Bias and the prospect of societal harm increasingly plague artificial-intelligence research — but it’s not clear who should be on the lookout for these problems.
Diversity and inclusion took centre stage at one of the world’s major artificial-intelligence (AI) conferences in 2018. But once a meeting with a controversial reputation, last month’s Neural Information Processing Systems (NeurIPS) conference in Vancouver, Canada, saw attention shift to another big issue in the field: ethics.
If your institution is involved in AI, algorithm or big data research, who advises on its ethical dimensions? Given the potential for societal harm, perhaps it’s time for serious consideration of the need for research ethics review for such work.
Ethicists have long debated the impacts of AI and sought ways to use the technology for good, such as in health care. But researchers are now realizing that they need to embed ethics into the formulation of their research and understand the potential harms of algorithmic injustice, says Meredith Whittaker, an AI researcher at New York University and founder of the AI Now Institute, which seeks to understand the social implications of the technology. At the latest NeurIPS, researchers couldn’t “write, talk or think” about these systems without considering possible social harms, she says. “The question is, will the change in the conversation result in the structural change we need to actually ensure these systems don’t cause harm?”