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Managing the benefits and risks of AI in healthcare | Jon Moore


The popularity of ChatGPT has triggered a surge of interest in artificial intelligence. But AI's promise also comes with some potential problems.

Artificial Intelligence (AI) hype spiked again recently with the public release of ChatGPT.

The easy-to-use interface of this natural language chat model makes this AI particularly accessible to the public, allowing them to experience first-hand the potential of AI. This experience has spurred users’ imagination and generated a wide range of feelings from great excitement to fear and consternation.

The reality is that for many years now, AI has been making remarkable strides in a wide range of industries and healthcare is no exception.

The potential benefits of incorporating AI into healthcare are numerous but like every technology, it comes with risks that must be managed if the benefits of these tools are to outweigh the potential costs. This article will explore the benefits of AI in healthcare and the potential security and privacy risks that must be considered.

One of the most significant benefits of AI is improved diagnostic speed and accuracy. AI algorithms can process large amounts of data quickly and accurately, making it easier for healthcare providers to diagnose and treat diseases.

For example, AI algorithms can analyze medical images, such as X-rays and MRI scans, to identify patterns and anomalies that might be missed by human providers. This can lead to earlier and more accurate diagnoses, resulting in better patient outcomes.

In addition, AI algorithms can help healthcare providers by providing real-time data and recommendations. For example, AI algorithms can monitor patients’ vital signs, such as heart rate and blood pressure, and alert healthcare providers if there is a sudden change. This can help healthcare providers respond quickly to potential emergencies and prevent serious health problems from developing.

AI can help healthcare providers better manage chronic conditions. AI algorithms can monitor patients’ health data over time and provide recommendations for lifestyle changes and treatment options that can help manage their condition. This can lead to better patient outcomes, improved quality of life, and reduced healthcare costs.

One of the most significant benefits of AI in healthcare is the ability to improve access to care. AI algorithms can help healthcare providers reach more patients, especially in remote and underserved areas. For example, telemedicine services powered by AI can provide remote consultations and diagnoses, making it easier for patients to access care without having to travel.

However, despite the many benefits of AI, there are also security and privacy risks that must be considered.

One of the biggest risks is the potential for data breaches. As healthcare providers create, receive, maintain, and transmit large amounts of sensitive patient data, they become a target for cybercriminals. Bad actors will attack vulnerabilities anywhere along the AI data pipeline.

Another risk is the unique privacy attacks that AI algorithms may be subject to including membership inference, reconstruction, and property inference attacks. In these types of attacks, information about individuals, up to and including the identify of individuals in the AI training set, may be leaked.

There are other types of unique AI attacks as well, including data input poisoning and model extraction. In the former, an adversary may insert bad data into a training set affecting the model’s output. In the latter, an opponent may extract enough information about the AI algorithm itself to create a substitute or competitive model.

Finally, there is the risk of AI being used directly for malicious purposes. For example, AI algorithms could be used to spread propaganda, or to target vulnerable populations with scams or frauds. ChatGPT, referenced above, has already been used to write more convincing phishing emails.

To mitigate these risks, healthcare providers should continue to take the traditional steps to ensure the security and privacy of patient data.

This includes conducting risk analysis to understand their unique risks and responding to those risks by implementing strong security measures, such as encryption and multi-factor authentication. Additionally, healthcare providers must have clear policies in place for the collection and use of patient data, to ensure that they are not violating patient privacy.

Healthcare providers should consider being transparent about the algorithms they are using and the data they are collecting. This can help reduce the risk of algorithmic bias and ensure that patients understand how their data is being used.

Finally, healthcare providers must be vigilant about detecting and preventing attacks on the AI algorithms themselves.

Jon Moore is the chief risk officer and head of consulting services and customer success of Clearwater, a cybersecurity firm.

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