This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"High-performance noise-canceling technology is literally music to our ears. It helps deliver the booming bass lines and crisp melodies as intended by the studio creatives that dream them up. But it could potentially save lives as well. Researchers from Northern Illinois University have designed new tech that blocks harmful noise from entering infant incubators. That technology could prove critical to the health of the countless fragile newborns admitted to neonatal intensive care units each year. Infants in neonatal intensive care units, or NICUs, are extremely sensitive to their surroundings. Numerous studies have shown that high-intensity noise can alter vital signs such as heart rate, respiratory rate, and blood pressure. While noise reduction programs have targeted staff behavior and recommended minor structural modifications, the NICU environment remains less than ideal. For the research team from Northern Illinois, that situation calls for a hard-wired solution..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Rolv-Arild Braaten, Freddy Wetjen, Javier De La Rosa, and Svein Arne Brygfjeld (National Library of Norway) present 'Newspapers Front Page Detection' during the AI & Collection Management session at the Fantastic Futures ai4LAM 2023 annual conference. This item belongs to: movies/fantastic-futures-annual-international-conference-2023-ai-for-libraries-archives-and-museums-02.

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Bart Murphy (OCLC) presents 'OCLC’s Explorations in Using Machine Learning to Deduplicate and Enrich Bibliographic Data' during the AI Use Cases session at the Fantastic Futures ai4LAM 2023 annual conference. This item belongs to: movies/fantastic-futures-annual-international-conference-2023-ai-for-libraries-archives-and-museums-02.

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OpenClass is a free learning tool for building mastery-based assignments that follow a research-based format to optimize knowledge retention for learners. I (Laura Neser) have partnered with them to provide a set of 17 non-punitive review assignments around our textbook content that you can easily incorporate into your classes.
**As of spring 2024, an additional set of 17 short quizzes has also been developed through OpenClass and is available at the same URL already linked for this resource.

Instructions: You can clone the review assignments for your own use via the URL link (click the "Clone this class" button at the top of the page to set up a free account with the assignments).

Please feel free to reach out directly with any recommended edits (or possible errors) in the OpenClass assignments (neser@vt.edu). Thank you for reviewing and/or adopting this textbook and I hope this free resource is useful to you!

Welcome to the Open Pedagogy Student Toolkit! The goal of this toolkit is to provide you, the student, a self-paced resource that will guide you through the ins and outs of open pedagogy, including defining open pedagogy, the benefits of open pedagogy, and student creator rights.

How To Use This Toolkit

For Students: If this is your first time in a class that uses open pedagogy we are excited for you! Your instructor is working towards creating a more equitable and engaging environment for you to learn in, and this is an opportunity to take agency over your own educational experience. We hope this toolkit will provide the support you need to understand not only why your instructor is incorporating open pedagogy into your class, but also the benefits of open pedagogy, and your rights and responsibilities as a creator.

The toolkit is broken down into two parts: What is Open Pedagogy? and So You're the Creator, Now What? The first part will introduce you to open pedagogy, its benefits, and some examples you might experience in your class. The second part focuses on the more logistical side of open pedagogy: your rights and responsibilities as a creator and how to exercise those rights and responsibilities.

Your instructor might assign just a few chapters and sections of this toolkit to further build your knowledge on open pedagogy, or you might be asked to go through the whole toolkit at your own pace.

For Instructors: If this is the first time you are incorporating open pedagogy and renewable assignments into your class, congratulations! You are working towards creating a more equitable and engaging environment for you students to learn in and to take agency in their own education. With that said, there is a lot to think about to ensure that your students get the most out of their experience in your class. This toolkit is a resource to provide additional context, background, and scaffolding for your students on the basics of open pedagogy, the benefits of open pedagogy, and student creator rights and responsibilities.

The toolkit is broken down into two parts: What is Open Pedagogy? and So You're the Creator, Now What? The first part will introduce your students to open pedagogy, its benefits, and some examples they might experience in your class. The second part focuses on the more logistical side of open pedagogy: student creator rights and responsibilities and how they can exercise those rights and responsibilities.

You can adapt any section of this toolkit for your class, or use it as a whole to give your students a self-paced guide.

