Sustainable AI Lifecycle Management
Bibliographic Data
| ID | 23567288 |
|---|---|
| Authors | Ishneet Kaur Dua (0009-0002-2928-8282), Parth Patel (0000-0001-8105-0031), Parth Girish Patel (0009-0003-7800-9486) |
| Year | 2024 |
| Pages | 259-287 |
| Publication date | 2024-01-01 |
| Open Access | Yes |
| Type | CHAPTER |
| Venue | Optimizing Generative AI Workloads for Sustainability (SOURCE_BOOK) |
| Publisher | Apress (PUBLISHER • US) |
| DOI | 10.1007/979-8-8688-0917-0_9 |
| OpenAlex | W4404480408 |
| ISBN | 9798868809170 |
| Language | EN |
Sustainable AI lifecycle management is an emerging discipline that addresses the environmental, social, and economic impacts of artificial intelligence throughout its lifecycle. As AI technologies become increasingly integrated into various sectors, it is imperative to adopt practices that ensure their development, deployment, and maintenance are sustainable. This chapter explores the principles and strategies for managing AI systems in a way that minimizes their carbon footprint, promotes ethical use, and ensures long-term viability. By examining the entire lifecycle—from data collection and model training to deployment and decommissioning—this chapter aims to provide a comprehensive framework for integrating sustainability into AI practices, which fosters innovation that aligns with global sustainability goals.
Application lifecycle management · Business · Operating system · Process management · System lifecycle · Computer Science · Digital Transformation in Industry
| Highly cited | No |
|---|