All resources in Oregon Artificial Intelligence (AI)

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AI in Practice: Preparing for AI

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This course, AI in Practice: Preparing for AI, is the 1st course of the online education program AI in Practice. The course gives you a kaleidoscope of examples of applications of AI in various organizations, outlines the state of the art in modern AI research, and provides practical tools for integrating AI into your own organization. The program AI in Practice is built from two initial courses, AI in Practice: Preparing for AI and AI in Practice: Applying AI. The AI in Practice: Preparing for AI course is designed for people who want to apply AI in their own practical situation. For the experienced manager who wants to know what AI can do for her own organization. For the data analyst or business consultant who wants to understand how AI can be applied in the business processes of the company for which they work. For the student who wants to understand how the results of AI research can be translated into practical applications.

Material Type: Full Course

Authors: Arie van Deursen, Hennie Huijgens

AI in Practice: Applying AI

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Learn about the implementation and practical aspects of Artificial Intelligence and how to write a plan for applying AI in your own organization in a step-by-step manner. This course is not about difficult algorithms and complex programming; it is a course for anyone interested in learning how to integrate AI into their own organization. To understand how current Artificial Intelligence applications can be successfully integrated in organizations, we look at different examples. For instance, how ING uses reinforcement learning for personalized dialog management with its customers or how Radboud UMC uses diagnostic image analysis to discover early stages of infectious diseases. As part of our two-course program ‘AI in Practice’, this course will guide you in the practical aspects of applying AI in your own organization. You will examine typical applications of AI in use already and learn from their experience. These include challenges of implementation, lifecycle aspects, as well as the maintenance and management of AI applications. The course presents a variety of case studies from actual situations in public organizations and private enterprises in the healthcare, financial, retail and telecommunications sectors. These include Radboud UMC, the Municipality of Amsterdam, ING, Ahold Delhaize and KPN. ‘AI in Practice – Applying AI’ gives you the ammunition to understand the practical aspects required for the implementation of a variety of AI applications in your organization.

Material Type: Full Course

Authors: Arie van Deursen, Bram van Ginneken, Floris Bex, Marleen Huysman, Sennay Ghebreab

Independent Study in Geospatial Intelligence

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This course provides an understanding of how geospatial perspectives and technologies support all stages of emergency management activities, from small scale emergency management efforts to large scale disaster/humanitarian efforts. This includes learning about commonly used and emerging geospatial tools. It also includes an exploration of advancements in data collection, processing and analysis capabilities, such as unmanned aerial systems, geospatial artificial intelligence, volunteered geographic information, social media, and many more.

Material Type: Full Course

Author: Todd Bacastow

Artificial Intelligence and Librarianship

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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.

Material Type: Reading, Textbook

Author: Martin Frické

Introduction to Data-Centric AI

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Typical machine learning classes teach techniques to produce effective models for a given dataset. In real-world applications, data is messy and improving models is not the only way to get better performance. You can also improve the dataset itself rather than treating it as fixed. Data-Centric AI (DCAI) is an emerging science that studies techniques to improve datasets, which is often the best way to improve performance in practical ML applications. While good data scientists have long practiced this manually via ad hoc trial/error and intuition, DCAI considers the improvement of data as a systematic engineering discipline. This is the first-ever course on DCAI. This class covers algorithms to find and fix common issues in ML data and to construct better datasets, concentrating on data used in supervised learning tasks like classification. All material taught in this course is highly practical, focused on impactful aspects of real-world ML applications, rather than mathematical details of how particular models work. You can take this course to learn practical techniques not covered in most ML classes, which will help mitigate the “garbage in, garbage out” problem that plagues many real-world ML applications.

Material Type: Activity/Lab, Full Course, Lecture, Textbook

Authors: Anish Athalye, Curtis G. Northcutt, Jonas Mueller

Hands-On AI Projects for the Classroom: A Guide on Ethics and AI

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ISTE and GM have partnered to create Hands-On AI Projects for the Classroom guides to provide educators with a variety of activities to teach students about AI across various grade levels and subject areas. Each guide includes background information for teachers and student-driven project ideas that relate to subject-area standards. The hands-on activities in the guides range from “unplugged” projects to explore the basic concepts of how AI works to creating chatbots and simple video games with AI, allowing students to work directly with innovative AI technologies and demonstrate their learning. 

Material Type: Reading

Author: Rebecca Henderson

Ethics of AI in Education For Students

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This video delves into the Ethics of AI in Education, catering specifically to students. Its purpose is to assist students in cultivating their own ethical standpoint concerning AI, drawing from pertinent information and factual insights into the realm of artificial intelligence. The content explores professional, educational, and personal perspectives, shedding light on both the pitfalls and benefits inherent in discussions about AI. This resource is designed to be utilized as a tool for initiating conversations among students before the commencement of a course. It serves to familiarize them with the landscape of policies surrounding AI within their courses or institutions. Current formats provided include: Youtube video H5P Interactive Video (Includes bookmarks and a reflective question to answer.) Preview and use this content: Youtube video: https://youtu.be/ZVUaOfHqGck H5P Module: https://h5p.org/node/1460884

Material Type: Interactive

Author: Skye Nguyen

What if? Ethics cases using various philosophies for decision-making

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This OER is a collection of case studies for discussions on ethical decision-making. It uses Communitarian and other philosophies to determine how and if outcomes might have been different uses alternatives to Utilitarianism. Cases cover recent issues in public relations, journalism, video games, social media, influencers, advertising, artificial intelligence, reality TV, and luxury brands.

