The evolution of "artificial intelligence"
Shreeharsh Kelkar, Professor
Interdisciplinary Studies Field (ISF)
Closed. This professor is continuing with Spring 2024 apprentices on this project; no new apprentices needed for Fall 2024.
The term "AI" or "artificial intelligence" is now regularly splashed across news articles and op-eds; most people have some, if vague, idea of what AI means. But the term today does not mean what it used to mean: in the last two decades, the crop of technologies we now call AI used to be called "machine learning", or even "pattern recognition".
This project seeks to understand how the meaning of the term changed and specifically what events and which actors were responsible for this transition over the last two decades. It starts with the hypothesis that this transition was not necessarily engineered as much as emergent from a confluence of forces and events such as the growing pre-eminence of Silicon Valley as a center of innovation, a series of events such as the DARPA autonomous vehicle challenge and their coverage in the media, as well as a political climate in which economic inequality was a prime object of discussion; the key actors in this transition were programmers and computer scientists in Silicon Valley, academia, and government along as journalists and other actors working in the media industries.
The project will use archival work and framing analysis to construct a historical narrative documenting the changing meaning of AI in public discourse. In the first phase of this project to be carried out over Spring 2023, we will carry out a framing analysis of articles about AI published in the New York Times (an index of public discourse in general) and Wired Magazine (a publication that has functioned as a voice of Silicon Valley). In later semesters, we will expand this framing analysis to more media publications and archival work.
Role: Learning outcomes:
Over the course of this project, the student will be able to:
- articulate the history of AI in the post-war era and the twists and turns of this history
- develop and hone research skills that involve archival work and framing analysis.
- develop and hone writing skills through writing a report that describes clearly the research findings and justifications for methods
Tasks
Over Spring 2023, the student will have to carry out the following tasks:
- use online databases and web searching skills to build a database of articles in the NYT and Wired that mention the term AI or "artificial intelligence"
- read and summarize these articles in an Excel sheet
- carry out some basic framing analysis of these articles to understand what the term AI *means* in these articles
- writing a report describing the findings.
Qualifications: Desirable but not essential:
- the student should have some background and interest in the topic and history of AI; this could be from having taken a CS course on machine learning, a course on the history of AI, or their background reading.
- the student should have some experience in working with qualitative research methods: doing searches in library databases for news articles as well as being able to summarize and analyze them.
- ideally, the student should be either a junior or a senior; those majoring in ISF, media studies, american studies, history, anthropology, sociology, rhetoric, political science/economy, computer science, and data science are especially encouraged to apply.
Hours: 3-5 hrs
Related website: https://shreeharshkelkar.net
Digital Humanities and Data Science Arts & Humanities Social Sciences