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AI and Libraries - Yasser Ayyash.pptx
- 1. AI and Libraries Presented by: Yasser Ayyash to Dr. Farah Sbayte Digital Services in Data Centers and Archives Master2- 22/23
- 3. Introducing AI • Let us start with a fact: There is really no intelligence in “Artificial Intelligence”. • AI resembles much more a “mindless robot” and much less a “thinking machine”. • In a whitepaper published titled ‘Artificial Intelligence in the Library: Advantages, Challenges and Tradition’ Machine learning is defined to be “AI technologies and applications are all based on machine learning algorithms.” • But After decades of hype, AI (artificial intelligence) has arrived.
- 4. Definition • AI is the theory and development of computer systems that can perform tasks normally requiring human intelligence, such as: • Visual perception • Speech recognition • Decision-making • Translation • Interpretation. - Oxford Dictionary
- 5. • AI has rapidly developed thanks to: • Better algorithm design • Bigger networked computing power • and Improved ability to capture and store massive amounts of data.
- 7. • Current forms of AI are considered to be narrow or weak, designed to perform one repetitive task such as: • Speech recognition on mobile devices • Self-driving cars • Many researchers are seeking to develop what is known as general or strong AI, with behaviors that are as flexible and skillful as humans (such as memory, autonomous learning and responding to emotions).
- 8. Are libraries ready to embrace AI technologies? • Where do we start? With the rapid integration of computer, network technology, communication technology, The emergence of the digital library shouldn’t be separable. Digital library is not only a new development in science, but also a new branch of electronics. People are moving around digital information. They no longer want to receive information through text (physically), but transmit data through the Internet. Due to the huge amount of Internet data, how to obtain more, better, more accurate, timely, and useful information from it has become a problem that people care about.
- 9. You can ask Google, Alexa, Cortana, Watson, or Siri—but will you be able to ask your local library? • We value libraries because they keep us • Informed • Connected • We read to • Enrich our lives • Inform our decisions But what happens when that decision-making process is fundamentally changed?
- 10. Libraries may yet have a critical role to play in the AI revolution • Today’s mainstream AIs are dominated by proprietary software. Apple, Microsoft, Google, Facebook, and other major tech players all have their own AIs. • These companies have invested heavily in research and development, and they have guarded their intellectual property closely. • The algorithms that give rise to machine learning are mostly kept secret, and the code that results from machine learning is often so complex that even the human developers don’t understand exactly how their code works. • So even if you wanted to know what AI was thinking, you would be out of luck. But if AI is a black box for which we have no key, Libraries can play an important role in providing open source AI solutions that allow for more transparency and more control.
- 11. • Libraries can help lower the barriers to AI by: • Producing, • Providing, • and promoting open source AI projects. • By supporting open source AI, libraries can ensure that researchers can access powerful systems that are free from corporate bias. Because Alexa is happy to answer your questions—and to sell you a subscription to Amazon Prime.
- 12. • Information literacy is about: • knowing when there is a need for information • being able to identify, locate, evaluate, and effectively use that information • I think it is safe to say that AI is capable of superior information literacy. • What’s worse, recent events (Political influence, claims of fake news, etc.) have illustrated just how bad humans are at assessing the accuracy of the things we read. • Dependence on AI information literacy will lead to a weakening of our own. • But if it is important to critically evaluate information sources, it will be doubly important (but more difficult) to evaluate our AI information providers and decision makers. • As we have seen in recent years, minor changes to a dataset or algorithm can greatly alter our digital experiences. Google has been accused of favoring its own products and services over those of its competitors.
- 13. Why Libraries? We are using AI every day. • For example, when we search Google, we are feeding data to RankBrain—an AI system that helps sort through search results. With machine learning, a computer teaches itself to do something rather than following detailed programming. Libraries promote data privacy. • They don’t give out library records • They don’t track web users, etc. But they will need a new set of sophisticated tools if they’re going to truly be champions of privacy rights in the coming decades. Libraries can help secure privacy by providing anonymous ways of interacting with AI systems.
- 14. • Books don’t talk—but your AI assistant listens and talks. • If you asked your AI home assistant how to murder someone or if you asked it to read a post by an anti-government activist, you could potentially be producing a trail of evidence that could be used against you. Maybe you were writing an episode of CSI. Whatever your reason for seeking that information, your queries were being recorded and saved. • As our primary means of gaining information moves from reading printed words to interacting with machine intelligences, we must ensure that the same safeguards we use to protect books are extended to AI.
- 15. Concluding • From intellectual freedom to information literacy and more, libraries provide a set of principles that have helped guide intellectual growth for the past century. • But libraries are not the center of the information world anymore • What steps can we take to ensure that the values of librarianship are incorporated into AI systems? • Advocacy should be directed not at maintaining traditional librarianship, but moving towards the emerging information systems that may come to replace us.
- 16. When I say, in my title, “Everything is data, except when it isn’t” I’m saying that try as we might, we cannot reduce our cultural experience, our scientific discoveries, or our lived experience to a set of data points. But I am also saying —to libraries in particular— that, "Except when it isn’t" — when we keep in mind that we cannot capture everything as data — it is nonetheless critical that we embrace the fact that just about everything in our holdings can be made computational and doing that work will benefit libraries while also advancing the creation of new knowledge. When we convert our library collections to machine- readable data the result will be something very different than the original and many decisions have to be accounted for along the way.
- 17. References • https://doaj.org/article/d04d26d88086463393c6fe5ed8687a9d • https://journals.ala.org/index.php/ltr/issue/view/709 • https://library.stanford.edu/blogs/stanford-libraries- blog/2021/05/everything-data-except-when-it-isnt • https://www.ijournalse.org/index.php/ESJ/article/view/650 • https://www.hindawi.com/journals/js/2022/9953787/ • https://www.undp.org/blog/lets-talk-about-artificial-intelligence • https://www.infotoday.com/cilmag/jan18/Johnson--Libraries-in-the- Age-of-Artificial-Intelligence.shtml
- 18. Thank you