Advancing AI through cognitive science

NYU PSYCH-GA 3405.001 / DS-GA 3001.014

This project is maintained by brendenlake

Advancing AI through cognitive science

Instructor: Brenden Lake

Meeting time and location:
Thursday 4-5:50 PM
Meyer Room 465 (4 Washington Place)

Course numbers:
PSYCH-GA 3405.001 (Psychology)
DS-GA 3001.014 (Data Science)

Office hours:
Wednesdays 10-11:00 am, or by appointment; 60 5th Ave., Room 610

Summary: Why are people smarter than machines? This course explores how the study of human intelligence can inform and improve artificial intelligence. We will look to cognitive science, with special focus on cognitive development, to help elucidate a set of “key ingredients” that are important components of human learning and thought, but are either underutilized or absent in contemporary artificial intelligence. Through readings and discussion, we will cover ingredients such as “intuitive physics,” “intuitive psychology,” “compositionality,” “causality,” and “learning-to-learn,” although students will be encouraged to contribute other ingredients. Each ingredient will be discussed and compared from the perspectives of both cognitive science and AI, with readings drawn from both fields with roughly a 50/50 proportion.

This is a small discussion-based seminar, so please come ready to participate in the discussion. Please note that this syllabus is not final and there may be further adjustments.



The final grade is based on the final paper or project (50%), written reactions to the reading (25%), and participating in discussions (25%).

The final paper or project is done individually. For the final assignment, students may either write a final paper that proposes an additional ingredient of human intelligence that is underutilized in AI, or complete a project that implements one of the ingredients discussed in an algorithm.

The project will represent either an substantial extension of one of the homeworks (e.g., exploring some new aspect of one of the assignments), implementing and replicated an existing cognitive modeling paper, or a written paper discussing one of the core modeling topics. The final projects will need to be approved by the instructor at least 6 weeks before the end of the semester.

Course discussion

We will be using Piazza for reactions to readings and class discussion.

The signup link for our Piazza page is available here (

Once signed up, our class Piazza page is available here (

Final assignment

Course policies

Auditing: Unfortunately we have no additional spots for auditors due to the large number of previous requests. If I have replied to your request, you may audit pending available seats. Priority goes to registered students and then by date of audit request.

Overview of topics and schedule

Detailed schedule and readings

Please see below for the assigned readings for each class (to be read before class). Before each class, students will be asked to submit a reaction to the readings (three paragraphs). Reaction posts are submitted via Piazza. Papers are available for download on NYU Classes in the “Resources” folder. Reactions are due by midnight the day before class (so I have time to read the reactions!)

1/25 Introduction and overview

2/1 Deep learning – Lecture

2/8 Deep learning – Discussion

2/15 Intuitive physics (part 1: humans)

2/22 Intuitive physics (part 2: machines)

3/1 Intuitive psychology (part 1: humans)

3/8 Intuitive psychology (part 2: machines)

3/15 NO CLASS. Spring Recess

3/22 Compositionality

3/29 Causality

4/5 Learning-to-learn

4/12 Critiques of “Building machines that learn and think like people”

4/19 Recent critiques and innateness (with special guest Gary Marcus )

4/26 Language and Culture

5/3 Emotion and Embodiment