Writing - Research
Using AI systems to gain a personal advantage over others such as through cheating, fraud, scams, blackmail or targeted manipulation of beliefs or behavior. Examples include AI-facilitated plagiarism for research or education, impersonating a trusted or fake individual for illegitimate financial benefit, or creating humiliating or sexual imagery.
Partly overlapping with the discussion on impacts of generative AI on educational institutions, this topic cluster concerns mostly negative effects of LLMs on writing skills and research manuscript composition. The former pertains to the potential homogenization of writing styles, the erosion of semantic capital, or the stifling of individual expression. The latter is focused on the idea of prohibiting generative models for being used to compose scientific papers, figures, or from being a co-author. Sources express concern about risks for academic integrity, as well as the prospect of polluting the scientific literature by a flood of LLM-generated low-quality manuscripts. As a consequence, there are frequent calls for the development of detectors capable of identifying synthetic texts.(p. 9)
Other risks from Hagendorff (2024) (16)
Fairness - Bias
1.1 Unfair discrimination and misrepresentationSafety
7.1 AI pursuing its own goals in conflict with human goals or valuesHarmful Content - Toxicity
1.2 Exposure to toxic contentHallucinations
3.1 False or misleading informationPrivacy
2.1 Compromise of privacy by leaking or correctly inferring sensitive informationInteraction risks
5.1 Overreliance and unsafe use