Internet Policy and Information

I tend to be a voice of “now hold up now y’all” with most of our topics, so I am going to stick with that theme for the last week.  Before saying anything else, though, I think it is important to stop conflating IoT or smart devices with digital versions of analog appliances. Smart devices are normally what people think of when they are discussing the IoT, and it implies a connectedness or the potential to communicate with other devices. So, a nest that communicates with your cellphone, or a wearable that connects to your smart coffee maker when you’re starting to get sleepy, or any other connected device, those are smart devices and should be considered in the IoT. A pacemaker that measures your heart rate and blood pressure and helps regulate health, however, if not connected to other devices, is not the same thing. If I have a wearable device that measures the atmosphere around me for toxins or checks health markers, but it is not connected, then it is not the same thing. Ubiquitous computing, maybe. IoT, not necessarily. I think this is important to note, because there are some real concerns with IoT that are different than the trend towards ubiquitous computing that we are also witnessing. One of the things that our readings mentioned was the decrease in possible physical crimes such as theft that would occur with the IoT. I found this an interesting point because I had been musing about the disintegration of user ownership as he was talking about this. Let me explain what I mean.

As of now, for the most part, once I buy a product, it is mine to use as I wish. The manufacturer and industry can suggest usage, but I can choose to go against that if I wish. Furthermore, I could (again, for the most part) disassemble that product, tinker with it to enhance it, resell it, give it to someone else as a gift, or use it in an innovative way that the manufacturers might not have considered. With the IoT, however, users seem to lose that control. 

While IOT is a really interesting issue, I feel like this is a good space to write about the concepts we’ve learned about in class and applying them to the recent election. I believe there are a lot of technology issues that will be important to the debate going forward, especially in understanding how this happened. 

The first is, did the data lie? So much of what we have discussed revolves around the use of big data and its ability to predict useful outcomes. The number of polls, models, and statistical jargon used this election was overwhelming. I remember reading for an hour on Tuesday the explanation of the Princeton statistical model that had a 99% prediction for Hillary Clinton. A 99%! And it was completely wrong. Is this a sign that we trust data too much or that was this a case of trusting bad data. When you really boil it down, polling relies on a person picking up the phone and telling a stranger who they are going to vote for. That seems like pretty weak data to make such strong predictions based on.  Where the polls reaching the wrong people or were the people not telling the truth? Not sure how we are ever going to figure that out, but I for one am not going to believe the polls again for a very long time.  Think about how much we rely on polling data. In order for a third candidate party to make it into a debate, they need about 15% support in the polls. Now that we have seen the polls miss be huge margins, do we re-think when we allow third parties into the debates?

Internet jurisdiction is one of those sticky concepts, governments want to impose their boundaries, like in the physical world, but it just creates more questions and issues. The Global War for Internet Governance, attempts to define this concept. Rachelle’s post talking about ICAAN reminded me of the little understanding of how the Internet actually works. I remember reading an article in the Austin Statesman about Ted Cruz’s erroneous fear-mongering about the U.S. giving up ICAAN governance. How can we start to develop talks about Internet governance with legislators without an understanding of how the Internet actually works. If we’re debating about the merits, how will, less enlightened, politicians make informed, well-balanced decisions? Also, domain names don’t even hold much weight, even though politicians like to think so. Countries like Tuvalu, whose domain name ends as .tv, actually sell their domain extension to television providers and shows. Its intended for Tuvalu entities, but its quite lucrative for Tuvalu to sell the extension for television shows. Another supportive read to Global War is Erica Wass’s Addressing the World: National Identity and Internet Country Code Domains. Her books delves into how countries either identity for use their domain codes more lucratively. It’s just a naming convention, and however a country uses it should make no nevermind to the US.

When thinking about copyright in an Internet governance sense, it become more convoluted than I thought. I have a fairly strong grasp of how US copyright works, but when you think about those being held to US copyright law, without being or ever setting foot in the US, it throws a kink in things. US copyright is enforceable if the copyrighted-object is registered with the US copyright office, the copyright holder (not necessarily the author) has the ability to enforce damages. If the copyright-holder’s work is registered with the copyright office, it depends on if the holder wants to proceed with a lawsuit, regardless of the offender’s nationality. Copyright holder may not want to pay for an international intellectual property lawyer, but that’s neither here nor there. The Internet has pushed copyright and intellectual property into the global arena. Before it was photos, ads, and written works on a local scale, now it’s international. With countries trying to impose their boundaries on the Internet, it’s going to pull new laws into the playing field.

