How Engineer AI Is Transforming Healthcare (And Why We're Not Ready For It)


Artificial Intelligence surpasses mere buzzword status, and rises to a level of universality. Humans have managed to engineer AI that can achieve a vast array of possibilities. From the field of robotics, to cybersecurity – professionals engineer AI to be used in various systems, for a better, more effortless functionality. Artificial intelligence has been used to alleviate cumbersome activities, which have been traditionally done through low skilled labour. One of the most rapid growth, is within the field of healthcare – especially now, as the globe is experiencing a crunch in manpower because of the coronavirus (Covid-19) epidemic.

Engineering AI For Pandemic Response

Within the field of AI, we have been able to engineer better machines, expediting the field towards advancement in the process. By 2030, the field of Artificial Intelligence and Machine Learning will have permeated every industry currently in existence. Healthcare is the most obvious example in this regard. Scientists have been able to engineer AI algorithms, which have accomplished everything from creating medicines (like antibiotics), to performing human-assisted surgeries.

Putting the existing threat of the coronavirus into picture, Artificial Intelligence has achieved in a span of three months, what humans couldn’t in a generation. Rapid scanning of patients, especially who harbour contagious pathogens, can be safely tackled with Robot Doctors (as they have come to be known). Scientists have managed to engineer AI paramedics that can provide a descriptive analysis of the patient’s physiology in no time.

These AI are not limited to scanning, they can also proficient in creating potent medicines – ones which a team of humans can spend up to 10 years in research for. Scientists are banking on engineering AI that will bring about the cure for Covid-19, embarrassingly faster, than it would take a human to do.
All in all, having a remote robot deal with a patient during an outbreak such as the coronavirus of 2020, is much more feasible (not to mention safer), than for a human being performing the same functions.

Artificial Intelligence Infrastructure

For all the leaps forward we have taken to engineer AI doctors, the reluctance to implement these systems supersedes any viable implementation it might possess. A lot of the countries affected by the novel coronavirus pandemic just don’t have the monetary fortitude to support such a leap in technological infrastructure.

Every penny that went into the provision of a Covid-19 testing kit could’ve easily gone to fund an AI-based pandemic response squad. Nearly 11,000 people have succumbed to this horrid disease, but it’s not too late yet. Nation-states can lend their coin to Engineer AI bots, in a joint cloud based race to find the cure that mankind so desperately seeks. The answer might be beyond humans, but is it beyond a machine? If we never try, we’ll never know.
Location: India

Comments

Post a Comment

Popular posts from this blog

Is Artificial Intelligence On The Backburner During The Coronavirus Outbreak

Image
Scientists have been able to engineer AI Doctors for a couple of years now, such as IBM Watson’s cardiologist AI, for example, identify algorithms, and potentially informs a patient of their disease. After that, a chatbot feature advices them thusly, on treating their condition. These AI-powered engineer doctors hold the key to self-diagnoses, and can dispense advice, almost as efficiently as any doctor could. Engineer AI To Fight A Pandemic Governments are in a fix, as we speak, as the looming threat of a Coronavirus outbreak (now pandemic), is threatening the safety of every nation state on the planet. Studies, like the one done at MIT, have demonstrated the potential of a “Robot Doctor” – an Artificial Intelligence that can do the same tasks as a Doctor, albeit with fewer mistakes! Artificial Intelligence, or the tasks we engineer AI for, have drastically seen a shift of pace in the last few years. A lot of them appear to be merely sorting tools, but their real potential is
Read more

Engineer.ai - Redefining diversity and inclusion at the workplace

Image
A glance back at the advancement made in building a different and comprehensive working environment up until now. The average employee will spend almost 90,000 hours over their life at their place of work. For some, this naturally promotes a sense of belonging towards the company, becoming a driving force for continually improving their performances. However, over the past few years, establishments have begun to realize that not all employees can cultivate a deep relationship with their workplace due to several internal or external factors. However, one thing is certain, the subject of diversity and inclusion has become a central point of every discourse on workplace culture, and companies are therefore focusing on creating a proressive atmosphere to amplify the intangible value they offer to their employees. Engineer.ai Co-founder said we can attribute the initiation of the diversity revolution to issues like gender disparity in allowing equal work and pay opportunity. Organi
Read more

Adoption of AI within the IoT Ecosystem

Image
Farnell has published new research on the IoT which confirms strong adoption of Artificial Intelligence within IoT devices, alongside new insights on key markets, enablers and concerns for design engineers working in Internet of Things. AIoT is the major emerging trend from the survey, demonstrating the beginning of the process to build a true Internet of Things ecosystem. Research showed that almost half (49%) of respondents already use Artificial Intelligence in their IoT applications, with Machine Learning the most used technology (28%) followed by cloud-based Artificial Intelligence (19%). This adoption of Artificial Intelligence within IoT design is coupled with a growing confidence to take the lead on IoT development and an increasing number of respondents seeing themselves as innovators. However, it is still evident that some engineers (51%) are hesitant to adopt AI due to being new to the technology or because they require specialized expertise in how to implement AI in Io
Read more