First, I think his analysis of how the efficient markets hypothesis affects the “marketplace of ideas” is quite interesting. I would like to add, though, that this is a “hypothesis” and not a fact or even a theory. I would suggest that efficiency is a continuum: some markets are more efficient than others (for example, the top stocks on the NYSE are more likely to be efficient than penny stocks). As he says, the efficiency depends on the information available in the market—but it is not a binary option.

I contend that prediction markets are more likely to be efficient than actual markets, for several reasons:

1) There is much less friction than in markets for goods because there are no physical products.
2) Prediction markets are much more granular and varied, so the information contained in the market is more clearly expressed (i.e., you are not only betting that a stock will go up by holding it, but on events in a variety of areas—imagine if you could bet separately on whether a stock will issue dividends, for example, or whether a certain division will release a product)
3) Institutional biases toward a market rise, such as restrictions on short-sellers, the structure of options contracts, etc. do not exist in a prediction market.

These and other factors mean, to put it into SAT terms, that prediction markets:physical markets as intellectual property:tangible property. Of course, there are many differences, as intellectual property might be considered a state-granted monopoly and not property at all, and prediction markets are a mechanism, not an object. However, there are some interesting comparisons to be drawn between the differences between physical markets and predictions markets and intellectual property and physical property.

Prediction markets not only create a market for ideas, but a way of freeing investment markets from their traditional domain (stocks, bonds, commodities) and ordinary gambling from its traditional domain (card games, sports, etc.) This decoupling is an extremely important source of information for policy decisions, which brings me to my second point. The same people who decry prediction markets as “useless” and “offensive” would not feel that way about the signals provided by the NYSE. They do not ask, “How can you bet so carelessly on the economic futures of people all around the world? How can you possibly report so casually on something that affects whether or not people can buy a TV this Christmas or not?”

I agree with Sunstein’s assessment of the pros and cons prediction markets, but also do not think he did enough to put the irrational negative perceptions into perspective.

In the context of the McChesney reading, this weakness becomes particularly potent. While McChesney spends most of the selection discussing the foundations of the field of “political economy of communication” and the place of critical perspectives in that field rather than making specific arguments or critiques of current media structures, his rhetoric indicates that he would likely agree with the notion that today’s media industry is dominated by several large conglomerate corporations (especially as he seems to appreciate Baran and Sweezy’s critiques of “large corporations working in oligopolistic markets” (68)), and that this is bad because limited control of the tools of material production results in controlled dissemination of information that favours the ideas of social elites (54-5).

If McChesney is correct, then prediction markets become much trickier beasts to deal with, because the information used by the majority of the population comes from such dominant media conglomerates. This means that the framework within which prediction markets are defined are limited by the media’s control over ideas. For example, prediction markets for presidential elections define the betting options in terms of what candidates are best covered and promoted by large media corporations. This isn’t bad on its own, since it just shows that prediction markets reflect what the population observes and believes, even if what the population observes and believes is restricted by dominant media corporations. However, prediction markets amplify the messages they project, i.e. when investing in Kerry becomes popular, even more people move to invest in Kerry. This means that the limited range of information that is ‘inputted’ into the prediction market is amplified by the structure of the market itself, so that the observations and conclusions that people make from the market are even more limited and biased.

Therefore, it seems that prediction markets can only function reliably well when media and communication are as free as McChesney would ideally like them to be. Presumably, the democratization of communication via the Internet and other networking and ubiquitous computing technology are supposed to help in this endeavour. However, the problem is even more general than mere control of the media industry; as McChesney notes, advertising has become increasingly necessary in recent years for corporations to sell their products profitably, and this pattern has extended itself to the basic structure of information exchange on the Internet. Advertising has become the dominant form of monetizing the free production and supply of information and information services on the Internet, threatening the integrity of the information economy. Prediction markets seem like they would only further incentivize corporations to invest in advertising as a way to convince people of certain beliefs, so that they will then investe in that belief in a prediction market, creating a positive feedback cycle in favour of that corporations.

I don’t have any immediately obvious solution handy here, but I think it’s important to analyze Sunstein’s observations on prediction markets in the context of McChesney’s wider observations about how information exchange is influenced and controlled by the way media entities are structured.

In terms of predicting outcomes of elections, while such markets might be better predictors, one still is left with the same question about the purpose of such predictions prior to the election? What is to be gained by publishing what others are feeling? Do we make for better elections by signaling to individual voters what the masses are feeling? Do we make politicians better by giving them up-to-the-minute polls on their electability or on specific issues? It seems that we continuously steer voters and politicians into the same surface level actions of voting the same as one peers and by setting policy through polls. In sum, prediction markets may be better forecasters of election results, I’m not sure more and more accurate forecasts are needed in this domain.