Author Jamie Bartlett’s book The Dark Net explores the shadowy world of the deep web, a parallel anonymous Internet. Its diverse set of users, including hackers, drug dealers, dissidents, and government agents, is a testament to the deep web’s equivocal nature. Originally developed as a means of protecting the identity of government officials and dissidents of oppressive regimes, Tor, the primary browser for the deep net, was advanced by the U.S. Naval Research Laboratory in 2002. By redirecting online traffic through a worldwide, volunteer network of computers (it’s open sourced), Tor obscures the IP addresses of its users. As time passed, however, the deep web morphed into a hotbed of nefarious activities, including human trafficking, money laundering, drug sales, and terrorist recruitment, to name a few. Central to this devolution was the creation of Bitcoin, which provides a cover for online transactions.

As it stands, the vast majority of Tor users do not engage in illicit online activities. They simply want to avoid data mining and online advertising and maintain their privacy. In fact, only three percent of Tor users even visit the deep net, with an even smaller fraction engaging in illegal activity. However, the dual nature of the deep net and Tor’s part in enabling it raises serious questions about the proper role of government. Sixty percent of Tor’s funding comes from the Department of Defense and the State Department. Meanwhile, the Department of Homeland Security, the Federal Bureau of Investigation, and law enforcement agencies around the world are engaged in multiple investigations of criminal activity made possible by Tor. For example, today hackers launched a cyber attack that disrupted service for several major websites and services in the United States. Some security experts have raised the concern that this event and several other recent, large-scale attacks indicate that some group(s) is learning how to take down the internet. Clearly, this would have a major and adverse impact on the global economy.

Also a really useful takeaway from the rolling stone story:  

Bartlett (2014) opens his book, The Dark Net, describing Jim Bell’s essay on Assassination Politics written in 1995. Bell imagined that on the Internet, with perfect anonymity, secrecy, and security, users could bet on the deaths of politicians which would inspire politicians to act without angering users otherwise an individual would be incentivized to carry out their own bet in order to win the cash. By 2013, Kuwabatake Sanjuro (a pseudonym) made this vision a reality and launched the Assassination Market. This exact concept underpinned the recent film Nerve. This film however is based in an application rather than in the dark net, but with perfect anonymity, secrecy, and security, the users are able to set conditions to incentivize murder (*spoiler* the plot twist is that the app’s security is not perfect).

Yet are these types of behaviors in Bell’s essay, Sanjuro’s website, and Nerve, necessarily unique behaviors tied to the Internet? In media/communications studies there is a strong tradition of the medium is the message (McLuhan) – where people focus on the uniqueness of technology as a determiner of human behavior and/or is the most important factor to understand. But how true is this? We do see non-mediated human behaviors replicated on the Internet and through other mediums (television, phone calling, radio, etc) – rather than being completely revolutionized by the technology. So why do we continue to see work that celebrates the Internet as revolutionary for human behavior?

In his 2015 TED Talk for his book, Bartlett explains the behaviors of drug markets on the dark web. Marveling at the creativity of the sellers, he describes their bogo deals, the importance of customer satisfaction and ratings, and even advertising. Yet none of these traits are exclusive to the dark web – they are not even exclusively internet behaviors. So what is unique? Similar black markets have cropped up in the physical world. Syrian refugee camps have creatively found ways to support markets and commerce despite being legally prohibited from doing so (for more info on this subject see Carleen Maitland’s work on Syrian refugee camps). Anecdotally, and as a case study, Bartlett’s work is fascinating but I think, for me, it is missing the ‘so what’ factor. Bartlett concludes with “ultimately, the dark net is nothing more than a mirror of society. Distorted, magnified, and mutated by the strange and unnatural conditions of life online – but still recognizably us” (p. 130). This seems somewhat trite. I am guessing that the value of this book lies in the fact that no one else is doing this kind of work with the dark net.  Because it seems to me that this book would not pass muster for a seminar much less publication.

Lastly, I would have loved a more self-aware disclosure of Bartlett as a researcher. In the introduction Bartlett (2014) writes:

My journey took me to new places online and offline. I became the moderator of an infamous trolling group and spent weeks in forums dedicated to cutting, starving, or killing yourself. I explored the labyrinthine world of Tor Hidden Services in search of drugs and to study child pornography networks. I witnessed online wars between neo-Nazis and antifascists on popular social media sites, and signed up to the latest porn channels to examine current trends in homemade erotica. I visited a Barcelona squat with anarchist Bitcoin programmers, run-down working men’s clubs to speak to extreme nationalists, and a mess bedroom to observe three girls make a small fortune performing sexually explicit acts on camera to thousands of viewers. (p. 8-9)

Correlation does not equal causation. Big Data: A Revolution…spends a whole chapter showing how correlations within big data are now the hard and fast rule in retail, health, and government. I feel like this chapter was missing the rule of “correlation doesn’t always equal causation”, often pushed in the sciences. Big data is often pushed as the only way to gather information, and the book even has pushed so far as to say the scientific method and hypotheses are no longer strong forms of research. It bothers me that Mayer-Schonberger is making the case that predictability and probability will replace structured methods such as methodical experiments. Not everything needs to be rushed and “fast thinking.” I can understand Walmart’s use of correlations between hurricanes and selling more Pop-tarts, but once my health insurance starts rising because they think I watch Netflix for hours, then I have something to be worried about.

