CCTP-607: Leading Ideas in Technology: AI to The Cloud
Professor Martin Irvine
Communication, Culture & Technology Program
This course will provide a conceptual and design-oriented introduction to some of the leading ideas in technology that everyone needs to know. The course is especially designed for students from non-technical backgrounds, but all students can benefit from learning the methods in this course.
Framework and Main Approaches
In this course, we will go beyond the hype and popular responses to technologies and learn the essential design principles and ideas that make our leading technologies possible. You will be able to answer the “why,” “what,” and “how” questions to answer bigger, general questions like:
- What are the basic principles of modern computing systems that underlie everything else?
- What is “artificial intelligence” (AI) and “Machine Learning” (ML)?
- What are “algorithms” and how are they designed?
- What is “Cloud Computing,” and how are Cloud systems extensions of the Internet and Web?
- What is “Big Data” and what do we mean by “Data Analytics” and “Data Visualization”?
- What is “the Internet of Things (IoT)”?
- What are “smart” appliances (home security, media services, shopping)?
We will combine four main methods and approaches for an interdisciplinary deblackboxing method (exposing the designs and concepts behind what we can’t observe when using a technology). This integrated method works to reveal how everyone, not just technical people, can understand the meaning of the ideas behind our technologies and find ways to participate in how they can be used. We will will combine:
(1) “Systems Thinking” to understand how a specific technology is part of a larger, interrelated system (for example, computing systems, kinds of software, networks, and social contexts);
(2) “Design Thinking” for uncovering how and why certain technologies are designed the way they are, including the history of designs and the consequences of design choices;
(3) “Semiotic Thinking” for understanding these technologies as artefacts of human symbolic thought, which includes (a) understanding how sign systems and media can be digitally encoded as “information” or data, (b) the relationship between abstract models (e.g., algorithms, code, data models) and how (or whether) they can be implemented technically, and (c) understanding the social meanings, values, and purposes of the technical systems;
(4) the “Ethics and Policy” viewpoint for evaluating the social consequences of design choices in the large-scale adoption of certain kinds of technologies, and for analyzing proposals for ethical decisions and governmental policy.