ENCS 691: Social Aspects Of AI Systems
Background
Artificial intelligence (AI) has globally transformed numerous industries over the past decade. Up to 70% of companies will be able to actively use at least one type of AI technology in their processes by 2030 and that this shift could produce an additional $16 trillion in global economic growth by 2030. AI holds a huge promise to solve global concerns over global warming, healthcare access, and providing advances in digital technologies. While AI-based systems are ultimately software systems, current Software Engineering (SE) research/training rarely considers the social intricacies of building AI-based software systems.
Course Description
The objective of this course is to provide the students with a solid background on the societal understanding of AI and its multiple aspects of human rights, sustainable development, and equity, diversity and inclusion. This new course will holistically address various social aspects related to AI, such as the distribution of benefits from the use of AI accounting for diversity (of gender, age, race, origin, etc.), privacy, ethics in algorithms, datasets, but also aspects of economy, employment and sustainability. These aspects span from the materiality of AI (mining, labour, economic divide) to solution-oriented approaches (policies, guidelines, responsible AI development). The course will introduce students to the terminology around social aspects of technology and will enable them to address and articulate social issues of AI.
Learning Objectives
The course will meet the following learning objectives:
- Understand why considerations of equity, diversity, and inclusion (EDI) are needed in SE
- Understand how AI is related to human rights and sustainable development
- Articulate the politics of AI
- Identify the social aspects and issues of AI applications
- Know about diverse ethical approaches to AI (e.g., Indigenous perspectives)
- Analyze SE knowledge, practice, and research with regards to EDI
- Develop skills for EDI analysis of AI development
- Apply responsible research and innovation (RRI) practices on AI
Evaluation
Grades will be based on in-class activities, reflection essays, and group project on case studies that consider responsible research and innovation principles. In the first week of the course, students will be assigned to write a motivation essay which requires them to actively engage with the theme of social aspects of AI. As part of the final course project, students will be expected to produce a final report and to present their project.
| Component | % |
|---|---|
| Motivation essay (one) | 10 |
| Reflection essays on course material (three) | 30 |
| Midterm project | 15 |
| Final project (report + presentation) | 30 |
| Mini-assingments (after each class; counts for participation) | 15 |
Motivation essay (10%) Students will be assigned to write a motivation essay about their interest in the course topic. The motivation essay is due on Tuesday, January 18th.
Reflection essays (30%) You will write three short reflection essays during the semester. These essays should be roughly 700-800 words each, or about two double-spaced pages. Your duty will be to reflect on the readings in the last week or two and write an informed and reasoned opinion about the readings (no summary).
Midterm project (15%) There will be one midterm project that you will complete in small groups. The midterm project includes a presentation.
Final project (report + presentation + ppt) (30%) There will be one major project, which you will complete in small groups. This component consists of three parts: (i) a group presentation, (ii) a ppt, and (iii) a project report. The group presentation will take place in the second half of the semester. The report will be approximately 2000 words and should include a bibliography. We will discuss the details of this project, as well as possible topics, during class. The project report is due April 20th.
Schedule
The course will take place weekly over a 13-week term on Wednesday, 14:45-17:30 EST. The schedule and topics are outlined below. Slight modifications might occur based on the specific interest of students and in response to current events and developments.
Zoom meeting link: Available upon request, please send an email to Tanja Tajmel (tanja [dot] tajmel [at] concordia [dot] ca).
| Week | Date | Topic |
|---|---|---|
| 1 | Jan 12 | Introduction to the course |
| 2 | Jan 19 | Terminology around social aspects and EDI |
| 3 | Jan 26 | Human rights and sustainable development |
| 4 | Feb 2 | Technology and politics |
| 5 | Feb 9 | AI and materiality |
| 6 | Feb 16 | AI, industry and employment |
| 7 | Feb 23 | AI application and cases |
| 8 | Mar 9 | AI harm, issues and concerns |
| 9 | Mar 16 | AI ethics |
| 10 | Mar 23 | AI policies and regulations |
| 11 | Mar 30 | AI and SE culture, practices, and values |
| 12 | Apr 6 | Indigenous perspectives on AI |
| 13 | Apr 13 | Final project presentation |
Reading and other resources
No textbook will be assigned for this course. For each lesson, I will prescribe readings and online assignments like selected book chapters, international reports, documentaries, films and interviews, which will be discussed in the lesson.