AI and Healthcare? Boon or a Bane?

Deepa -

As you well know, primary healthcare such as hospitals and clinics tend to be laggards in adopting comprehensive new technologies given a number of factors including regulations, patient safety, and clinician resistance to changes which may not directly improve patient outcomes.

I certainly do see point solutions adding tremendous value - for example, the learning models which are able to identify specific types of skin cancers.

And it is also quite possible that a Gen AI tool fed the appropriate reference materials might serve as a good assistant to clinicians so long as the usual rules of "don't trust AND do verify" are followed!

Kiron

Deepa, the utilization of AI in healthcare is huge (Some surgeons are now able to perform some surgeries remotely using robotics). With regards to your question, I Data Privacy and Security as a big challenge because AI systems require access to vast amounts of data to be trained effectively but Healthcare data is highly sensitive and subject to strict regulations so this could present an impediment in many cases. 

There is a constant risk of data breaches, unauthorized access, and misuse of patient information, which can lead to severe consequences including legal penalties, loss of trust from patients, and damage to the reputation of healthcare providers.
Addressing these challenges requires robust cybersecurity measures, strict data governance policies, encryption techniques, and innovative solutions for preserving privacy while maximizing the utility of healthcare data for AI applications.
AI systems require large amounts of data to train effectively, which means healthcare organizations need to collect, store, and share vast quantities of patient data. Ensuring the privacy and security of this data throughout its lifecycle, from collection to analysis to storage, poses a significant challenge.
Data sharing and collaboration among healthcare providers with strict privacy regulations adds another layer of complexity. Healthcare organizations must find ways to share data for training AI models and collaborating on research while still protecting patient privacy and complying with regulations.
It also necessitates ongoing efforts to educate stakeholders about the importance of data privacy and security and to cultivate a culture of trust and transparency in data handling practices within the healthcare industry.

AI (not GenAI) has been used in healhtcare from long time ago. More than 40 years ago. I can say that because, between other things, I was involved on that. Regarding all related to risks and ethics is outside there from that time. In fact, regarding risks, there are some unfortunately examples in the software engineering literature. Regarding GenAI, because as other things is a new buzzword and lot of people is talking about without enough knowledge, organizations that like to take advantage has to be taking into account that a whole new structure or business unit has to be created to face things like to validate the GenAI outputs and to create the right answers (prompt) do not generate waste.

Hello Deepa. The biggest issue and realistically risk with AI in healthcare is privacy. I am keeping my eyes and ears open for solutions to create secure environments. Until then, no proprietary or personal data is to be entered into any AI open tool. Other than that, we can use to look up regulations, ideas for protocols, training, new technology / instruments. Again, anything that isn't proprietary can be utilized and save us time with recreating the wheel.