Material Type: Case Study, Textbook

Author: Sarah Maben

Social and Ethical Responsibilities of Computing (SERC)

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Social and Ethical Responsibilities of Computing (SERC), a cross-cutting initiative of the MIT Schwarzman College of Computing, works to train students and facilitate research to assess the broad challenges and opportunities associated with computing, and improve design, policy, implementation, and impacts. This site is a resource for SERC pedagogical materials developed for use in MIT courses. SERC brings together cross-disciplinary teams of faculty, researchers, and students to develop original pedagogical materials that meet our goal of training students to practice responsible technology development through incorporation of insights and methods from the humanities and social sciences, including an emphasis on social responsibility. Materials include the MIT Case Studies Series in Social and Ethical Responsibilities of Computing, original Active Learning Projects, and lecture materials that provide students hands-on practice and training in SERC, together with other resources and tools found useful in education at MIT. Original homework assignments and in-class demonstrations are specially created by multidisciplinary teams, to enable instructors to embed SERC-related material into a wide variety of existing courses. The aim of SERC is to facilitate the development of responsible “habits of mind and action” for those who create and deploy computing technologies, and fostering the creation of technologies in the public interest.

Material Type: Full Course

Authors: Kaiser, David, Shah, Julie

Ethics of AI Bias

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This video aims to delve into the human problems brought out by issues in artificial intelligence, specifically with respect to bias. It is suitable for classroom use or as a standalone video for those who wish to understand the issue more deeply than is conventionally covered. For classroom use, we recommend watching the and working through the teaching materials provided for each chapter.

Material Type: Full Course

Authors: Minkov, Svetozar, Trout, Bernhardt

Ethics of Technology

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This course introduces the tools of philosophical ethics through application to contemporary issues concerning technology. It takes up current debates on topics such as privacy and surveillance, algorithmic bias, the promise and peril of artificial intelligence, automation and the future of work, and threats to democracy in the digital age from the perspective of users, practitioners, and regulatory/governing bodies.

Material Type: Full Course

Author: Mills, Kevin

AI4ALL: Bytes of AI - AI & Ethics

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Bytes of AI are fun, quick introductions to artificial intelligence through a variety of different topics. These can be used to spark an interest in AI before exploring the AI4ALL curriculum further. Bytes of AI introduce students and teachers to some of the core ideas of AI including:How data becomes output in an AI modelWhat AI is capable of, what risks it can haveHow human biases enter datasetsHow AI can be used in diverse fields Access the full series of AI4ALL's Bytes of AI from their website. 

Material Type: Lesson

Author: Vanessa Clark

AI4ALL: Bytes of AI - AI & COVID-19

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Bytes of AI are fun, quick introductions to artificial intelligence through a variety of different topics. These can be used to spark an interest in AI before exploring the AI4ALL curriculum further. Bytes of AI introduce students and teachers to some of the core ideas of AI including:How data becomes output in an AI modelWhat AI is capable of, what risks it can haveHow human biases enter datasetsHow AI can be used in diverse fields Access the full series of AI4ALL's Bytes of AI from their website. 

Material Type: Lesson

Author: Vanessa Clark

AI4ALL: Bytes of AI - AI & Dance

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Bytes of AI are fun, quick introductions to artificial intelligence through a variety of different topics. These can be used to spark an interest in AI before exploring the AI4ALL curriculum further. Bytes of AI introduce students and teachers to some of the core ideas of AI including:How data becomes output in an AI modelWhat AI is capable of, what risks it can haveHow human biases enter datasetsHow AI can be used in diverse fields Access the full series of AI4ALL's Bytes of AI from their website. 

Material Type: Lesson

Author: Vanessa Clark

AI4ALL: Bytes of AI - AI & The Environment

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Bytes of AI are fun, quick introductions to artificial intelligence through a variety of different topics. These can be used to spark an interest in AI before exploring the AI4ALL curriculum further. Bytes of AI introduce students and teachers to some of the core ideas of AI including:How data becomes output in an AI modelWhat AI is capable of, what risks it can haveHow human biases enter datasetsHow AI can be used in diverse fields Access the full series of AI4ALL's Bytes of AI from their website. 

Material Type: Lesson

Author: Vanessa Clark

Ethical Considerations and Risks

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15. Brave New World: Ethical Considerations and Risks The trifecta of globalization, urbanization and digitization have created new opportunities and challenges across our nation, cities, boroughs and urban centers. Cities in particular 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, governments 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.

Material Type: Lesson

Author: Rhonda S. Binda

Artificial Intelligence and Machine Learning

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9. Brave New World - AI/ML 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.

Material Type: Lesson

Author: Rhonda S. Binda

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