Ethical obligations to consider social and environmental harms in data-driven research: a call for action

COEX 

Health research that uses data-driven and artificial intelligence (AI) methods is associated with a range of environmental, social, and health harms. These include harms associated with carbon dioxide emissions related with the energy required to generate and process data, increasing resource use associated with the ever need for minerals to manufacture technological components, and electronic-waste (e-waste) that comes from the amount of digital devices constantly disposed. They also include harms associated with issues of bias, discrimination, and inequities. I describe these harms and argue that researchers have a moral obligation as part of any research ethics best practice to address them as a matter of justice.