Transforming Digital Archives with AI: Strategies, Tools, and Ethical Practices

Course Info

Length: 12 Days

City: Kuala Lumpur

Type: In Classroom

Available Dates

  • July-01-2024

    Kuala Lumpur

  • Aug-05-2024

    Kuala Lumpur

  • Sep-02-2024

    Kuala Lumpur

  • Oct-07-2024

    Kuala Lumpur

  • Nov-04-2024

    Kuala Lumpur

  • Dec-02-2024

    Kuala Lumpur

Dates in Other Venues

  • June-17-2024

    Amsterdam

  • June-17-2024

    London

  • June-24-2024

    Barcelona

  • June-24-2024

    Dubai

  • July-01-2024

    Istanbul

  • July-08-2024

    Paris

  • July-08-2024

    Singapore

  • July-15-2024

    Amsterdam

  • July-15-2024

    London

  • July-22-2024

    Barcelona

  • July-29-2024

    Dubai

  • Aug-05-2024

    Istanbul

  • Aug-12-2024

    Singapore

  • Aug-12-2024

    Paris

  • Aug-19-2024

    Amsterdam

  • Aug-19-2024

    London

  • Aug-26-2024

    Barcelona

  • Aug-26-2024

    Dubai

  • Sep-02-2024

    Istanbul

  • Sep-09-2024

    Singapore

  • Sep-09-2024

    Paris

  • Sep-16-2024

    Amsterdam

  • Sep-16-2024

    London

  • Sep-23-2024

    Barcelona

  • Sep-30-2024

    Dubai

  • Oct-07-2024

    Istanbul

  • Oct-14-2024

    Singapore

  • Oct-14-2024

    Paris

  • Oct-21-2024

    London

  • Oct-21-2024

    Amsterdam

  • Oct-28-2024

    Barcelona

  • Oct-28-2024

    Dubai

  • Nov-04-2024

    Istanbul

  • Nov-11-2024

    Singapore

  • Nov-11-2024

    Paris

  • Nov-18-2024

    Amsterdam

  • Nov-18-2024

    London

  • Nov-25-2024

    Barcelona

  • Nov-25-2024

    Dubai

  • Dec-02-2024

    Istanbul

  • Dec-09-2024

    Singapore

  • Dec-09-2024

    Paris

  • Dec-16-2024

    London

  • Dec-16-2024

    Amsterdam

  • Dec-23-2024

    Barcelona

  • Dec-30-2024

    Dubai

Course Details

Course Outline

12 days course

Introduction to AI in Digital Archives

 

  • Let us have an overview of AI and its evolution
  • what is digital archives and their importance?
  • What is the intersection of AI and digital archiving
  • Key technologies in AI: Machine Learning, NLP, Computer Vision
  • The role of AI in managing digital collections
  • what are the Benefits and the challenges of AI in archives?
  • First Case studies of AI application for archival settings
  • Discussion: Expectations and goals for the course
  • Read a case study on AI in archives

What are the Digital Archival Practices

 

  • Basics of digital archival processes
  • Standards and best practices in digital archiving
  • Metadata creation and management
  • Digital preservation strategies
  • Access and user engagement in digital archives
  • Ethical considerations in digital archiving
  • Role of AI in enhancing archival workflows
  • Group activity: Identifying pain points in digital archiving

AI Technologies and Tools for Archiving

 

  • Overview of AI tools relevant to archives
  • Machine Learning algorithms and their applications
  • Natural Language Processing for metadata and text analysis
  • Image and video recognition in archival materials
  • Data mining techniques for archival data
  • Interactive systems: Chatbots and virtual assistants
  • Evaluating AI tools for archival needs
  • Workshop: Hands-on with a basic AI tool
  • Homework: Explore an AI tool of choice

Implementing AI in Archival Workflows

 

