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Adapting to Change Is the New World Order, Same as the Old World Order

On July 20, 1969, Apollo 11’s lunar module Eagle landed humans on the moon. That was more than 50 years ago. NASA engineers and astronauts took the technology they had, adapted it, and accomplished great things.

Never has humankind been better positioned. Today, there is nearly unlimited data, computing power, and funding for the ideas that offer promise. We have the tools, the capability, and the need. Furthermore, adapting to change is not just optimal, the existential survival of Western civilization may depend on it. That is the new world order.

In the early days of World War II, President Franklin D. Roosevelt said, “We have nothing to fear but fear itself.” That is still partially true. Fear is easily our worst enemy, but as FDR learned, the powerful American economy provided his military with the weapons to defeat that terrible threat to Western civilization. Now, the capabilities of the American economy must again be summoned to answer the call to defeat the invisible risk posed by COVID-19.

The companies that adapt and participate in this effort will enjoy the spoils of those achievements, but the companies that are unwilling or unable to adapt will join the carnage of pervasive failure, which is the inevitable result of this environment of fear and danger.

AI and Machine Learning

There is a plethora of varied new and imaginative uses for machine learning and AI. Possible innovations which constitute some of the adaptations we espouse for the future include the following:

Security Companies of the Future

As a large percentage of American city populations move to more secure locations, a variety of different physical- and AI-based security options will emerge. Some have started already. dwellingLIVE (https://access.dwellinglive.com/advanced-security-tech?nology), for example, a web-based security platform built to serve residential communities, can provide most of the common security features heretofore provided by live security officers. The use of these technologies and others will free up capable security personal to engage in the more serious and immediate security needs of the community.

Moving Toward Machine Learning and AI

Andrew Ng, founder and CEO of Landing AI, recently discussed the difficulties that have historically plagued the adoption of AI in industry as a whole in a Forbes article (www.forbes.com/sites/insights-ibmai/2020/07/07/solving-the?-small-data-problem-and-other-challeng?es-with-ai-a-conversation-with-andrew?-ng/#a65100429478). “If your AI is exposed to data that’s different from what the system was trained on, the performance will degrade. But the real world changes all the time; how to deal with this is something that AI teams still need to get better at,” he told Forbes. Right now, he noted, “We’re seeing COVID-19 create a huge need in multiple industries for digitization and for AI transformations.”

Call Centers Reimagined

The use of call centers around the world for every conceivable requirement is accelerating exponentially. Call center personnel are overwhelmed. Every BDQ reader has probably had the experience of calling their local bank over the last 4 months and being told that they are 37th in line. One trend to deal with the higher number of calls streaming into call centers, particularly during challenging times, is that of the “AI-powered support agent” (www.forbes.com/sites/insights?-ibmai/2020/06/25/how-ai-is-revamping?-the-call-center), where the call center agent is trained to use AI tools that provide information which help address callers’ needs. Some studies and tests have reported a 40% improvement in call response times.

What’s Ahead

The world is adapting and changing. Eventually, the old normal will return, but unfortunately, it is likely that the dangers and the inadequacies exposed by the COVID-19 pandemic in 2020 will reside in our collective memories. This experience should inspire us to develop systems through the use of AI that both improve our lives and save our civilization.

Once again, we call for a modern-day Manhattan Project or moon-landing-scale effort. The mission of such a project would be to invent new uses for AI and machine learning using the power of modern-day computers.

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