Syllabus for Human-centered Machine learning (CSCI 7000, Spring 2018)

Course description and goals

Machine learning is everywhere, but why do we need machine learning systems? The answer depends on the situation. In this course, we will take a human-centered approach and explore how machine learning systems can assist humans in various tasks to improve the ability of humans.

It is required that you have regular access to a computer and an Internet connection throughout this course. A laptop is preferable.

Approach

We have two lectures per week and each student is expected to present once in class. As a crucial step of research is to come up with a good research question, we will ask each student to write two research proposals in this class. Each proposal will be at most five pages and is expected to identify a research question, explain why it is a good research question, and propose a tentative plan to address it (e.g., computational models, experiment designs, etc). The final project will be done in groups with at most two or three people depending on class size.

Preliminary topics (check course page for updated schedule)

  • Behavioral/psychological biases
  • Interpretable machine learning
  • Human-in-the-loop machine learning
  • Machine-in-the-loop theory
  • Machine-in-the-loop applications (creative writing, accessibility, robotics)
  • Fairness and algorithmic biases

Required background

Mathematical background: Linear algebra, probability, calculus, and statistics. Students are expected to have basic knowledge about machine learning.

Programming: Students are expected to be familiar with coding related to machine learning applications. Knowledge of scikit-learn and deep learning packages such as tensorflow, pytorch, and keras would be useful.

Course evaluation

  • proposals (2 times, 20%)
  • course presentation (10%)
  • final project (50%)
  • peer feedback (15%)
  • participation (5%)

Late policy

We do not allow for any late submissions.

Academic Integrity

All students of the University of Colorado at Boulder are responsible for knowing and adhering to the academic integrity policy of this institution. Violations of this policy may include: cheating, plagiarism, aid of academic dishonesty, fabrication, lying, bribery, and threatening behavior. All incidents of academic misconduct shall be reported to the Honor Code Council (honor@colorado.edu; 303-735-2273). Students who are found to be in violation of the academic integrity policy will be subject to both academic sanctions from the faculty member and non-academic sanctions (including but not limited to university probation, suspension, or expulsion).

Other information on the Honor Code can be found at http://www.colorado.edu/policies/honor.html and at http://www.colorado.edu/academics/honorcode/.

Course Policies

If you qualify for accommodations because of a disability, please submit to your professor a letter from Disability Services in a timely manner (for exam accommodations provide your letter at least one week prior to the exam) so that your needs can be addressed. Disability Services determines accommodations based on documented disabilities. Contact Disability Services at 303-492-8671 or by e-mail at dsinfo@colorado.edu. If you have a temporary medical condition or injury, see Temporary Injuries guidelines under the Quick Links at the Disability Services website and discuss your needs with your professor. Please inform the professor of any accommodations needed relative to disabilities at the start of the semester.

Campus policy regarding religious observances requires that faculty make every effort to deal reasonably and fairly with all students who, because of religious obligations, have conflicts with scheduled exams, assignments or required attendance. In this class, inform the professors of conflicts at the start of the semester. See full details at http://www.colorado.edu/policies/fac_relig.html

Students and faculty each have responsibility for maintaining an appropriate learning environment. Those who fail to adhere to such behavioral standards may be subject to discipline. Professional courtesy and sensitivity are especially important with respect to individuals and topics dealing with differences of race, culture, religion, politics, sexual orientation, gender, gender variance, and nationalities. Class rosters are provided to the instructor with the student's legal name. I will gladly honor your request to address you by an alternate name or gender pronoun. Please advise me of this preference early in the semester so that I may make appropriate changes to my records. See policies at http://www.colorado.edu/policies/classbehavior.html and at http://www.colorado.edu/studentaffairs/judicialaffairs/code.html#student_code.

The University of Colorado Boulder (CU Boulder) is committed to maintaining a positive learning, working, and living environment. CU Boulder will not tolerate acts of sexual misconduct, discrimination, harassment or related retaliation against or by any employee or student. CU’s Sexual Misconduct Policy prohibits sexual assault, sexual exploitation, sexual harassment, intimate partner abuse (dating or domestic violence), stalking or related retaliation. CU Boulder’s Discrimination and Harassment Policy prohibits discrimination, harassment or related retaliation based on race, color, national origin, sex, pregnancy, age, disability, creed, religion, sexual orientation, gender identity, gender expression, veteran status, political affiliation or political philosophy. Individuals who believe they have been subject to misconduct under either policy should contact the Office of Institutional Equity and Compliance (OIEC) at 303-492-2127. Information about the OIEC, the above referenced policies, and the campus resources available to assist individuals regarding sexual misconduct, discrimination, harassment or related retaliation can be found at the OIEC website.