  • Integrating AI into existing archival processes
  • Managing digital collections with AI
  • Automating metadata creation and curation
  • Enhancing user access and discoverability with AI
  • AI for digital preservation and conservation
  • Case study analysis: Successful AI implementation
  • Challenges and solutions in AI integration
  • Group discussion: Potential AI applications in participants' archives
  • Homework: Draft an AI implementation plan for a given scenario

Responsible Use of AI in Archives

 

  • Ethical considerations in AI deployment
  • Bias and fairness in AI algorithms
  • Data privacy and security in AI systems
  • Transparency and accountability in AI usage
  • Legal implications of AI in digital archiving
  • Developing ethical guidelines for AI in archives
  • Guest speaker: Expert on AI ethics in digital archiving
  • Q&A and discussion with the guest speaker
  • Homework: Analyze an ethical dilemma in AI archival use

AI for Digital Preservation and Conservation

 

  • The role of AI in digital preservation
  • Predictive analysis for preservation needs
  • AI in conservation: Detecting and addressing degradation
  • Automating backup and redundancy processes
  • Case study: AI in preserving at-risk archives
  • Challenges in AI-driven preservation
  • Workshop: AI tools for digital preservation
  • Group activity: Brainstorming AI solutions for preservation challenges
  • Homework: Propose an AI-based preservation strategy for a case study

AI and User Engagement in Archives

 

  • AI in enhancing user experience
  • Personalized access and content discovery
  • AI-driven virtual exhibitions and storytelling
  • Chatbots and AI assistants for user queries
  • Analyzing user behavior with AI
  • Case study: AI in engaging diverse audiences
  • Workshop: Creating an AI-driven user engagement tool
  • Group discussion: Innovating user engagement with AI
  • Homework: Design a user engagement campaign using AI

Managing Expectations and Limitations of AI

 

  • Realistic expectations from AI in archives
  • Addressing AI limitations and challenges
  • Managing stakeholder expectations
  • Training and capacity building for AI
  • Overcoming resistance to AI adoption
  • Balancing AI and human expertise
  • Case study discussion: Overcoming AI challenges in archives
  • Role-play activity: Managing expectations in an AI project
  • Homework: Reflect on the role-play and propose solutions

AI, Metadata, and Text Analysis

 

  • AI in metadata generation and enhancement
  • Text analysis and extraction techniques
  • Semantic analysis and ontologies
  • Enhancing searchability and discoverability
  • Case study: AI in metadata management
  • Workshop: Using an AI tool for metadata and text analysis
  • Challenges in AI-driven metadata creation
  • Group activity: Designing an AI-based metadata strategy
  • Homework: Evaluate an AI metadata tool

Bias and Fairness in AI for Archives

 

  • Understanding bias in AI algorithms
  • Impacts of biased AI in archives
  • Methods for detecting and mitigating bias
  • Ensuring fairness and inclusivity in AI systems
  • Case study: Addressing bias in an archival AI project
  • Workshop: Tools and techniques for bias detection
  • Group discussion: Strategies to promote fairness in AI
  • Role-play activity: Resolving a bias issue in an AI project
  • Homework: Analyze a biased AI scenario and propose solutions

Future of AI in Digital Archives

 

  • Emerging trends in AI and archival science
  • Predictive analytics and its potential in archives
  • AI in large-scale digital preservation
  • Augmented and virtual reality in archives
  • The role of AI in disaster recovery and risk management
  • Panel discussion: Future directions of AI in archives
  • Q&A with panelists
  • Group brainstorming: Innovative AI applications in archives
  • Homework: Create a future vision for AI in your archive

Course Wrap-up and Project Presentations

 

  • Review of key course learnings
  • Presentation of AI implementation plans by participants
  • Feedback and discussion on presentations
  • Challenges and opportunities ahead in AI for archives
  • Course evaluation and feedback
  • Networking and building a community of practice
  • Certificates and closing remarks
  • Future learning resources and opportunities
  • Farewell and course conclusion