College of Professional and Global Education · School of Information
Seminar in Information Science - AI, Data, and Ethics
- Fall 2023
- Section 20
- 3 Unit(s)
- 08/21/2023 to 12/06/2023
- Modified 06/29/2023
This course will be available on Canvas beginning August 21st, 6 am PT.
You will be enrolled in the Canvas site automatically.
Course Description and Requisites
This course reviews the principal issues and ethical frameworks in artificial intelligence ethics and relates these issues to the fields of information management and governance. Topics covered include: AI ethics frameworks; algorithmic bias and due process, transparency, accountability; explainable AI (XAI) and records, automation and knowledge work (including information professions); AI and data privacy, the global South; intellectual property and legal liability; and AI Governance; and AI and virtual reality. In addition to providing a solid grounding in ethical issues based in widely used applied ethics principles and methods, the class provides an informal, math-free introduction to artificial intelligence.
- NO understanding of formal logic or mathematics is required in order to understand the issues and perform the work in the course. Background information about AI relevant to the ethical analysis of issues will be provided through readings and lectures. This information will be high-level, describing types of AI, types of training methods, and examples of AI applications in various contexts.
- NO background knowledge in applied ethics or law is required. Relevant knowledge in ethics and law will be provided through the selected readings and lectures.
Organization of Course
- The course is organized into six (6) content modules, two (2) practica, and one (1) capstone project.
- The content modules include lectures, group discussions, and reading assignments. These modules are broken down into two blocks. Blocks are typically one week.
- Practica are one week each. They provide an opportunity to work on a reflective, integrative assignment.
- The capstone project is roughly one week. It comes at the end of the course. It builds on the practica and content modules. It provides an opportunity to work on a reflective, integrative assignment that allows you to synthesize and apply the knowledge you gained in the course.
Students are expected to participate fully in all class activities. It is expected that students will be open-minded and participate fully in discussions in class and debate in a mature and respectful manner. Use of derogatory, condescending, or offensive language including profanity is prohibited. Disagreement is healthy and perfectly acceptable. Expressing disagreement should always include an explanation of your reasoning and, whenever possible, evidence to support your position. In accordance with San José State University's Policies, the Student Code of Conduct, and applicable state and federal laws, discrimination based on gender, gender identity, gender expression, race, nationality, ethnicity, religion, sexual orientation, or disability is prohibited in any form.
Success in this course is based on the expectation that students will spend, for each unit of credit, a minimum of forty-five hours over the length of the course (normally 3 hours per unit per week with 1 of the hours used for lecture) for instruction or preparation/studying or course related activities including but not limited to internships, labs, clinical practica. Other course structures will have equivalent workload expectations as described in the syllabus.
Instructional time may include but is not limited to:
Working on posted modules or lessons prepared by the instructor; discussion forum interactions with the instructor and/or other students; making presentations and getting feedback from the instructor; attending office hours or other synchronous sessions with the instructor.
Student time outside of class:
In any seven-day period, a student is expected to be academically engaged through submitting an academic assignment; taking an exam or an interactive tutorial, or computer-assisted instruction; building websites, blogs, databases, social media presentations; attending a study group; contributing to an academic online discussion; writing papers; reading articles; conducting research; engaging in small group work.
Core Competencies (Program Learning Outcomes) Supported
INFO 287 supports the following core competencies:
- A Demonstrate awareness of the ethics, values, and foundational principles of one of the information professions, and discuss the importance of those principles within that profession.
- H Demonstrate proficiency in identifying, using, and evaluating current and emerging information and communication technologies.
- O (For students entering from Spring 2015 onwards) Understand global perspectives on effective information practices that are supportive of cultural, economic, educational, or social well-being.
Course Learning Outcomes (CLOs)
Upon successful completion of the course, students will be able to:
- Students will be able to identify ethical dimensions of artificial intelligence and systematically analyze issues using ethical concepts and principles.
- Students will be able to competently explain ethical risks associated with artificial intelligence within business organizations and articulate and defend policy positions and strategies that address these risks, particularly as applied to records and information management.
- Students will be able to identify and apply ethical frameworks and legal authorities to artificial intelligence technologies and use cases typical in commercial and public sector organizations.
- Students will be able to describe and distinguish different types of artificial intelligence, tasks, applications, and use cases.
