October 31, 2016
On balance, the benefits of the Internet of Things outweigh the harms of decreased personal privacy.
The November topic presents an interesting comparative debate for this month. Debaters may not be used to the wording of this topic-where the Affirmative is allowed to weigh any benefit in the round while the Negative seems to just be restricted to defending the very narrow ground of harms to personal privacy. The strategy on this topic, however, I think can be better balanced out to serve both sides equally with some unique links, big picture framing, and impact analysis.
The Affirmative definitely benefits from contextualizing the debate as much as possible-who are the largest beneficiaries of the Internet of Things? Where does the majority of information from the Internet of Things go and who uses it in what way? These are questions that allow the Aff to discuss the most important and probably the most convincing arguments from the Internet of Things. It’s best to think about these warrants in two ways: how the Internet of Things benefits industry and how it benefits people. This gives teams a structured way to think about different arguments. For example, the Internet of Things allows more innovative, efficient green technology that can be implemented on a larger scale. The impact level becomes twofold: this not only provides better financial incentives to invest in cleaner technology, but individuals then reap the benefits of cheaper green technology and the environmental benefits of better air quality, less greenhouse gas emissions, etc. Framing Affirmative arguments on two levels helps to hedge against the Negative’s topical burden to only talk about personal privacy.
The Negative, on the other hand, benefits from keeping the ground of the debate wider in scope. Neg should argue at the top of their case that ANY harms of the Internet of Things-not just those to personal privacy-should still be considered Neg ground. This essentially means that the Neg should be able to win on disadvantages alone. Given the wording of the topic, it is still preferable to link these through harms to personal privacy. However, I think it is still reasonable for the Negative to argue that disadvantages that are stand alone should still weighable defense at the end of the round. The Neg could frame it as an ‘even-if’ scenario; meaning, that even if they lose some of the access to impacts linked through the loss of personal privacy, they should still be able to win on the defense against the Affirmative proving that the Internet of Things still does more harm than good in other ways.
The Affirmative has a wide variety of arguments to link into that can be classified as straight benefits of the Internet of Things. The best teams, however, will carefully choose the links that guarantee impacts with the greatest magnitude and scope. This goes back to how the Affirmative should work on framing the debate in their favor. I think the most convincing arguments on the Affirmative side will be linked through economic growth. Industry investment in the Internet of Things and the measurable increase in efficiency for these industries provide some pretty powerful impacts. These include benefits to green technology and energy conservation, healthcare, manufacturing, tech, and other sectors. Growth is an easily weighable impact for Affirmative teams and grants diverse but important ground for Aff arguments. Additional arguments can also be linked through the Internet of Things as an interconnected platform of information for consumers. This includes better accessibility to consumer specific information, from which individuals make more informed decisions about their lifestyles. Affirmative arguments should rely on clear links throughout to avoid getting caught in a definition debate or having their arguments be muddled by Negative teams.
The Negative may have a trickier time coordinating effective arguments, but there is no shortage of convincing Negative arguments on this topic. Surveillance is probably going to be a common argument among Negative teams, but the best teams will take the links through surveillance to make more nuanced arguments about the harms of the Internet of Things. Teams should avoid discussing surveillance as an impact in of itself-when asked to adjudicate between the vague impacts of surveillance and the quantified impacts of economic growth or consumer benefits, judges may tend to lean towards the Affirmative. Negative strategies, then, ought focus on what links like government surveillance, network and information vulnerability, and potential hacking scenarios actually mean. These are all arguments that can be related back to decreases in personal privacy relatively easily-but again, teams should not stop there and rather paint more comprehensive pictures of what these breaches of privacy actually look like. For example, institutionalized government surveillance through the Internet of Things increases rights violations of individuals and could lead to potential increases in profiling, and other types of rights violations. Hacking scenarios could reveal sensitive information or consumer behavior, potentially making people targets of other predatory schemes, like identity theft, extortion, or other crimes. Hacking of sensitive information could also lead to larger security breaches of sensitive government information, which could end up in the hands of dangerous people. Each of the Negative arguments can and should definitely link through harms to personal privacy, but should go on to talk about larger-scale implications.
Both sides should follow similar trends in impact analysis, which entails breaking down vague benefits or harms into real world impacts. The Affirmative side should definitely weigh out the multiple levels of benefits to individuals through the Internet of Things. Starting at a point like economic growth, impact scenarios could include environmental implications, benefits of information accessibility, potential political enfranchisement scenarios and collective impact arguments. The point is to start with a overarching benefits that can be broken down into parts-benefits to industry, government power, individuals, etc. When weighing these impacts in the debate, I think it would be extremely useful for Affirmative teams to discuss how individuals make these types of risk calculations themselves-meaning, that even though individuals know of the potential dangers of internet interconnectedness, majority of people in the world still opt into using it. A useful example to contextualize this would be to point out that even after Edward Snowden leaked information about the NSA surveillance program, and people were temporarily outraged at their breach of personal privacy, this didn’t necessarily prompt every American with an iPhone to suddenly disconnect from the grid. This is a useful example to prove that even with the risks to their own rights presented to them, most people still choose to reap the benefits of the Internet of Things.
The Negative, however, can absolutely frame the impacts of surveillance, government institutionalization, and hacking as harms that individuals still aren’t fully aware of. As I mentioned above, its important to go beyond just the harms to personal privacy and to impact to larger scale harms. An effective way to weigh this against Affirmative benefits would be to point out that these are vulnerabilities of the Internet of Things that pose larger risks than many people realize. For example, information breaches can have widespread reverberations in industry sectors and drop investor confidence, thus decreasing the economic growth and efficiency that the Affirmative claims. Hacking puts individual information at immense risk and the Internet of Things gives people a false sense of security-effectively wiping out consumer benefits or positive public opinion. The important thing to remember when doing impact analysis for either side is to contextualize the weighing for your judge. Think about how your impacts can short-circuit your opponents’, outweigh them, or prevent them from happening.