8 What’s next for AI and LLMs

 

This chapter covers

  • Exploring the ultimate vision of LLM developers
  • Formalizing best practices for responsibly using generative AI models
  • Understanding the regulatory landscape for AI systems
  • Discussing a potential framework for a global AI governance body

In an infamous article for Newsweek in 1995, astronomer Clifford Stoll wrote the following:

Today, I’m uneasy about this most trendy and oversold community. Visionaries see a future of telecommuting workers, interactive libraries and multimedia classrooms. They speak of electronic town meetings and virtual communities. Commerce and business will shift from offices and malls to networks and modems. And the freedom of digital networks will make government more democratic. Baloney. Do our computer pundits lack all common sense? The truth is no online database will replace your daily newspaper, no CD-ROM can take the place of a competent teacher and no computer network will change the way government works. [1]

For better and for worse, the internet has done much more than Stoll expected. Digital networks have made government more democratic in some ways, but concentrated the power of authoritarians in others; have connected people across the globe but have also been tied to increasing social isolation; and have reshaped the global economy.

Where are LLM developments headed?

Language: The universal interface

LLM agents unlock new possibilities

The personalization wave

Social and technical risks of LLMs

Data inputs and outputs

Data privacy

Adversarial attacks

Misuse

How society is affected

Using LLMs responsibly: Best practices

Curating datasets and standardizing documentation

Protecting data privacy

Explainability, transparency, and bias

Model training strategies for safety

Enhanced detection

Boundaries for user engagement and metrics

Humans in the loop