Prompt engineering
Challenges in understanding or explaining the decision-making processes of AI systems, which can lead to mistrust, difficulty in enforcing compliance standards or holding relevant actors accountable for harms, and the inability to identify and correct errors.
"With the wide application of generative AI, the ability to interact with AI efficiently and effectively has become one of the most important media literacies. Hence, it is imperative for generative AI users to learn and apply the principles of prompt engineering, which refers to a systematic process of carefully designing prompts or inputs to generative AI models to elicit valuable outputs. Due to the ambiguity of human languages, the interaction between humans and machines through prompts may lead to errors or misunderstandings. Hence, the quality of prompts is important. Another challenge is to debug the prompts and improve the ability to communicate with generative AI (V. Liu & Chilton, 2022)."(p. 289)
Part of Technology concerns
Other risks from Nah et al. (2023) (17)
Technology concerns
7.3 Lack of capability or robustnessTechnology concerns > Hallucination
3.1 False or misleading informationTechnology concerns > Quality of training data
7.3 Lack of capability or robustnessTechnology concerns > Explainability
7.4 Lack of transparency or interpretabilityTechnology concerns > Authenticity
6.3 Economic and cultural devaluation of human effortRegulations and policy challenges
6.5 Governance failure