What healthcare can learn from Facebook's data scandal
Facebook's recent data scandal had lawmakers grilling founder and CEO Mark Zuckerberg for more than three hours in an April 11 Senate hearing regarding the social network’s involvement with the British political data firm Cambridge Analytica.
According to an article by STAT News, the hearing was less about the data breach and more about privacy and the ethical conflicts of implementing artificial intelligence (AI) into an online platform used by more than one billion people worldwide.
The scandal also presented bioethical lessons for healthcare leaders who are creating AI models for clinical decision-making.
"The biggest bioethical challenge in building these [AI] models is how we prevent algorithms from imitating human biases in decision-making," according to the article.
Clinical information lacking context that is repeatedly fed to AI algorithms may led to incorrect or biased assumptions, resulting in flawed results and clinical decision making, according to the article. The same concept may be applied to an AI algorithm built to analyze patient risks or outcomes based on genetic testing.
"The problem behind these shocking algorithmic decisions is that they reflect human biases that are ingrained in the data used to build them; algorithms are also prone to unethical clinical decision-making," according to the article. "Just like Facebook algorithms are built to generate maximum revenue from advertisements, clinical decision-making algorithms can be built in ways that maximize profit over optimal treatment for patients by overprescribing certain drugs or unnecessary imaging studies."
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A recent graduate from Dominican University (IL) with a bachelor’s in journalism, Melissa joined TriMed’s Chicago team in 2017 covering all aspects of health imaging. She’s a fan of singing and playing guitar, elephants, a good cup of tea, and her golden retriever Cooper.