A Large-Scale, Automated Study of Language Surrounding Artificial Intelligence

TL;DR

This large-scale study analyzes how language surrounding AI and ML has evolved in news and scientific literature from 2011 to 2019, revealing shifts in perception, emerging topics, and the growth of discourse over time.

Contribution

It introduces automated methods for analyzing large corpora to track language changes and perceptions around AI/ML, surpassing prior manual and small-scale studies.

Findings

Identified evolving perceptions and definitions of AI/ML.

Detected emerging application areas like blockchain and cybersecurity.

Quantified shifts in language associations over time.

Abstract

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.