705.612.8VL - Values and Ethics in Artificial Intelligence

Course Structure

The course is divided into modules, listed below. Each module starts with an introduction during office hours. Every module has assigned readings, which should be used as sources and references for other assignments.

There is also one larger group project, due near the end of the term with several checkpoints during the semester.

Most modules have a longer module assignment and a shorter discussion assignment. Discussions are usually, but not always, posted on the class discussion board. Many assignments are cases requiring a decision and a justification.

Some assignments also require data analysis or design work.

Many discussion assignments are due midway through the module, leaving a couple of days for required responses to other posts.

Course Topics

• Frameworks for values-based decisions. (Modules 1 and 2). Perspectives from Philosophy, Engineering, Psychology and Organizational Studies.
• Lethal Autonomous Weapons. (Module 3). Contrasting perspectives on autonomous weapons and "meaningful human control."
• Autonomous Vehicles. (Module 4). Anticipating values-based decisions on a new technology Algorithm Bias. (Module 5). Causes of algorithm bias, diagnostics, and mitigation strategies.
• Explainability. (Module 6). Strategies for providing transparency and asserting human control.
• Privacy. (Module 7). Current and near-future threats to privacy, including "Deep Fakes" and de-anonymization.
• Midterm review and guest lecture on Moral Scene Assessment (Module 8).
• Organizational decision-making. (Modules 9 and 10). Organizational dynamics and pressures that affect values-based decisions, and strategies for advocacy within organizations.
• Safety and Design. (Module 11.) Design problems for assuring safety with intelligent, adaptive systems.
• The Future of Work. (Module 12.) A.I. is a short-term cause of technological unemployment, and a longer-term force that reshapes what people do and how we do it.
• Long-term A.I. Safety. (Module 13.) Anticipating possible futures with superhuman intelligence.
• Review and Artificial Life. (Module 14.) Project presentations, final review and anticipating the future of artificial life.

Course Goals

1. Analyze current and near-future AI-related issues to identify underlying moral, ethical, and values-based components from different perspectives.
2. Understand technical aspects of current technology well enough to have pragmatic and well-informed ideas about what is possible now and in the near future.
3. Understand how decisions are made and constrained by organizational, legal, and cultural frameworks, and anticipate how these may adapt to changing capabilities.
4. Develop and clarify a personal perspective on values and ethics that can be applied to many issues from different roles.
5. Be prepared to identify key value and ethical issues of whatever amazing, surprising, troubling, or confusing developments the future of this fascinating technical area holds.

Course Learning Outcomes (CLOs)

• Recognize and mitigate issues related to Algorithm bias.
• Identify key ethical issues and the current state of the art solutions related to autonomy, safety, and privacy.
• Identify values conflicts that make ethical cases difficult in high tech environments; develop and explain solutions to these types of conflicts.
• Forecast and critically evaluate future developments related to AI, including short and long-term safety, changes in the economy and changes in the workforce.

Textbooks

Christian, B. (2020). The alignment problem: Machine learning and human values. W. W. Norton. ISBN:978-0-393-63583-6.

2021 coursepack: https://hbsp.harvard.edu/coursepacks/847313

Other Materials & Online Resources

Student Coursework Requirements

Course project (25% of total grade)

Class members will work in groups to complete a larger project with a data analysis or design component on one of the course topics.

Discussions (25% of total grade)

Most modules have a Discussion assignment, although not all will be posted on the discussion board, see module instructions.

Weekly assignments (50% of total grade)

Most modules include a weekly assignment.

Grading Policy

EP uses a +/- grading system (see “Grading System”, Graduate Programs catalog, p. 10). 

Course Policies

Tutoring Website

Johns Hopkins Engineering for Professionals offers a tutoring connection network that allows students to connect with other Johns Hopkins Engineering students or alumni for tutoring services. This service allows students to search a list of courses to “Find a Tutor” or complete a profile to “Become a Tutor.” More information about this service can be found on the tutoring website (https://tutor.ep.jhu.edu/).

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.