COVID-19 has had an immeasurable effect on everything from online commerce to mental health, and its impact is still being felt in every corner of the world.
One of the most pertinent attitudinal and physical changes to how people work, live, communicate, socialise and travel has been how tech and tech companies have innovated. AI and robotics have gone from play-thing of the rich, to a vital pandemic response resource.
From wearable tech in healthcare wards being used to reduce unnecessary contact, to the rise of QR codes in restaurants to reduce linger time at tables, the “hands off” approach has been technologically freeing for companies developing these solutions. But it’s also become a critical expectation from customers and end users.
Most importantly, AI has been a core facet of the pandemic response. From UK health departments using AI-based algorithms to better analyse collated x-ray data across departments and NHS trusts, to MIT and the Mayo clinic using machine learning to better understand the spread and severity of disease and better repurpose existing drugs, AI, and AI developers, have played a huge part in the global response to COVID-19.
So how has AI helped human’s better respond to the pandemic? What is in store for AI in the future and where does AI development stand in light of the changes wrought by COVID?
Trust is a Long Game
AI played a dual role in understanding and mapping the spread of the disease in China in the initial months of the outbreak through: data collation, analysis and results based findings to inform healthcare officials about the spread of the disease; and diagnostic improvements in fields such as radiology and CT scanning as healthcare teams came under impossible pressures.
Trust and collaboration, both of what AI can achieve and how global healthcare teams understand it, is vital in mitigating the worst of any further outbreak, and that more communication channels need to be opened up.
The future of Drug Testing
Specifically, drug repurposing. The mechanics of drug repurposing – saving time and huge amounts of effort on creating new drugs – requires an enormous amount of data analysis, database access, testing, modeling, and the combination of these data sets into actionable intel. Clinicians obviously have the final say, but AI makes the process of finding the right drug creation path much much faster.
“Such real-world data have many confounding factors, but with sufficient dataset size, useful information can be teased out by AI, which is invaluable in the fight against a fast-developing infectious disease”.
I am Robot
Robotics are already firmly established in logistics, warehousing, engineering and manufacturing. But COVID represented a novel occasion where robotics could be pivotal in drastically improving patient care. From supply chain automation to in-patient critical care, robots reduce unnecessary pandemic-related proximity time, can provide a real time resource in wards and, alongside IoT like devices such as wearable tech, can provide incredible amounts of data at the edge to be used in rapid patient care.
These three examples show hard evidence of how AI helps clinicians and healthcare providers improve their care, and how they turned the tide against the pandemic. But the spread of AI is not done – from AI at the edge to IoT in homes, on shop floors and in work places, AI will be central to how the interconnected world of the future connects, communications and socialises.