What to do about AI in health?

Estimated reading time: 7 minutes

Artificial intelligence (AI) is transforming the health sector in unprecedented ways. From diagnosis and treatment to research and innovation, AI is enabling new possibilities for improving health outcomes and reducing costs. However, AI also poses significant challenges and risks that need to be addressed by policymakers, practitioners, and researchers.

In this News Round the Clock (NRTC) post, I will discuss some of the main opportunities and challenges of AI in health and suggest some actions that can help ensure its ethical and responsible use.

AI applications in health care

AI is an umbrella term that covers a variety of processes that use computers and machine learning algorithms to simulate or enhance human intelligence. Some of the most common forms of AI used in health care include:

Machine learning (ML): training algorithms using data sets, such as health records, clinical studies, or genetic information, to create models that can perform tasks such as categorizing information or predicting outcomes.

Deep learning: a subset of machine learning that involves greater volumes of data, training times, and layers of ML algorithms to produce neural networks that can perform more complex tasks.

Natural language processing (NLP): the use of ML to understand human language, whether it be verbal or written. In health care, NLP is used to interpret documentation, notes, reports, and published research.

Robotic process automation (RPA): the use of AI in computer programs to automate administrative and clinical workflows. Some health care organizations use RPA to improve the patient experience and the daily function of their facilities.

Some examples of how AI is used in health care are:

Diagnosis and screening: AI can help detect diseases and conditions faster and more accurately than human doctors, by analyzing images, scans, tests, or symptoms. For example, AI can help diagnose skin cancer by comparing images of skin lesions with a database of thousands of cases. AI can also help screen for diseases such as diabetes or cardiovascular disease by analyzing risk factors and biomarkers.

Treatment and care: AI can help personalize treatment plans and care for patients based on their individual characteristics, preferences, and outcomes. For example, AI can help recommend the best drugs or dosages for patients based on their genetic makeup, medical history, or response to previous treatments. AI can also help monitor patients’ conditions and alert doctors or nurses if there are any changes or complications.

Research and development: AI can help accelerate the discovery and development of new drugs, vaccines, or therapies by analyzing large amounts of data from clinical trials, literature reviews, or molecular simulations. For example, AI can help identify potential drug candidates or targets for diseases such as Alzheimer’s or cancer by finding patterns or connections among biological molecules.

Prevention and public health: AI can help predict and prevent diseases and outbreaks by analyzing data from various sources such as social media, environmental sensors, or population surveys. For example, AI can help track and forecast the spread of infectious diseases such as COVID-19 or influenza by using data on mobility patterns, contact tracing, or symptoms. Artificial Intelligence can also help promote healthy behaviors and lifestyles by providing personalized feedback or interventions based on data on physical activity, nutrition, or mental health.

AI benefits in health care

AI has the potential to bring many benefits to health care, such as:

Improving quality: AI can help improve the quality of health care by reducing errors, increasing accuracy, and enhancing outcomes. For example, AI can help reduce dosage errors by checking prescriptions against patient records or drug interactions. AI can also help improve surgical outcomes by assisting surgeons with robotic equipment or providing real-time information during operations.

Increasing efficiency: AI can help increase the efficiency of health care by saving time, money, and resources. For example, AI can help automate administrative tasks such as scheduling appointments, managing medical records, and processing insurance claims. This allows healthcare professionals to focus more on patient care and less on paperwork. Additionally, AI can streamline diagnostic processes, enabling faster and more accurate results, leading to quicker treatment decisions.

Enhancing accessibility: AI has the potential to bridge gaps in healthcare accessibility by providing services in remote or underserved areas. Telemedicine, powered by AI, allows patients to consult with healthcare providers virtually, overcoming geographical barriers. AI can also assist in the development of mobile health applications, wearable devices, and other technologies that empower individuals to monitor their health and well-being from the comfort of their homes.

Facilitating innovation: AI fosters innovation in healthcare by contributing to groundbreaking discoveries and advancements. The ability of AI to analyze vast datasets quickly can lead to insights that may have otherwise taken years to uncover. This acceleration in research and development can lead to the discovery of new treatments, diagnostic tools, and preventive measures.

Also Read: Risks of Generative AI as great as rewards

Challenges and Risks

Despite its numerous benefits, the integration of AI in healthcare comes with challenges and risks that need careful consideration:

Data privacy and security: The use of AI in healthcare relies heavily on the analysis of sensitive patient data. Ensuring the privacy and security of this information is crucial to maintain patient trust. Striking the right balance between data accessibility for AI development and safeguarding patient confidentiality is a complex task.

Bias and fairness: AI systems may inherit biases present in the data used to train them. In healthcare, biased algorithms could lead to disparities in diagnosis and treatment recommendations, affecting different demographic groups unequally. Addressing bias in AI systems is imperative to ensure fair and equitable healthcare outcomes.

Regulatory considerations: The rapid evolution of AI technology often outpaces regulatory frameworks. Establishing clear guidelines and regulations for the development and deployment of AI in healthcare is essential to ensure patient safety, ethical standards, and the responsible use of AI.

Integration with existing systems: Implementing AI in healthcare requires seamless integration with existing infrastructure and workflows. Resistance to change, interoperability issues, and the need for additional training can hinder the effective adoption of AI technologies.

Ensuring Ethical Use of AI in Health

To harness the benefits of AI in healthcare responsibly, several actions can be taken:

1. Robust regulations: Governments and regulatory bodies should develop and update regulations that address the unique challenges posed by AI in healthcare. These regulations should prioritize patient safety, data privacy, and ethical considerations.
2. Transparent and explainable AI: Developers should prioritize creating AI systems that are transparent and provide explanations for their decisions. Understanding how AI reaches its conclusions is crucial for building trust among healthcare professionals and patients.
3. Continuous monitoring and evaluation: AI systems should undergo regular assessments to identify and rectify biases, errors, or security vulnerabilities. Continuous monitoring ensures that AI remains aligned with ethical standards and evolving healthcare practices.
4. Collaboration and interdisciplinary research: Collaboration between AI experts, healthcare professionals, ethicists, and policymakers are essential. Interdisciplinary research can lead to a more comprehensive understanding of the ethical implications of AI in healthcare and the development of guidelines that promote responsible use.
5. Public awareness and engagement: Educating the public about AI in healthcare, its potential benefits, and associated risks is crucial. Informed and engaged communities can contribute to the development of ethical guidelines and advocate for responsible AI practices.

In conclusion, AI holds tremendous potential to revolutionize healthcare positively. However, careful consideration of ethical, regulatory, and technical challenges is essential to ensure its responsible and equitable integration into the healthcare ecosystem. Balancing innovation with ethical considerations will pave the way for a future where AI contributes to improved health outcomes for individuals and communities worldwide.