In CampGPT, educators experimented with generative AI-enabled tools like chatbots and image generators to learn and explore together. Their work and insights have been compiled in the Open Prompt Book from CampGPT. Throughout this prompt book, you’ll learn more about generative AI, what educators use it for, and key tips and tricks. The “Try It Out” links enable you to try the prompts in your own account (links for ChatGPT and Bard are provided). This means that, if you like an idea, you can start with the prompt in the book and then continue interacting with a chatbot to further adapt the output to your needs. In addition to the open prompts, we’ve included quotes from the educators from whom the ideas and prompts in this book were crowdsourced.

Opening Keynote delivered by Thomas Hervé Mboa Nkoudou, Researcher in Residence, Centre d’Expertise International de Montreal en Intelligence Artificielle (CEIMIA, International Centre of Expertise In Montreal on Artificial Intelligence). This item belongs to: movies/fantastic-futures-annual-international-conference-2023-ai-for-libraries-archives-and-museums-02.

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Tom Cramer (Stanford University) and Svein Arne Brygfjeld (National Library of Norway), Laurie Allen (Library of Congress), Ingrid Mason, (National Film and Sound Archive of Australia), Stu Snydman, (Harvard University), Emmanuelle Bermès (moderator) discuss 'Organizing within LAMs to Address AI' a... This item belongs to: movies/fantastic-futures-annual-international-conference-2023-ai-for-libraries-archives-and-museums-02.

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This lesson centers around the How AI Works: Privacy and the Future of Work video from the How AI Works video series. Watch this video first before exploring the lesson plan.

In small groups, students conduct research using articles and videos that expose ethical pitfalls in an artificial intelligence area of their choice. Afterward, each group develops at least one solution-oriented principle that addresses their chosen area. These principles are then assembled into a class-wide “Our AI Code of Ethics” resource (e.g. a slide presentation, document, or webpage) for AI creators and legislators everywhere.

This lesson can be taught on its own, or as part of a 7-lesson sequence on How AI Works. Duration: 45 minutes

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Researchers have developed a new method for teaching self-driving cars how to respond to emergencies. Unlike other approaches, which teach cars to respond according to hard and fast rules, this new method trains onboard computers to react like humans do. That unique ability could make self-driving cars vastly quicker at recognizing and avoiding potential accidents. Human drivers react instinctively to road hazards—whether that’s a car that brakes suddenly or a cyclist who rushes into traffic. It’s an ability that comes from years of experience and one that’s often taken for granted. As AI experts have learned, teaching computers to do the same is notoriously difficult. Rule-based methods provide basic functionality. But they tend to be very time-consuming and can’t account for unforeseen emergencies—two tremendous liabilities for self-driving cars..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Researchers from China have pooled together some of the most powerful techniques in machine learning to create the ultimate control system. Successfully deployed in AI-regulated hybrid electric vehicles, the framework could grant other autonomous systems unprecedented levels of control and foresight. Machine learning is booming. And arguably the most popular technique in this branch of artificial intelligence is deep reinforcement learning. Loosely modeled after our brains’ reward system, deep reinforcement learning has enabled machines to reach or even surpass human-level performance in various tasks. Those tasks range from the trivial, like playing Go or video games, to the possibly life-saving, such as detecting firearms from video. But deep reinforcement learning algorithms have their limitations. For one, they generally lack the ability to take lessons learned in one task and apply them to another..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

The People's Guide to Artificial Intelligence is an educational and speculative approach to understanding artificial intelligence (AI) and its growing impact on society. The 78-page booklet explores the forms AI takes today and the role AI-based technologies can play in fostering equitable futures. The project resists narratives of dystopian futures by using popular education, design, and storytelling to lay the groundwork for creative imaginings.

With over 305,000 open educational resources cataloged on OER Commons since 2007, ISKME works to make learning and knowledge sharing more participatory, equitable, and open, in pursuit of a more just society.

Those resources don’t describe themselves, though. The metadata of every resource in OER Commons was put together by someone before it got added to our collection, and then a librarian at ISKME reviewed it for quality – and that’s a lot of work, both in and out of house!

