Society of Mind: AI for Humans
Time: Tue/Fri 3:25-5:05 ET/Boston
Location: Online (See Canvas for connection info.)
John Rachlin
Associate Teaching Professor, Northeastern University
| j.rachlin@northeastern.edu | |
| Web | https://www.khoury.northeastern.edu/home/rachlin/ |
| Office Hours | Wed 2-5p, Thu 1-4p on Zoom. By appointment only. Please email me with your availability to arrange other times. |
Course Information
Course Description
This course offers a comprehensive introduction to Artificial Intelligence (AI) designed for non-computer science majors. No programming experience is required. Students will explore the history and major milestones of AI, gaining insight into the technologies that are rapidly reshaping industries, enhancing human intelligence, and sparking new avenues of creativity. Key concepts such as deep learning, natural language processing, recommendation systems, and generative AI will be demystified through real-world examples. The course will also delve deeply into the legal, ethical, and societal implications of AI, equipping students with the skills needed to effectively engage with modern AI technologies. Through discussions, case studies, and interactive activities, students will develop a nuanced understanding of AI’s strengths and limitations, preparing them to make informed decisions about the use of AI in their personal and professional lives.
4.000 credit hours
Prerequisites: None
Textbooks and Readings
Required: Mauro and Valigi (2020) Zero to AI: A nontechnical
hype-free guide to prospering in the AI era, Manning Publications.
This is a very good book for a future business leader or project manager looking to leverage AI in a business context. It is, however, very light on details about how AI works and although the book is only a few years old, it's coverage of natural language processing (chapter 5) is quite out-of-date already.
Recommended: Provost and Fawcett (2013) Data Science for Business:
What you need to Know About Data Mining and Data-Analytic Thinking, O'Reilly Media.
This book goes into much more detail about the key concepts and algorithms of machine learning while remaining accessible to non-CS majors. A useful reference.
Recommended (One short story possibly required): Ted Chiang (2019) Exhalation, Vintage Books.
A highly thought-provoking collection of AI-themed science fiction short stories. I might have you read one short story: The Lifecycle of Software Objects which delves into the societal implications of sentient programs and their legal rights.
Additional readings may be assigned from books freely available to Northeastern students through O'Reilly E-Books or distributed as PDFs.
Class Recordings and Advice for taking a synchronous (live) online class.
Classes will be recorded. Recordings are available through Canvas....Zoom Meetings....Cloud Recordings. Recordings should not be used as a substitute for coming to class. In fact, I do take attendance, and attendance counts towards your final participation grade.I understand that taking a class online can be a challenge for some students. I will do everything in my power to make the class as personalized and engaging as possible. This course was not designed for 100,000 anonymous strangers. I will tailor the material to your questions and feedback and your assignments will be individually evaluated by me. As this is a relatively small class, group discussions will be an important part of the experience. You can make this class more interesting and fun by asking questions, engaging in discussions and debates, expressing opinions, and having a voice.
Please turn your cameras on as you would in any professional meeting.
Evaluation
The final grade for this course will be weighted as follows:
- Homework: 50%
- Project: 30%
- Participation (attendance, discussions, etc.): 20%
Final grades will be assigned based on the following scale. Computed grades are NOT rounded.
| Letter | Range |
|---|---|
| A | 94 - 100 |
| A- | 90 - 94 |
| B+ | 87 - 89 |
| B | 83 - 86 |
| B- | 80 - 82 |
| C+ | 77 - 79 |
| C | 73 - 76 |
| C- | 70 - 72 |
| D+ | 67 - 69 |
| D | 63 - 66 |
| D- | 60 - 62 |
| F | <60 |
Homework Late Policy
My homework late policy is:- Up to 48 hours late: 10% penalty
- After 48 hours: Not accepted.
Academic Misconduct
Homework is a creative process. Individuals or pair groups (when allowed) must reach their own understanding of problems and discover paths to their unique solutions. During this time, discussions with friends and colleagues are encouraged—you will do much better in the course, and at Northeastern, if you find people with whom you regularly discuss problems. But those discussions should take place verbally. If you simply copy solutions or large blocks of text from another student you are breaking the rules. Each solution must be largely the product of your own mind. However, each assignment will clearly specify whether using AIs such as ChatGPT is permitted and how they may be used. For most assignments, the appropriate use of AI will be both permitted and encouraged!The university's academic integrity policy discusses actions regarded as violations and consequences for students:
http://www.northeastern.edu/osccr/academic-integrity
Schedule
Note: This schedule is subject to change and will be adjusted as needed throughout the semester.
