The 4th blog in the #AI4BetterScience series explores the challenges and solutions of implementing generative artificial intelligence (GenAI) in science. The blog discusses the issue of trusting the output of AI models, which can sometimes be factually incorrect, leading to potential errors in scientific studies. The blog introduces the HAKIM model, which visualizes the interaction between human knowledge and AI model data. It highlights different interaction situations based on the overlap between user knowledge and model data, emphasizing the importance of user knowledge in assessing the accuracy of AI outputs. The blog concludes by suggesting ways to optimize interactions with generative AI models and invites feedback and discussion on future topics related to AI and science.
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Source link: https://medium.com/@quentin.loisel/a-human-ai-knowledge-interaction-model-for-trustworthy-generative-ai-5cf283c4a0f5?source=rss——artificial_intelligence-5
Trustworthy Generative AI: Human-AI Model for Knowledge Interaction #AItrustworthy
