The Human-AI Partnership: An Intelligence Leap for Healthcare

This is the second of three articles, sponsored by Philips Healthcare, exploring how healthcare organizations can realize the powerful promise of AI to improve efficiencies and help improve patient outcomes by addressing AI implementation barriers strategically, balancing the best of AI and humans, and focusing on ethical AI and related governance. 

In a bustling emergency room, a physician faced with a critically ill patient swiftly analyzes medical images with the aid of an AI-powered diagnostic tool. The AI system highlights subtle anomalies, helping the physician make a rapid and accurate diagnosis, potentially saving precious minutes and a life. This seamless collaboration between human expertise and artificial intelligence exemplifies the transformative power of the human-AI partnership in healthcare.    

Understanding the strengths and limitations of humans and AI

To fully realize the potential of AI in healthcare, it is essential to recognize that humans and AI each possess unique strengths and limitations. Humans excel in critical thinking, empathy, and ethical decision-making, while AI can process vast amounts of data, identify patterns, and make predictions with speed and accuracy. By understanding these complementary capabilities, healthcare organizations can design and implement AI tools that leverage the strengths of both humans and AI.  

AI tools should be designed to integrate seamlessly into existing healthcare workflows, processes, and systems to enhance rather than disrupt the work of healthcare professionals. This requires a human-centered design approach that prioritizes usability, intuitiveness, and the needs of healthcare professionals. AI tools should provide healthcare professionals with the information they need in a clear and concise manner, allowing them to make informed decisions quickly and efficiently.  

For instance, the University of Pennsylvania Perelman School of Medicine, which has a close and mutually beneficial relationship with healthcare provider Penn Medicine, is developing AI systems to assist with personalized treatment for breast cancer, heart attacks, and sepsis.  

The project developers are working closely with clinicians to understand real-world constraints – such as data availability, workflow integration, and thresholds for medical markers – and incorporate them into the AI system’s design. This collaborative approach ensures the AI tool is truly supportive and aligns with existing clinical practices.    

Enhancing trust and transparency

While AI offers tremendous potential for improving healthcare, its “black box” nature can hinder trust and adoption. The Penn AI project is developing solutions to predict patient response to treatment, but researchers acknowledge the need for transparency and accuracy suitable for clinical use. To achieve clinically viable transparency and accuracy, the project is pursuing a multi-faceted AI strategy that combines data-driven models with logical and symbolic reasoning. 

Explainable AI (XAI) aims to address this challenge by providing insights into the decision-making processes of AI models. XAI techniques can reveal which factors contribute to an AI’s prediction, increasing transparency and allowing clinicians to understand and validate the AI’s recommendations. This promotes trust and helps ensure AI systems adhere to ethical principles. 

Beyond XAI, the increasing use of agentic AI in healthcare brings new dimensions to trust and transparency. AI agents such as RPA and other bots have been around for a while and help automate tasks based on predefined rules. Agentic AI is a more advanced agent designed to act with human-like autonomy, acting more independently and adapting to a changing environment to complete tasks such as dynamic scheduling or care coordination. While agentic AI offers benefits by improving efficiency and reducing complexity, there are some important considerations: 

• Autonomy-human balance: Healthcare professionals must clearly understand the level of autonomy of agentic AI tools, recognizing when human oversight is necessary. 

• Explainability of actions: Providing some level of explanation for the actions taken by agentic AI can enhance trust. 

• Potential risks: It is important to acknowledge the risks to patient safety, regulatory compliance, and data privacy and security.    

By addressing transparency and explainability for all types of AI, including agentic AI, healthcare organizations can foster greater trust and confidence in these powerful technologies. 

Related content: What is agentic AI and what does it mean for healthcare? 

Fostering a culture of trust and collaboration between humans and AI

The successful integration of AI into healthcare depends on building a culture of trust and collaboration between humans and AI. Healthcare professionals need to be confident that AI tools are reliable, accurate, and unbiased. They also need to be comfortable working alongside AI, recognizing that AI is a tool that can augment their capabilities, not replace them. Penn Health’s focus on developing “transparent” AI tools is a crucial step in fostering this trust. By making the AI’s decision-making process more understandable, clinicians can feel more confident in using the technology and interpreting its outputs.    

In addition to transparency, clear governance frameworks are essential for establishing trust in AI systems. These frameworks provide guidance on ethical development, responsible implementation, and ongoing monitoring of AI tools to ensure they align with healthcare values and patient needs. 

Investing in Education and Training 

To ensure that healthcare professionals are equipped to work effectively with AI, it is essential to invest in education and training. This should include providing healthcare professionals with opportunities to learn about AI, its applications in healthcare, and how to use AI tools in their practice. It should also include training on ethical considerations related to AI – such as bias, transparency, and data privacy — and should cover relevant governance frameworks. 

Initiatives like those at Penn, with seed grants for AI researchers and symposia on trustworthy AI, demonstrate the commitment to equipping healthcare professionals with the knowledge and skills needed to navigate this evolving landscape.    

Shaping the Future of Healthcare

The human-AI partnership has the potential to revolutionize healthcare, leading to improved patient outcomes, increased efficiency, and a more sustainable healthcare system. By embracing the elements outlined above, healthcare providers can develop and implement AI technology that saves time and lives, improves accuracy and outcomes, and marries the best of AI and human expertise. To successfully integrate AI, healthcare organizations must prioritize human-centered design, continuous learning, and robust ethical and data governance frameworks to ensure responsible and effective use. By fostering a collaborative environment between humans and AI, healthcare can achieve new levels of innovation and excellence. 

The next article in this series will dive deeper into these critical topics, exploring how healthcare can ensure AI remains a tool for good, enhancing care without compromising ethical standards. 

About Philips

Royal Philips is a leading global health technology company focused on improving people’s health and well-being through meaningful innovation, employing about 74,000 employees in over 100 countries. Our mission is to provide or partner with others for meaningful innovation across all care settings for precision diagnosis, treatment, and recovery, supported by seamless data flow and with one consistent belief: there’s always a way to make life better. For more information, please visit https://www.philips.com/global.