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Interaction between AI and healthcare professionals

How does the healthcare professional interact with artificial intelligence? Explanation of deskilling and over -reliance.
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Recently a hospital decided to include artificial intelligence in its clinical practice. An application was bought that helps nurses to determine optimal dressing of surgical wounds. Nurse Tim has to change the dressing of Kate’s leg. After removing the initial dressing, the nurse decides to use the AI-based application to learn how to dress the surgical wound next. The application indicates that the wound shows signs of infection and that the nurse should consider an antiseptic dressing. The nurse decides to fill in extra information about the patients. Based on this additional information, the application recalculates the patient’s risk for septic symptoms. Oh, look, the patient is at high risk and the device informs the nurse to consider administering additional antibiotics.
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The nurse applies a new antiseptic dressing to the leg. He also decides to call a physician and asks him whether he should administer antibiotics. The physician agrees, and a patient receives the proper medication. Everybody is happy. The AI device made an accurate prediction. And the patient should be discharged soon. However, the situation also could have gone completely different. Let’s go back a moment to consider an alternative situation. What if the device suddenly started to malfunction? Nurse Tim forgot how to examine the wound himself and hasn’t had any training on this in a long time. As he was told, he could always rely on the software to tell him what to do.
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This is called deskilling, a natural consequence if the automated tool has performed a task for a long time. This can become a risk if the tool is not available for whatever reason. We could also have a look at yet another situation. What if the iPad had made a mistake and provided the wrong prediction? If the nurse just accepted this prediction without thinking critically, this could have gone terribly wrong for the patient. This is called over-reliance, which occurs if the tool has always worked perfectly. This could result in an incorrect diagnosis and, therefore, treatment. These examples show that bodies killing and overreliance can potentially lead to dangerous situations and thus have to be considered in the implementation of AI in healthcare.
Although healthcare professionals can make good use of AI tools, there are some risks to the use of new automated tools in general that also apply to these AI tools.

One of these risks is deskilling. By getting used to having an automated tool to perform a certain task for a long time, people tend to lose the skills they don’t use anymore. Eventually, new professionals do not even get taught that skill anymore, since it is deemed unnecessary. Although this is quite a natural thing to happen, it can also become a risk when the automated tools are not available anymore for whatever reason.

Another challenge is the risk of over-reliance. This also happens when a healthcare professional is using the same tool for a long time. If the tool has always worked perfectly and provided the right decisions, the healthcare professional could start relying on it blindly, without thinking critically about the results that are shown.

The examples in the video show that both deskilling and over-reliance can potentially lead to dangerous situations, and thus have to be considered in the implementation of AI in healthcare.

Which of the two consequences do you think is more concerning? Why do you think so? Share your thoughts in the discussion section.

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How Artificial Intelligence Can Support Healthcare

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