Finally, I appreciated Torvald’s take on intellectual property, especially as it relates to patents. I share his same opinion that “the right solution is likely to be somewhere in between the two” sides, i.e. no ` `IP” and strong “IP”. It is telling that someone who demonstrably a creator on the internet, who has given some of his work freely to others, has such an opinion. I really appreciated his point that “I have the obligation to use those rights in responsible ways, and not as a weapon against others who lack such rights” (208) and that “one day IP laws will be dictated by morals” (212). Although this might seem polemical given that it infers those on either extreme lack morals, I prefer to interpret his “morals” as “reason” which invites us to try to understand both sides of the issue and craft a solution (or solutions) that meet the needs of both, as best as possible.

were focused not on whether or not a zombie Walt Disney would allow permanent copyright status of Steamboat Willie but on a new way of viewing the world. Interestingly, while not directly focused on the seemingly main points of the class, these two articles seem to have distilled a point that was made again and again in all of our other readings: there’s a war between those who want to see what’s going on in the world and act accordingly, and those who want to shape the world into how they think it should be.

The best example of this from past readings would be the death of internet radio at the hands of the music industry, because they thought that with a few large internet radio stations, the costs they were imposing would not be a problem.Similarly, the Communication Revolution exert in particular held this spirit in my opinion, especially with the example of America invading Chile because their democratic process chose the incorrect candidate(p 38).

The laws surrounding copyright seem cut from the same cloth. In control are supposed experts on the subject who are not – as viewed by the younger generation- completely moral or originally in line with the preported goal. Those who keep arguing that copyright would
be most effective in stoking the creative fires of today if they extend beyond the life of the creator’s grandchildren are hesitant to listen to the other side in the same way that the communication experts were unwilling to take Chompsky seriously at the communication conference.

This is perhaps not terribly surprising (would we willingly give up the model of the atom in favor of something else?) but it is interesting to see that the issues that come into play in the copyright debate really are widespread problems that affect us in everyday life.

I find it dreadfully ironic that in his last chapter, McChesney calls for media scholars to “re-imagine the forms and structures of nonprofit and noncommercial media, developing a palette of policy options to study, debate and consider…the vision must be broad, going far beyong what has been done in the past—and beyond journalism to broader cultural productions as well” (215). If McChesney is described as “one of America’s leading media scholars and activists” and is only willing to sound a call to action for other scholars to propose solutions, and the state of communication studies is jilted and inadequately regarded by their own universities, when will we ever see anything of substance on this matter? It frustrates me that he would rather offer a perspective on the communication revolution than start one with a 220 page book.

The author has shown evidence that at least on occasion we can believe that predictive markets would do a better job than polling, but I am curious as to how “risky” these situations can be. In other words it would seem to me that statistical polling is a much safer choice because predictive markets could be closer to the mark 9 times out of 10, but that 10th time is far worse than a statistical poll. For example, in the presidential race of 2004 Kerry was a strong favorite in the IEM predictive market throughout part of the day because of information coming in. He was raised to a seventy percent “Winner take all” even though I am sure that the information at the time did not support that high of a rise. If we were to poll the country at the time and asked them who they thought the next president would be, I am pretty confident their answer would be closer than the predictive market.

However, the issue gets more complicated when we consider the likelihood that Kerry’s stock did so well for a period of time was because of statistical polling. It was the early exit polls that showed Kerry in a comfortable lead, and I’m not sure why Sunstein did not mention this in the article. Perhaps it is because these exit polls did not reflect the magnitude of shift towards Kerry. In other words how could we limit predictive markets cascading effects? Or better yet when does the speculation stop?

I’m glad that the author has mentioned that in ways predictive markets could probably not accurately pin point a terrorist attack because any public knowledge of the market would make it self-defeating. But what about predictions that are self-ensuring? This is a problem that I have found with the speculation we have in general. It seems that when certain polls come out they only help to bolster the outcome that was predicted. One only needs to look at the current democratic primary and see how Senator Clinton for awhile was trying to show she was inevitable with the help of polls( I don’t blame her for doing this). Nothing bothers me more than the bandwagon effect, and the way the media noise machine assists in the effect. Would predictive markets increase the tendency of self-ensuring predictions?

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In other news when I wikipedia’ed Sunstein, I found that he wrote a book called Republic.com where he argued that the Internet may be polarizing. Supposedly in the book he argues that people who use the internet can easily see their own views mirrored. This has been an issue that we have talked about during class, and I had to mention that term that it is coined for groups on the internet that fragmented political discourse: cyberbalkanization. It rolls so nicely off the tongue. (I apologize if we have already used this term in class and I missed it)

Torvalds’s discussion of creativity struck a note with me. Forgotten in our intellectual discussions of IP and non-market production, the human act of creation is, as Torvalds describes it, “sacred” (205). I imagine that his words in this short section may not have had the same impact as other readers, but, before we start talking about rival and non-rival goods, there is something fundamentally true in these words: “[the bond between the created and the creator] is something that everybody in the whole world should be able to be part of, because it is humanity” (205). I can’t really back this up, but I imagine that if fine art had a more prominent position in American culture, that if we revered our creators as we revered our sports stars, individuals would be winning the tug-of-war with corporations overIP.