- Mooradian, N. (2018). Ethics for records and information management. ALA. Available as Free eBook through King Library
Course Requirements and Assignments
|Assignment||% Value||Quantity||Total %||CLOs|
|Discussion Posts||5||10||50||CLO1, CLO2, CLO3, CLO4|
|Practica||10||2||20||CLO1, CLO2, CLO3, CLO4|
|Tell Us Something We Don’t Know Report||5||1||5||CLO1, CLO2|
|E-Portfolio Assignment||5||1||5||CLO1, CLO2, CLO3, CLO4|
|Capstone Project: AI Governance Planning Report||20||1||20||CLO1, CLO2, CLO3, CLO4|
- There will be ten (10) discussion assignments. Each student will write a response to the discussion prompt and will comment on at least one other student’s post.
- The initial post should be approximately three (3) full paragraphs.
- It will be evaluated based on thoughtfulness, clarity of writing, and relevance to the question.
- The commentary on another student(s) post can be in the form of a clarification, critical observation, expansion, etc. The comment should include at least one question.
- On one or more occasions, I may post a response from ChatGPT and ask you to critique it as part of your post or reply.
There will be two (2) practica. For each practicum, you will have a full week to reflect on the previous modules. In the first practicum, you will write a brief ethical impact assessment report. In the second practicum, you will prepare a brief presentation explaining an AI ethical issue. Details for each practicum assignment are below:
Practicum 1: Ethics Assessment Report
This assignment will allow you to apply knowledge gained in previous modules, in particular, AI ethics principles, algorithmic bias & opacity, and data privacy & AI. You will write a report that combines elements of an algorithmic impact assessment and a data protection impact assessment.
- The report will have two parts. The first will allow you to explain the ethical principles, values, and issues. The second will allow you to plan an assessment that operationalizes the ethical principles. (This will not be a full plan, just the starting points.)
- The report will be evaluated based on your demonstrating an understanding of the central concepts, clarity of writing, logical organization and coherence, and effectiveness in explaining or supporting its central ideas.
- You will use a hypothetical scenario as the reference point for your ethics assessment.
- Format: Report/Plan – 8 pages, double-spaced, 12 pt. font, following APA style
Practicum 2: Explanatory/Persuasive Presentation for a Target Audience
- For this assignment, you will create a (roughly) 5 to 10-minute recorded presentation using PowerPoint or a presentation and recording tool of your choice. You will explain (a) the importance of any issue/topic related to the central themes of the course, and (b) will present some ideas on how the issue can be addressed (mitigated, avoided, managed, etc.). Imagine that your audience is a group of decision-makers and/or stakeholders in a context of your choice (e.g., library or archives management; a committee of a professional association such as the ALA, SAA; a regulatory agency; a corporate board, etc.).
- The topic can be any issue related to artificial intelligence, automation, and data, even if it was not addressed directly in the class. The topic can be the same one you use for your capstone report.
- You can record audio, video or, if you are not comfortable with either modalities, you can submit a PowerPoint file or equivalent with a transcript or slide notes.
Tell Us Something We Don’t Know Report
- For this assignment, you will find an issue not within the scope of the class that you find interesting and report on it. It can be from a blog, AI think-tank, forum, or even materials in the future readings folder.
- A list of relevant sites (blogs, centers, think tanks) will be available to assist your explorations.
- We will use a discussion post for this assignment. The report will be informal. You will simply be describing the issue and providing a link (if available) to the site or resource used. You will paste or write the information directly into the discussion post.
E-Portfolio Head Start
- For this assignment, you will explain how at least one assignment in the course helped you achieve MLIS Comps A and H. They can be the same assignment(s) or different for the two comps. There will be plenty to choose from.
- The objective of the assignment is to help you get ahead on your E-Portfolio while the knowledge learned is fresh.
- Format: Report/Plan – 2 pages, double-spaced, 12 point font, following APA style
- This capstone report option will allow you to integrate and further clarify the knowledge you gained during the course and apply it to a hypothetical context. You will build on the two impact assessment practica you did earlier in the semester. You can use the same hypothetical AI implementation scenarios you used in the practica or envision a new one.
- You will write a report that has three (3) parts: Principles, Issues, and Governance Tasks.
- For the principles section, you will select a set of the guiding principles for your AI governance plan and explain why you selected these principles.
- For the issues section, you will identify any issues that are particularly relevant to your envisioned use(s) of AI and explain why they are relevant.
- For the governance section, you will select some governance tasks from one of the AI Governance Frameworks and describe their relevance to your hypothetical AI system.
- The report will be evaluated based on demonstration of understanding the central concepts, clarity of writing, logical organization and coherence, and effectiveness in explaining or supporting its central ideas.
