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In this paper, we expand on our previous research of the potential for abuseof generative language models by assessing GPT-3. Experimenting with promptsrepresentative of different types of extremist narrative, structures of socialinteraction, and radical ideologies, we find that GPT-3 demonstratessignificant improvement over its predecessor, GPT-2, in generating extremisttexts. We also show GPT-3's strength in generating text that accuratelyemulates interactive, informational, and influential content that could beutilized for radicalizing individuals into violent far-right extremistideologies and behaviors. While OpenAI's preventative measures are strong, thepossibility of unregulated copycat technology represents significant risk forlarge-scale online radicalization and recruitment; thus, in the absence ofsafeguards, successful and efficient weaponization that requires littleexperimentation is likely. AI stakeholders, the policymaking community, andgovernments should begin investing as soon as possible in building socialnorms, public policy, and educational initiatives to preempt an influx ofmachine-generated disinformation and propaganda. Mitigation will requireeffective policy and partnerships across industry, government, and civilsociety.

The Radicalization Risks of GPT-3 and Advanced Neural Language Models