KDD全体小组讨论会:数据科学和人工智能的社会影响KDD Plenary Panel: Societal Impact of Data Science and Artificial Intelligence |
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课程网址: | http://videolectures.net/kdd2018_panel_societal_impact_of_data_sc... |
主讲教师: | Jennifer Neville |
开课单位: | 普渡大学 |
开课时间: | 2018-11-23 |
课程语种: | 英语 |
中文简介: | 对KDD和其他数据科学/机器学习/人工智能会议的兴趣激增,只是这些技术不再局限于学术界和科技公司的众多迹象之一。随着我们的日常生活无缝集成了越来越多的数据驱动应用程序,人们的兴奋情绪因担心这些技术可能会破坏他们的生存而减弱。经过近30年的设计和开发,KDD社区现在应该研究和辩论机器学习和人工智能对更广阔世界的影响。除了炒作,我们对危险的立场是什么?我们的社区可以发挥什么作用来缓解人们对人工智能接管工作或接管工作的担忧?如何公平地分配从数据中获得的价值?对不公平的担忧是有充分依据的,还是很大程度上是认知问题?可以做些什么来使数据饥饿和数据共享问题达到均衡水平?我们如何让人们做好大规模与智能系统交互的准备?我们能否释放KDD社区对健康、环境可持续性和公共福利等对社会公益至关重要的部门的长期、更有影响力的项目的惊人反应。 |
课程简介: | The explosion of interest in KDD and other Data Science/Machine Learning/AI conferences is just one of the many signs that these technologies are no longer confined to the realms of academia and a handfull of tech companies. As our daily lives seamlessly integrate more and more data-driven applications, people’s excitement is tempered by worry about the technologies’ potential to disrupt their existence. Having worked for almost 30 years to design and develop these technologies, the KDD community now should examine and debate the impact of Machine Learning & AI on the broader world. Beyond the hype, Where do we stand with respect the the dangers? What role can our community play to alleviate concerns around AI taking jobs, or taking over? How can the value derived from data be distributed fairly? Are concerns about inequity well-founded or rather largely problems of perception? What can be done to bring data hunger and data sharing concerns to a level of equilibrium? How do we prepare people to interact with intelligent systems at scale? Can we unleash the incredible responsiveness of the KDD community toward longer-term more impactful projects across sectors that are essential for social good, such as Health, Environmental Sustainability, and Public Welfare. |
关 键 词: | KDD全体小组讨论会; 数据科学和人工智能; 数据饥饿和数据共享; 人工智能的社会影响 |
课程来源: | 视频讲座网 |
数据采集: | 2023-03-16:cyh |
最后编审: | 2023-05-19:liyy |
阅读次数: | 30 |