全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

大数据和人工智能如何改变中国的数字鸿沟——以ChatGPT为例
How Big Data and AI Are Changing China’s Digital Divide—Taking ChatGPT as an Example

DOI: 10.12677/mm.2024.149263, PP. 2251-2259

Keywords: 大数据,人工智能,数字鸿沟,政策建议
Big Data
, Artificial Intelligence, Digital Divide, Policy Recommendations

Full-Text   Cite this paper   Add to My Lib

Abstract:

文章探讨了大数据和人工智能对中国数字鸿沟的影响,并提出相关案例研究和政策建议。研究发现,这些技术在信息获取、数字技能、数字内容和服务、数据保护和隐私等方面具有双重影响。一方面,它们提供了便捷的智能服务,降低了数字技能和知识的门槛,促进了公众参与和数字素养的普及。另一方面,它们也加剧了信息真实性和准确性的问题,扩大了数字技能和知识的不平等,并带来了新的数据保护和隐私挑战。基于现有研究,文章提出一系列政策建议,以期更好地消除数字鸿沟带来的消极影响。随着大数据和人工智能技术的进步,它们将在数字化社会中发挥重要作用。我们应密切关注其对数字鸿沟的影响,采取措施促进数字包容性和公平性,确保数字化发展惠及所有人。
This paper explores the impact of big data and AI on China’s digital divide, and proposes relevant case studies and policy recommendations. The study found that these technologies have a dual impact on information access, digital skills, digital content and services, data protection, and privacy. On the one hand, they provide convenient intelligent services, lower the threshold of digital skills and knowledge, and promote public participation and the popularization of digital literacy. On the other hand, they also exacerbate the problems of information authenticity and accuracy, widen the inequality of digital skills and knowledge, and bring new challenges to data protection and privacy. Based on existing research, this paper proposes a series of policy recommendations to better eliminate the negative impacts of the digital divide. With the advancement of big data and AI technology, they will play an important role in the digital society. We should pay close attention to their impact on the digital divide, take measures to promote digital inclusiveness and fairness, and ensure that digital development benefits all people.

References

[1]  段兴利. 社会学视野中的数字鸿沟[J]. 科学∙经济∙社会, 2011, 29(3): 64-67.
[2]  曹静, 周亚林. 人工智能对经济的影响研究进展[J]. 经济学动态, 2018(1): 103-115.
[3]  Laney, D. (2001) 3D Data Management: Controlling Data Volume, Velocity and Variety. META Group Research Note, 6.
[4]  LeCun, Y., Bengio, Y. and Hinton, G. (2015) Deep Learning. Nature, 521, 436-444.
https://doi.org/10.1038/nature14539
[5]  王元卓, 靳小龙, 程学旗. 网络大数据: 现状与展望[J]. 计算机学报, 2013, 36(6): 1125-1138.
[6]  蔡永明, 马夏夏. 生成式人工智能(AIGC)赋能工业企业高质量发展的机制与建设策略[J/OL].
http://kns.cnki.net/kcms/detail/37.1377.C.20240702.1440.002.html, 2024-06-14.
[7]  薛晓源, 刘兴华. 数字全球化、数字风险与全球数字治理[J]. 东北亚论坛, 2022, 31(3): 3-18.
[8]  Brynjolfsson, E. and McAfee, A. (2014) The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. WW Norton & Company.
[9]  Donald, R.H. (2020) The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Journal of Information Technology Case and Application Research, 22, 288-292.
https://doi.org/10.1080/15228053.2020.1860404
[10]  吕丹阳, 郎元柯, 范柏乃, 等. 生成式人工智能在公共服务中应用的机遇与挑战[J]. 电子科技大学学报(社会科学版), 2024, 26(3): 35-45.
[11]  吴鼎铭. 互联网时代的“数字劳工”研究[D]: [博士学位论文]. 武汉: 武汉大学, 2015.
[12]  刘丹鹤, 孙嘉悦. 人工智能规制政策制定的风险与治理[J]. 人文杂志, 2023(2): 121-128.
[13]  蒲清平, 向往. 生成式人工智能——ChatGPT的变革影响、风险挑战及应对策略[J]. 重庆大学学报(社会科学版), 2023, 29(3): 102-114.
[14]  肖峰. 生成式人工智能与数字劳动的相互关联——以ChatGPT为例[J]. 学术界, 2023(4): 52-60.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133