Final Project
The image above represents the concept of consent within the anthropological study of science and technology. What is consent within science and within technology? Generally speaking, consent is permission for something to happen or agreement to do something. That definition remains the same across whichever field, but I will explain and give examples of how consent was used and abused in both science and technology. My first example regarding consent in science comes from “Your DNA Is Our History: Genomics, Anthropology, and the Construction of Whiteness as Property” by Jenny Reardon and Kim TallBear. This article discussed the struggles between Arizona State University (ASU) and the Havasupai Tribe over the use of Havasupai DNA in 2012. The Hart Report indicated that none of the researchers who received Havasupai DNA asked for documentation that the Havasupai had given their consent for the distribution of their DNA. 52 individual members of the Havasupai Tribe sued ASU for $50 and $25 million for misuse of their blood samples. Blood samples were collected from members of the Havasupai Tribe in the early 1990s to perform studies on diabetes. There was a diabetes epidemic taking over, so the Havusapai people wanted to know how to prevent diabetes and why so many of their people had it. Their blood was then misused by ASU researchers to conduct other studies. The Havusapai people were taught that they grew up in the plains, but one of the illegal, non-consented studies found out that the Havusapai people originated from elsewhere which conflicted with the Havusapai’s origin stories. The second example I give, in regard to consent within technology, is from: “Dressing up Tinderella: interrogating authenticity claims on the mobile dating app Tinder” written by Stefanie Duguay. This article explains how people question the authenticity of their suitors on Tinder, since anyone can easily exaggerate or lie about their truths. For instance, a person could lie about their age and upload pictures of someone else to such media platform. For instance, if Elizabeth consents to meet up with Greg, age 20, brown hair, blue eyes; but, Greg ends up being Larry, age 35, brown hair, green eyes; did Elizabeth really give her consent? She may have agreed to go on a date with Greg, but not the true Greg or Larry. This is why people question or do not fully feel comfortable with using dating apps or websites for the potential of a false suitor.
The image above represents the concept of hard vs. soft science within the anthropological study of science and technology. My first example explains the difference between what is thought of as hard and soft science. “Perturbing the System: “Hard Science,” “Soft Science,” and Social Science, The Anxiety and Madness of Method” written by: Joan Cassell describes “hard” science as that of natural science examples being: biology, physics, and chemistry; while, the social sciences: psychology, sociology, and anthropology are usually described as “soft”. She also describes “hard” sciences as being more “masculine”, because they are commonly pursued more so by the male population; while, “soft” sciences are more so pursued by the female population. People may also have the misconception of difficulty of the two. Hard science being more “difficult” than soft science. This is, of course, absurd. On what scale does one base difficulty? I have no idea, because how does one base difficulty? Especially regarding two unrelated fields of study. This got me thinking of the words: hard and soft and the connotations of difficulty associated with each of them. The second example I give is from “Geeks, Social Imaginaries, and Recursive Publics” written by Christopher Kelty. Kelly explains how there is: “a cultural analysis [of] assessments of how and why particular configurations of software, hardware, and legal regulation are valued over others, and how these values are discussed and acted on in practical settings”. My focus here is on “software” and “hardware” and which is, as Kelly put, valued over the other. A computer system consists of both hardware and software. Hardware is the collection of physical parts of a computer such as a screen or keyboard. Software is the coding of a computer to perform specific operations. Here, I feel as though “software” may be considered as “hard” science and “hardware” may be considered more of a “soft” science based on “difficulty”. Yet, the whole is greater than the sum of its parts. A computer is not complete, cannot function, and its software cannot be protected without the wires pieces of hardware.
The image above represents the concept of data collection via hacking, big data, and the ethics of both within the anthropological study of science and technology. What is big data? Big data is many sets of data that reveal patterns, trends, and associations, especially relating to human behavior and interactions. Big data is the overall collection of all the data taken and shared. The data on consumers collected from Facebook and the data of pictures of streets and whatever cars and people were caught in those pictures on Google Maps all go towards big data. My first example, taken from: “Big Data, Ethical Futures Futures” by Mary L. Gray states, “there is nothing obvious about how to design and execute ethical research that examines people’s individual or social lives through the ebbs and flows of our daily routines.” For instance, if a person with breast cancer in Champaign, IL Google searches: “best ways to cure and deal with breast cancer”, and the next day a native ad pops up in this person’s Facebook newsfeed for Carle Hospital Cancer Center, is this ethically right? Is the data collected from this person’s search too private/personal to be used for an ad? Or is this a proper and ethically balanced way of collecting data on a sick individual and Carle Hospital trying to help that person by promoting their cancer center as a solution? My second example is from: “Hacker practice Moral genres and the cultural articulation of liberalism” by E. Gabriella Coleman and Alex Golub. This article explains the different types of hackers and the extent of their hacking. If a hacker collects information and keeps it to themselves or sells or trades it with other hackers. Are both ethically wrong, because general hacking and collection of unauthorized data is illegal? Or is keeping data to oneself less ethically wrong than selling it to another hacker? This all ties back to the quote by Mary L. Gray: “there is nothing obvious about how to design and execute ethical research”. What a particular person believes is “ethically” right is completely based on that person’s own social, political, physiological viewpoints and is completely subjective. It is impossible to please everyone or to have 100% agreement on difficult topics such as big data collection and hacking because someone, somewhere, somehow will find it “ethically” wrong.
The image above represents the concept of the advancement of technology regarding creation, speed, and human acquisition within anthropological study of science and technology. My first example is taken from “The Perception of the Environment: Essays on livelihood, dwelling and skill” by Tim Ingold. Ingold explains how human evolution has gone to show that we love to control nature, and technology’s quest is: “to transform the heuristics of technique into algorithms of practice.” 2 year olds are using iPads to play games. 2 year olds are using technology already. Judy Wajcman, in her book Pressed for Time explains further explains this concept of technology’s algorithmic being, creation, and speed. She explains how we live in a harried or rushed society and technology is actually making us busier. Technology is helping us to finish tasks quicker, giving us more time to do other tasks; therefore, making us busier. Technology in and of itself is becoming faster. Its algorithms are becoming more complex to promote speed. The washing machine your mom used in 1994 is in no comparison to the speed and efficiency of her washing machine in 2018.
The image above represents the concept of lay expertise within anthropological study of science and technology. My first example is from: “The Construction of Lay Expertise: AIDS Activism and the Forging of Credibility in the Reform of Clinical Trials” by Steven Epstein. Epstein explains how activists during the 1980s AIDS epidemic became players in the construction of credible knowledge of AIDS. Their experience, understanding, and creation of conceptual ideas made them lay experts. This concept of lay expertise carries on into my second example from author Anna Tsing with her book: The Mushroom at the End of the World On the Possibility of Life in Capitalist Ruins. Tsing wrote about Mien tribesmen matsutake hunters searching for this mushroom in the industrial forests of Oregon. These mushroom hunters are not botanists or geographers; they are not experts of matsutake. They are immigrants from China displaced by the Vietnam War who settled in the United States from the late 1970s to the mid 1990s and are now mushroom hunters. Yet, they may still be considered “lay experts”; although they may not have a collegiate degree in geography, they do understand the land and where to look and find matsutake.