AI in healthcare: the saviour or the next step to 1984?
With the rise of the AI era came a boost of innovation in the healthcare sector. Every patient journey has been transformed by the use of data as a way of optmizing processes, such as diagnosis, recurrent monitoring, drug matching, behaviour analyses, medical procedures and a lot more.
The optmization powered by AI generated a drop in the cost of healthcare, which also allowed some services to become more accessible for patients. However, the need of data as the combustor for more authomatized processes comes at a cost for the service’s users and we are going to discuss their impact in the following topics of this article.
How accessible will AI be
AI definetly improves and makes diagnosis faster while also creating personalized drugs for patients. But the digital world is still pretty inaccessible since 47.9% of the population doesn’t have access to it.
Futhermore, we have an upcoming and growing issue with the aging population. When it comes to the elderly population, the addition of software might cause the oppositive effect when it comes to accessability, since the majority of them are not familiar digital products.
The tendency of dehumanizing health
As we move towards a more digitalized health service there we will ecounter more moments in which the process lacks humanization. Healthcare is about people. Product Managers and Designers in this sector will have the challenge to identify where and when a more subjective eye or treatment is necessary.
Policy and Governance
In this day and age, no government, public or private institution has yet come to the conclusion of what kind of data can be shared or not, or what is the right way to share data. There are two sides to this coin: a completely open regime of data such as China where they allow companies to have more data to train AI models in a faster pace.
Nevertheless, this generates a dictatorship and a supersurveillance state that disrespects human rights, just like in George Orwell’s book “1984”. Obvioulsy, there is a fine line between the privacy of the population and governmental interference for monitoring which consequently boosts models that require a Big Data for training.
The need of human supervision
Even though AI will also be a great partner in assisting tasks in the healthcare sector, it will still need supervision from medical and technical professional to guarantee its quality.
Since parameters of quality are not yet well established, it is also a hard task for the supervisors to understand which beahviour the AI should or shouldn’t have.
As we have discussed, the healthcare as we know today will continue to change and develop as AI and its applications become more mainstream. Consequently, I believe it is our job as citizens to be aware of the impact AI generates and to create solutions and rules to tackle these issues.
