Joseph Aylett-Bullock
Papers
1
Total Citations
13
H-Index
1
About
Joseph Aylett-Bullock is a researcher at the intersection of artificial intelligence, natural language processing, and international policy. His work critically examines the societal implications of AI-generated content, with a particular focus on the risks posed by automated text generation in high-stakes domains. His most cited paper, "Automated Speech Generation from UN General Assembly Statements: Mapping Risks in AI Generated Texts" (2019, 13 citations), pioneers the analysis of how generative models could be misused to produce synthetic political speeches, highlighting vulnerabilities in diplomatic and governance contexts. By applying text generation techniques to UN statements, Aylett-Bullock demonstrates the dual-use nature of AI—where tools designed for marketing, chatbots, or creative writing can also amplify disinformation and erode trust in public discourse. His work bridges technical AI research with policy-oriented risk assessment, offering a framework for understanding the ethical and security challenges of widespread access to generative models. With a growing citation footprint, Aylett-Bullock is establishing himself as a vital voice in responsible AI development, urging researchers and policymakers to anticipate the societal harms of unchecked text synthesis before they materialize at scale.
Research Focus
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Top Papers
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