Is Healthcare AI Prioritizing People or Profit?

Prioritizing convenience and efficiency goals over avoiding common AI missteps may come at the cost of effective care. Even if medical profits increase, patient outcomes and healthcare disparities could worsen. However, AI has many beneficial implications for patients, so the industry cannot ignore it. Healthcare organizations can follow these steps to ensure ethical, patient-centric AI usage.

SwissCognitive Guest Blogger: Zachary Amos – “Is Healthcare AI Prioritizing People or Profit?”

In many sectors, artificial intelligence (AI) is largely a tool for driving efficiency, but in healthcare, it can save lives. However, medical practices are still businesses at the end of the day, so AI’s cost-saving benefits are hard to overlook. While that’s not an issue in and of itself, the push to save money can lead to healthcare organizations prioritizing profit over people.

How Healthcare AI May Put Profit Before People

AI is a powerful financial management tool. It can analyze vast amounts of data to highlight opportunities to increase profits and emphasize areas that may not pay back investment.

AI insight in healthcare could lead private practices to drive high-value drug or treatment sales instead of focusing on care accessibility. It may also lead to preferential treatment of more profitable patients. Some hospital systems claim they have lost as much as $640 million on Medicare recipients. AI-driven cost analysis may drive hospitals to reduce their investment in these populations because of the lower financial incentive.

AI’s profit-driving capabilities can influence healthcare ethics in subtler ways, too. Staff may over-rely on automation and machine learning because it saves them time. However, AI hallucinations are still possible. Similarly, the underrepresentation of diverse patients in training datasets can lead to biased AI results, which may negatively impact a medical system’s ability to care for historically underserved groups.

Prioritizing convenience and efficiency goals over avoiding these missteps may come at the cost of effective and equitable care. Even if medical profits increase, patient outcomes and healthcare disparities could worsen.

How to Ensure Responsible AI Usage in Healthcare

Despite these risks, AI has many beneficial implications for patients, so the industry cannot ignore it. Healthcare organizations can use these steps to ensure ethical, patient-centric AI usage.

1. Focus on Direct Patient-Impacting AI Applications

First, hospitals must prioritize AI use cases that directly impact patients over those that drive economic or efficiency gains for the organization. Medical imaging and diagnostic tools are among the most crucial.

AI can identify Alzheimer’s with 99.95% accuracy and achieve similar results with many cancers and other conditions. Investing in these applications rather than in AI-based financial analysis will ensure AI’s benefits go directly to promoting better care standards.

Personalized treatment is another promising area for responsible AI usage. Machine learning models can analyze an individual patient’s medical history and physiology to determine which courses of action will help them most. This application is more ethical than using AI to compare the profitability of different treatment options.

2. Ensure Responsible AI Development

Healthcare organizations must address the bias issue in their AI models. Studies have found that removing specific biased factors from training datasets can maintain model accuracy while reducing the risk of prejudice. Common examples of these factors include names, ethnicities, age and gender-related labels.

Having a diverse team of AI developers who regularly inspect models for signs of bias or hallucinations can help. Relying on synthetic data is also a useful strategy, as this can make up for gaps in historical real-world information that may lead to unreliable or biased results.

3. Train Medical Staff on AI Best Practices

Finally, medical companies should train their staff so they’re familiar with how AI can affect care equality. When users understand how misusing AI or failing to catch errors can harm patients, they’ll be more likely to use it responsibly.

Cybersecurity deserves attention, too. A criminal can hinder reliable AI results by poisoning just 0.01% of its data, which can lead to harmful results if unnoticed. Training employees to follow strict access policies and resist phishing attempts will mitigate some of these concerns.

Healthcare teams should also write formal policies to ensure a human expert always makes the final decision on anything affecting patients. AI can provide insights to inform human choices, but it should never be the ultimate authority, given the risk of bias and the temptation to prioritize profit over equitable care.

Ethical Healthcare AI Is Possible

When organizations use it responsibly, healthcare AI can make the industry a safer, more equitable place. However, failing to account for possible shortcomings and errors will create the opposite effect. Learning about how AI can influence both ethics and profitability is the first step in creating a better future for patients and their care providers.

About the Author:

Zachary Amos is the Features Editor at ReHack, where he writes about artificial intelligence, cybersecurity and other technology-related topics.