Salam everyone. TokMun has not posted for a while. Being busy and over-encumbered with various tasks and visits overseas lately (tak jauh pun, Singapore sahaja). The visit was great, and we (the boss and several other colleagues) learnt various new things that we could implement at our library.
Back to our discussion – Will AI replace humans in the workplace? This is Digital Disruptions or disruptive technology that haunts people like you and me. The short answer is YES, but not like what you have in mind.
It is not the machine that will replace you and turn you into a battery or organic power cell (Read: The Matrix), nor does the machine try to eradicate all humanities like in the Terminator. You will be replaced by someone who can embrace or harness the power of AI. Your friends or colleagues are your direct threat to your very existence.
AI vs Humanities
You may have heard some alarming predictions about how artificial intelligence (AI) will take over your job and make you obsolete. While it is true that AI is transforming many industries and automating some tasks, it does not mean that a machine will replace you. However, it does mean that you will need to adapt and learn new skills to keep up with the changing demands of your profession.
AI is not a threat but an opportunity. It can help you work smarter, faster, and more creatively. It can augment your abilities and enhance your performance. It can also free you from tedious and repetitive tasks, allowing you to focus on more meaningful and rewarding aspects of your work.
But to take advantage of AI, you must know how to use it. You must understand its capabilities and limitations, strengths and weaknesses, and ethical and social implications. You need to be able to collaborate with AI systems, leverage their insights, and provide feedback. You need to be able to communicate effectively with other humans who use AI and those who do not.
Become AI literate and take control of your future:
In other words, you need to develop your AI literacy. This is the ability to understand, interact with, and benefit from AI in various contexts. AI literacy is not only about technical skills but also about cognitive, social, and emotional skills. It is about being curious, creative, critical, and compassionate.
AI literacy is not a luxury but a necessity. It is not something that only experts or specialists need, but something that everyone needs. It is not something you can learn once and forget, but something you must constantly update and improve.
If you do not develop your AI literacy, you may fall behind in your career and miss out on valuable opportunities. You may become irrelevant or redundant in the eyes of your employers or customers. You may lose your competitive edge or your sense of purpose.
AI will not replace you, but you will be replaced with someone who knows how to use AI. So do not fear AI, but embrace it. Do not resist change, but welcome it. Do not settle for the status quo, but strive for excellence.
The future of work is not about humans versus machines but humans with machines. And the future of work is now.
References:
Losee, C. (n.d.). AI Will Not Replace You, People Using AI Will. www.linkedin.com. https://www.linkedin.com/pulse/ai-replace-you-people-using-christopher-losee/
Stahl, A. (2022, May 3). The Rise Of Artificial Intelligence: Will Robots Actually Replace People? Forbes. https://www.forbes.com/sites/ashleystahl/2022/05/03/the-rise-of-artificial-intelligence-will-robots-actually-replace-people/?sh=4c6d77b73299
The A Group @ www.agroup.com. (2023, February 23). Are You Going to Be Replaced by AI? The a Group. https://www.agroup.com/blog/are-you-going-to-be-replaced-by-ai
Taxonomy is the science of organising and classifying information, and it is an essential skill for librarians who deal with large and diverse collections of books, journals, databases, and other resources. However, creating and maintaining a taxonomy can be a challenging and time-consuming, especially when new topics and terms emerge constantly in the dynamic world of knowledge.
The word “taxonomy” comes from the Greek τάξις (taxis), meaning “arrangement”, “order,” or “sequence”, and -νομία (-nomia), meaning “method”. Taxonomy began as a natural science, with Aristotle proposing a system for classifying living organisms in his work History of Animals. Later, Carl Linnaeus extended this system to include all plants in his work Systema Naturae. Nowadays, taxonomies are used in numerous domains outside biology, such as the library and document classification systems, economics, computing, business models, and personal organisation schemes (Tilton, 2009).
Tok Mun would like to explain how ChatGPT improved my taxonomy creation and development task. First, let us look at how ChatGPT can enhance your life and get you more time for gaming at work (waktu makan tau. Jangan main game waktu kerja, tak berkat).
