AI: Making or Breaking the Healthcare Industry
Artificial intelligence in healthcare has numerous applications; this week’s focus was on client security, job market impact, and gene editing. Though it may seem extremely convenient to have a phone app that records, stores, and analyzes all your health data, the risk comes with who is granted access to this data. Though storage of healthcare data allows for better treatment programs and monitoring of a patient’s lifestyle, this is private information that could be deadly if it reaches the wrong hands. Efficiency increases, but at what cost? AI in healthcare also means a loss of some jobs. Menial, repetitive tasks will be overtaken by AI, but this doesn’t render humans useless in healthcare. AI in healthcare is seeking to complement humans, not replace us. Lastly, the ethics of gene editing was addressed in light of two women winning the Nobel Chemistry Prize for award-winning work on CRISPR. Though gene editing may seem far-fetched, a biophysicist, He Jiankui, used CRISPR technology and in vitro fertilization to create babies with innate immunity to the HIV virus. At first glance, this seems like an extraordinary scientific advancement. But what if humans start to “fashion” their own babies, by selecting for ideal qualities in a child? The world of AI in healthcare is large, but this week we focused on the biggest issues in this field and the ethics associated with it.
After the lecture, the team took on a different approach to the regular discussions. Instead of beginning with a group Q&A type of discussion, four volunteers were selected to go head to head in two debates with prompts probing at the ethics of incorporating AI in healthcare. The first prompt asked whether hospitals ought to have the right to store patient data, and the ensuing arguments and rebuttals pulled from a wealth of knowledge including the risk of hacking, the benefits of improved treatment, and the synergistic effects of AI with treatment. The second prompt questioned the creators of health-tech AI, questioning whether the blame of faulty AI systems should be placed on the AI creators or the AI system itself. The following clash pitted a healthy combination of specific examples such as the racist AI system implemented by multiple hospitals and more theoretical arguments regarding the necessity of responsibility falling on an actor that can change the mistake. Ultimately, these discussions, though only directly involving four individuals, stimulated further conversation on the respective topics and encouraged those who were listening to form and/or change their opinions.
AI will continue to be integrated into the healthcare system, whether it be something as simple as sifting through data and selecting anomalies or something as difficult as assisting surgeons precisely navigate through a hemispherectomy. From a business standpoint, the increased utilization of AI in healthcare only lends to more investment opportunities. As hospitals are able to lower costs, the margins (and thus the bottom line) of many companies are bound to improve, elevating the stock prices of many formerly struggling companies. From a technological standpoint, the importance of AI in healthcare may lend to a wealth of new job offerings focused specifically on maintenance or the development of code related to chronic illnesses. There may come a day when the human genome becomes little more than a coding language that people may learn . . .
Though the ethical considerations of rewiring our genetics or allowing AI to build upon a biased environment may be uncertain with little hope of resolving any time soon, it is integral that as citizens and as humans that we strive to make the best decisions (whether by voting, protesting, working, etc.) to move mankind forward.