The use of machine learning (ML) in healthcare raises numerous ethical concerns,
especially as models can amplify existing health inequities. Here, we outline ethical …

Data on social media contain a wealth of user information. Big data research of social media
data may also support standard surveillance approaches and provide decision-makers with …

Researchers and policy makers worldwide are interested in measuring the subjective well-
being of populations. When users post on social media, they leave behind digital traces that …

There is increasing interest in the potential of artificial intelligence and Big Data (eg,
generated via social media) to help understand economic outcomes. But can artificial …

Objective We explore the personality of counties as assessed through linguistic patterns on
social media. Such studies were previously limited by the cost and feasibility of large‐scale …

Targeting of location-specific aid for the US opioid epidemic is difficult due to our inability to
accurately predict changes in opioid mortality across heterogeneous communities. AI-based …

Natural language is generated by people, yet traditional language modeling views words or
documents as if generated independently. Here, we propose human language modeling …

Algorithms play a critical role in steering online attention on social media. Many have
alleged that algorithms can perpetuate bias. This study audited shadowbanning, where a …

Cultural variation exists between nations (eg, the United States vs. China), but also within
regions (eg, California vs. Texas, Los Angeles vs. San Francisco). Measuring this regional …

Opioid poisoning mortality is a substantial public health crisis in the United States, with
opioids involved in approximately 75% of the nearly 1 million drug related deaths since …