Artificial Intelligence: an Illustrated History by
A History of the Future that's Happening Right Now Artificial Intelligence: An Illustrated History explores the historic origins and current applications of AI in such diverse fields as computing, medicine, popular culture, mythology, and philosophy. Through more than 100 entries, award-winning author Clifford A. Pickover, offers a granular, yet accessible, glimpse into the world of AI--from medieval robots and Boolean algebra to facial recognition, and artificial neural networks. First released in 2019, this updated paperback edition brings readers up to speed with coverage of technologies such as DALL-E and ChatGPT, and it explores the very real fear that AI will alter the course of humanity--forever.
How AI Works: from sorcery to science by
AI isn't magic. How AI Works demystifies the explosion of artificial intelligence by explaining-without a single mathematical equation-what happened, when it happened, why it happened, how it happened, and what AI is actually doing "under the hood." Artificial intelligence is everywhere-from self-driving cars, to image generation from text, to the unexpected power of language systems like ChatGPT-yet few people seem to know how it all really works. How AI Works unravels the mysteries of artificial intelligence, without the complex math and unnecessary jargon. You'll learn- The relationship between artificial intelligence, machine learning, and deep learning The history behind AI and why the artificial intelligence revolution is happening now How decades of work in symbolic AI failed and opened the door for the emergence of neural networks What neural networks are, how they are trained, and why all the wonder of modern AI boils down to a simple, repeated unit that knows how to multiply input numbers to produce an output number. The implications of large language models, like ChatGPT and Bard, on our society-nothing will be the same again AI isn't magic. If you've ever wondered how it works, what it can do, or why there's so much hype, How AI Works will teach you everything you want to know.
Artificial intelligence is a tool that requires information literacy skills for ethical and effective use. In this guide, you will find tips on:
A simple definition of Generative AI is that it "can do creative, intellectual work that previously only humans could do." (Quote from Henrik Kniberg, in the video above.)
Non-generative AI models work with existing data rather than generating new content. Think of spam email filtering - a system collects emails, analyzes them for content and sender information, learns the patterns and characteristics, and then filters some as "spam".
Generative AI, on the other hand, can write an email for you. It does this using an LLM (large language model), a type of artificial intelligence trained on massive datasets. This allows the LLMs to recognize patterns in language, predict what comes next in a sentence, and produce content. LLMs include GPT (Generative Pre-trained Transformer) models, which can create text, images, code, and much more, based on prompts entered by the user. The range of what these models can create expands by the day.
A big part of what librarians do is teach strategies for finding, evaluating, and using information effectively - this is the definition of Information Literacy.
Just as we evaluate traditional sources (books, articles, websites), we need to critically assess AI tools and their outputs. The SIFT/PICK framework already recommended for research can be applied to AI with some modifications.
Lateral Reading (SIFT): fact-checking by examining other sources and internet fact-checking tools
Vertical Reading (PICK): examining the source itself to decide whether it is the best choice for your needs.
Tips for effective AI Use:
For a more in-depth look at core information literacy skills, see our guide How to Do Library Research.
SIFT & PICK by Ellen Carey is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Last updated 4/11/23.
AGI (Artificial General Intelligence)
A hypothetical type of artificial intelligence that can understand, learn, and apply knowledge across a broad range of tasks at or above human-level capabilities of reasoning.
Alignment
Ensuring that an AI system’s goals and actions remain aligned with human values and objectives to avoid harmful outcomes.
Machine Learning (ML)
A branch of AI in which computers learn patterns from data to make predictions or decisions without being explicitly programmed.
Natural Language Processing (NLP)
An area of AI focused on enabling computers to understand, interpret, and respond to human languages, rather than individual keywords. (Think of the difference between searching "Shakespeare feminist criticism" and "What are the most-cited works critiquing Shakespeare from a feminist lens?")
Prompt
A guided, well-directed sequence of words that educates AI and leads to tailored responses, solutions or answers.
Singularity
A hypothetical point when artificial intelligence surpasses human intelligence, potentially leading to rapid, uncontrollable technological growth.