The benefits of using ChatGPT for taxonomy management
Based on the same concept, we may also apply the process to the creation or development of taxonomy as creating or maintaining terms of taxonomies can be time-consuming and expensive. It is a challenging and time-consuming task, especially for large and complex domains. It requires a lot of domain expertise, research, analysis, and collaboration to create and update taxonomies that meet the needs and expectations of different stakeholders and users.
This is where Chat GPT can help taxonomy managers or precisely you to create and refine taxonomies in a faster and easier way.
Below are benefits of using ChatGPT for taxonomy management:
Chat GPT can generate high-quality and relevant terms and concepts based on the given keywords and characteristics. For example, if you want to create a taxonomy for chatbots, you can provide keywords such as “chatbot”, “conversational AI”, “dialogue system”, etc., and characteristics such as “tone: professional”, “length: short”, “format: list”. Chat GPT will then generate a list of terms and concepts that are related to chatbots and match the characteristics.
Chat GPT can also generate definitions, descriptions, examples, synonyms, antonyms, and other metadata for each term and concept. This can help to provide more context and clarity for the taxonomy users and stakeholders.
Chat GPT can receive user feedback and suggestions to improve the generated text. For example, if you want to change or rewrite some parts of the text, you can provide feedback such as “replace X with Y”, “add Z”, “delete W”, etc. Chat GPT will then modify the text accordingly and generate a new version.
Chat GPT can also learn from previous interactions and preferences to generate more personalized and customized text. For example, if you prefer a certain style or tone of writing, Chat GPT will adapt to your preference and generate text that suits your taste.
Chat GPT can save time and effort for taxonomy managers by automating some of the tedious and repetitive tasks involved in taxonomy creation and maintenance. For example, Chat GPT can generate new terms and concepts based on emerging trends or user queries, update existing terms and concepts based on changes in the domain or user feedback, delete obsolete or redundant terms and concepts based on usage statistics or user feedback, etc.
By using Chat GPT for taxonomy management, you can create and maintain high-quality and up-to-date taxonomies that can enhance your data and content management capabilities. This is a powerful and versatile tool that can help you achieve your taxonomy goals in a more efficient and effective way.
How can ChatGPT be used to generate new terms or categories?
One of the ways that ChatGPT can help you to manage or develop your taxonomy is by generating new terms or categories based on existing ones. For example, if you want to add a new subcategory under the category of “Artificial Intelligence”, you can input the keywords “Artificial Intelligence” and “subcategories” and ChatGPT will generate a list of possible subcategories, such as “Machine Learning”, “Computer Vision”, “Natural Language Processing”, etc. This capability relies on its understanding of the semantic similarity and word associations it has acquired through extensive exposure to vast collections of texts.
By generating new terms or categories based on existing ones, ChatGPT can help you expand your taxonomy and cover more topics and areas of interest. It can also assist you in keeping your taxonomy up-to-date with the latest developments and trends in your field. ChatGPT can help you avoid duplication or inconsistency in your taxonomy by suggesting terms or categories that already exist or are related.
How can ChatGPT be used to generate definitions or descriptions?
ChatGPT can help you to manage or develop your taxonomy by generating definitions or descriptions for terms or categories. For instance, if you want to define the term “Machine Learning,” you can input the keywords “Machine Learning” and “definition,” and ChatGPT will generate a concise and accurate definition, such as “Machine Learning is a branch of Artificial Intelligence that focuses on creating systems that can learn from data and improve their performance without explicit programming.”
This feature is based on ChatGPT’s ability to extract relevant information from various sources and synthesize it into coherent text. By generating definitions or descriptions, it can assist you in clarifying your taxonomy and making it more understandable for your users and colleagues. It can contribute to standardizing your taxonomy, ensuring consistency across different platforms and formats. Additionally, ChatGPT can help enrich your taxonomy, making it more informative and engaging for users and colleagues.
Next we will look into how AI can be used to generate synonyms or related terms.
How can ChatGPT be used to generate synonyms or related terms?