I feel like big data was a buzz word of the late 2000’s but now has become more of a way of how things are. Companies that have the ability constantly mine metadata and use it to their advantage: how long you spend on a checkout page of a site, which ad you click, the setting of your thermostat (if it’s hooked up to the internet). The notion of big data was new and useful when we were just realizing its potential but now it’s just another tool in the statistics handbook. Sampling size is becoming less and less an issue for companies that have the reach and capacity to measure and record that data like Google, Netflix and Amazon. As consumers we enter into an agreement when we utilize their services that our data (whether we like it or not) will be used and farmed from that point on. A lot of times it’s for our benefit like showing us what to watch next after I finish watching Parks and Rec for the 5th time, or forecasting trends in flu outbreaks like they mention in the book. But, a lot of people are realizing just how much information these companies keep on record. It’s a lot. If you refer back to my first post I can look up almost every interaction I’ve ever had on my Google account. I don’t mind it because they offer a service that I can’t get anywhere else and so far I haven’t found any negative connotations in their use or intent to use that information.

Bitcoin is a technology with possible game changing applications for the developing world, but is the developing world ready for it? The idea of developing countries in leapfrogging technologies is so “hot” these days, but is what is the evidence to back it up? There is some truth to this idea: most Africans never had a landline and went right to cell phones, but will developing countries Africa really leapfrog over the world and adopt Bitcoin first? To try and answer this question, I’m going to discuss the money environment in Africa and talk about existing financial systems.

Proponents of the leapfrog theory of development often say the developing world’s lack of old technological infrastructure leaves the market wide open for new technologies. This appears to be true for the financial industry. In the continent as a whole, there is a huge pent-up demand for banking services with only 66% of the Africans having access to financial services. Banks have a hard time reaching people in rural areas and people without a lot of capital. One can see the potential for digital financial services to take off in Africa and reach these customers by looking at the success of mobile money on the continent.  

Mobile money is a technology that has taken off in Africa and but not in the developed world. Mobile money is a technology that allows users to deposit or receive money in kiosks and use their phone account as a bank account. It has done well in Africa because there was a demand and all the new technology (mobile phones) were in place. This method lowers startup costs for banks to reach rural people and takes advantage of telecoms existing infrastructure to reach out to new customers. Mobile money is also used for people to have a safe place to store their money and for sending remittances. Several of these reasons for using mobile money apply to Bitcoin so why wouldn’t Africa just leapfrog again and move from mobile money to bitcoin?  

Some of the reasons for adopting mobile money are similar to those for adopting bitcoin but there are several major disadvantages to using bitcoin: lack of political capital, high fluctuation in price, and general trust issues. It took years of political negotiation in countries to get create the mobile money policy structure to allow mobile money businesses to flourish. Regulators created new policies around Know Your Customer (KYC) and Anti Money Laundering (AML) laws in order for the technology to take off. This kind of steady policy environment was what businesses needed to feel secure to make a large investment in countries. Considering the amount of energy it took to secure this political capital, it seems unlikely that Bitcoin will be able to do so in a few years, especially with the entrenched interests in mobile money and banking putting their weight against keeping them out of the market. Also many of the anonymity features of Bitcoin don’t lend themselves well to KYC and AML regulations.  

Secondly, companies that have gained the trust of poor and rural customers had to educate them on how mobile money technology works and the barriers to teaching people about bitcoin technology are much higher. I have a hard time understanding how it works and can imagine how hard it would be to explain to an uneducated rural farmer. In markets that rely on trust and can be reticent to change their saving strategy, Bitcoin can seem like a risky bet. Poor people are unlikely to make risky financial decisions. The fluctuation of Bitcoin prices makes the decision an even riskier bet for poor, rural people. There is a theory that if more people use Bitcoin, then there will be more people in the market and so the fluctuations will be smoothed out. There are more people buying  into the currency every day and so this theory might just turn out to be true.

This week’s reading was a little bit of a circus. On the one hand, I’m not convinced that THE WEALTH OF NETWORKS was even written by a human author because the same words seemed to repeat infinitely. On the other hand, BLOCKCHAIN REVOLUTION felt like taking a tour of a chocolate factory hologram guided by two Willy Wonkas. Yochai Benkler writes unbelievably complicated sentences, while Alex Tapscott and Don Tapscott offer a vision of our future that is totally made out of candy. 