How much work? Well, if a librarian were to spend just five minutes on each record that ever found its way into our collection, that would take 25,433 hours. That’s enough time to…

- do 123 round trips to the moon (time to finally take that leave you’ve been saving)

- get 3,178 full nights of sleep (unless you’re a cat, then it’s only 1,413)

- walk 8 times from Cape Town to Copenhagen (we’re gonna need a bigger passport)

- work full-time for over 13 years (don’t worry, that excludes 4 weeks vacation)

All of that to say, metadata takes time.

It can be a challenge to balance metadata creation with other tasks like maintaining existing records, curation work, and supporting educational partners with curation. As such, we’re always on the lookout for tools and techniques that boost our capacity without compromising quality.

In 2023 and 2024, we’re testing out how generative AI tools like large language models can support our work in the OER landscape. This poster highlights some of the places where we’ve had successes, along with possible future applications that we think are both useful and doable.

Short Description:
This book is intended to be a pragmatic guide to helping able citizen data scientists to utilize common frameworks and tools to create conversational artificial intelligence experiences for users.

Long Description:
This book is intended to be a pragmatic guide to helping able citizen data scientists to utilize common frameworks and tools to create conversational artificial intelligence experiences for users.

Word Count: 4670

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

Short Description:
This book provides an overview of the field of natural language processing and recently developed methods, presuming only knowledge of computing with data structures.

Long Description:
This book allows a reader with a background in computing to quickly learn about the principles of human language and computational methods for processing it. The book discusses what natural language processing (NLP) is, where it is useful, and how it can be deployed using modern software tools. It covers the core topics of modern NLP, including an overview of the syntax and semantics of English, benchmark tasks for computational language modelling, and higher level tasks and applications that analyze or generate language. It takes the perspective of a computer scientist. The primary themes are abstraction, data, algorithms, applications and impacts. It also includes history and trends that are important for understanding why things have been done the way that they have.

Word Count: 70048

ISBN: 978-1-7376595-1-8

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

14. Brave New World: Privacy, Data Sharing and Evidence Based Policy Making

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.

As emerging technologies in artificial intelligence continue to evolve, their influence in educational settings is becoming increasingly significant. “The presence of AI systems and chatbots in education needs to be considered as an opportunity of development rather than a threat.” (Kooli, 2023). The primary objective of this guide is to assist you in navigating this new landscape. This guide will equip you to make informed decisions on how to proactively design and adapt your college courses for the age of AI.

Elizabeth Tait (Charles Sturt University), Cameron Pierson (Victoria University of Wellington) and A. Nick Vera (University of South Carolina) present 'Professional positioning on Artificial Intelligence in the Library and Information Science sector' during the AI & Professional Development session ... This item belongs to: movies/fantastic-futures-annual-international-conference-2023-ai-for-libraries-archives-and-museums-02.

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Los proyectos de esta guía utilizan un enfoque centrado en los alumnos para el aprendizaje. En lugar de solo aprender acerca de la IA con videos o conferencias, los alumnos que realizan estos proyectos son participantes activos en la exploración de ella. En el proceso, los estudiantes trabajarán directamente con tecnologías innovadoras de IA, participarán en actividades no en línea para ampliar su comprensión de cómo funcionan las tecnologías de IA y crearán diversos productos auténticos
desde modelos de aprendizaje automático hasta videojuegos— para demostrar su aprendizaje.

PROYECTO 1: Programación con aprendizaje automático
PROYECTO 2: Jugadores asistidos por IA en videojuegos
PROYECTO 3: Uso de la IA para planificar movimientos robóticos
PROYECTO 4: El aprendizaje automático como un servicio

Esta guía ofrece proyectos centrados en los alumnos que pueden enseñar directamente estándares de áreas de estudio en conjunto con comprensiones fundamentales de los que es la IA, cómo funciona y cómo impacta a la sociedad. Fueron considerados varios enfoques clave para diseñar estos proyectos. Entender estos enfoques sustentará su comprensión y la implementación de los proyectos de esta guía, así como su trabajo para diseñar más actividades que integren la enseñanza sobre la IA en su plan de estudios.

PROYECTO 1: Lo que la IA hace bien y lo que no hace tan bien
PROYECTO 2: Datos de entrenamiento y aprendizaje automático
PROYECTO 3: Los sentidos comparados con los sensores
PROYECTO 4: Navegación e IA