" This course explores a range of contemporary scholarship oriented to the study of 'cybercultures,' with a focus on research inspired by ethnographic and more broadly anthropological perspectives. Taking anthropology as a resource for cultural critique, the course will be organized through a set of readings chosen to illustrate central topics concerning the cultural and material practices that comprise digital technologies. We'll examine social histories of automata and automation; the trope of the 'cyber' and its origins in the emergence of cybernetics during the last century; cybergeographies and politics; robots, agents and humanlike machines; bioinformatics and artificial life; online sociality and the cyborg imaginary; ubiquitous and mobile computing; ethnographies of research and development; and geeks, gamers and hacktivists. We'll close by considering the implications for all of these topics of emerging reconceptualizations of sociomaterial relations, informed by feminist science and technology studies."

Courses on Artificial Intelligence (AI) and Librarianship in ALA-accredited Masters of Library and Information (MLIS) degrees are rare. We have all been surprised by ChatGPT and similar Large Language Models. Generative AI is an important new area for librarianship. It is also developing so rapidly that no one can really keep up. Those trying to produce AI courses for the MLIS degree need all the help they can get. This book is a gesture of support. It consists of about 95,000 words on the topic, with a 3-400 item bibliography.

An introduction to the main techniques of Artifical Intelligence: state-space search methods, semantic networks, theorem-proving and production rule systems. Important applications of these techniques are presented. Students are expected to write programs exemplifying some of techniques taught, using the LISP lanuage.

This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to develop intelligent systems by assembling solutions to concrete computational problems, understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering, and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective.

An infographic with Quick Facts on AI in higher education by Mandy Jordan, Researcher, SHSU Online

Bloom’s Taxonomy is often used as a resource to help higher education faculty assess what kinds or “levels” of learning are planned based on course-level outcomes and, relatedly, to align appropriate activities and assessments to support student learning and success. Oregon State University's E-Campus used Bloom’s Taxonomy as a touchstone for reconsidering course outcomes and student learning in the age of generative AI. The visual outline and accompanying narrative are intended for faculty use as a guide to reflect on their activities, assessments, and (possibly) course outcomes and begin to identify what changes may be needed to ensure meaningful learning going forward.

The trifecta of globalization, urbanization and digitization have created new opportunities and challenges across our nation, cities, boroughs and urban centers. Cities are in a unique position at the center of commerce and technology becoming hubs for innovation and practical application of emerging technology. In this rapidly changing 24/7 digitized world, city governments worldwide are leveraging innovation and technology to become more effective, efficient, transparent and to be able to better plan for and anticipate the needs of its citizens, businesses and community organizations. This class will provide the framework for how cities and communities can become smarter and more accessible with technology and more connected.

This course is an introduction to computational theories of human cognition. Drawing on formal models from classic and contemporary artificial intelligence, students will explore fundamental issues in human knowledge representation, inductive learning and reasoning. What are the forms that our knowledge of the world takes? What are the inductive principles that allow us to acquire new knowledge from the interaction of prior knowledge with observed data? What kinds of data must be available to human learners, and what kinds of innate knowledge (if any) must they have?

In this section, you will learn about the importance of ethical considerations and implications of Generative Artificial Intelligence (GenAI), particularly Large Language Models (LLMs) like ChatGPT. This section highlights that LLMs are not inherently good or bad. Instead, the importance of user engagement in ethical practices is emphasized to ensure responsible use of these tools.

Ethical considerations for educators include attention to student privacy, expectations, and consequences—all of which should clearly be defined in syllabus statements, classroom policies, or institutional statements. Meanwhile, ethical implications exist involving varying ethical standards for how people approach LLMs differently, how human and machine bias influence GenAI, and how style guides differ on citing information garnered from ChatGPT.

After reading this section, you should be able to articulate your own ethical queries and concerns related to LLMs, such as ChatGPT, both as a general user and an educator.

Author: C. Anneke Snyder
Contributors: Gwendolyn Inocencio, Mary Landry, Jonahs Kneitly
Designers: Irene AI, Sweta Kailani
Supervisors: Terri Pantuso, Sarah LeMire

This course examines computers anthropologically, as artifacts revealing the social orders and cultural practices that create them. Students read classic texts in computer science along with cultural analyses of computing history and contemporary configurations. It explores the history of automata, automation and capitalist manufacturing; cybernetics and WWII operations research; artificial intelligence and gendered subjectivity; robots, cyborgs, and artificial life; creation and commoditization of the personal computer; the growth of the Internet as a military, academic, and commercial project; hackers and gamers; technobodies and virtual sociality. Emphasis is placed on how ideas about gender and other social differences shape labor practices, models of cognition, hacking culture, and social media.

