Exploring the Evolving Relationship Between AI and Libraries

AI and Libraries: Friends or Enemies?

By Dr. Luba Pirgova-Morgan, University of Leeds

In a recent presentation, Dr. Luba Pirgova-Morgan explored the evolving relationship between artificial intelligence (AI) and libraries. Drawing from her report titled "Looking Towards a Brighter Future," completed in 2023 at the University of Leeds, she examined whether AI is a friend or foe to the library world.

AI in the Library Space: Hero or Villain?

Dr. Pirgova-Morgan posed the question of AI's role in libraries—is it a hero enhancing library services or a villain introducing challenges? She concluded that AI is a multifaceted tool that is neither inherently good nor bad. Its impact depends on how it is utilized within the library context.

On one hand, AI can be a hero by:

• Enhancing Efficiency: Automating routine tasks, allowing librarians to focus on complex responsibilities.
• Personalizing User Experience: Providing tailored recommendations and improving search optimization.
• Improving Accessibility: Assisting users with disabilities through tools like text-to-speech and language processing applications.

On the other hand, AI can be a villain by introducing:

• Bias and Inequality: Perpetuating existing biases if algorithms are not carefully designed.
• Privacy Concerns: Handling large amounts of user data, which may infringe on privacy if not properly managed.
• Reduction of Human Element: Potentially diminishing the value of human interaction in libraries.

AI and Libraries: Friends or Enemies?

The presentation also delved into whether AI and libraries can be friends or are destined to be enemies. Dr. Pirgova-Morgan suggested that a harmonious relationship is possible through:

• Education and Skills Development: Librarians should develop AI-related skills to navigate the evolving landscape effectively.
• Ethical Implementation: Libraries must address ethical considerations, ensuring AI is used responsibly.
• User Engagement: Encouraging open dialogue with users about AI to foster understanding and trust.

She emphasized that the key to a positive relationship lies in balancing the benefits of AI with mindful awareness of its limitations.

Current Initiatives at the University of Leeds

The University of Leeds is actively exploring AI applications within its library system, including:

• Digitizing Ancient Texts: Using AI to enhance the digitization process, making historical documents more accessible.
• Digital Humanities Projects: Integrating AI into research workflows to support academic studies.
• Policy Development: Engaging in debates and consultations to develop strategies for ethical AI integration.

Conclusion

Dr. Pirgova-Morgan concluded that the relationship between AI and libraries is complex but holds great potential. By establishing clear guidelines and fostering collaboration, libraries can leverage AI as a powerful ally rather than viewing it as an adversary.

For more information or to access the full report, please contact Dr. Luba Pirgova-Morgan at [email protected].

Note: This summary is based on a presentation by Dr. Luba Pirgova-Morgan discussing the intersection of AI and library services.

Understanding Generative AI: Implications for Academic Integrity and Citation

Ethical and Productive—Considering Generative Artificial Intelligence Citation Across Learning and Research

Introduction

• Host: Daniel Pfeiffer from Choice and LibTech Insights.
• Speakers:
  • Kari Weaver: Learning, Teaching, and Instructional Design Librarian at the University of Waterloo.
  • Antonio Muñoz Gómez: Digital Scholarship Librarian at the University of Waterloo.
• Context: Discussion on ethical considerations and citation practices for generative AI tools like ChatGPT in academia.

Acknowledgment of Land

• Recognition of the traditional territories where the University of Waterloo is situated.
• Reflection on how citation practices are influenced by colonial approaches to knowledge ownership.

Background of the Project

• Campus Context:
  • Research-intensive university with over 42,000 students.
  • Home to the Waterloo Artificial Intelligence Institute.
• Emergence of Generative AI:
  • Open availability of tools like ChatGPT sparked campus-wide discussions.
  • Initial focus on AI's impact on teaching, learning, and academic integrity.

Focus on Citation Practices

• Purpose of Citation:
  • Creates an information trail and establishes academic connections.
  • Provides standardization and consistency in student assignments.
  • Supports academic integrity through transparency.
• Challenges with AI-generated Content:
  • Difficulty in citing AI-generated outputs.
  • Lack of initial guidance from traditional citation styles.
  • Need for practical solutions for students and faculty.

Ethical Dimensions

• Academic Integrity Concerns:
  • Fear of students using AI to cheat on assignments.
  • Issues with AI detection software misidentifying non-native English speakers.
• Power Dynamics:
  • Discrepancy in the use of AI tools between students and instructors.
  • Data privacy concerns when student work is uploaded to detection software.
• Reproducibility and Accountability:
  • AI outputs are inconsistent; same prompts yield different results.
  • Challenges in preserving AI-generated content for verification.

