defender of the innocent and a pain in the party’s collective ass. This is because the paladin and, to a somewhat lesser extent, all lawful good characters are very strict about being good. They are usually willing to impose their goodness on the party, even when this means that the party must take more risks, do things the hard way, or forgo some gain. For example, lawful good characters usually insist on destroying evil magical items or sealing them away, even when they could be cashed in for stacks of gold.

In terms of actual world moral theories, lawful good tends to closely match virtue theory: the objective is to be a paragon of virtue and all that entails. In actual game play, players tend to (knowingly or unknowingly) embrace the sort of deontology (rules-based ethics) made famous by our good dead friend Immanuel Kant. On this view, morality is about duty and obligations, the innate worth of people, and the need to take action because it is right (rather than expedient or prudent). Like Kant, lawful good types tend to be absolutists—there is one and only one correct solution to any moral problem and there are no exceptions. The lawful good types also tend to reject consequentialism—while the consequences of actions are not ignored (except by the most fanatical of the lawful good), what ultimately matters is whether the act is good in and of itself.

In the actual world, a some purport to be lawful good—that is, they claim to be devoted to honor, goodness, and order. Politicians, not surprisingly, often try to cast themselves, their causes and their countries in these terms. As might be suspected, most of these people are trying to deceive others or themselves—they mistake their prejudices for goodness and their love of power for a devotion to a just order.  While those skilled at deceiving others are dangerous, those who have convinced themselves of their own goodness can be far more dangerous: they are willing to destroy all who oppose them for they believe that those people must be evil.

Fortunately, there are some lawful good types in the world. These are the people who sincerely work for just, fair and honorable systems of order, be they nations, legal systems, faiths or organizations. While they can seem a bit fanatical at times, they do not cross over into the evil that serves as a key component of true fanaticism.

Neutral good types tend to see the lawful good types as being too worried about order and obedience. The chaotic good types respect the goodness of the lawful good types, but find their obsession with hierarchy, order and rules oppressive. However, good creatures do their best to avoid willingly and knowingly harming other good creatures. So, while a chaotic good person might be critical of a lawful good organization, she would probably not try to destroy it. 

Chaotic evil types are the antithesis of the lawful good types and they are devoted enemies. The chaotic evil folks hate the order and goodness of the lawful good, and delight in destroying them. Many in the Trump regime seem to embrace chaos and evil.

Neutral evil types are opposed to the goodness of the lawful good but can be adept at exploiting both the lawful and good aspects of the lawful good. Of course, the selfishly evil need to avoid exposure, since the good will not willingly suffer their presence.

Lawful evil types can often get along with the lawful good types in serving the cause of order. Both respect tradition, authority and order—although they do so for very different reasons. Classic American Republicans and Democrats tended to be lawful evil. Bill Clinton, for example, seems to abide by this alignment although some might see him as more lawful neutral.  Lawful evil types often have compunctions that can make them seem to have some goodness and the lawful good are sometimes willing to see such compunctions as signs of the possibility of redemption. In general, the lawful good and lawful evil are most likely to be willing to work together at the societal level. For example, they might form an alliance against a chaotic evil threat to their nation. Inevitably, though, the lawful good and lawful evil must end up in conflict.  Which is as it should be.

 

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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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Having been in academics for quite some time, I have seen fads come, go and stick. Way back in 2004 I witnessed the arrival of assessment at my university. While I initially thought it might be a passing fad, almost a quarter century later I am still serving (in perpetuity) on the General Education Assessment committee and completing yearly assessment plans and reports for Philosophy & Religion. As with all such things, assessment arrived with acronyms and buzz words. Those more cynical than I would say that all acronyms of administrative origin (AAO) amount to B.S. But I would not say such a thing. While I diligently engage in assessment, I am still aware of reasonable concerns about it.

One concern was succinctly put by a fellow philosopher: “you don’t fatten the pig by weighing it.” The criticism behind this homespun remark is that time spent on assessment is time taken from the core function of education, namely education. At the K-12 level, the burden of assessment and evaluation has become quite onerous in many places. At the higher education level, the burden is not as great—but we spend considerable time on it.

A sensible reply is that assessment is both valuable and necessary: if the effectiveness (or ineffectiveness) of education is not assessed, then there would be no way of knowing what is working and what is not. A counter is that educators assessed their efforts before the rise of modern assessment and there is the question as to whether these new efforts have improved education.

Another concern is that in addition to the time spent by faculty on assessment, a bureaucracy of assessment was created. Some schools have entire offices devoted to assessment complete with staff and administrators. With higher education facing financial woes and students confronting ever increasing tuition rates, it could be argued that assessment should be cut in favor of better serving the core mission of the university. A reply is to argue that funding an assessment office is more important to serving the core mission of the university than more faculty or lower tuition would be.

Another common concern is that assessment is part of the micromanagement of public education imposed by state legislatures. These are, unsurprisingly, usually the same legislators who speak loudly about getting government off peoples’ backs and cutting regulations (for business). This, some critics contend, is part of a campaign to discredit and damage public education.

One reply is that a state legislature has the right to insist that public schools provide evidence that the (ever-decreasing) public money is being well spent. If the legislatures showed real concern for the quality of education and were committed to public education, this reply would have considerable merit.

