Summary: COO Carlos Melendez presents at two local events to share how AI is enabling a new era in biosciences and healthcare.
What is AI and What is it Not When it Comes to Life Science Markets
Each event served to elucidate what exactly AI is, and more importantly what it is not.
Carlos explained that AI is an interdisciplinary field that leverages mathematics and statistics, cognitive science, and computing to enable problem-solving based on vast and robust datasets with high-performance computers.
While generative AI is all the rage today, when it comes to critical biosciences and healthcare applications, it’s the more traditional types of AI that are currently in use. This includes predictive analytics, to determine the likelihood of a molecule behaving in a certain way, or a patient being readmitted into the hospital. It also involves deep learning to help a doctor find problem areas on an X-ray. Additionally, today chatbots are being used in physicians’ offices to answer routing patient questions 24/7. These are all practical applications where AI has already proven its value.
As Carlos explained, AI conjures up images of sci-fi robots, but AI is not fictional or magical — it’s mathematical. Below is what he said AI is not:
AI is not a replacement for humans. When it comes to life-critical decisions made in life science fields, humans must always be leading the way. AI can never have the experience, logic or insights that medical professionals and scientists possess. It should always have a supporting role.
AI is not without error. AI is data-driven but not always correct. AI is only as good as the data and inputs it receives but can be, and often is, wrong in its decisions. Another reason why humans must be in control.
AI is not RPA – There seems to be misconceptions that robotic process automation (RPA) is a form of AI, but Carlos clarified this in his presentations. RPA only conducts repetitive tasks, much like assembly-line functions, but AI is trained to think more like humans based on the data they receive.
AI in not always fair. Carlos cautioned about the need to create unbiased AI, especially when it comes to healthcare. This means training algorithms on diverse data-sets and ensuring that data scientists and those building algorithms are aware of the need to factor in all types of data and scenarios. Biased AI can result in minorities receiving less than adequate attention; to certain groups of people being denied healthcare coverage; or other situations where people are treated unjustly or ignored because of how the algorithm was trained.
Forging a Career in AI-Driven Biosciences and Healthcare
Speaking to UPR students, as well business and government leaders across Puerto Rico, Carlos discussed the new roles that are being created thanks to AI. From chief data officers, to data scientists, data specialists and large language model developers, there are new opportunities that only a decade ago were nonexistent within organizations.
He recommended that students utilize integrated studies that combine science, math and biosciences disciplines; and that industry/academic partnerships are formed to provide students with real-world training. He also said that introducing students to STEM education at the youngest levels is key to nurturing talent.
As AI and other disruptive digital tools become integral for continued biosciences and healthcare innovation – as well continue economic growth across Puerto Rico and beyond –
Carlos was thrilled to share the role Wovenware plays in helping organizations explore this brave new world. Yet it wasn’t only a one-way dialogue. He was inspired by how engaged and interested students and government and business leaders alike are in gaining a better understanding of how AI can be applied to life science markets to improve patient care and breakthrough medical innovation.