Humans are social animals; social demands, both cooperative and competitive, structure our development, our brain and our mind. This course covers social development, social behaviour, social cognition and social neuroscience, in both human and non-human social animals. Topics include altruism, empathy, communication, theory of mind, aggression, power, groups, mating, and morality. Methods include evolutionary biology, neuroscience, cognitive science, social psychology and anthropology.

This book is the result of a co-design project in a class in the Masters of Education program at the University of Calgary. The course, and the resulting book, focus primarily on the safe and ethical use of technology in digital learning environments. The course was organized according to four topics based on Farrow’s (2016) Framework for the Ethics of Open Education and discusses Artificial Intelligence (AI) , social networking services (SNS), 3D printing, resource sharing, adaptive learning systems, STEM, assistive technologies, admissions, and communications. In each of the nine chapters, the authors discuss the connection to the value of technology in education, and practical possibilities of learning technologies for inclusive, participatory, democratic, and pluralistic educational paradigms.

This book is the result of a co-design project in a class in the Masters of Education program at the University of Calgary. The course, and the resulting book, focus primarily on the safe and ethical use of technology in digital learning environments. The course was organized according to four topics based on Farrow’s (2016) Framework for the Ethics of Open Education.

The Ethics of AI is a free online course created by the University of Helsinki. The course is for anyone who is interested in the ethical aspects of AI – we want to encourage people to learn what AI ethics means, what can and can’t be done to develop AI in an ethically sustainable way, and how to start thinking about AI from an ethical point of view.

Advances in cognitive science have resolved, clarified, and sometimes complicated some of the great questions of Western philosophy: what is the structure of the world and how do we come to know it; does everyone represent the world the same way; what is the best way for us to act in the world. Specific topics include color, objects, number, categories, similarity, inductive inference, space, time, causality, reasoning, decision-making, morality and consciousness. Readings and discussion include a brief philosophical history of each topic and focus on advances in cognitive and developmental psychology, computation, neuroscience, and related fields. At least one subject in cognitive science, psychology, philosophy, linguistics, or artificial intelligence is required. An additional project is required for graduate credit.

This two-part resource is designed to support instructors and students as they navigate the presence of generative AI tools, specifically Large Language Models (LLMs) such as ChatGPT, in the rhetoric and composition classroom. Part I of this resource offers an instructor-focused introduction to what LLMs are and how they operate, as well as an in-depth exploration of the privacy concerns and ethical considerations related to using a tool like ChatGPT. Additionally, Part I provides insights on the practical application of LLMs within the realm of reading and writing in the rhetoric and composition classroom, while promoting a modified stasis theory as a strategy for evaluating any generated output.

Part II of this resource offers student-focused tutorials that demonstrate how ChatGPT can augment the writing process for assignments commonly given in a rhetoric and composition course. These tutorials cover the evaluation essay, rhetorical analysis, Rogerian argument, annotated bibliography, and research essay—all while promoting the responsible and ethical use of AI in writing and research. With this comprehensive resource, instructors and students can not only build confidence in their understanding of generative AI within academia, but also build digital literacy that will serve them in the world beyond.

This guide provides student-driven projects that can directly teach subject area standards in tandem with foundational understandings of what AI is, how it works, and how it impacts society.

This guide provides student-driven projects that can directly teach subject area standards in tandem with foundational understandings of what AI is, how it works, and how it impacts society. Several key approaches were taken into consideration in the design of these projects. Understanding these approaches will support both your understanding and implementation of the projects in this guide, as well as your own work to design further activities that integrate AI education into your curriculum.

In this guide, students’ exploration of AI is framed within the context of ethical considerations and aligned with standards and concepts, and depths of understanding that would be appropriate across various subject areas and grade levels in K–12. Depending on the level of your students and the amount of time you have available, you might complete an entire project, pick and choose from the listed activities, or you might take students’ learning further by taking advantage of the additional extensions and resources provided for you. For students with no previous experience with AI education, exposure to the guided learning activities alone will create an understanding of their world that they likely did not previously have. And for those with some background in computer science or AI, the complete projects and resources will still challenge their thinking and expose them to new AI technologies and applications across various fields of study.