- Format: Report/Plan – 12 pages, 12 pt. font, following APA style.
- Note: You can build on practicum 1 for this option.
- This capstone report option will allow you to deepen your knowledge of any of the issues in the course or explore an issue not covered in the courses.
- This capstone project option will allow you to more deeply explore an issue that interests you and write something that you may wish to present at a conference or submit for publication. It does not have to be an issue that we covered in this course, but it should connect with the information sciences.
- The topic can focus on ethics, law, or information science.
- You can take the approach that best suits your thinking and writing style, whether that is an argumentative paper, an explanatory report, or a case study.
- Whatever approach you take, make sure that you provide an overview of the issue, that you explain the aspect that is the focus of the paper, and that you present a critical or constructive response to the issue. The critical response may address the ethical or legal issue as such. The constructive response may look at ways that information scientists can provide practical solutions.
- Format: Report/Plan – 12 pages, double-spaced, 12 pt. font, following APA style.
- Note: You can build on practicum 2 for this option.
The standard SJSU School of Information Grading Scale is utilized for all iSchool courses:
|97 to 100||A|
|94 to 96||A minus|
|91 to 93||B plus|
|88 to 90||B|
|85 to 87||B minus|
|82 to 84||C plus|
|79 to 81||C|
|76 to 78||C minus|
|73 to 75||D plus|
|70 to 72||D|
|67 to 69||D minus|
In order to provide consistent guidelines for assessment for graduate level work in the School, these terms are applied to letter grades:
- C represents Adequate work; a grade of "C" counts for credit for the course;
- B represents Good work; a grade of "B" clearly meets the standards for graduate or undergraduate (for BS-ISDA) level work;
For core courses in the MLIS program (not MARA, Informatics, or BS-ISDA) — INFO 200, INFO 202, INFO 204 — the iSchool requires that students earn a B in the course. If the grade is less than B (B- or lower) after the first attempt you will be placed on administrative probation. You must repeat the class if you wish to stay in the program. If - on the second attempt - you do not pass the class with a grade of B or better (not B- but B) you will be disqualified.
- A represents Exceptional work; a grade of "A" will be assigned for outstanding work only.
Graduate Students are advised that it is their responsibility to maintain a 3.0 Grade Point Average (GPA). Undergraduates must maintain a 2.0 Grade Point Average (GPA).
Per University Policy S16-9 (PDF), relevant university policy concerning all courses, such as student responsibilities, academic integrity, accommodations, dropping and adding, consent for recording of class, etc. and available student services (e.g. learning assistance, counseling, and other resources) are listed on the Syllabus Information web page. Make sure to visit this page to review and be aware of these university policies and resources.
Below is the schedule for modules, blocks and assignments. Descriptions of module topics are provided.
|MODULE 1: INTRODUCTION TO AI AND ETHICS|
|Block 1: Friday 8/21 to Sunday 8/27|
|Title||Introduction to AI and Ethical Issues in AI||Due Dates|
|Description||This block introduces concepts in AI, ethics, and AI ethics. It reviews different types of AI (e.g., symbolic, machine learning) and the ethical issues associated with them. It also provides a general ethical framework used across applied ethics fields (medical ethics, professional ethics, engineering ethics, etc.)|
|Assignments||Discussion Post 1: Write a Personal introduction; describe your vision of how knowledge in AI/data ethics will be integrated into your career plans/path.||Friday, 8/25|
|Replies to posts||Sunday, 8/27|
|Block 2: Monday 8/28 to Sunday 9/3|
|Title||Ethical Principles and AI Ethics Frameworks|
|Description||This block introduces ethical frameworks developed for AI. It connects these ethical frameworks with the main ethics frameworks and with key problems of AI ethics.|
|Assignments||Discussion Post 2||Friday, 9/1|
|Replies to posts||Sunday, 9/3|
|MODULE 2: BIAS AND ACCOUNTABILITY|
|Block 3: Monday 9/4 to Sunday 9/10|
|Description||This block examines bias, discrimination, and justice issues that arise within AI. It looks at how bias arises from machine learning based on big data as well as bias that arises from a lack of diversity within the technology companies that develop AI systems. Finally, it will look at due process and fairness issues that are connected to automated decision-making that impacts human and social rights.|
|Assignments||Discussion Post 3||Friday, 9/8|
|Replies to posts||Sunday, 9/10|
