Regulating Chatbot Output via Inter-Informational Competition
Jiawei Zhang
The advent of ChatGPT has sparked over a year of regulatory frenzy. However,
few existing studies have rigorously questioned the assumption that, if left
unregulated, AI chatbot's output would inflict tangible, severe real harm on
human affairs. Most researchers have overlooked the critical possibility that
the information market itself can effectively mitigate these risks and, as a
result, they tend to use regulatory tools to address the issue directly. This
Article develops a yardstick for reevaluating both AI-related content risks and
corresponding regulatory proposals by focusing on inter-informational
competition among various outlets. The decades-long history of regulating
information and communications technologies indicates that regulators tend to
err too much on the side of caution and to put forward excessive regulatory
measures when encountering the uncertainties brought about by new technologies.
In fact, a trove of empirical evidence has demonstrated that market competition
among information outlets can effectively mitigate most risks and that
overreliance on regulation is not only unnecessary but detrimental, as well.
This Article argues that sufficient competition among chatbots and other
information outlets in the information marketplace can sufficiently mitigate
and even resolve most content risks posed by generative AI technologies. This
renders certain loudly advocated regulatory strategies, like mandatory
prohibitions, licensure, curation of datasets, and notice-and-response regimes,
truly unnecessary and even toxic to desirable competition and innovation
throughout the AI industry. Ultimately, the ideas that I advance in this
Article should pour some much-needed cold water on the regulatory frenzy over
generative AI and steer the issue back to a rational track.