Kate Crawford

Simply expanding large language models is not sufficient to achieve artificial general intelligence. While these models have made significant improvements in understanding and generating text, they do not possess understanding, consciousness, or the ability to reason abstractly in the way humans do. Relying merely on size and scale overlooks critical elements like ethical considerations, context awareness, and the profound complexities of human intelligence.

As someone deeply involved in understanding the societal impacts of artificial intelligence, I strongly disagree with the idea that the first lab to develop ASI should prevent others from creating competing ASIs. Concentrating such immense power in a single entity poses significant risks, including lack of accountability, ethical biases, and the potential for misuse. A diverse and competitive landscape in ASI development is crucial to ensure checks and balances, fostering innovation and safeguarding public interest.

Releasing Spanish data into the public domain to improve Spanish LLMs raises significant concerns about privacy and data protection. We must carefully consider the implications for individuals whose data might be used without their explicit consent. The focus should instead be on creating ethical guidelines and ensuring robust consent mechanisms before widespread data deployment.