Google Cloud is adding regions in Malaysia, Thailand and New Zealand

Google Cloud is adding regions in Malaysia, Thailand and New Zealand.Source: Shutterstock

3 ways Google AI is helping combat COVID-19 disruptions

  • Google AI applications have been leveraged in more ways than one, in bids to help organizations weather the effects of COVID-19
  • Crowdsourcing its data scientist community, repurposing AI solutions, & offering financial service APIs have all contributed towards helping companies manage operations

Google, like most of the other technology heavyweights, has been contributing towards efforts to manage the impacts of the COVID-19 coronavirus on individuals, governments, and organizations.

Besides making some of its technology freely available and collaborating with the likes of Apple and Amazon to help the US government track the spread of the virus, Google Cloud AI– the cloud-based artificial intelligence (AI) arm of Google products– has also seen its applications be adopted to address a variety of operational issues that were borne out of the coronavirus pandemic.

“From sifting through huge research datasets to finding potential treatments, to more accurately forecasting the spread of the disease, to powering virtual agents to answer questions about COVID-19, AI is helping all kinds of organizations,” remarked Rajen Sheth, vice president of product management for Google Cloud AI, in a recent blog post that detailed the company’s AI- and machine learning-driven solves for business headaches.

Crowdsourcing the Kaggle community

Sheth pointed to one example where the White House Office of Science and Technology Policy revealed that it now had a library of over 59,000 articles and literature that might contain necessary insights to finding a vaccine for the coronavirus.

Google Cloud’s subsidiary, the Kaggle community, was called upon to help sift through and discern some of the more pressing queries that needed answering, such as identifying COVID-19 risk factors or what were the virus’ origins and genetic traits.

Over 4 million data scientists that form the Kaggle community then came up with new AI models that could predict the spread of the pandemic with precision, and also helped develop a variety of data mining and text mining tools to comb through what became known as the COVID-19 Open Research Dataset, CORD-19.

Repurposing contact center AI

Google also recently unveiled the Rapid Response Virtual Agent software that taps the Contact Center AI that was developed for enterprises and repurposes it to assist companies that are experiencing a high volume of calls related to COVID-19.

The free program can be set up quickly to address the first line of queries via voice or chat, and the customized AI bots can help direct communication traffic and alleviate some of the tasks from human workforce, who could be otherwise redirected to more relevant jobs.

Sheth’s blog highlighted the use case of grocery chain Albertsons Companies which had been overwhelmed with customer calls during the first weeks of the outbreak. “The pandemic sparked a number of inquiries from our customers, causing a rush of calls, and impossibly long wait times,” said Cameron Craig, the Vice President of Digital Product, Design & Experience for Albertsons.

“With the Rapid Response Virtual Agent program we were able to quickly set up our virtual agent, answering questions and directing traffic at the first inquiry level. Saving us time and money, while better servicing our customer’s needs.”

Integrating financial resilience tools

Another recent development is the PPP Lending AI Solution that helps resource lenders to integrate a range of AI-based document ingestion tools with their existing underwriting systems to enhance efficiency.

The PPP Lending AI Solution comprises three components: a Loan Processing Portal for both loan applicants and agents to observe the status of their Paycheck Protection Program (PPP) loan applications; the Document AI PPP Parser application programming interface (API) that extracts structured information from loan applicants’ documentation; and Loan Analytics, which enables lenders to rapidly onboard historical loan data, privatize sensitive information, and securely store and perform analytics on the data.