AI in Higher Ed Reading List

7 competencies that the Dean and Professor at the University of New Mexico, Dr. Leo Lo put forward to increase AI literacy among librarians while ensuring its ethical usage across academic sectors.

This paper synthesizes a variety of interdisciplinary literature into a set of core competencies of AI literacy and suggest several design considerations to support AI developers and educators in creating learner-centered AI.
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This activity is a group discussion prompt but it can also be interesting as a solo activity just as a thought experiment.

Need an introduction to the basics of generative artificial intelligence for yourself or your staff? This 30-minute video series from the Massachusetts Library System covers how it works, how to use it, limitations, and concerns.

The ROBOT checklist is a resource to help you think critically and support you in making judgements about which AI tools to use.

In this report, Hanover Research presents
strategies for managing Artificial Intelligence (AI) in
higher education settings. This report discusses the unique challenges that AI presents as well as guidance for management and faculty to effectively engage with artificial intelligence.

The aim of this paper is to provide the reader with examples of how LLMs can be utilized for materials development, classroom activities, and providing feedback. After giving specific examples and explanations, the paper will conclude with a discussion of how this technology can provide teachers with new innovative ways to streamline the teaching process to focus on learner needs.

A "virtual petting zoo" to get to know different GenAI tools for educators.

Recommends and links to articles and resources from the Writing Across the Curriculum Clearinghouse resource list

List of main ethical concerns involving using Generative AI in educational settings

To ensure that AI serves as a valuable tool rather than a potential hazard, it's not only crucial to adopt a framework for responsible use, but acknowledge the key role we play as the users of that technology.

The aim of the Global AI Ethics and Governance Observatory is to provide a global resource for policymakers, regulators, academics, the private sector and civil society to find solutions to the most pressing challenges posed by Artificial Intelligence.

(USC Center for Generative AI and Society)

This research article explores the impact of AI on higher
education by examining its effects on teaching and learning, assessment, ethics, required skills, and
future careers. The aim of this study is to analyse the influence of AI on higher education,
investigate its impact on the teaching and learning process, examine its effect on assessment and
grading, and predict its influence on graduates' future careers.

These articles are sourced by Casey Fiesler; she posts occasional news roundups on TikTok and Instagram @professorcasey.

In a video conversation with Columbian College of Arts and Sciences Dean Paul Wahlbeck, George Washington University's Elton Professor of Philosophy David DeGrazia discusses the concept of "moral status" and the role of ethics on policies relating to artificial intelligence, animal research and healthcare access.

This paper presents a literature review and analysis of 38 papers out of 894 retrieved papers that focus on user privacy concerns arising from interactions with text-based conversational chatbots through the lens of social informatics.

The purpose of this work is to investigate the wide-ranging effects of generative content on personal data security and ethical considerations. The article dives into the privacy concerns that may arise from using generative material. Since this kind oftechnology depends heavily on user data, the ease with which accurate and tailored content may be generated raises concerns about data privacy. Unauthorized content synthesis, which may lead to the proliferation of bogus data, counterfeits, and other types of illicit tampering, is also a source of worry.

Since the introduction of OpenAI's ChatGPT-3 in late 2022, conversational
chatbots have gained significant popularity. These chatbots are designed to
offer a user-friendly interface for individuals to engage with technology using
natural language in their daily interactions. However, these interactions raise
user privacy concerns due to the data shared and the potential for misuse in
these conversational information exchanges.

Generative Artificial Intelligence (GAI) has sparked a transformative wave across various domains, including machine learning, healthcare, business, and entertainment, owing to its remarkable ability to generate lifelike data. This comprehensive survey offers a meticulous examination of the privacy and security challenges inherent to GAI. It provides five pivotal perspectives essential for a comprehensive understanding of these intricacies. The paper encompasses discussions on GAI architectures, diverse generative model types, practical applications, and recent advancements within the field. In addition, it highlights current security strategies and proposes sustainable solutions, emphasizing user, developer, institutional, and policymaker involvement.

This research paper highlights the limitations, challenges, potential risks, and opportunities of GenAI in the domain of cybersecurity and privacy.