This article is part of a mini-series where we explore the challenges and difficulties in healthcare today.
What is Generative AI:
Generative AI has emerged as a transformative force, akin to having a creative partner that enhances human capabilities. Imagine an artist collaborating with an AI assistant, where ideas are generated and refined together, resulting in unique and imaginative artwork. In healthcare, generative AI leverages data and algorithms to push the boundaries of medical creativity, inspiring fresh ideas and unlocking new possibilities.
In this blog post, we will explore the impact of generative AI in healthcare, emphasizing its role in early intervention and personalized care, and the challenges it presents.
It’s not Stealing Everyone’s Job
In various industries, we have witnessed significant transformations. For example, the manufacturing sector in Australia has shifted its low-level, mundane tasks offshore due to cheaper labor abroad. Similarly, we anticipate a similar evolution in healthcare (one of the highest-paid sectors) with the introduction of generative AI. It’s important to note that generative AI is not intended to replace jobs but rather to automate mundane, repetitive tasks that require less creativity, empathy, and relationship management. By delegating these tasks to AI, healthcare professionals can focus their expertise on more complex and critical aspects of patient care, ultimately improving overall outcome
Advancing Early Intervention and Preventative Measures:
Healthcare professionals excel in caring for sick patients, but what about those on the path to illness? This is where AI shines, detecting deviations from baseline or homeostasis, and thus enabling early intervention and preventive measures. With the ability to analyze extensive patient data, AI assists in identifying trends and flagging potential health risks. From this generative AI is able to provide simple yet effective and personalised recommendations, it complements clinicians’ expertise, improving patient outcomes and reducing the burden on healthcare systems.
Empathy and Patient Care:
While generative AI can offer valuable insights, it cannot replace the human touch and care that define healthcare. However, studies have shown that healthcare providers prefer the answers generated by generative AI (specifically ChatGPT) as they often demonstrate greater patience and time for patients questions for mundane and run-of-the-mill questions. Also, generative AI, doesn’t have long wait lists and can be accessed where-ever you are, whenever you need it. Ultimately, there will always be a role for human caregivers in healthcare, and generative AI should be seen as a supportive tool, removing much of the low-level mundane tasks, augmenting human decision-making processes and providing guardrails to reduce the potential for human error.
Goldilocks: A Real-World Application:
But this isn’t decades away technology, at Goldilocks we are already harnessing the potential of generative AI. For instance, Goldilocks utilises generative AI in our baby and age care products. By getting infants and seniors to wear the Goldilocks smart clothing, we are able to collect an enormous amount of biometrics in real-time. This allows Goldilocks to establish personalized baselines, generative AI is then used to provide tailored recommendations right when the wearer or loved one needs them most. From what to do with a high temperature to organising your aged care provider to give you more water on a hot day, Goldilocks provides holistic care to keep you in the ‘Goldilocks Zone’ – safe, happy and well.
Goldilocks is a first-of-its-kind, virtual health assistant that supports home healthcare and early intervention efforts. This integration showcases the potential of generative AI to transform patient care and enhance well-being.
Challenges and Ethical Considerations with Generative AI:
As generative AI gains prominence in healthcare, challenges emerge that require attention. Determining accountability for decisions made by AI systems is crucial. Currently, there is no established framework to determine responsibility, whether it lies with the clinician or the AI developer. To ensure transparency and ethical decision-making, government regulations must address this issue. Additionally, the availability of diverse and representative datasets is essential. Historically, healthcare datasets lacked proper representation, with male-centric biases. Efforts should be made to rectify this disparity, allowing for fair and accurate healthcare applications of generative AI.
What’s the Future of Generative AI in Healthcare?
Generative AI holds immense potential to revolutionize healthcare, augmenting medical professionals’ abilities and improving patient care. By enabling early interventions and personalized care, generative AI becomes a valuable tool for achieving better patient outcomes. While challenges around accountability and dataset diversity need to be addressed, generative AI should be embraced as a supportive partner in healthcare, enhancing human decision-making and delivering innovative solutions. By leveraging the power of generative AI, we can usher in a new era of healthcare, where technology and human compassion work hand in hand to provide optimal care for all.
