Generative AI: (1) A term now used to refer to a heterogeneous network of technologies—including machine learning, natural language processing, expert systems, deep learning, computer vision, and robotics—which have in common the automation of functions of the human brain. (Dillon et al. 2024). (2) Generative AI can be thought of as a machine-learning model that is trained to create new data, rather than making a prediction about a specific dataset. A generative AI system is one that learns to generate more objects that look like the data it was trained on. (MIT News, “Explained: Generative AI,” November 9, 2023)

Neural networks:

Natural language processing (NLP):

Turing test:

Pattern recognition:

Enshittification:

Hallucination:

Automation:

Large language model (LLM):

Human-machine interaction (HMI):

Metadata:

Soft robotics:

Algorithmic governance:

Instrumental convergence:

Paperclip maximiser apocalypse: Suppose we have an AI whose only goal is to make as many paperclips as possible. The AI will realize quickly that it would be much better if there were no humans because humans might decide to switch it off. Because if humans do so, there would be fewer paperclips. Also, human bodies contain a lot of atoms that could be made into paperclips. The future that the AI would be trying to gear towards would be one in which there were a lot of paperclips but no humans. (Nick Bostrom)