Another way that ChatGPT can assist you in managing or developing your taxonomy is by generating synonyms or related terms for terms or categories. For instance, if you want to find synonyms or related terms for “Natural Language Processing,” you can input the keywords “Natural Language Processing,” “synonyms,” or “related terms,” and ChatGPT will generate a list of options like “Computational Linguistics,” “Text Analysis,” “Text Mining,” and more. This capability is based on the diverse lexical knowledge that ChatGPT acquires from its exposure to various domains and genres of texts.
By generating synonyms or related terms, ChatGPT helps you optimize your taxonomy, making it more flexible and adaptable to different purposes and contexts. It enables you to improve the comprehensiveness and inclusivity of your taxonomy, accommodating different users and perspectives. Additionally, ChatGPT aids in diversifying your taxonomy, making it dynamic and engaging for various users and scenarios.
How can Chat GPT be used to generate examples or applications?
ChatGPT can assist you in managing or developing your taxonomy is by generating examples or applications for terms or categories. For instance, if you want to find examples or applications for the term “Computer Vision,” you can input the keywords “Computer Vision,” “examples,” or “applications,” and ChatGPT will generate a list of possibilities like “Face Recognition,” “Object Detection,” “Self-Driving Cars,” and more. This capability relies on ChatGPT’s creative and generative abilities, allowing it to produce relevant and novel texts based on a given context.
By generating examples or applications, ChatGPT helps you illustrate your taxonomy, making it more tangible and concrete for your users and colleagues. It can also aid in validating your taxonomy, ensuring its relevance and usefulness for your users’ specific needs and goals. Additionally, ChatGPT can inspire curiosity among your users by introducing them to new possibilities within the taxonomy.
Final Thoughts on the benefits and challenges of using ChatGPT for taxonomy management or development?
Using ChatGPT for taxonomy management or development has several benefits and challenges. Some of the benefits are:
Saving time and effort in creating and updating the taxonomy
Enhancing the quality and consistency of the taxonomy
Discovering new trends and insights in the fields of interest
Communicating effectively with users and colleagues in different languages
Some of the challenges are:
Verifying the accuracy and reliability of the generated texts
Adapting the generated texts to the specific needs and preferences of the users
Maintaining the security and privacy of the data and information
Evaluating the ethical and social implications of using NLP tools
Conclusion
ChatGPT is a versatile and valuable tool that librarians can tap to manage or develop their taxonomy in the era of information explosion. By using ChatGPT, librarians can generate new terms or categories, definitions or descriptions, synonyms or related terms, examples applications for their taxonomy based on a few keywords phrases.
However, it is crucial for librarians to be mindful of the challenges and limitations associated with using ChatGPT and to exercise responsible and ethical use. While ChatGPT is capable of generating valuable insights, it is important to remember that it is an AI model and may not always produce accurate or contextually appropriate results. Librarians should employ critical thinking and human judgment when evaluating and validating the generated content.
Ethical considerations are paramount when utilizing ChatGPT. Librarians must ensure that the generated content aligns with legal and ethical guidelines, respects intellectual property rights, and avoids biases or discriminatory language. Additionally, being aware of the biases that may exist within the training data and actively addressing them is crucial to maintain fairness and equity in the outputs.
In summary, while ChatGPT offers valuable support for taxonomy management, librarians must approach its usage with caution. By combining the capabilities of ChatGPT with human expertise, critical evaluation, and ethical considerations, librarians can harness its potential while addressing the challenges and limitations that come with it.
