STS-3094B Diversity and Technology

First off, before this class and outside of this class I didn't know anything about the NYU aging incubator until today. I learned I liked a lot of programs such as the student photo competition and the buddy program. I also think that it is really good these programs have continued in a modified fashion throughout quarantine and the COVID-19 pandemic. Overall I think they have a great mission. It is good to remember that aging and getting old isn't a bad thing. Western culture is strongly and oddly against aging, and -- although they aren't married ideas -- death, as well. In a lot of other cultures death is considered just another part of life, and aging is a sign that somebody should be respected. Just recently, my grandmother passed, and the mayor of her town came and organized the flowers at her wake personally. I think this goes to show that aging should not be stigmatized as much as it is. The way we express our disdain for aging is very subtle, but it is still there

The other midterm project that I looked into was Helen's about voice controlled devices and language as a salient social identity. Helen and I were partners in this class at the beginning of the semester. We both chose to target language as the salient social identity we were going to grapple with. I ended up choosing natural language processing as my technology, and I believe that our projects therefore end up complementing each other. Our projects were very similar in the issues that were brought up, however Helen approached language from the lens of accents and I approached language from the lens of vernacular. I think that if natural language processing were to consider all vernaculars and voice control devices were to consider all accents, we would have seamless voice controlled devices that are accessible to all. Making this type of human to computer communication accessible to all would remove a lot of barriers in the world of technology 

Presentation Problem: Natural language processing is generally considered to have started with Alan Turing’s work in the 1950s, although the implementation of artificial intelligence into the field in the last decade has given its developers a social responsibility in preventing their technology from perpetuating demographic biases.  This includes sexual and racial bias, as well as language bias. While the technology is researched worldwide, the diversity in the United States makes it especially important for American developers to be vigilant with these issues. English may be spoken by 1.75 million globally (Harvard Business Review), but vernacular and skill level brings up the question, what can be considered natural language? Affected Populations, SSIs: “In psychology, where most studies are based on western, educated, industrialized, rich, and democratic re- search participants (so-called WEIRD, Henrich et al. (2010)), the tacit assumption that human nature

Algorithms of Oppression , while dated, demonstrates Google's disregard for bias prevention.  My midterm project is on how NLP can open up perpetuation of demographic biases, and the examples drawn from the book are directly related to this.  Today's discrimination can take on a more insidious form, less and less lunging to tear down and more and more hiding behind systemizing the us/them mentality.  This is the type of discrimination brought up in Algorithms of Oppression .  Google never outright states that women of color are sexual objects but is certainly ready to direct you to HotBlackPussy.com upon a keyword search "black girls" (Safiya 3). One of the Google Talk's proposed solutions that came up fairly often was diversifying their team.  While this is a good idea generally, it brought up a lot of notions that did not sit well with me.  The most obvious of which is the fact that the need to diversify your team indicates there isn't already diversity in