A final concern is that the results of the previous assessment must be applied to improve each academic program, and this seems to rest on an assumption of perpetual improvement. Unfortunately, due to budget cuts and administrative policies, faculty rarely get raises and salary compresence is a serious problem.  So faculty are supposed to better each year, but get paid less because inflation and the rising cost of living reduces the value of the salary each year. As such, the system demands perpetual improvement of faculty and schools, but there are usually no incentives or rewards—other than not getting fired or not being punished. Interestingly, the folks imposing this system claim that taxation and government impositions hurt business. That is, they seem to think it is bad for businesses to have less money and be regulated too much by the state, then it will be bad. This view does not extend to education. But there might be an ironic source of hope as education is being “businessified” and perhaps once the transformation is complete, the universities will get the love showered on corporations.

 

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The United States persists in waging and endless war on drugs and faces ever increasing and problems with higher education. I will reconsider an immodest proposal I made years ago intended to address both problems.

In the case of higher education, one problem is that the cost of education exceeds the resources of many Americans. One reason is that America’s political and economic elites repeatedly blow up the economy and have been engaged in an unrelenting extermination of the middle class. Another reason is the view that higher education has been cast as a private (rather than public) good and is seen by the elites as just another area to exploit for profit. Because of this, funding to public schools has been reduced and funding has been diverted from public schools to costly and ineffective for-profit schools. Yet another reason is that public universities have an ever-expanding administrative burden. Even the darling of academics, STEM, has seen significant cuts in support and public funding.

Through their war on drugs, the rulers have imposed a massive cost on the United States. First, there is the cost of the resources devoted to policing citizens, trying them and incarcerating them for drug crimes. Second, there is the cost of the social and personal damage done to individuals and communities. From the perspective of most citizens, the war on drugs has been a losing fight—mainly because “we have met the enemy and he is us.”

Fortunately, I have a solution to both problems. Years ago, I spoke with an engineering student about Florida State’s various programs aimed at creating businesses and heard a piece on NPR about the financial woes of schools and how faculty and staff were being pushed to be fund-raisers for schools. Unsurprisingly, things are even worse now.

This got me thinking about how universities could generate funding and I remembered a running joke from long ago. Back when universities started to commit to  “businessification, I joked with a running friend (hence a running joke) that we faculty members should become drug lords to fund our research and classes. While I do not think that I should become a drug lord, I would propose that public universities get into the drug business.

States should begin by legalizing marijuana and pass a general law allowing recreational drugs that can be shown to be as safe as tobacco and alcohol (that sets the bar very low).  The main restriction will be that the drugs can only be produced and sold by public universities. All the profits will go directly to the universities, to be used as decided by boards composed of students and faculty. To be realistic, the ruling elites would need to get a cut of this, but I’ll leave the corruption aspects to others.

To implement this plan, faculty and students should be actively involved. Business faculty and students would develop the models, plans and proposals. Design and marketing students and faculty will handle those aspects. Faculty and students in chemistry, biology and medicine will develop the drugs and endeavor to make them safer. Faculty and students in agriculture will see to the growing of the crops, starting with marijuana. Engineering students and faculty will develop hydroponics and other technology.

Once the marijuana and other drugs are available, the universities will sell the products to the public with all profits being used to fund the educational and research aspects of the universities. Since the schools are public universities, the drugs will be tax-free—there is no sense in incurring the extra cost of collecting taxes when the money is going to the schools already. Since schools already have brand marketing, this can be easily tied in. For example, Florida State can sell Seminole Gold and Seminole Garnet marijuana, while my own Florida A&M University can have Rattler Green and Rattler Orange.

One practical objection is that the operation might not be profitable. While this is obviously a reasonable concern, the drug trade can be very profitable. Also, by making such drugs legal, the cost of the war on drugs would drop, thus potentially freeing up resources for education and reducing the harms done to individuals and the community.  So, I am not too worried about this.

One reasonable objection is that drugs are unhealthy. The easy reply is that while this is true, we already tolerate unhealthy products such as tobacco, alcohol, cars and firearms. If these are tolerable, then the drugs sold by the schools (which must be at least as safe as tobacco and alcohol) would also be tolerable. The war on drugs is also very unhealthy—so scaling back the war would be good for public health.

One moral objection is that drugs are immoral. There are three easy replies. The first is that the drugs in question are no more immoral than alcohol and tobacco. If these can be morally tolerated, then so can the university drugs. Second, there is the consequentialist argument: if drugs are going to be used anyway by Americans, it is better that the money go to education rather than ending up in the coffers of criminals, gangs, terrorists and the prison-industrial complex. Third, there is also the consequentialist argument that university produced drugs will be safer and of higher quality than drugs produced by drug lords, gangs, terrorists and criminal dealers. Given the good consequences of legalizing university-manufactured drugs, this plan is clearly morally commendable.

Given the above arguments, having universities as legal drug sellers would clearly help solve two of America’s serious problems: the high cost of education and the higher cost of the ineffective and destructive war on drugs. As my contribution to the brand, I offer the slogan “get high for higher ed.” As you would suspect, I am not good at marketing.

 

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