Citation in Research vs. Learning Contexts

• Research Context:
  • AI tools generally not allowed as authors in publications.
  • AI-generated images discouraged due to reliability concerns.
  • Disclosure of AI use required in methodology sections.
• Learning Context:
  • Adaptation of citation practices to include AI tools.
  • Encouragement for students to be transparent about AI use.

Development of Resources

• Initial Outputs:
  • Created a LibGuide on ChatGPT and generative AI.
  • Developed infographics and annotated prompts illustrating citation practices.
• Ongoing Work:
  • Updating resources to include guidance on citing AI-generated images and videos.
  • Exploring AI tools for literature reviews and knowledge synthesis.
• Campus Collaboration:
  • Formed a campus-wide committee with diverse representation.
  • Contributed to faculty programming and standardized syllabus language.
  • Supported resource development in partnership with other academic units.

Library Initiatives

• Internal Exploration:
  • Monthly sessions on AI tools like Whisper for transcription.
  • Workshops on AI and machine learning in academic libraries.
• Interest Groups and Bibliographies:
  • Formed an interest group on AI within the library.
  • Created a Zotero bibliography with curated readings on AI topics.
• Future Directions:
  • Participation in provincial and federal AI initiatives for academic libraries.

Q&A Session Highlights

• Use of AI in Professional Practice:
  • Librarians using AI tools for brainstorming and instructional design.
• Access to Paywalled Content:
  • AI tools generally cannot access content behind paywalls unless provided by the user.
• Guidance on AI Use in Assignments:
  • Importance of transparency and attribution when students use AI for brainstorming or editing.
  • Encouragement for faculty to discuss AI expectations with students.
• Ethical Considerations:
  • Need to address citation as a colonial practice and explore decolonized approaches.
  • Challenges with integrated AI features in tools and implications for citation.
• Institutional Policies:
  • University of Waterloo currently has no formal policy on AI use.
  • Emphasis on ongoing conversations and collaborative efforts to address AI's impact.

Conclusion

• Recognition of the complexities and rapid development of AI technologies.
• Importance of grappling with ethical, practical, and pedagogical implications.
• Encouragement for open dialogue between faculty, students, and librarians.
• Acknowledgment of the need for adaptable approaches rather than rigid policies.

Note: This summary captures key points from a presentation discussing the ethical considerations and citation practices related to the use of generative AI tools in academic learning and research contexts.

Streamline Your Writing Process with QuillBot Flow: A Comprehensive Overview

Introduction to QuillBot Flow—Enhancing Your Writing Process

Introduction

• Host: Gul, leading Business Development at QuillBot.
• Team Members Present:
  • Aim: Handling administrative issues.
  • Ashish: Addressing general questions.
  • Jerry: Addressing product-related questions.
• Audience Engagement:
  • Participants from around the world, including Tanzania, Indonesia, Scotland, France, Germany, Italy, Canada, Netherlands, Philippines, Mexico, USA, South Africa, Sri Lanka, Pakistan, and South Korea.
  • Shared favorite quotes and New Year greetings to foster community spirit.

Webinar Overview

• Purpose: To introduce QuillBot Flow, an AI-powered writing tool designed to streamline and enhance the writing process.
• Agenda:
  • Introduction to QuillBot and its mission.
  • Deep dive into QuillBot Flow features.
  • Interactive Q&A session.
  • Special surprise announcement for attendees.

About QuillBot

• Founded: In 2017 by three computer science graduates from the University of Illinois—Rohan Gupta, Anil Jason, and Dave S.
• Headquarters: Chicago, USA, and Jaipur, India.
• Mission: To make the writing process painless and help users grow and learn as writers.
• User Base:
  • Over 35 million monthly active users.
  • More than 50 million users globally.
• Key Features:
  • AI writing tools for drafting, brainstorming, researching, editing, proofreading, creating citations, summarizing, and translating.
  • Ad-free platform focused on user efficiency.

