This work presents a large-scale analysis of artificial intelligence (AI) and machine learning (ML) references within news articles and scientific publications between 2011 and 2019. We implement word association measurements that automatically identify shifts in language co-occurring with AI/ML and quantify the strength of these word associations. Our results highlight the evolution of perceptions and definitions around AI/ML and detect emerging application areas, models, and systems (e.g., blockchain and cybersecurity). Recent small-scale, manual studies have explored AI/ML discourse within the general public, the policymaker community, and researcher community, but are limited in their scalability and longevity. Our methods provide new views into public perceptions and subject-area expert discussions of AI/ML and greatly exceed the explanative power of prior work.
翻译:这项工作对2011年至2019年新闻文章和科学出版物中的人工智能和机器学习参考资料进行了大规模分析;我们实施了文字联系测量,自动识别与AI/ML相关的语言变化,并量化了这些词协会的力量;我们的成果突出显示了AI/ML周围认识和定义的演变,并检测了新兴应用领域、模式和系统(如块链和网络安全);最近的小规模手工研究探索了在一般公众、决策者和研究界中的人工智能/ML讨论,但其可扩展性和寿命有限;我们的方法为公众对AI/ML的看法和主题领域的专家讨论提供了新观点,大大超出了先前工作的推论力。