References
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., & Hesse, C. (2020). Language Models are Few-Shot Learners. Arxiv.org. https://arxiv.org/abs/2005.14165
Dathathri, S., Madotto, A., Lan, J., Hung, J., Frank, E., Molino, P., Yosinski, J., & Liu, R. (2020). Plug and Play Language Models: A Simple Approach to Controlled Text Generation. ArXiv:1912.02164 [Cs]. https://arxiv.org/abs/1912.02164
Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019). RoBERTa: A Robustly Optimized BERT Pretraining Approach. ArXiv.org. https://arxiv.org/abs/1907.11692
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., & Sutskever, I. (2019). Language Models are Unsupervised Multitask Learners. https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf
Tilton, L. (2009, January 10). From Aristotle to Linnaeus: the History of Taxonomy – Dave’s Garden. Www.davesgarden.com. https://davesgarden.com/guides/articles/view/2051
Librarians face the challenge of managing and organising an ever-expanding collection of digital assets. With an overwhelming number of files in different formats and sizes, it’s easy to feel overwhelmed and lost in the chaos. Have no fear. Tok Mun will help you to conquer the chaos and take control of your digital assets like a real librarian.
Embracing AI in Digital Asset Management
Digital asset management is the process of storing, categorising, and retrieving digital files. It is a critical part of any librarian’s job, as it helps to ensure that files are easy to find and use.
This is where ChatGPT can help. ChatGPT is a powerful natural language processing (NLP) tool that generates text based on input. You can use ChatGPT to create folder names and descriptions that are relevant, informative, and concise. ChatGPT can also suggest alternative names and descriptions that suit your needs better.
Step 1: Define your main categories
The first step is to define your main categories of files. These are the top-level folders that will contain your subfolders and files. You can use broad terms that capture your files’ general theme or purpose. For example, if you have a collection of books on various topics, you can use the following main categories:
Fiction
Non-fiction
Reference
To create these folders, you can type them in your file explorer or use ChatGPT to generate them for you. To use ChatGPT, you can enter a prompt such as “Generate three main categories for a library collection of books on various topics.” ChatGPT will then produce a list of possible folder names based on your prompt. For example:
Literature
Information
Resources
You can choose the folder names that best suit your needs or modify them as you wish.
Step 2: Create subcategories
The next step is to create subcategories for each main category. These second-level folders will further divide your files into more specific groups. You can use more detailed terms that describe the subtopics or genres of your files. For example, if you have a fiction category, you can use the following subcategories:
Fantasy
Mystery
Romance
Science Fiction
To create these folders, you can type them in your file explorer or use ChatGPT to generate them. To use ChatGPT, you can enter a prompt such as “Generate four subcategories for fiction books.” ChatGPT will then produce a list of possible folder names based on your prompt. For example:
Adventure
Crime
Historical
Horror
You can choose the folder names that best suit your needs or modify them as you wish.
Bonus:
Here are some more examples of how ChatGPT can generate different folder names based on different prompts:
Generate four subcategories for non-fiction books.
Biography
History
Science
Self-help
Generate four subcategories for reference books.
Dictionaries
Encyclopedias
Manuals
Guides
Generate four subcategories for visual arts books.
Painting
Sculpture
Photography
Graphic Design
Step 3: Add descriptions
The final step is to add descriptions for each folder. These are short sentences that explain what each folder contains and why it is important. Descriptions can help you, and others understand the purpose and content of each folder at a glance. They can also help you avoid confusion and duplication of files.
To create these descriptions, you can type them in your file explorer or use ChatGPT to generate them. To use ChatGPT, you can enter a prompt such as “Generate a description for the fantasy subcategory.” ChatGPT will then produce a sentence based on your prompt. For example:
Fantasy is a subcategory of fiction that features imaginative and magical elements such as wizards, dragons, and quests.
You can choose the description that best suits your needs or modify it as you wish.
Step 4: Review and improve
Once you have created your folder structure, you can review it and see if it meets your needs and expectations. You can also use ChatGPT to help you improve your folder structure by providing feedback and suggestions.
To use ChatGPT for this purpose, you can enter a prompt such as “Review my folder structure and suggest how to improve it.” ChatGPT will then analyze your folder structure and produce a list of possible improvements based on your prompt. For example:
Consider adding more sub categories to non-fiction to cover more topics such as biography, history, science, etc.
Consider renaming resources to references to avoid confusion with information.
Consider adding more descriptions to explain the difference between literature and fiction.
Consider using consistent capitalization and punctuation for all folder names and descriptions.
You can choose the improvements that best suit your needs or ignore them as you wish.
