Key Takeaways

• AI in healthcare enhances diagnostic accuracy and efficiency

• AL alleviates the burden on healthcare professionals

• AI makes quality diagnostics accessible in resource-limited settings

• Mitigating ethical bias concerns through proper oversight and collaboration is crucial

As we approach the fortieth anniversary of the release of James Cameron’s science fiction thriller The Terminator, starring Arnold Schwarzenegger, we are reminded of its profound impact. The film's premise, that we had created an artificial intelligence called ‘Skynet’ that became self-aware and started a war with humanity, nearly eradicating humans, still resonates today. For those who remember, it is difficult not to recall The Terminator and Skynet when we encounter dire warnings about the dangers of artificial intelligence (AI).

These fears are normal; they are a part of human nature. They are also unfounded. The Terminator series was entertaining, but it was based on fantasies stemming from a phenomenon known as ‘moral panic’.

According to Wikipedia, a moral panic is “the process of arousing social concern over an issue, usually perpetuated by moral entrepreneurs and mass media coverage and exacerbated by politicians and lawmakers”. Moral panics are not new; the best-known example for Americans is the witch hunts of the late seventeenth century, which culminated in the infamous Salem Witch Trials of 1692. Sadly, history repeats, as seen in the Satanic Panics of the 1980s and 90s.

In the modern era, moral panics are generally directed at technology, specifically artificial intelligence. In March 2024, the US State Department generated a report warning that AI systems could ‘pose an extinction-level threat to the human species’. Forbes magazine warned that AI would someday eliminate virtually all white-collar jobs. The psychological underpinning of this version of moral panic and the mainstream news articles it generated is an irrational (though understandable) fear of the unknown. These fears are built on the misconception that, at best, technology will render humans irrelevant and, at worst, expendable.

The truth is not nearly so scary. In medicine, AI plays a pivotal role in predictive diagnostics. Machine learning models can predict the likelihood of diseases such as diabetes, cardiovascular conditions, and even certain cancers based on historical and real-time health data. These predictive capabilities allow for early interventions, potentially preventing the progression of diseases and reducing healthcare costs.