2023-08-16 –, HS 120
Since its release, ChatGPT is now widely adopted as "the" text generation tool used across all industries and businesses. This also includes the domain of scientific research where we do observe more and more scientific papers partially or even fully generated by AI. The same also applies to the peer-reviews reports created while reviewing a paper.
What are the guidelines in the scientific research world? What is now the meaning of the written word and how do we build a model that can identify whether a text is AI-generated? What are the potential solutions to solve this important issue?
Within this talk, we are discussing on how to detect AI-generated text and how to create a scalable architecture integrating this tool.
ChatGPT and its Open Source alternatives are nowadays being integrated in different text writing workflows. The scientific research, being also heavenly impacted by those new technologies, creates a lot of debate about whether or not these technologies should be used for scientific papers writing. The COPE guidelines are very clear about it, however, there is currently no effective tools available that can efficiently identify whether a text is AI-generated.
There are already some promising principles on how to solve this problem that can be categorized as: watermarking, likelihood detection, and classification. How can these algorithms be used within the scientific writing to detect AI-generated text and how to integrate them into the AI-infrastructure using Python and other modern tools (such as vector search engine for example)?
GPT generated text detection: problems and solution in the scientific publishing
Category [Machine and Deep Learning]:Other
Expected audience expertise: Domain:some
Expected audience expertise: Python:some
PhD in Computer Science, IT executive, certified project and product manager oriented to complex assignments with 12 years` working experience in the academic publishing business, focusing on distinct R&D, technology innovation, system administration and information security projects covering ML/AI, Web development and Linux infrastructure.
AI Tech Leader at MDPI, Founder and organiser of PythonBiellaGroup, Computer scientist and Nerd by Night.