Link Search Menu Expand Document

Syllabus

Table of contents

  1. About 🧠
  2. Canvas & Course Website πŸ’»
  3. Enrolling As Pass/Fail
  4. Lecture πŸ‘¨β€πŸ«
  5. Section πŸ‘©β€πŸ«
  6. Class Notes πŸ—’οΈ
  7. Assignments πŸ“
  8. Course Prerequisites ➰
  9. Assessment πŸ’―
  10. Summary of Important Dates❗
  11. Collaboration and Academic Integrity πŸ‘¨πŸ»β€πŸ’»
  12. Academic Accommodations 🀝

About 🧠

What is intelligence? An inquiry into the nature of intelligence can take different forms – philosophical, biological, mathematical or technological. In this course, we will use machine intelligence (everything from voice recognizing smartphones to game-playing computers) as a handle to think about natural intelligence (brains and behavior of animals). Although we will start with big, general questions, we will quickly move to concrete queries about brains and computers. This approach, rather than just starting with brains of animals, may be useful in framing more universal questions independent of the specific architecture of brains of animals. As machines increasingly perform tasks that were once thought to be solely in the domain of humans, there is an urgent need for discussions of the moral and societal implications of artificial intelligence. This course targets students interested in brains and computers in equal measure, and who are comfortable discussing ethical concerns.

Canvas & Course Website πŸ’»

The course website will be used for the course schedule and links to all readings and problem set submissions, while the course Canvas will be where you submit your problem sets, midterm, and final paper, and where we send announcements via the course emailer (be sure you have notifications turned on in Canvas!).

Enrolling As Pass/Fail

We are open to enrollment as pass/fail. In terms of assessment - we expect >80% lecture/section attendance and >65% across all assessments to grant a passing grade.

Lecture πŸ‘¨β€πŸ«

Lectures are held every Monday and Wednesday from 3-4:15PM in NW B103. Lecture attendance is mandatory and part of your final grade. We will use an interactive poll system (PollEv) to record class participation. Lectures will be recorded and released after each class for review. If you need to miss lecture for whatever reason, please email the Head TF (Kumaresh).

Section πŸ‘©β€πŸ«

Sections will be held by the course TFs on different days of the week. Section will be a mix of content review, group discussion, and going over problem sets. At the beginning of the semester, every student will be assigned a section (by rank-order preference) and section attendance is mandatory and part of your final grade. You must attend your own section to recieve credit. If you need to miss section for whatever reason, please email your section TF so that you can get caught up on the material for that week.

Class Notes πŸ—’οΈ

Class notes and material will be released and linked on the course website.

Assignments πŸ“

Problem sets will be a mix of short-form discussion questions and simple technical problems. No coding knowledge is needed; everything you will need to know to do the problem sets will be covered in lecture / section. Late policy: You are allowed one (1) late pass for problem sets (up to two days). After that, 1 point will be deducted off your problem set grade for each subsequent day that it is late.

Course Prerequisites ➰

There are no formal prerequisites to this course, and students do not need to be from a technical or science background. Some basic high school math may be required for some problem sets.

Assessment πŸ’―

%Course Component
10%Lecture/Section participation/attendance
10%Readings
40%Problem sets (4 total), 10% each
20%Mid-term in class exam
20%Final paper (2+3+15 across deliverables)

*Lectures will be interactive, with discussions throughout. Lectures will also be live-recorded and released after each class.

Summary of Important Dates❗

All problem sets due on Friday at 11:59pm

DateEvent
01/31PSet 1 handed out (Lectures 1-4)
02/09PSet 1 due @ 11:59pm
02/14PSet 2 handed out (Lectures 5-8)
02/20Deadline to add / drop a course (fee) and to change from letter-graded to Pass/Fail or vice versa
02/23PSet 2 due @ 11:59pm
03/06Midterm (in class)
03/09 to 03/17Spring Break!
03/27PSet 3 handed out (Lectures 13-16)
04/05PSet 3 due @ 11:59pm
04/10PSet 4 handed out (Lectures 17-20)
04/19PSet 4 due @ 11:59pm, paper proposal due (in Section)
05/06Final paper due

Late policy: You are allowed one (1) late pass for problem sets (up to two days). After that, 1 point will be deducted off your problem set grade for each subsequent day that it is late.

Collaboration and Academic Integrity πŸ‘¨πŸ»β€πŸ’»

Discussion and the exchange of ideas are essential to doing academic work. For assignments in this course, you are encouraged to consult with your classmates as you work on problem sets and exercises. However, after discussions with peers and/or TFs, make sure that you can work through the problem yourself and ensure that any answers you submit for evaluation are the result of your own efforts. If any books, articles, websites, lectures, etc that have significantly helped you with your work, please use appropriate citation practices. Be sure to familiarize yourself with the Harvard honor code, and follow it.

Academic Accommodations 🀝

Any student needing academic adjustments or accommodations is requested to present their letter from the Disability Access Office (DAO) and speak with the professor by the end of the second week of the term. Failure to do so may result in the course head’s inability to respond in a timely manner. All discussions will remain confidential, although AEO may be consulted to discuss appropriate implementation.