Paradigm Change and Countermeasures of Knowledge Production and Communication in Generative AI
Currently,generative AI has brought profound changes to the paradigm of knowledge production and communication in fields such as scientific research,education,finance,healthcare and manufacturing,and has sparked extensive discussions in academia and industry.These changes are reflected in the ontology transformation based on large-scale pre-training models,the innovation of knowledge production paradigm under the new human-ma-chine relationship,and the industrial transformation driven by the new paradigm of AI content creation and interaction.From the perspective of epistemol-ogy,the extensive integration of generative AI and human in knowledge production challenges the traditional epistemology of human subject.From the per-spective of practice,knowledge production practices in human-machine collaboration face the challenges such as lack of transparency,interpretability and data bias.From a value perspective,generative AI has limitations in judgment of value and fact,intentionality and autonomy,judgment of emotions and morality,and understanding and inclusiveness of multiculturalism.To cope with the uncertainties in this new form of knowledge production practice,promote knowledge justice,and protect intellectual property rights,it is necessary to use new theories and methods to understand and evaluate the roles and responsibilities of generative AI and human in knowledge production,optimize human-machine division of labor and collaboration,and realize hu-man-machine co-evolution in a responsible way.
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