However, there is another side to the matter. As Torvalds points out, IP laws may not be great for exponential, out-of-control technological advancement, but they produce the only kind of results capitalism understands: dependable progress and profits (211). Many authors we have read this quarter focused our attention of how copyright and patent laws, when abused, require America to sacrifice creativity on the altar of the Free Market. I applaud Torvalds for explaining whatIP laws are good for, even when they are abused.

Torvalds says that he wishes that IP law was driven by morals and not money (212). I don’t think he means morals in this case, but rather parody. There is an imbalance in the scales, but instead of buying new scales and throwing out the laws that we have, Torvalds implies that the scales would be fine if some key players would stop throwing their weight around on one side. Sounds hopeless, but the check to re-balance power has already emerged from the network. If corporations want to deliberately abuse the laws in place and use their influence and affluence to escape penal repercussions then the individual is exonerated from any moral worries when violating these organizations’ copyrights and patents. When both big business and the individual disregard the law, the scales are balanced. However, if corporations, either voluntarily or in response to legislation, respect not just the law but the rationale behind the law, then software piracy and illegal downloads are the evil the DMCA was created to destroy. Lessig wrote about how having ridiculous laws creates a culture of criminals. Based upon my reading of Torvalds, the way (some) individuals and (mostly) corporations abuse IP laws is the problem, not necessarily the laws themselves. The criminal act has been committed by those who abuse IP laws to pimp creativity, “sacred” in the eyes of Torvalds and myself, out to those who will pay; individuals who ignore the laws that protect this practice act in just retribution — similar to the way our criminal justice system feels justified in taking away the autonomy of those who have been found guilty in court.

Like Torvalds, I believe that we need only to respect our current laws by obeying the words and also honoring the purpose of them. And if one side is not willing to do this, then that is as good as a declaration of war.

The biggest problem with intellectual property I see is the overworked patent system, and the web of beaurocracy and legalese which prevents an innovative outsider from using it while protecting already-wealthy companies. Would it be possible to cut through the red tape so the system runs efficiently, giving patents to only worthwhile inventions while becoming easily navigable to the shallow-pocketed and lawyerless? One problem with patents we read about last week in Stallman is that patent definitions are so broad they can be used to threaten anyone dipping so much as a toe into the same field. A stricter interpretation of each app is necessary. The question is, if each patent must define a narrower idea, would this make the applications shorter (describing fewer things) or longer (to specify precisely the idea in question)? Perhaps the patent examiners need to take a cue from schoolteachers and professors everywhere and state that the author must produce the clearest work possible while staying within a mandatory page limit in order to achieve the desired grade/rights.

It just seems like niche markets and niche populations might be able to take advantage of this model because they are the ones who have a stronger chance of having enough information to make the market predictions accurate.

Another thought I had about this reading is that the overall tone of the reading made prediction markets seem shady–almost as if they are a self-serving mechanism to make money for certain groups of individuals.I know that this isn’t true, but the fact that most of the general population doesn’t know of this type of market’s existence or that mass media doesn’t use this type of market when making election predictions points out that market prediction has a long way to go before it becomes a better alternative to certain kinds of market transactions. This is ironic in some sense because this type of model only works well, especially in the case of elections, when the mass population can take part and understands what the market is trying to achieve.

Imagine if this was the situation with other “meatspace” laws. What if your neighbors could stop you from having noisy parties by shutting off your utilities? What if you could be prevented from loitering by having your shoes disintegrate if you did so?

These seem like pressure tactics more than due process remedies. I think that institutions ill-prepared to deal with cyberlaw issues respond with extreme punishments rather than think through what the equivalent due process would be in cyberspace.

One issue that was not addressed in the chapter was the use of humiliation as a tactic for government control of online behavior. Local governments have, for example, posted the names of people arrested for soliciting prostitution in an attempt to shame people away from using prostitutes. They have also posted photos of people involved in the commission of a minor crime (smoking marijuana, drinking underage) and asked those on the ‘net to identify the perpetrators.

This is an example of distributed government enforcement to match the examples in the chapter of distributed evasion of government power. By posting this information in a way that a search engine can pick it up, this enforces law without having to seek out each individual “john”. Not only can law-breakers avoid the government by spreading the risk, government itself can spread the enforcement through selected intermediaries.