Course Details

Navigating the AI Frontier: Artificial Intelligence & Ethics in Libraries Training Course

INTRODUCTION

"Harness the power of AI responsibly with our Artificial Intelligence & Ethics in Libraries Training Course. Delve into the ethical considerations surrounding AI implementation, including bias detection, algorithmic fairness, and responsible data use. This Artificial Intelligence & Ethics in Libraries Training Course empowers librarians to critically assess AI technologies, develop ethical guidelines, and foster a culture of responsible AI adoption. Learn to navigate the complex landscape of AI ethics, ensuring that your library's use of artificial intelligence aligns with principles of equity, transparency, and user trust."

DURATION

10 days

TARGET AUDIENCE

This course is meticulously designed for:

• Library Directors and Managers: To develop ethical AI policies.
• Systems Librarians: To implement and monitor AI systems.
• Digital Services Librarians: To ensure ethical use of AI in online services.
• Reference and User Services Librarians: To understand and address AI-driven biases.
• Information Science Students and Professionals: To gain expertise in AI ethics for libraries.
• Anyone interested in the responsible use of AI in library settings.

COURSE OBJECTIVES

Upon completion of this course, participants will be able to:

• Understand the ethical implications of AI in libraries.
• Identify and mitigate algorithmic bias in AI systems.
• Develop ethical guidelines for AI adoption and use.
• Implement strategies for transparent and accountable AI.
• Understand the legal and regulatory landscape of AI ethics.
• Promote responsible data collection and usage practices.
• Evaluate the impact of AI on user privacy and autonomy.
• Foster a culture of ethical AI awareness among library staff and patrons.
• Use tools and techniques for AI bias detection.
• Understand the importance of explainable AI.

COURSE MODULES

Module 1: Introduction to AI Ethics in Libraries:

• Overview of AI concepts and applications in libraries.
• The importance of ethical considerations in AI.
• Understanding the potential impacts of AI on library services.
• Key ethical principles and frameworks for AI.

Module 2: Identifying and Mitigating Algorithmic Bias:

• Understanding the sources and types of algorithmic bias.
• Techniques for detecting and measuring bias in AI systems.
• Strategies for mitigating bias through data and algorithm design.
• Case studies of algorithmic bias in real-world applications.

Module 3: Developing Ethical Guidelines for AI:

• Creating ethical guidelines for AI adoption and use in libraries.
• Implementing policies for responsible data collection and usage.
• Ensuring transparency and accountability in AI systems.
• Developing frameworks for ethical decision-making.

Module 4: Legal and Regulatory Landscape of AI Ethics:

• Understanding relevant laws and regulations related to AI.
• Navigating data privacy and security regulations (GDPR, CCPA, etc.).
• Addressing intellectual property and copyright issues.
• Understanding the implications of AI for legal compliance.

Module 5: Responsible Data Collection and Usage:

• Implementing data governance and management practices.
• Ensuring informed consent and data subject rights.
• Utilizing anonymization and pseudonymization techniques.
• Promoting data minimization and purpose limitation.

Module 6: Evaluating the Impact of AI on User Privacy and Autonomy:

• Understanding the privacy implications of AI technologies.
• Assessing the impact of AI on user autonomy and decision-making.
• Implementing measures to protect user privacy and control.
• Addressing concerns about surveillance and profiling.

Module 7: Fostering a Culture of Ethical AI Awareness:

• Developing training programs for library staff on AI ethics.
• Promoting awareness and understanding of AI ethics among patrons.
• Engaging with stakeholders and the community on AI issues.
• Creating resources and materials for ethical AI education.

Module 8: Tools and Techniques for AI Bias Detection:

• Introduction to tools and techniques for bias detection.
• Utilizing metrics for evaluating fairness and equity.
• Implementing bias mitigation algorithms and methods.
• Conducting bias audits and assessments.

Module 9: Explainable AI (XAI) and Transparency:

• Understanding the importance of explainable AI.
• Implementing techniques for making AI decisions transparent.
• Communicating AI processes and outcomes to users.
• Addressing concerns about black-box algorithms.

Module 10: Future Trends and Ethical Considerations:

• Exploring emerging AI technologies and applications.
• Understanding the long-term ethical implications of AI.
• Developing strategies for ongoing ethical evaluation and adaptation.
• The future of ethical AI in libraries and information services.

 CERTIFICATION

• Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

• Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

• Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

• Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com