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作 者:袁健 段巍[1] Yuan Jian;Duan Wei(School of Economics,Nanjing University,Nanjing 210093)
机构地区:[1]南京大学经济学院,南京210093
出 处:《管理评论》2024年第6期3-18,共16页Management Review
基 金:国家社会科学基金重大项目(20&ZD123);国家自然科学基金青年项目(71903086);教育部人文社会科学研究规划基金项目(23YJA790019)。
摘 要:本文从数据交易的经济激励切入,通过构建一个包含数据要素与人工智能的内生增长模型,研究了企业数据在训练通用人工智能,以形成专业化人工智能方面的应用,并探讨了企业自行训练模式与专业化人工智能服务商训练模式在产生数据交易激励效果上的差异及其对经济增长的影响。研究发现,一方面,数据与人工智能的结合,强化了数据的经济增长效应;另一方面,相比企业训练模式,当由专业化人工智能服务商进行训练时,企业有更高的数据交易意愿,进而数据交易规模增加,最终推动了总产出水平增加。进一步的分析表明,专业性数据的贡献度是导致差异出现的关键。只有在专业化人工智能服务商训练模式中,企业数据交易意愿会随着专业性数据贡献度的增加而增加。本文拓展了数据经济的内生增长模型,同时为数据交易所设计激励机制提供了参考。This paper delves into the economic incentives of data trading by developing an endogenous growth model that incorporates data as a factor in combination with AI.It examines the application of corporate data in the training of generalized AI to create vertical AI.Furthermore,the study investigates the differences in data trading incentives between in-house training models and those trained models provided by specialized AI service providers,as well as their respective impacts on the economy.It is found that,on the one hand,the combination of data and AI reinforces the growth effect in the data economy.On the other hand,compared to the in-house training model,firms have a higher willingness to sell data when trained by the AI service provider,which in turn increases the scale of the data trading and ultimately drives an increase in the level of total output.Further analysis suggests that the key driver behind these differences is the contribution of specialized data.It is observed that only within the training model facilitated by specialized AI service providers,the willingness of firms to engage in data trading increases in tandem with the rising contribution of specialized data.This paper expands the endogenous growth mechanism of the data economy and provides a reference for the design of incentive mechanisms for data trading centers.
分 类 号:TP18[自动化与计算机技术—控制理论与控制工程] F272[自动化与计算机技术—控制科学与工程]
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