Course Syllabus


Woman at desk with laptop, abstract wave above labeled "Generative AI".

Welcome to Gen Ed 1188!

Are you curious about ChatGPT, Dall-E, Midjourney, and other forms of Generative AI?

Do you want to learn how to use these tools effectively, and understand how they work?

Are you excited and/or concerned about the impact that AI will have in our future?

Then this course might be for you!

Open to all—we expect no background in computer science or AI. Just a sense of curiosity and a spirit of adventure.

(Image created by C. Stubbs using DALL-E, 2023)

Course Schedule:

The course is divided into 4 parts, each 3 weeks long:

  1. Introduction to Generative AI (GAI)
  2. Near-term impacts of GAI across the disciplines
  3. Technological aspects of GAI
  4. The speculative, long-term future of GAI

A detailed weekly schedule is available from the Course Modules page.

Course goals:

Students will gain proficiency in the following areas:

  1. Foundational Understanding: Grasp the fundamental distinctions and principles behind machine learning and generative artificial intelligence (GAI).
  2. Ethical Awareness: Recognize the ethical challenges and implications of GAI, from truth validation to academic integrity and societal impacts.
  3. Technological Mechanics: Understand the inner workings of large language models (LLMs) and other GAI systems, including neural networks and transformer architecture.
  4. Multimodal AI: Gain insights into the realm of multimodal GAI tools, including creative opportunities and deepfakes in image, audio, and video formats.
  5. Practical Applications: Acquire hands-on experience with GAI tools, exploring their capabilities and limitations. Learn to validate and verify GAI outputs.
  6. GAI in Disciplines: Analyze the influence and potential of GAI across arts and humanities, social sciences, and science/engineering/medicine domains.
  7. Historical Context: Examine the evolution of GAI against the backdrop of past technological revolutions and anticipate its trajectory.
  8. Regulation and Governance: Understand the historical and current frameworks for technological regulation, speculating on the needs and challenges specific to GAI.
  9. Philosophical Inquiry: Engage in debates surrounding the consciousness, existential significance, and broader philosophical ramifications of advanced GAI systems.
  10. Future Preparedness: Reflect on and strategize for a future shaped by GAI, emphasizing responsible usage, regulation, and coexistence.

These goals aim to provide students with a comprehensive understanding of GAI and its implications, allowing them to engage thoughtfully with the technology both now and in the future.

Course format:

  1. Lectures (attendance required):
    • Held on Tuesdays and Thursdays from 9:00 to 10:15.
    • Participatory in nature, where students are encouraged to engage and contribute during the lecture sessions.
  2. Mandatory Weekly Discussion Sections:
    • Small-group sessions designed for deeper discussion and debate on topics covered in the lectures.
    • These sections are mandatory, and missing more than two unexcused sessions could result in a substantial reduction of the student's grade.

Typical enrollees:

As a General Education course we welcome all students regardless of background. We expect the course will be particularly appealing to students who want to learn to use generative AI tools, students who want to understand more about how these tools work (at a general non-technical level), and students who want to engage in thoughtful dialogue about how these AI tools will shape the future, and the philosophical, ethical, and regulatory questions that society will face.

When is the course typically offered?

Spring 2024 will be the first offering of this course; at this point we do not know when the course will next be offered.

What can students expect from you as an instructor?

  • Dynamic Learning Experience: We're passionate about Generative AI, offering a blend of lectures, hands-on sessions, and discussions to foster deep understanding.

  • Access to Tools & Resources: You'll have direct access to AI tools throughout the semester, supported by our guidance and real-world application projects.

  • Open Dialogue & Collaboration: We value diverse perspectives, promoting open discussions in class, panel debates, and active interactions on our Slack channel.

  • Hands-on & Experiential Approach: Our teaching style emphasizes active participation, where you'll experiment with AI tools, engage in group projects, and explore AI's broader implications through multimedia.

  • Guidance & Support: We're here for you, with open office hours and a commitment to guiding you through both the technical and philosophical aspects of Generative AI.

Assignments and grading:

  • Class attendance and in-class quizzes (20%): Regular attendance to lectures and discussion sections, along with quizzes conducted during class.
  • Homework (20%): Weekly assignments due by midnight on Thursdays.
  • Paper (20%): A 10-page research or exploration paper on a topic related to Generative AI. The use of GAI is allowed but must be appropriately acknowledged and cited.
  • Final Project (20%): Undertaken in teams of 2-3, this project focuses on real-world applications of GAI methods.
  • Final Exam (20%): An in-class cumulative exam, which includes both sections that permit the use of GAI and those that don't.

Sample reading list:

There are two required texts for the course:

Life 3.0: Being Human in the Age of Artificial Intelligence
Author: Max Tegmark
Publisher: Vintage
ISBN-13 ‏ : ‎ 978-1101970317

Frankenstein (1818 text preferred; 1831 text also OK)
Author: Mary Shelley
Publisher ‏ : ‎ Penguin Classics; also available free online from Project Gutenberg
ISBN-13 ‏ : ‎ 978-0143131847

Additional short stories and short articles will be assigned, TBA.

Absence and late work policies:

Attendance at lectures and sections is required; students may miss 2 course meetings (of any kind) without grade penalty. Late work will be downgraded 20% for each day it is late.


We expect students to be proficient with the operation and use of personal computers, including simple spreadsheets, word processing, and web browsing. No programming experience is necessary. Bring an open mind, a healthy skepticism, and a willingness to explore. You’ll need a laptop or tablet to participate in class exercises. We expect that you’ll have or have access to a computer with a simple text editor, Excel or the equivalent, a web browser, and WiFi.

AI Policy:

This course encourages students to explore the use of generative artificial intelligence (GAI) tools for components of assignments and assessments. Any such use must be appropriately acknowledged and cited. It is each student’s responsibility to assess the validity and applicability of any GAI output that is submitted; you bear the final responsibility. Assignments will include sections that we strongly recommend be completed without GAI tools, since the final exam will be undertaken without access to GAI.  Violations of this policy will be considered academic misconduct. We draw your attention to the fact that different classes at Harvard could implement different AI policies, and it is the student’s responsibility to conform to expectations for each course.