  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.
