The “Positive Disruption: Transformation Revolution” has accelerated
The "Positive Disruption: AI Revolution" has accelerated
This lighthouse provides an overview of the environmental impact of generative AI and the need for technical and behavioral changes to make it greener. The post includes a collection of 10 relevant facts from the golden knowledge article “How to Make Generative AI Greener” by Ajay Kumar and Tom Davenport on Harvard Business Review. The post highlights the hidden environmental costs and impact of generative AI models and the need for more efficient hardware, algorithms, and practices to reduce their environmental impact.
- While observers have marveled at the abilities of new generative AI tools such as ChatGPT, BERT, LaMDA, GPT-3, DALL-E-2, MidJourney, and Stable Diffusion, the hidden environmental costs and impact of these models are often overlooked.
- There are many considerations involved with the use of generative AI models by organizations and individuals: ethical, legal, and even philosophical and psychological.
- Ecological concerns, however, are worthy of being added to the mix.
- We can debate the long-term future implications of these technologies for humanity, but such considerations will be moot if we don’t have a habitable planet to debate them on.
- The data center industry, which refers to a physical facility designed to store and manage information and communications technology systems, is responsible for 2–3% of global greenhouse gas (GHG) emissions.
- Almost all of the best-known generative AI models are generated by “hyperscale” (very large) cloud providers with thousands of servers that produce major carbon footprints; in particular, these models run on graphics processing unit (GPU) chips.
- There is a movement to make AI modelling, deployment, and usage more environmentally sustainable. Its goal is to replace power-hungry approaches with more suitable and environmentally-conscious replacements.
- Change is needed from both vendors and users to make AI algorithms green so that their utility can be widely deployed without harm to the environment.
- Generative models in particular, given their high energy consumption, need to become greener before they become more pervasive.
- We know of several different ways in which AI and generative AI can move in this direction.
Ajay Kumar and Tom Davenport, How to Make Generative AI Greener, Harvard Business Review, HBR, July 20, 2023.
ABOUT THE AUTHORS
Ajay Kumar is an Associate Professor of Information Systems & Business Analytics at EMLYON Business School, France. Ajay has held postdoctoral fellow positions at the Massachusetts Institute of Technology, and Harvard University. Presently, he is affiliated as a visiting fellow with the Said Business School at the University of Oxford.
Thomas H. Davenport is the President’s Distinguished Professor of IT and Management at Babson College, a research fellow at the MIT Center for Digital Business, co-founder of the International Institute for Analytics, and a Senior Advisor to Deloitte Analytics. He is author of the new book Big Data at Work and the best-selling Competing on Analytics.
g-f(2)1218: The Juice of Golden Knowledge
Some relevant characteristics of this "genioux Fact"
- NUGGET KNOWLEDGE
- Category 2: The Big Picture of the Digital Age
- The Lighthouse of the Big Picture of the Digital Age
- The "Positive Disruption: AI Revolution" has accelerated
- The internal title
- g-f(2)1218 The Lighthouse of the Digital Age: How to Make Generative AI Greener
- [genioux fact deduced or extracted from HBR]
- This is a “genioux fact fast solution.”
- Tag "GkPath" highway
- GKPath is the highway where there is no speed limit to grow.
- GkPath is paved with blocks of GK.
- "genioux facts", the online program on "MASTERING THE BIG PICTURE OF THE DIGITAL AGE”, builds The Golden Knowledge Path (GKPath) digital freeway to accelerate everyone's success in the digital age.
- Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).
- Type of validity of the "genioux fact".
- Inherited from sources + Supported by the knowledge of one or more experts.
- Authors of the genioux fact