Description

MAS.S63 Cognitive Enhancement

2019 Spring Course

Instructor: Pattie Maes, Professor of Media, Arts and Sciences

Units: 2-0-7
Time: Friday 1PM-3PM
Place: E14-514B

TAs:
Angela Vujic (avujic@mit.edu)
Mina Khan (minakhan@media.mit.edu)

Note: Prior application and approval of instructors required

Computers and smartphones are generally considered to be tools that enhance productivity. But while they have put the world’s knowledge at our fingertips, people need additional skills in order to be successful and realize their goals. This class will explore how future personal digital devices may help us with issues such as attention, motivation, behavior change, memory, and emotional regulation. We will read relevant literature from Brain & Cognitive Sciences and Human-Computer Interaction to inform the design of wearable and immersive systems that in minimally disruptive ways can help people strengthen some of these “soft skills”. Our devices these days are with us 24 x 7 and have access to a growing array of real-time data about our context, behavior, body, and mind. They can run powerful machine learning algorithms that analyze this data to form models and predictions. We will explore how they can use such data and models to intervene in real time to support users. We will discuss ethical and social issues that come up in designing such highly personal and intimate enhancement systems, such as avoiding dependence and guaranteeing privacy and control. Students will be asked to read and comment on 1-2 papers every week, make occasional presentations in class, come up with novel design concepts and finally develop and implement one larger scale small group project. Students will have access to novel devices and platforms developed in the Fluid Interfaces research group to base their projects on. The class will be limited to 16 highly motivated, qualified students.

Candidates should fill out this form by Wednesday 2/6/19 at the latest to be considered:
https://goo.gl/forms/WblEmhPRHaOGZBHQ2

Grading:
Final project – 30%
2 Proposals – 20% total
8 Assignments – 50% total

MAS S63