Building Trust in AI: A Healthcare Odyssey

The healthcare landscape is ever-evolving. The “recent” infusion of Artificial Intelligence is among its most exciting advancements. We are talking about it. Healthcare professionals are talking about it. The world is talking about it. But how comfortable are our medical maestros–doctors and nurses, with this tech-driven colleague “walking” through their corridors? Let’s delve into some real-world situations where AI played the virtuoso, aiding our healthcare heroes in delivering A+ performances.

Building Blocks of Trustworthy AI in Healthcare

For AI to be the co-star in our healthcare script, it must earn its place on the stage. Here are the key ingredients for receiving standing-ovation-worthy performance every time:

• Fairness: A fair AI is like a fair judge—impartial and equitable. AI systems must provide unbiased healthcare outcomes regardless of race, gender, or socioeconomic status. For example, an AI algorithm for predicting the future risk of breast cancer may suffer from a performance gap wherein black patients are more likely to be incorrectly assigned as “low risk” incorrectly. This is a much broader topic and can be discussed further. On the other hand, how many times the ethical standards of a medical expert were brought into question?
• Explainability: Our medical maestros need to understand their AI colleague’s reasoning. A clear, understandable AI decision-making process is crucial to gaining the trust and confidence of healthcare professionals. A study from BMC shows that "A major goal of AI in healthcare product development is to approximate this ideal state via thorough clinical validation and development on heterogeneous data sources. While this ensures that AI bias can be reduced to a minimum, it will still be almost impossible to generate AI tools without any trace of bias. If bias is present, there will be prediction errors in patients not representing the training sample.
• Privacy: In the healthcare theatre, patient data is the script, and it's sacrosanct (the rehearsal process). AI systems must uphold patient data privacy like it’s the holy grail.?
• Robustness: The healthcare stage is dynamic, with no room for irregular performances. AI systems need to be reliable and perform consistently under varying conditions and without any excuses.
• Transparency: Transparency fosters trust. Openness about AI’s capabilities, limitations, and performance metrics is essential for medical professionals to have confidence in AI systems.?

Bridging the Trust Gap: The Journey Ahead

In order to bridge the trust gap between AI applications and healthcare practitioners, various measures and initiatives have been undertaken, so far. Here are some ongoing efforts and discussions in this sphere:

• Standardization for Trustworthiness: The Consumer Technology Association (CTA) has launched a trustworthiness standard for AI in healthcare. This initiative aims to streamline the implementation of medical and healthcare solutions built on AI. It is designed to provide solutions from diagnosing diseases to offering advanced remote care options, addressing some of the most pressing challenges in healthcare today.
• Improving AI Transparency: The discourse around AI in healthcare often circles back to transparency. It's believed that for AI to revolutionize healthcare, a significant amount of progress needs to be made in gaining the trust of healthcare professionals and patients. Improving AI transparency is seen as a promising avenue to address trust issues, although it's acknowledged that the notion of transparency still lacks maturation and clear definitions.
• Collaborative Dialogue: A session titled "Trust and The Impact of AI on Health Care" during CES 2021 brought together subject matter experts from Philips, the American Medical Association, and the Duke Margolis Center for Health Policy. This session showcased the opportunities and barriers regarding the promise of AI for healthcare, shedding light on the essential collaborative dialogue between different stakeholders to address trust issues.?

Real-Life Cases: AI as a Reliable Co-Pilot

In the medical world, errors can produce grave repercussions. It may sound a little bit harsh, but that’s the truth. So, if we take everything into consideration, it all comes down to trust, which is essential. Talking about AI, it has already proven its expertise in several healthcare performances:

• Diagnosis Déjà Vu: AI systems have been instrumental in diagnosing conditions from skin cancer to diabetic retinopathy with a finesse often matching or even surpassing human experts. Doctors can now “replicate” their eyes with AI, seeing through their lenses and discovering diseases without harming their expertise.?
• Treatment Trailblazers: AI isn’t just a diagnostic tool. It’s also a driving force in suggesting treatment plans. For instance, IBM’s Watson can analyze the meaning and context of structured and unstructured data in clinical notes and reports to help find the most effective treatment for cancer patients. Imagine having a co-pilot by your side who could find several effective treatments ongoing in the world in seconds.

These real-life acts have not only saved lives but also earned standing ovations from the medical community. Just think about all the life-changing or life-improving treatments that can be applied in medical centers and hospitals.?

Embracing AI’s Promise in Healthcare

The journey of blending AI with healthcare is like pairing up a new duo for a big concert. The real success lies not just in hitting the right notes but in creating a melody that resonates with everyone. Real-world stories of AI assisting in diagnosing diseases or planning treatments are the first few notes of a tune that has the potential to become a healthcare anthem. These instances spark hope that with AI, we're not taking small steps towards better healthcare anymore. Somehow, these steps transformed into giant leaps. However, trust is the key to every relationship, so this one is not an exception.?

Being fair, explainable, respecting privacy, staying robust, and being transparent are the chords AI needs to strike to create a harmonious tune with healthcare professionals. The ongoing discussions, setting standards, and innovative solutions are like the rehearsals before the grand concert. They are preparing the stage for a show where AI and healthcare professionals come together to deliver a life-saving performance. As this narrative unfolds, it's clear - build trust in AI, support our healthcare heroes, and let the concert of better healthcare begin.?

Authors: Darko Todorovski & Lyudmila Todorovska