New From Lorcan Dempsey: “Generative AI and Libraries: 7 Contexts”

From Lorcan Dempsey (LorcanDempsey.net):

This is the third of four posts on Generative AI:

1. Generative AI and large language models: background and contexts
2. Generative AI, scholarly and cultural language models, and the return of content
3. Generative AI and libraries: 7 contexts
4. Generative AI and library services: some directions

It is now a year since the momentous appearance of ChatGPT. So much has happened in that time. Whether one measures by new product and feature announcements, business churn (investment, startups), or policy, safety and ethical debate. Usage is increasingly integrated into daily applications. Much of this has become routine, some of it is tedious, and much still has the ability to surprise. Capacities continue to expand. See the recent inclusion of voice and image capabilities into ChatGPT for example, or the introduction of the confusingly named GPTs, which allow you to create and share custom versions of ChatGPT based on your own data (more below and NYT coverage here).

The Seven Contexts Discussed in the Post:

1. AI is both constructive and problematic
2. AI is extractive and generative
3. AI and LLMs are not search engines or databases
4. AI is appearing differently in different products and services
5. AI is weird
6. AI is cumulative: the infrastructure is getting thicker
7. AI is complicated: policy and governance

Direct to Full Text (about 7500 words)

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