|Block 4: Monday 9/11 to Sunday 9/17|
|Title||Accountability, Explainable AI (XAI), Liability, and Records|
|Description||This block examines accountability within the context of AI systems that distribute and/or automate decisions and actions that impact rights. It looks at the concept of explainable AI (XAI) and its relation to accountability. It examines concepts of liability for “autonomous” systems, and finally, it connects explainability and liability with core records concepts.|
|Assignments||Discussion Post 4||Friday, 9/15|
|Replies to posts||Sunday, 9/17|
|MODULE 3: PRIVACY AND CULTURE|
|Block 5: Monday 9/18 to Sunday 9/24|
|Title||AI and Data Privacy|
|Description||This block explores how issues in data privacy, which already constitute a major issue area in digital ethics, are extended and exacerbated by AI technologies that automate surveillance and that generate inferences beyond the data they use. It looks at the role of personal data in AI and how privacy rules apply to and affect the development and deployment of AI systems.|
|Assignments||Discussion Post 5||Friday, 9/22|
|Replies to posts||Sunday, 9/24|
|Block 6: Monday 9/25 to Sunday 10/1|
|Title||Ethical Impact Assessment|
|Assignments||See topic description in Course Requirements.||Sunday, 10/1|
|Block 7: Monday 10/2 to Sunday 10/8|
|Title||Global South/Cultural Competence|
|Description||This block examines the impact of big data and AI on the Global South. It looks at the question of how privacy and other AI-based risks are altered/exacerbated by political, legal, cultural, and economic differences. It also examines the concept of data colonialism as a critical perspective of big data in Global South countries and communities.|
|Assignments||Discussion Post 6||Friday, 10/6|
|Replies to posts||Sunday,10/8|
|MODULE 4: AUTOMATION AND KNOWLEDGE
|Block 8: Monday 10/9 to Sunday 10/15|
|Title||Automation and Expertise|
|Description||This block examines ethical issues relating to employment and how they are impacted by “hyper-automation”. It reviews technologies such as robotic process automation (RPA) and business process automation and how their integration with AI impacts employment and working conditions.|
|Assignments||Discussion Post 7||Friday, 10/13|
|Replies to posts||Sunday,10/15|
|Block 9: Monday 10/16 to Sunday 10/22|
|Title||AI and Knowledge Management|
|Description||The block examines the distinction between replacement automation versus augmentation/enablement augmentation and considers how AI and knowledge management may be integrated in a way that is human-centric and human-enabling.|
|Assignments||Discussion Post 8||Friday, 10/20|
|Replies to posts||Sunday,10/22|
|MODULE 5: LEGAL ISSUES|
|Block 10: Monday 10/23 to Sunday 10/29|
|Description||This block examines special issues that AI poses for copyright and trade secrecy concepts. In particular, it looks at debates as to who is the rights holder where the creations of AI depend on data and environments provided by other parties than the developers and where the “autonomy” of AI systems either creates the semblance of a competing claimant (the AI system) or weakens the claim of the creator. Also, it looks at the tension between trade secrecy and discrimination/due process concerns.|
|Assignments||Discussion Post 9||Friday, 10/27|
|Replies to posts||Sunday,10/29|
|Block 11: Monday 10/31 to Sunday 11/6|
|Title||Explanatory/Persuasive Presentation for a Target Audience|
|Assignments||See topic description in Course Requirements.||Sunday, 11/5|
|Readings||Optional selection from text on ethical reasoning.|
|Block 12: Monday 11/6 to Sunday 11/12|
|Description||This block re-examines questions of accountability and responsibility in the context of civil liability/torts and criminal liability. It will connect the issue of responsibility with the concept of an AI record raised earlier.|
|Assignments||Discussion Post 10||Friday, 11/10|
|Replies to posts||Sunday,11/12|
|MODULE 6: AI GOVERNANCE|
|Block 13: Monday 11/13 to Sunday 11/19|
|Title||AI Governance Frameworks|
|Description||This block reviews general governance and regulatory frameworks being developed to mitigate potential harms caused by AI, while reaping its potential benefits.|
|Assignments||Tell us Something We Don’t Know Report||Sunday,11/19|
|Block 14: Monday 11/20 to Sunday 11/26|
|Title||Ethical Issues in Virtual Reality|
|Description||This block looks at virtual reality and examines ethical issues that VR raises and how the issues and technologies converge with artificial intelligence.|
|MODULE 9: CAPSTONE PROJECT|
|Block 15: Monday 11/27 to Wednesday 12/6|
|Title||Capstone Report: Option 1 or Option 2|
|Description||See topic description in Course Requirements.|
Option 1: Supporting materials, guides;
Option 2: materials of your choice