Much has been written about the ‘double edged sword’ that is AI, but perhaps this is most evident in climate change, on the one side AI can process enormous volumes of data, extract insightful knowledge and improve predictive models that can revolutionize the battle against climate change. Yet, the other side of the sword is how energy-intensive the technology is and therefore the carbon emissions generated.
MIT Technology Review reported that training just one AI model can emit more than 626,00 pounds of carbon dioxide equivalent – which is nearly five times the lifetime emissions of an average American car.
Sims Witherspoon, climate action lead at Google DeepMind said, “It is absolutely true that AI is an energy-intensive technology, and until we have a grid that is run completely on clean energy, those technologies will have a carbon footprint.”
#RISK A.I.
20 & 21 March 2024 | A Global Livestream Experience
Mitigate the risks, maximise the benefits.
2 Days | 20+ Sessions | 80+ Experts
Gen AI will impact every part of an organization, sales, customer service, marketing, finance, IT, legal, HR, ESG, privacy, security and perhaps, most importantly, ethics.
AI-related regulations are being finalized by governments around the world, but governing AI will be challenging, and organisations of all sizes need to develop robust governance frameworks.
AI is certainly an opportunity but how can organisations ensure that they can deliver the benefits of AI while mitigating the risks?
Attend #RISK A.I. Global
Generative AI holds much promise for enterprises of all sizes, but many organisations are ill prepared to cope with the associated limitations and risks.
#RISK A.I. will:
- Explore global AI regulations.
- Examine AI risk exposure.
- Showcase potential AI use cases.
- Help you accelerate your AI adoption, safely.
- Demonstrate how AI can improve effectiveness, efficiency, and reliability.
- Deep-Dive into the Legal, Ethical and Technological Risks of AI.
- Discuss why meaningful AI controls are necessary.
- Illustrate how to build safe, secure, trustworthy AI systems.
- Debate IP challenges & identify solutions.
- Help you govern, map, measure and manage AI risks.