 Both books are fundamentally about building trust. Both argue that comparing the blockchain future to perfection isn’t the point; instead, we’re supposed to compare the blockchain future to our present-day broken “Franken-finance” system, which we can’t trust anyway. The Tapscotts reference an interesting Gallup poll that points out that there’s nothing we trust less than business and Congress, so I guess they’re trying to make us feel things can only get better.

It’s hard to imagine how blockchain infrastructures will suddenly cause companies to become transparent and personal data to become private, as if we’re being handed an immensely powerful pair of glasses that correct everyone’s vision at once. I love the reference to the Economist’s reporting, which describes blockchain technology as “the trust machine.” Benkler and both Tapscotts desperately want to convince us that blockchain technology produces unimaginably high levels of trust among global strangers because, put simply, “the ledger itself is the foundation of trust.” (?) More than anything, my takeaway is that these books might have been written about any emerging technology in any time, urging us to consider electricity, ride an airplane, or try chemotherapy. They sound insane, like everyone always does. They’re describing an economy based on simplified payment verification (SPV), which seems to require nothing in order to participate. I guess I feel impressed by everything that blockchain might make possible but also disappointed that these authors sound like Dr. Oz trying to sell you on magic vitamins. Why is it so hard to sound honest? 

I love this. It’s exactly what these pro-blockchainers want us to think. Not that i’m a part of some conspiracy theory movement against blockchain, but it’s easier to say that something is going to fix all our problems and create an easier process for something. Chances are whether blockchain is accepted in the financial industry or not, it’s never going to directly affect me. And you’re right, this is inherently a very trust-driven innovation. If something happens, even though it sounds like it won’t by the explanation of the technology behind it, the entire system goes down (like the left-pad debacle earlier this year). 

The web has facilitated the emergence of organized complex systems, where people create macrobehaviors that are much larger than the sum of their components. Portals such as Facebook, Reddit or Twitter represent extremely complex systems that only function because of their large size (the so-called network effect) and the relative ignorance of each of their users (a person liking a post is not aware this post could go “viral”). All this seems similar to how Johnson describes the functioning of ant colonies. Yet our social media on the internet seem to lack that all-important third factor: randomness. The way ants know what job they are supposed to do (harvesting, disposing of cadavers, etc.) is because they will encounter a large number of random other ants on their walks. By having access to local information from this random sample of other ants, they are able to gauge what tasks need to be done and can form macrobehavior they are not even aware of.

Precisely this randomness is what we lack in our hyper-personalized world of recommendations. Think about your Facebook feed. Assuming you are a Democrat, try to remember when the last time was you saw a post promoting a conservative issue. Exactly. You are caught in what’s called a “filter bubble”, where posts you see reflect your own biases and where you are unlikely to be exposed to opposing views. You can have fun on this Washington Post site by seeing what types of posts people are shown regarding certain topics based on whether they are liberals or conservatives. This happens because the people we follow on Twitter or people we are friends with on Facebook are not random and more often than not are a very homogeneous group (akin to our offline friends group). Smart algorithms can determine based on our friendships and likes what political views we have, what our favorite foods are and more. While this may be very convenient, from a policy perspective we have to worry whether this is not exacerbating the problems of polarization in our society.

Johnson writes in his book that the web is inherently “hostile” to the creation of a high-level order through macrobehavior because it lacks the connections and feedback loops of other organized complexities. Perhaps this view is due to the relative age of the book. I feel that today we live in an internet age where we are extremely connected and feedback is everything. Feedback comes in the forms of likes, comments, retweets, star-ratings, etc. But still, does this mean that the internet is turning into the giant brain that some have predicted? I think not.

Our actions on the internet are governed by a series of algorithms in order for the chaos to be more manageable. And the algorithms we are governed by are becoming ever more concentrated. In June, Facebook reported that it had 1.7 billion monthly active users. That represents around half of the world’s internet users or more than 63% of users when China is excluded (where Facebook is banned). What this means is that our interactions on the internet are in large part governed by only one algorithm – Facebook’s. This also means that our interactions with each other on the internet are far from random. This is precisely where I think the problem lies. If we were to truly speak of the internet as an emergent system then we would be ignoring the missing randomness. Without this randomness, we lack the necessary information in order to form macrobehaviors on a global scale.

However, I do believe that the internet and social media platforms have a certain amount of randomness. Yes, content is largely determined by algorithms, and we choose to follow certain individuals and groups – often ones we agree with. But it is random in other ways. Take Twitter for example. I have tweeted at people or about certain topics, and random people have interacted with me – sometimes positively, but more often negatively – about that content. There are other ways to engage with opposing views than to make the internet a more random place. I think that this requires a more conscious effort on the part of individuals.