Introduction
The programme “Using Artificial Intelligence for Book Recommendations” develops professional practice in Libraries. It connects the subject with workplace challenges by examining existing evidence and practices and choosing methods appropriate to the organization and its available resources.
The learning progresses from artificial intelligence applications and controls to data analysis and decision support, with practical work on library service development and knowledge organization, document, records, and digital preservation management, information systems analysis, integration, and service management. Participants prepare outputs to support workplace application and review the quality and results of implementation.
Learning objectives
- Design an AI use case with verification criteria and human review in an application related to “Using Artificial Intelligence for Book Recommendations”.
- Design a library service and organize its resources to facilitate access and use.
- Build a document life cycle controlling classification, permissions, retention, and retrieval.
- Analyze information system requirements and design acceptance, integration, and operational criteria.
- Turn available data into documented analysis that supports a specific professional decision.
Learning areas
1. Artificial Intelligence Applications and Controls
- Identify a task that AI can support, and separate inputs and human decisions from outputs produced by the tool.
- Prepare suitable test data and examples while respecting confidentiality, privacy, and permissions, and use de-identified training exercise data.
- Write clear instructions covering the task, context, constraints, and output format, and compare multiple formulations using a fixed set of examples.
- Check outputs for errors, bias, and unsupported information, and identify cases that require specialist review.
- Assess the feasibility of use in terms of quality, time, cost, and risk, and document controls for approval, monitoring, and stopping when failures occur. The application examines a case related to “Using Artificial Intelligence for Book Recommendations”.
2. Library Service Development and Knowledge Organization
- Analyze beneficiary groups, their needs, and search and access methods, identifying gaps between available resources and actual use.
- Develop an acquisition and collection development policy considering specialization, currency, rights, budget, and multiple content formats.
- Apply principles of description, cataloging, authority control, and access points, reviewing rules and fields appropriate to the system in use.
- Design research and guidance services and a digital repository with metadata, permissions, and accessibility features suited to beneficiaries.
- Select indicators for discovery, lending, use, and satisfaction, and prepare a pilot to improve a library service and evaluate its results.
3. Document, Records, and Digital Preservation Management
- Inventory document and record types, owners, and reasons for retention, and distinguish operational copies from the authoritative record.
- Design classification, coding, metadata, and version control rules, with clear naming, indexing, and search criteria.
- Define viewing, editing, and approval permissions and usage tracking, and protect confidentiality and record integrity throughout circulation.
- Prepare a retention and disposal or permanent preservation transfer schedule after reviewing legal and regulatory requirements specific to each record type.
- Test retrieval, migration, backups, and file integrity verification, and set indicators for indexing accuracy and continuity of access.
4. Information Systems Analysis, Integration, and Service Management
- Analyze system users, processes, and the decisions it supports, translating needs into clear functional and nonfunctional requirements.
- Model data flows, entities, relationships, and interfaces, identifying each data item's source and the party responsible for its quality and updating.
- Compare build, buy, integration, and hosting alternatives according to constraints, security, total cost, and available support capabilities.
- Design test cases covering performance, permissions, usability, and integration, and connect each test to a testable acceptance criterion.
- Prepare a transition, operations, support, change management, and backup plan, defining indicators for service availability, fault resolution, and improvement review.
5. Data Analysis and Decision Support
- Frame an analytical question linked to a specific decision, and define the unit of measurement, time period, and data needed to answer it.
- Check data quality for completeness, accuracy, consistency, and duplication, and document cleaning steps and limitations on reliance.
- Select appropriate comparisons, indicators, and charts, and distinguish statistical correlation from causal explanations of results.
- Interpret results in the work context, test assumptions and unusual values, and present alternatives and their associated uncertainty.
- Prepare an analytical report containing the finding, recommendation, data source and date, review owner, and next follow-up step.
Practical outputs
- A use case brief and a test template for the quality of AI outputs.
- A library service plan, resource description card, and usage indicators.
- A classification plan, retention schedule, and document metadata template.
- A requirements document, data flow map, and testing and acceptance plan.
- A dashboard and decision memo explaining the data, assumptions, and alternatives.
Who should attend
- Practitioners, specialists and supervisors whose work relates to the programme subject.
- Managers and teams working in libraries, according to their practical responsibilities.
- Professionals responsible for applying the outputs of “Using Artificial Intelligence for Book Recommendations” within their organizations.
Prerequisites
- Working familiarity with the programme field and the ability to discuss a professional case or challenge.
- Confirm the suitability of your experience and any specialist prerequisites with the Union before participation.
Conclusion
The programme “Using Artificial Intelligence for Book Recommendations” brings together concepts, case review and a practical application. Participants prepare steps that can be adapted to their responsibilities and organizational resources, with an indicator to follow application and review results after returning to work.
Participation arrangements and any special requests are specified in the confirmation issued by the Union.