While this all sounds incredible, it is important to keep in mind that the industry’s adoption of these technologies has been slow in consideration of the litany of risks that come with the usage of AI models. These risks include data privacy concerns, security issues, and bias in models. Before this technology can be truly beneficial for all, developers must undertake the responsibilities of making it fair, transparent, ethical, and secure. However, if there exists possibilities to save more lives with tools that have greater accuracy than the current system, I think it is worth investing the time and research into making tools that are responsible.

In this Padlet, I will delve into three AI applications and technology being researched and tested to showcase just how much potential AI has for saving lives. I will also discuss ethical considerations and societal impact in greater depth, because keeping that in mind is important to understand why industry adoption will not happen right away.

However, these promising trends also raise important ethical considerations. As AI systems are trained on historical and clinical data, there's a risk of bias. For example, if datasets lack diversity, predictions may be less accurate for underrepresented populations. In personalized medicine, it's crucial to ensure transparency in how AI recommends treatments, so that patients and doctors can trust and understand its guidance. Data privacy is another major issue because AI models rely heavily on sensitive medical data. Ensuring secure storage, informed consent, and responsible use of this data is essential to protect patients’ rights.

Personally, I believe AI will bring healthcare improved speed, accuracy, and personalization for every patient. But this future must be built with trust, fairness, and human oversight. It's exciting to think that tools already helping in early detection of heart disease or vision loss could soon become everyday instruments in clinics. Still, we must ensure AI complements, not replaces, human care, and that ethical safeguards keep pace with innovation. AI tools should exist to help inform and supplement a provider’s decision, not take it over.

From my perspective, these societal implications make it clear that AI in healthcare is more than just a technical issue. Its success depends on inclusive design, equitable access, and public trust. I am interested in how AI can assist, not replace, healthcare professionals, offering tools that can prevent vision loss, detect heart failure early, or choose life-saving cancer drugs faster as has been showcased on this wall. These innovations hold incredible promise, but we must guide them with empathy, ethics, and equity at the core.