Introduction to QuillBot Flow

• Formerly Known As: QuillBot's Co-Writer.
• Description: A comprehensive AI writing platform integrating all of QuillBot's tools in one place.
• Demonstration Highlights:
  • Templates:
    • Options for blogs, academic papers, emails, letters, and custom templates.
  • Structure Generation:
    • Helps create an outline or flow for writing projects.
  • Research Assistance:
    • Integrated search within the platform.
    • Ability to insert researched content directly into the document.
  • QuillBot Flares:
    • Generate ideas, complete paragraphs, add examples or counter-examples.
  • Paraphrasing Modes:
    • Multiple styles (e.g., standard, fluency, formal) and multilingual capabilities.
  • Summarizer Tool:
    • Condenses long texts into key sentences or paragraphs.
  • Translation Feature:
    • Supports over 45 languages, including French, German, and Spanish.
  • Plagiarism Checker:
    • Scans documents for originality and assists with citations.
  • AI Review:
    • Offers suggestions to improve writing style and tone.
  • Suggest Text Feature:
    • Predicts the next sentence based on the current content.
  • Dictate and Listen Feature:
    • Converts speech to text and text to speech for increased productivity.

Interactive Q&A Session

• Poll Conducted:
  • Asked attendees what they hoped to gain from the webinar.
  • Majority wanted to learn how to enhance their writing process.
• Common Questions Addressed:
  • Differences Between QuillBot and Other Tools:
    • Multilingual paraphrasing accuracy.
    • Integrated features like summarizer and translator.
  • Subscription Options and Discounts:
    • Availability of monthly, semi-annual, and annual subscriptions.
    • Special discounts for students and educational institutions.
  • Language and Accent Adjustments:
    • Ability to choose between American, British, Canadian, and Australian English.
  • Upcoming Webinars:
    • Plans for future sessions covering various topics based on user feedback.
  • Templates and Citation Support:
    • Access to multiple templates and citation formats (APA, MLA, Chicago, etc.).
  • Device Accessibility:
    • QuillBot is accessible across different devices.
• Feedback Encouraged:
  • Participants were invited to share topics they would like covered in future webinars.
  • Emphasized the importance of user feedback in improving QuillBot.

Special Surprise for Attendees

• Exclusive Offer:
  • A 50% discount on the annual premium subscription.
  • Valid for 24 hours post-webinar.
  • Coupon code provided during the session.
• How to Avail:
  • Instructions to contact support if assistance is needed with the coupon code.
  • Encouraged to reach out via email or the QuillBot website for any queries.

Conclusion

• Gratitude Expressed:
  • Thanked attendees for their participation and engagement.
  • Expressed excitement about the overwhelming response.
• Encouragement to Connect:
  • Invited attendees to follow QuillBot on social media for updates.
  • Encouraged sharing feedback and suggestions for future webinars.
• Final Remarks:
  • Wished everyone a great and exciting journey ahead.
  • Anticipated how QuillBot's tools can empower users to achieve writing excellence.

Note: This summary captures key points from a webinar introducing QuillBot Flow, an AI-powered writing platform designed to enhance and streamline the writing process by integrating multiple tools into one comprehensive solution.

Navigating the AI Landscape: How Libraries Can Adapt

Libraries and AI—Challenges and Responses

Introduction

• Host: Don from the Gigabit Libraries Network.
• Speakers:
  • Andrew Cox: Member of the AI Special Interest Group at IFLA; Information School in Sheffield.
  • Richard Whitt: President of GLIA Foundation.
• Series Context: Part of the "Libraries in Response" series on technology issues affecting libraries.

Context and Background

• Libraries are facing multiple crises: COVID-19, climate change, political unrest, and AI.
• AI is seen as both an opportunity and a challenge for libraries.
• The importance of libraries as trusted institutions in navigating technological changes.

Challenges of AI for Libraries

• Existential Concerns: AI's potential impact on humanity and societal structures.
• Trust Issues: Ensuring AI agents act in the best interest of users, avoiding "double agents."
• Digital Divide: AI might exacerbate inequalities between connected and unconnected communities.
• Regulatory Landscape:
  • Federal and state policies are being developed to address AI.
  • Challenges in effectively regulating complex AI technologies.

Role of Libraries in the Age of AI

• Leveraging the high trust in libraries to guide communities through AI challenges.
• Promoting AI literacy and responsible AI use among patrons.
• Developing AI capabilities, including data stewardship and ethical practices.
• Potential partnerships with technology companies for AI development.

Presentations

Richard Whitt

• Referenced Cerf's work on digital libraries and intelligent agents (knowbots).
• Discussed the rise of AI bots and personal digital assistants.
• Introduced the concept of "double agents" in AI that may not serve users' best interests.
• Highlighted potential roles for libraries:
  • Providing infrastructure and connectivity.
  • Serving as repositories of trustworthy digital knowledge.
  • Acting as fiduciaries with obligations to patrons.
  • Developing AI agents aligned with library values.
  • Educating patrons on AI and digital citizenship.

