This NPR piece was done on “Science Friday” and featured a conversation between Ira Flatow, and guest Dr. Eric Horvitz, a Microsoft Research scientist. The discussion follows the role of increasing internet searches for health-related topics in discovering critical information about the interactions between drugs. Horvitz and his team were able to find a connection between Pravastatin, a drug used to lower cholesterol, and Paroxetine, an antidepressant. When combined, these drugs can cause hyperglycemia. It is noted that these two drugs are both quite common and yet no drug testing had proven the adverse side effects of combining the two. While Horvitz clarifies that in this case, another study at Stanford had found the connection between the two drugs, Horvitz’s team aimed to see if they could have predicted what the study found through looking at search history. As a result, Horvitz went back to a year before the Stanford study, 2010, and, with consent, conducted an analysis that showed similar findings. Thus, this technology could be used in the future too, without scientific study, predict negative interactions between medicine.

While this specific incidence does not necessarily pose a significant ethical question with regards to privacy, as consent was asked, how technology is used in this application does bring about some issues. For example, while we hold Microsoft to a high standard because we know the company, what about other companies using similar technologies, both for good and bad? Will privacy always be prioritized?

The article also highlights the current issue in the U.S., and around the world, of “cyberchondria,” which is a phenomenon where people tend to look to the internet to answer what their symptoms mean, only to escalate their symptoms to the worst extreme. Perhaps with the transition to more forms of e-health, this cyberchondria issue will become less of a problem.

The New York Times article covered the flawed facial recognition technology created by Amazon. With a database of 25,00 publicly available mugshots, the “technology incorrectly matched lawmakers with people who had been charged with a crime.” Although the software initially served to prevent human trafficking, facial recognition is fast becoming a top target for civil liberties groups and privacy experts. This way, civil liberties groups view it as a surveillance system to lower political protests by eliminating anonymity. In the wrong hands, facial recognition can be inseparable from a tool of social control.

Northpointe’s algorithm has been shown to turn up flawed results. Broward County, Florida uses the score in pretrial hearings, and ProPublica’s research proved it remarkably unreliable. Only 20 percent of those predicted to commit violent crimes did so, and when looking at all crimes it was only slightly more reliable “than a coin flip.” Moreover, it turned up black defendants as more likely to be future criminals two times as much as whites, and also incorrectly labeled whites as low risk more frequently.

Regarding ethics, we determined multiple options for possible outcomes. One extreme would be for technologies such as the risk assessment algorithm and Amazon’s facial recognition to continue to be used in their current capacities. This would mean bias being perpetuated in yet another mode. The opposing option for the former would be for these technologies to be banned entirely. While this would prevent the fundamental flaws currently happening with both the algorithm and facial recognition, there are also benefits that can be had from using this technology, were bias, specifically against people of color, to be removed. As we spoke about in class, just because a product has a high success rate, that does not mean that the success rate of predicting is equal among everybody. Thus, while an average looks successful, the accuracy can be completely skewed. Therefore, the third alternative, which is the alternative our group said we could live with, is to ban products like these until they can be re-thought and created to display no bias.

Jim Isaak explains the unauthorized access of personal information of more than 87 million Facebook users to data firm Cambridge Analytica. Researchers at this data firm accomplished such a task through a personality test taken on Facebook to evaluate the user’s psychological profile. To their surprise, this research established a clear relationship between Facebook activity and their personality profile. So, Cambridge Analytica “micro-targeted” their consumers with messages to influence their political behavior, such as with “Project Alamo” under President Trump’s campaign. It wasn’t only members being affected; in fact, every website linked to Facebook allows the tracking of non-members data. Therefore, Cambridge Analytica purposefully targeted messages to the users as a way to influence their political power.

Towards the end of the article, Isaak lays out propositions for how to preserve privacy and protect data. The principles fall under four sub-categories, “public transparency,” “disclosure for users,” “control,” and “notification.” Regarding actual legislation that has been proposed, there are three current propositions in the works. The first, the Blumenthal-Markey bill, focuses on protecting the privacy, focusing on the “opt-in” aspect of consent, while the second bill, put forth by Senator Amy Klobuchar, maintains similar elements but also adds more on notification of changes. Lastly, California is pushing to further secure privacy rights for its citizens, hopefully setting a standard for how to address user privacy in the U.S., and the world, following Facebook & Cambridge Analytica’s inappropriate handling of user data.

Luis wrote the first paragraph, and Kate wrote the second.

Ritchie provides a detailed explanation of the development of the Unix operating system that was developed at Bell Laboratories during the late sixties and early seventies.

In 1968-69 Bell commissioned the development of a precursor software called Multics. The project was enormously expensive and failed to deliver the usable features promised during development. The technical research conducted by Ritchie, Thompson, and Canaday on Multics did, however, prove fruitful as a preliminary design for the filing system rolled out in Unix.

The first part of this early design was PDP-7 Unix file system. This system consisted of an i-list, directories, and special files describing devices. Unlike the current system,  PDP-7 had no path names, configurations were hard to change, and there was a lack of path names. Processes existed early in this system such as system calls fork, exec, wait, and exit.