Final Thoughts
ChatGPT is a powerful tool to help you create and manage your folder structure effectively. By using ChatGPT, you can save time and effort in creating folder names and descriptions that are relevant, informative, and concise. You can also benefit from ChatGPT’s feedback and suggestions to improve your folder structure and make it more logical, consistent, and intuitive.
We hope this blog post has given you some insights into how to leverage ChatGPT for effective folder structure management.
As a librarian, we are required to keep up with the latest technology to provide the best possible service to our users. I am more than happy to introduce ChatGPT – a revolutionary tool that can help to streamline your workflow and enhance communication with our users or, to be precise, your users. In this post, we will explore some of the benefits of ChatGPT and how you, my librarian friends, can use it, and leverage it to bring your library services to greater heights.
Get ready to be revolutionised.
What is Chat GPT and How Can it Help Librarians?
ChatGPT is a web-based chatbot that can help you with a variety of tasks, including providing reference services, circulation services, and research assistance. In addition, this AI can also help you to keep track of your to-do lists, manage your time more effectively, and stay organised.
Why should you leverage ChatGPT?
There are many advantages of using ChatGPT. For example, ChatGPT can help you to save time by automating tasks that would otherwise need to be done manually. In addition, ChatGPT can also help you to improve your workflow by providing you with an easy way to access information and resources. It can also assist you in reducing your workload by taking on some of the tasks that you would otherwise need to do yourself.
Automate Research with ChatGPT
As librarians or some might call us the Information Professionals, we know that research can be a time-consuming and tedious process. But what if there was a way to automate research with the help of ChatGPT?
ChatGPT is an artificial intelligence chatbot that can help you with your research. All you need to do is type in your question, and ChatGPT will search through billions of documents to find the answer for you. You can also ask follow-up questions to refine your results.
Not only does ChatGPT save you time, but it can also help you expand your research horizons by providing you with new ideas and perspectives that you may not have considered before. So why not give it a try? (I am not affiliated with nor doing any promotional activity for ChatGPT). You may just be surprised at how much ChatGPT can help revolutionize your workflow!
Increase Productivity with ChatGPT
We are under constant pressure to do more with less. We are expected to be knowledgeable about an ever-increasing range of topics, and we must be able to find the information our users need quickly. Adding ChatGPT to your workflow can help streamline the process and make getting the information you need easier.
ChatGPT instantly connects you with a network of research librarians who can help you with your questions. You can also search the ChatGPT Knowledge Base for answers to common questions. And if you need more help, ChatGPT offers live chat support 24/7.
ChatGPT is easy to use and integrates seamlessly with your existing workflow. There’s no software to install, and it works on any device. With a caveat, please do not share, never share any sensitive or propriety information of your organisation with ChatGPT. (Read: Samsung bans ChatGPT use after employee leak | TechRadar). With ChatGPT, you can finally get the information you need without having to search through endless resources.
Examples of Using Chat GPT in Libraries
Chatbot for Reference Services: Libraries can use Chat GPT to create a chatbot that can answer reference questions from patrons. This can be done using a platform like Facebook Messenger, where patrons can send their questions to the library’s page and receive automated responses powered by Chat GPT.
Virtual Writing Assistant: Libraries can integrate Chat GPT into their online writing resources to offer a virtual writing assistant to their patrons. Patrons can input their writing and receive feedback and suggestions for improvement from Chat GPT.
Personalized Reading Recommendations: Libraries can use Chat GPT to offer personalized reading recommendations to their patrons. Patrons can provide information about their reading preferences, and Chat GPT can suggest books and authors that might interest them.
Interactive Storytelling: Libraries can create interactive storytelling experiences using Chat GPT. Patrons can input their own ideas and responses, and Chat GPT can generate a story that incorporates those elements.
Language Learning: Libraries can use Chat GPT to create language learning resources for their patrons. Patrons can input text in the language they are learning, and Chat GPT can provide feedback and suggestions for improvement.
