AI Is Dangerous, but Not for the Reasons You Think | Sasha Luccioni | TED

Recent questions

• What are the environmental impacts of large language models?

  Large language models like Bloom and GPT-3 have significant environmental costs, emitting more carbon for the same task compared to smaller models. Switching to larger language models increases energy consumption and carbon emissions, contributing to environmental concerns.

• How can AI bias affect society?

  Bias in AI models can perpetuate stereotypes and lead to wrongful accusations, impacting society negatively. Tools like Stable Bias Explorer help explore biases in image generation models, highlighting the importance of addressing and mitigating bias in AI systems to prevent harmful consequences.

• What are the concerns regarding AI's impact on society?

  AI's impact on society includes contributing to climate change, lack of consent for training data, and discrimination. These concerns raise ethical and societal implications, emphasizing the need for responsible AI development and deployment to mitigate potential harms.

• How can artists protect their work from unauthorized use in AI models?

  Spawning.ai's "Have I Been Trained?" tool enables artists to prove unauthorized use of their work in AI models, offering a way to protect intellectual property rights and prevent misuse of creative content in artificial intelligence applications.

• How can AI energy consumption and carbon emissions be estimated?

  CodeCarbon provides estimates of energy consumption and carbon emissions associated with AI training, offering insights into the environmental impact of AI technologies. By using tools like CodeCarbon, researchers and developers can assess and mitigate the carbon footprint of AI models and applications.