Art der Publikation: Beitrag in Sammelwerk

Exploring Generative Artificial Intelligence: A Taxonomy and Types

Autor(en):

Strobel, Gero; Banh, Leonardo; Möller, Frederik; Schoormann, Thorsten

Titel des Sammelbands:

Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS)

Ort(e):

Hawaii, USA

Veröffentlichung:

2024

Sprache:

Englisch

Schlagworte:

Generative Artificial Intelligence, Machine Learning, LLM, Taxonomy, Typology

Link zum Volltext:

https://scholarspace.manoa.hawaii.edu/items/2323c064-ba02-4fc5-826b-2ff3364bdfd9

Zitation:

Download BibTeX

Kurzfassung

Generative Artificial Intelligence (GAI) is a prevalent topic in recent research and business, seemingly taking the position of a disruptive technology that has the potential to significantly transform industries ranging from productivity (e.g., ChatGPT-4) to creativity (e.g., DALL-E). While the emerging scientific discussion on GAI covers a variety of fields and issues, such as privacy, accuracy, and application scenarios, this paper sheds light on the business side of GAI by investigating the morphologic nature of start-ups and incumbents leveraging GAI. Based on the structured analysis of 100 real-world instances, we report on a taxonomy of GAI applications and services that advances our practical understanding, strengthens the distinguishability, as well as adds clarity to the discourse of GAI potentials. We provide an initial framework and five types of GAI, namely Generator, Reimaginator, Synthesizer, Assistant, and Enabler, that are informed by the core characteristics of the technology paradigm.