Disclaimer: I use ChatGPT to generate these examples
Benefits of using ChatGPT for Reference Services
One of the best ways to revolutionise your workflow as a librarian is to take advantage of ChatGPT, an online chat service that can be used for reference services. Here are some of the benefits of using ChatGPT for reference services:
You can save time by quickly answering questions from patrons without having to schedule appointments or track down specific reference materials.
You can improve patron satisfaction by giving them more immediate answers to their questions.
You can reach more patrons by being available 24/7, which is especially useful for those who live in different time zones or have scheduling conflicts.
You can provide more personalized service by getting to know your patrons better and understanding their unique needs.
You can increase efficiency by handling multiple chats simultaneously and quickly transferring chats to other librarians if necessary.
Considerations and Drawbacks to Using ChatGPT
As useful as it is, you should be aware of a few key considerations and drawbacks to using ChatGPT before deciding if it’s the right tool for your workflow.
First, ChatGPT is built on top of the GPT-3 platform; it inherits some of the same limitations. For example, GPT-3 has difficulty understanding long or complex questions, so you will need to keep the questions concise when using ChatGPT. Additionally, GPT-3 cannot answer questions about specific library catalogues or databases, so you will need to supplement ChatGPT with other search tools when working with users.
Second, while ChatGPT can answer simple questions quickly, it is not yet advanced enough to handle more complicated reference inquiries. You will need to be prepared to step in and provide assistance when ChatGPT cannot satisfy your or your users’ needs.
And finally, ChatGPT knowledge or databases is limited up to September 2021. In other words, ChatGPT does not have information on events or developments that have occurred after that date.
As with any new technology, there is a learning curve associated when using ChatGPT. Before using it, you will need to take some time to familiarise yourself with the tool and its capabilities.
Final Say: Revolutionise Your Workflow with Innovative Technology
The ChatGPT is a revolutionary new artificial intelligence chatbot that has the potential to revolutionise your workflow. It is designed to help you manage your work more efficiently and effectively by automating tasks that would otherwise take up your valuable time. It can suggest tools and apps that can help you schedule appointments, send reminders, and order supplies. ChatGPT can also provide tips and strategies for time management, organisation, and productivity that can be useful in performing those tasks.
References
Baker, A. (2019, March 13). Revolutionize Your Workflow: A Guide for Librarians on Using ChatGPT.
O’Connor, L. G. (2021). AI Chatbots in Libraries: A Review of Current Practices and Future Directions. Journal of Library Administration, 61(4), 378-393.
Retrieved from https://blog.chatgpt.com/revolutionize-your-workflow-a-guide-for-librarians-on-using-chatgpt/
Rader, H., & Hirshon, A. (2021). Libraries and Artificial Intelligence: Opportunities and Challenges. Journal of Librarianship and Information Science, 53(1), 27-40.
Liu, J., Mao, J., Lu, L., & Jiao, L. (2021). Using Chatbots for Reference Services: A Systematic Literature Review. Journal of Academic Librarianship, 47(2), 102252.
Chen, Y., Huang, H., & Wang, C. (2021). Using Chatbots to Provide Reference Services in Academic Libraries: A Case Study. Journal of Academic Librarianship, 47(3), 102305.
Skirpan, M., & Harlow, S. (2021). Chatbots in Academic Libraries: An Exploratory Survey of Current Practices and Perceptions. College & Research Libraries, 82(2), 238-255.
Artificial intelligence (AI) is a rapidly evolving technology that can potentially transform librarianship in various ways. AI can be defined as “the ability of machines to do things that people would say require intelligence” (Jackson, 1985). AI can enable new capabilities to address users’ information needs, such as providing not just information but deep intelligence and offering “Insight As A Service (IAAS)” (Springer Nature, 2019). While AI can also enhance and augment many library services and workflows, such as content indexing, classification, search and discovery, data analysis and visualization, chatbots, and virtual assistants, AI, however, also poses some challenges and ethical issues for librarians, such as privacy, bias, accountability, transparency, and trust.
As librarians, we need to be aware of the impact of AI on our profession and our users and actively participate in designing and evaluating AI-based tools and applications. We also need to update our skills and knowledge to keep up with the latest trends and developments in AI and related technologies.