Andrew Cox

• Introduced the work of the IFLA AI Special Interest Group.
• Presented a strategic framework for libraries responding to AI challenges.
• Discussed the AI capability model:
  • Material Resources: Data and infrastructure needs.
  • Human Resources: Technical and business skills required.
  • Intangible Resources: Leadership, coordination, and adaptability.
• Suggested key actions for libraries:
  • Implement responsible and explainable AI solutions.
  • Enhance data stewardship and management skills.
  • Promote AI literacy and critical understanding among patrons.
• Addressed challenges like resource limitations and the need for collaboration and vision.

Discussion and Audience Participation

• Practical Steps for Libraries:
  • Start small with AI projects relevant to existing services.
  • Define a clear vision for AI integration.
  • Collaborate with other libraries and institutions.
• Partnerships with Tech Companies:
  • Potential benefits and risks of collaborating with technology firms.
  • Need for libraries to advocate for ethical AI practices.
• Comments from Participants:
  • Diane: Shared a tool developed by her library using AI to assist patrons; emphasized the importance of prompt engineering.
  • Stephen Abram: Highlighted the need for collaborative efforts, use cases, and establishing guardrails for AI implementation.
  • Fiona: Mentioned Toronto Public Library's leadership in using AI.

Conclusion

• Recognized that AI presents both significant challenges and opportunities for libraries.
• Emphasized the unique position of libraries to leverage trust and promote ethical AI use.
• Committed to ongoing discussions and exploring AI's impact on libraries in future sessions.
• Encouraged proactive engagement with AI, focusing on community needs and responsible practices.

Note: This outline summarizes a presentation on how libraries can respond to the challenges and opportunities presented by AI, featuring insights from industry experts and audience participation.

Data Science 101: Understanding Statistical Concepts and Analysis

From Couch to Jupyter: A Beginner's Guide to Data Science Tools and Concepts

Introduction

• Host: Manogna, Senior Data Scientist at Slalom.
• Presenter: Kiko K., Analytic Scientist at FICO on the Scores Predictive Analytics team.
• Background:
  • Graduated from UC Berkeley in 2019 with a degree in Applied Mathematics and Data Science.
  • Led teams integrating data science into non-traditional curricula.
  • Passionate about data science's power and community.

Workshop Overview

• Title: "From Couch to Jupyter—A Beginner's Guide to Data Science Tools and Concepts"
• Objective: Provide foundational knowledge and tools for beginners in data science.
• Structure:
  • Introduction to Jupyter Notebook.
  • Basics of Python programming.
  • Understanding data structures and statistical concepts.
  • Interactive code demonstrations.
• Resources:
  • GitHub repository with tutorial notebooks and datasets.
  • Anaconda installation guide for environment setup.

Key Topics Covered

• Using Jupyter Notebook
  • Understanding markdown and code cells.
  • Running cells and writing code.
• Python Basics
  • Data types: integers, floats, strings, booleans.
  • Variables and functions.
  • Arithmetic operations and function calls.
• Data Structures
  • Arrays with NumPy.
  • Pandas Series and DataFrames.
  • Indexing and slicing data.
• Data Manipulation and Analysis
  • Importing libraries and reading data files.
  • Handling missing data (NaN values).
  • Filtering and selecting data.
  • Basic statistical calculations: mean, median, standard deviation.
• Practical Demonstrations
  • Working with a stroke prediction dataset from Kaggle.
  • Visualizing data distributions.
  • Imputing missing values.

Additional Resources

• Anaconda Installation Guide: For setting up the Python environment.
• Tutorial Notebooks: Covering various topics in more depth.
• External Links: Videos and other learning materials for further study.

Conclusion

• Q&A Session: Addressed audience questions on topics like:
  • Differences between Jupyter Notebook and JupyterLab.
  • Handling missing data and NaN values.
  • Differences between arrays and series.
  • Recommendations for beginners starting with data sets.
• Final Remarks:
  • Encouraged attendees to explore provided resources.
  • Emphasized continuous learning in data science.
  • Thanked the audience for participation.

Note: The workshop aims to make data science accessible to beginners by providing hands-on experience with tools like Jupyter Notebook and Python, using practical examples and interactive code demonstrations.