6.xxx (AKA 6.803 and 6.833)

The Human Intelligence Enterprise: 2019

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Prospectus

Purpose

6.xxx is designed to help you learn about progress toward the scientific goal of understanding human intelligence from a computational point of view.

6.xxx complements 6.034, because 6.xxx focuses on long-standing scientific questions, whereas 6.034 focuses on existing tools for building applications with reasoning and learning capability.

Why you should not take 6.xxx

Take a subject in machine learning instead. 6.xxx focuses on cognition and what makes humans special. It is not about popular statistical mechanisms.

Because of the emphasis on reading and discussion, and the limitation on enrollment, regular attendance is obligatory, along with commitment to reading the papers. If you cannot picture yourself in class at 9:30 am or 11:00 am, every Monday and Wednesday, you should not register, so as to make room for others who would otherwise be excluded because of the enrollment limitation. A corollary is that you probably should not register for 6.xxx if you are taking five subjects or course equivalents, such as UROP. You definitely should not register you are involved in a startup or you are taking six or more subjects or subject equivalents.

Believing that both mind-stretching and near-miss learning are educationally useful, some of the papers I have selected are boring, stupid, or nearly unintelligible. One goal of the subject is to develop the skill of gleaning useful ideas from such papers, but if you have little or no interest in understanding human intelligence, you should not subject yourself to the necessary reading. For more detail on what you will need to read, have a look at the previous year's schedule.

About one-third of the subject is devoted to discussing how to package ideas orally and in writing. You need to be enthusiastic about practicing the skills taught with a positive attitude. For more detail on what will be covered in the communication dimension, have a look at the previous year's schedule.

Alas, advanced AI subjects are scarce, and fairness dictates that they should be offered as broadly as possible. This fairness goal must be balanced, however, against the need to keep some of them small. If you are just generally interested in AI, you should take one of the graduate lecture-based subjects.

Why you should take 6.xxx

Why 6.xxx can be viewed as a humanities subject

Level

6.803 is the undergraduate version of 6.xxx, and 6.833 is the graduate version. The two differ in that 6.833 may require you to attend some extra classes and will require you to complete a substantial term project. Both meet together ordinarily.

The graduate subject forms a bridge between 6.034 and design/project/thesis work in Artificial Intelligence.

Content

The content of 6.xxx is largely based on papers identified in an informal survey of representative AI leaders, who were asked what has most influenced the way they think about human intelligence. The papers mentioned tend to fall into the following categories, ranked by frequency:

Style

The following mechanisms are used to ensure that you read the papers and absorb the material:

The reading list, assignments, and other information are accessible via the 6.xxx home page.

Limit on enrollment

Because of the emphasis on reading, discussion, and presentation, enrollment is limited.

Credit and projects

Doing a substantial project is required for graduate credit. See projects link on subject's home page.

Catalog description, Undergraduate Version

6.803/6.833 The Human Intelligence Enterprise



Prereq.: 6.034
U (Spring)
3-0-9


Analyzes seminal work directed at the development of a computational understanding of human intelligence, such as work on learning, language, vision, event representation, commonsense reasoning, self reflection, story understanding, and analogy. Reviews visionary ideas of Turing, Minsky, and other influential thinkers. Examines the implications of work on brain scanning, developmental psychology, and cognitive psychology. Emphasis on discussion and analysis of original papers. Students taking graduate version complete additional exercises and a substantial term project. Enrollment limited.

P. H. Winston