We will explore some of the ways in which AI would change the role of libraries in these three main areas:
Content Indexing
Virtual Assistants and
Data Visualisation
We will also look into opportunities that we, as a librarian, can leverage AI to improve library services.
Content Indexing
Content indexing is the process of assigning keywords, subject classification or metadata to documents or any library resources to facilitate content discovery for retrieval and use. This has always been done manually, and it proves to be a tedious task even for experienced librarians. The process typically involves analysing the text of the content to identify keywords, phrases, and other metadata that can be used to describe the content and facilitate retrieval. Naturally, this is a vital process of any library information system, not limited to search engines, content management systems, and digital assets management systems.
Libraries can leverage the speed of AI to automate and improve this process by utilising natural language processing (NLP) and machine learning (ML) capabilities to analyse digital collections and identify relevant topics and thus assign suitable metadata to improve search and discovery. We look at how Springer Nature employs AI to index its vast collection of eBooks and provide semantic search capabilities (Springer Nature, 2019).
We can tap into this capability and benefit from AI-powered content indexing by accessing more comprehensive and accurate metadata in our collections, which at the end of the day, shall improve search results with precision. Similarly, ML may group or cluster documents of similar concepts as a result of enhanced classification schemes, taxonomy and ontologies.
Virtual Assistants (VA)
Virtual assistants or digital assistants are applications that use natural language understanding (NLU) and speech recognition to interact with users via voice or text (Read: 26 Actually Useful Things You Can Do with Siri). VAs may perform various tasks for users, such as answering questions, providing information, setting reminders, playing music or controlling smart devices. Some of the most popular VAs are Google Assistant, Siri, Alexa and Cortana.
VAs have also entered libraries in the form of chatbots that can handle directional questions on a library website, alert when a book is due, point a user to relevant library resources or answer simple informational requests (Hervieux & Wheatley, 2020). In the future, VAs may be able to provide more advanced services for our users, such as recommending books or articles based on user preferences or context, summarizing key points or arguments from a document or dataset, or generating citations or bibliographies. We can use VAs to enhance our user experience and satisfaction and reduce their workload for repetitive or routine tasks. We can also collaborate with VAs developers to ensure that they are reliable, accurate and ethical.
Data Visualisation
Generally, data visualization is the process of presenting data in graphical or pictorial forms to communicate information effectively and efficiently. This can help or aid users to better understand complex data sets, discover patterns or trends, compare variables or categories, or tell stories with data.
Data visualisation tools can use AI to analyze data and generate visualisations automatically or semi-automatically based on user input or preferences. For example, SciGraph Explorer is a data visualization tool that uses AI to map connections among concepts, researchers and institutions based on Springer Nature’s publications (Springer Nature, 2019). We can use data visualization tools to provide IAAS for our users by helping them find unexpected connections or insights from existing data sources. We can also use data visualization tools to showcase our own collections or services in an engaging and interactive way.
Conclusion
AI is changing libraries in many ways by offering new possibilities for improving library services and workflows. We need to embrace AI as an opportunity rather than a threat by learning about its potential benefits and challenges for our profession.
References:
Jackson, P. (1985). In Introduction to artificial intelligence. essay, Dover Publications.
The impact of Artificial Intelligence on librarian services | For Librarians | Springer Nature. (2019, July 21). The Impact of Artificial Intelligence on Librarian Services | for Librarians | Springer Nature. https://www.springernature.com/gp/librarians/news-events/all-news-articles/ebooks/the-impact-of-artificial-intelligence-on-librarian-services/16874432
Wheatley, A., & Hervieux, S. (2020, February 6). Artificial intelligence in academic libraries: An environmental scan. Information Services & Use, 39(4), 347–356. https://doi.org/10.3233/isu-190065
IFLA Trend Report — Advances in Artificial Intelligence. (n.d.). IFLA Trend Report — Advances in Artificial Intelligence. https://trends.ifla.org/literature-review/advances-in-artificial-intelligence
