Accepted Paper:

MACSYMA  

Author:

Stephanie Dick (Harvard University)

Paper short abstract:

The MACSYMA system was developed at MIT beginning in the 1960s. It was meant to be a "mathematical laboratory" that would enable new forms of problem solving and experimentation. I explore the vision of mathematical labor embodied in the system and the novel practices that emerged among its users.

Paper long abstract:

This talk explores new forms of mathematical thinking and doing that developed among users of MACSYMA, "Project MAC's SYmbolic MAnipulator," created at MIT in the early 1960s. The system was envisioned as a "mathematical laboratory" in which users could experiment with formal mathematical systems. At its heart, it was a toolkit of automated mathematical processes, like factorization, integration, and logical deduction. Processes like these are central to the exploration and solution of many mathematical problems, but can be incredibly tedious to do by hand. MACSYMA offered very efficient automated methods for executing them, allowing users to explore, understand, and solve problems in ways that were previously impossible. MACSYMA's developers hoped this would "free the mathematician" for what they believed were more "fundamental" parts of mathematical labor - like formulating conjectures and interpreting results. By the 1970s, MACSYMA was one of the most popular nodes on ARPANET, a precursor to the internet, with thousands of users across the country. But the system turned out to be very hard to use. MACSYMA's developers penned draft after draft of user's manuals, tutorials, and primers to help users work with the system. A close reading of these materials reveals that the developers also had to show users how to think differently about problem solving in order to recognize where the system might be useful. This paper explores the vision of mathematical labor that motivated MACSYMA's development and the reality of instituting new approaches to problem-solving throughout its user community.

Panel T158
Soft Focus: How Software Reshaped Technical Vision and Practice