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Question

Artificial Intelligence (AI) has reshaped information retrieval in libraries by enabling faster, more accurate, and context-aware access to resources. Traditional systems relied heavily on Boolean logic, keyword matching, and subject indexing, often demanding strong search skills. In contrast, AI-driven tools use Natural Language Processing (NLP), Machine Learning (ML), and semantic search to interpret user intent and retrieve results that match the user’s context. For instance, instead of listing thousands of items for a term like "digital preservation," AI systems can identify whether the user needs theoretical insights, technological solutions, or case studies and prioritise accordingly. Chatbots and Virtual Reference Services (VRS) represent another major advancement. Earlier reference services were limited by staff availability and slower response times. AI-enabled chatbots now provide 24/7 scalable support, assisting users with catalogue navigation, database searching, and citation queries. Enhanced VRS also include voice-enabled interaction, multilingual help, and links to institutional repositories and e-learning platforms, expanding access for remote and diverse users. However, AI adoption introduces challenges. Ethical concerns include data privacy, dependence on automated systems, and algorithmic bias, which may unintentionally suppress unconventional research areas if tools are trained on mainstream datasets. Additionally, chatbots, despite their efficiency, cannot replicate human empathy, judgement, or critical thinking, making a hybrid approach that blends AI with human expertise the most sustainable model. For LIS professionals, integrating AI demands new competencies. Librarians must develop skills in digital ethics, algorithmic transparency, and data analytics while ensuring that AI tools are critically assessed. Their role increasingly includes evaluating AI systems to ensure they align with educational goals, rather than purely commercial interests. Balancing human expertise with AI capabilities remains central to ensuring equitable and meaningful access.

What approach does the passage consider most sustainable for library services?

The correct answer is
Blending AI tools with human expertise

Understanding Sustainable Library Services

Identifying the Most Sustainable Approach

The passage discusses the integration of Artificial Intelligence (AI) in libraries and its implications for service sustainability.

  • The text highlights the limitations of AI, such as the inability of chatbots to replicate human empathy, judgment, or critical thinking.
  • It also points out ethical concerns like data privacy and algorithmic bias.
  • Based on these considerations, the passage explicitly states that "a hybrid approach that blends AI with human expertise the most sustainable model."
  • This balanced approach combines the efficiency and advanced capabilities of AI tools with the essential human qualities provided by library professionals.
  • The passage emphasizes that balancing human expertise with AI capabilities is crucial for ensuring equitable and meaningful access to library resources.

Therefore, the most sustainable approach for library services, according to the passage, is the blend of AI tools with human expertise.

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Important Questions from Artificial Intelligence

  1. In designing an agent in AI, PEAS stands for :
  2. How do computational models contribute to disaster research?
  3. Arrange the progression of machine learning methodologies from basic to advance in terms of complexity and abstraction in proper order
    A. Supervised Learning
    B. Unsupervised Learning
    C. Deep Learning
    D. Reinforcement Learning
    Choose the correct answer from the options given below :
  4. Machine Learning (ML) model aims to assess Landslide Susceptibility of a region. What could be the general steps which must be followed to set up ML model? Identify the correct sequence.
    A. Training and exploration of datasets
    B. Choice of algorithm and running algorithm
    C. Project goals and data collection
    D. Validation, reinforcement and re-running and output
    Choose the correct answer from the options given below :
  5. Artificial Neural Networks (ANNs) trained on meteorological data sets (AI tools) is used for :
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