A new disk allowed for the first PDP-11 system to be created. Unlike PDP-7, this system was dedicated to word processing. Due to it only running on a single .5 MB disk, every new program required care and boldness because the system could easily crash.

Throughout this article also ran a string of social aspects to go along with the technical history that Ritchie provided. For example, though Ritchie describes the downfall of Multics, he also adds that he and the group were able to use the operating system just between them, saying, “what we wanted to preserve was not just a good environment in which to do programming, but a system around which a fellowship could form” (Ritchie, 2). It seemed odd to find these types of sentences interwoven with the more technical aspects, as the document itself seems to naturally focus on the changes made to and the problem-solving of the operating system itself. These interesting additions to the text all culminate at the end of the document, where Ritchie ends on a nostalgic note, even including the phrase “rosy glow.” At the same time, Ritchie is describing a process that involved many idea proposals and rejections and versions of the final product.

• Sean → wrote the first two paragraphs
• Luis → wrote the second two
• Kate → wrote the final paragraph

Vannevar Bush was an American inventor who worked on a machine called the differential analyzer that was capable of solving first order differential equation. Bush also theorized about a device called the memex that would be capable of storing referential knowledge in an encyclopedic manner. Bush was also the director of the Scientific Research and Development and coordinated research between Harvard and Berkeley that led to the creation of ARPA (Advanced Research project agency) and eventually DARPA.

By the 1960s the Department of Defense’s program was working on creating network-to-network protocol that would allow computers to communicate with one another. The new protocol was known as the TCP, which details how information is broken into packets, and IP, which focuses on sending the packets across the network. Although some computers connected with each other, Tim Berners-Lee created a system for universal communication using a URL accessible through HTTP formatted in HTML. Since the technical terms are not necessary for the story, the essay summarizes its purpose: “Browsers are used to connect to remote computers over the Internet and to request, retrieve and display the web pages on the local machine” (O’Regan 169).

Many may wonder why O’Regan may have included a section regarding business models in a chapter about the history of the internet. However, it is essential to see how the World Wide Web changed so much about how business was conducted, as it has had a profound influence on how the internet influences society today. While the World Wide Web grew at a staggering pace, creating many financial successes, it is crucial to acknowledge the mess it produced as a result of the dot-com bubble. O’Regan two main issues of this era that lead to the subsequent downfall of many companies. The first was the fact that many companies had deeply unsound business models (the article discusses how a good business model with a bad idea can be more beneficial than a flawed business model and even the best of ideas), and the share price of stocks were severely inflated, as companies values were examined based on “potential future earnings.” Thus, while we recognize that the World Wide Web has paved the way for a “new economy,” it is important to acknowledge the various occurrences as a result of this significant change.

Sean: 1st paragraph  | Luis: 2nd paragraph  | Kate: 3rd paragraph & post

The Nakamura article told a story that complicates the narrative of Silicon Valley being the epicenter of the technological revolution. Rather than simply retelling the already household histories of tech giants like Steve Jobs and Bill Gates Nakamura focuses on the contribution of Navajo women who worked at the Fairfield plant in New Mexico producing computer chips. Because the Navajo women were willing to work for a low wage and because Fairfield could avoid paying taxes by building on reservations, costs remained low.

Fairfield publicized that these women were particularly well suited for the job due to their transferable skill from their practice of weaving, an algorithmic art that was often overlooked due to its association with the domestic sphere. Because of the meticulous attention to detail necessary to weave rugs, Navajo women were seen as perfect for producing chips accurately, quickly, and painlessly. These women were also hailed as the ideal workforce because they were mobile, cheap, and above all, flexible; they could be laid off at any time. As a result, their previous experiences allowed for these digital circuits to be manufactured in such a large scale.

However, although this decision to insource work was advertised as of dual benefit to both Fairfield and Navajo women from both sides, the project did not result in a great economic payoff to the women themselves. Furthermore, the manufacture itself was made to seem like it was “preserving” Navajo culture. Nakamura describes a Fairchild brochure from 1969 in which the transition from weaving to circuit making is made to seem an “extension of Navajo culture. Through the reading we come to understand that it is not due to these traits that Navajo women were hired, but rather, as Nakamura eloquently explains, “these traits were identified after the company learned about the tax incentives available to subsidize the project, the lack of unions and other employment options in the area…” (Nakamura, 935). Thus, while on the base surface the whole project was seen in one light, Nakamura urges us to realize and understand the “cultural” rhetoric adopted for the exploitation of the fact that there was a lack of jobs for Navajo women.

This article comes from the tradition of critical theory, calling for us to look beyond the commonalities of the digital field and see this labor for what it is, digital manufacture, not an innate part of the “Indian psyche.”

• Sean → wrote the topic sentences for each paragraph, the introduction, and helped edit
• Luis →  wrote the second paragraph
• Kate →  wrote the third paragraph and part of the fourth paragraph