Second Level Effects of Large Language Models (LLMs)

Here are some potential second level effects of large language models (LLMs) like ChatGPT:

• Job disruption – As LLMs get better at generating human-like text and conversing, they could displace many jobs that involve writing, customer service, telemarketing, etc. This could lead to structural unemployment in these sectors.
• Misinformation proliferation – The ability of LLMs to generate very convincing text could allow bad actors to easily create false or misleading content at scale, making it harder to combat misinformation.
• Loss of human uniqueness – Some argue LLMs may eventually become so good at mimicking human conversation and creativity that it lessens the perceived value of uniquely human skills and abilities. This could have psychological and philosophical implications.
• Widening digital divide – Widespread use of LLMs may make it even harder for lower income individuals and developing nations to keep up, as they won’t have the same access to cutting edge AI systems. This could exacerbate digital inequality.
• Automation of high skill jobs – As LLMs advance, they may automate tasks and jobs requiring higher education and specialized training, like certain legal, medical, and financial analysis roles. This could displace many high skill workers.
• Energy usage concerns – Very large ML models require extensive computing resources to train and run, consuming huge amounts of energy. Widespread LLM adoption would greatly increase tech’s energy footprint, raising sustainability issues.

Those are some of the major potential second order effects that could emerge as LLMs become more capable and widely used. Monitoring and addressing these effects will be an important challenge.

source: A\nthropic