| Week | Date | Topic | Reading | HW Due |
|---|---|---|---|---|
| 1 | Sep 6 | An Introduction to AI: Course structure and expectations. Remember when everyone was hyping Big Data? Now we know why. My funny recent encounters with AI, and we answer the question, once and for all: What is Intelligence? | Zero2AI:Ch1 | |
| 2 | Sep 10/13 | History of AI: We explore the evolution of AI from early theoretical foundations to modern advancements. That time I watched Garry Kasparov lose to IBM Deep Blue. From Rogerian therapists (How does that make you feel?) in 420 lines of code to ChatGPT with its billions of parameters and why the lastest developments are so compelling. Hint: It's not what it knows. It's what it understands. | Zero2AI:Ch2 | HW1 (9/15):Are you smarter than my AI? |
| 3 | Sep 17/20 | Retail AI: Applications in sales and marketing. Predicting churn. Sales forecasting. Customer segmentation. Supervised vs. unsupervised learning. Regression vs. Classification. The challenge of overfitting. | Zero2AI:Ch3 | |
| 4 | Sep 24/27 | Every move you make: Image analysis, facial recognition, object classification and tracking, and deep learning. Self-driving trucks and cars and the reinvention of transportation logistics. The rise of the surveillance state: When corporations and governments track everywhere you go, every purchase you make, every person you meet, every website you visit, every tweet you post, and how you vote. | Zero2AI:Ch4 | HW2:Machine learning algorithms in a spreadsheet. |
| 5 | Oct 1/4 | Talking to Machines: Ever wonder how your phone’s assistant understands you? We’ll decode the mysteries of natural language processing and chat with some famous bots. Is AI customer support a good thing? We put Turing to the Test: ChatGPT pretends to be a 20-something Business Administration major at NEU. | Zero2AI:Ch5 (Rip it out after reading.) |
|
| 6 | Oct 8/11 | The AI Doctor will see you now: Can AI be your next healthcare provider? We’ll explore how algorithms diagnose and predict disease and even perform surgery—minus the white coat. Analyzing MRIs in 4-dimensional spacetime. Type I and Type II errors and why they both matter. Your robot electric toothbrush knows you don't floss regularly and your dental insurance provider isn't happy. (Un)explainable AI. | TBA | HW3: Translation Challenge |
| 7 | Oct 15/18 | I know what you're thinking: Why does Netflix know exactly what I want to watch? Why is Youtube Shorts showing me an endless stream of cat rescue videos and interviews with Neil deGrasse Tyson? We dive into the world of recommender systems and the goal of customer engagement. You're living in a bubble, man! How to read a newspaper for a healthier, less polarized, worldview. | Zero2AI:Ch6 | |
| 8 | Oct 22/25 | AI at play: That time I beat my AI classmates at Gomoku. Beyond minimax. Chess, Go, Jeopardy, and welcoming our new computer overlords. | TBA | HW4:Rachlin needs new music |
| 9 | Oct 29/Nov1 | AI Experts: From Expert Systems to Intelligent Decision-Support. Darwin in the Machine: Evolutionary Computing and Complex Systems. Intelligence as an emergent phenomenon. Effective decision making according to Peter Drucker. | TBA | |
| 10 | Nov 5/8 | Professor AI: AI in education. Transforming how we learn and how we teach. Using AI tools effectively. Intelligence is the ability to alter your own programming. Adapting in a rapidly changing world. The role of empathy in pedagogy and why I think my job is safe for a few more years. | TBA | HW5:Design your own AI problem solver. (Python Code Optional.) |
| 11 | Nov 12/15 | The Alignment Problem: What happens when a machine learning model fails to reflect the values of our society? Who’s the boss—humans or machines? We’ll tackle the big ethical questions, from bias in algorithms to AI making decisions about who to hire, who to parole, or who shall receive a kidney transplant. | TBA | |
| 12 | Nov 19/22 | The AI Research Assistant: AI isn’t just for business. Scientists are teaming up with AI algorithms to define novel research directions, interpret and analyze experimental results, discover new drugs, measure the impacts of climate change, and even explore space. The Mars Curiosity rover gets a brain upgrade. | TBA | |
| 13 | Nov 26 | Creative AI: Examine AI’s role in generating creative works from art and music to literature. The implications of deepfake photos and videos. Generative AI and the role of copyrights and trademarks. Freedom is the freedom to say that two plus two make four. If that is granted, all else follows. | TBA | Project: Business Plan for AI adoption or Science Research Proposal (To be shared in the last week of class.) |
| 14 | Dec 3 | AI Futures: Speculations on the impact of AI in 10, 50, and 100 years. Singularities and Transhumanism. Utopias and Dystopias. Beyond human intelligence. The constitutional rights of sentient silcon. | Ted Chiang: The Lifecycle of Software Objects |
Inclusive Class
Northeastern University values the diversity of our students, staff, and faculty; recognizing the important contribution each makes to our unique community.
Respect is demanded at all times throughout this course. In the classroom, not only is participation required, it is expected that everyone is treated with dignity and respect. We realize everyone comes from a different background with different experiences and abilities. Our knowledge will always be used to better everyone in the class.
We strive to create a learning environment that is welcoming to students of all backgrounds. If you feel unwelcome for any reason, please let me know or reach out to your academic advisor so we can work to make things better.
Northeastern is committed to providing equal access and support to all qualified students through the provision of reasonable accommodations so that each student may fully participate in the learning experience. If you have a disability that requires accommodations, please contact the Disability Resource Center http://www.northeastern.edu/drc/, DRC@northeastern.edu, 617-353-2675. Accommodations cannot be made retroactively and to receive an accommodation, a letter from the DRC or LDP is required.