  With various AI tools such as ChatGPT becoming increasingly popular, we are
entering a true AI era. We can foresee that exceptional AI tools will soon reap
considerable profits. A crucial question arise: should AI tools share revenue
with their training data providers in additional to traditional stakeholders
and shareholders? The answer is Yes. Large AI tools, such as large language
models, always require more and better quality data to continuously improve,
but current copyright laws limit their access to various types of data. Sharing
revenue between AI tools and their data providers could transform the current
hostile zero-sum game relationship between AI tools and a majority of
copyrighted data owners into a collaborative and mutually beneficial one, which
is necessary to facilitate the development of a virtuous cycle among AI tools,
their users and data providers that drives forward AI technology and builds a
healthy AI ecosystem. However, current revenue-sharing business models do not
work for AI tools in the forthcoming AI era, since the most widely used metrics
for website-based traffic and action, such as clicks, will be replaced by new
metrics such as prompts and cost per prompt for generative AI tools. A
completely new revenue-sharing business model, which must be almost independent
of AI tools and be easily explained to data providers, needs to establish a
prompt-based scoring system to measure data engagement of each data provider.
This paper systematically discusses how to build such a scoring system for all
data providers for AI tools based on classification and content similarity
models, and outlines the requirements for AI tools or third parties to build
it. Sharing revenue with data providers using such a scoring system would
encourage more data owners to participate in the revenue-sharing program. This
will be a utilitarian AI era where all parties benefit.
