AI, COVID19 and the Nature of Work -- Notes from the Frontier
Sadly, the COVID19 pandemic is nowhere close to peaking globally. The human and economic costs will be staggering. But in an effort to be positive, it might be helpful to remember that pandemics throughout history have also sparked great creativity and scientific achievement. Increased understanding about the origin and transmission of disease have spurred scientists, doctors and engineers to create better, safer, more sanitary ways for humans to share space and ideas.
Today’s pandemic arrives in a world accelerating rapidly in the direction of increased automation and virtual connectivity. Existing institutional infrastructures have been experiencing difficulty in adapting to this new environment, as we noted last summer in THIS POST regarding the Bretton Woods institutions. Real existential challenges at the base of Maslow’s Hierarchy of Needs will only make the institutional evolutional process that much harder at the international level, as we noted last week in THIS POST.
Mandatory mobility restrictions create personal challenges for knowledge workers and the global supply chain, but they also require companies to accelerate adoption of remote working and distance collaboration mechanisms in order to preserve jobs and continue delivering value to their customers. We are only starting to glimpse the coordination and managerial challenges that can arise when the “new normal” increasingly involves teams whose only interaction with each other is a periodic video call.
The shifting nature of work due to analytical automation (often dubbed artificial intelligence) pre-dates the pandemic, of course. From Davos to Aspen to Salzburg to Singapore to Hong Kong, the last few years have seen a proliferation of futurists and experts providing perspectives on how the workplace might evolve incrementally. People fretted over how machines might take over the world. From truck drivers, ocean freighters, and drones to bookkeepers, lawyers, sports writers, business journalists, and analysts, many were prepared to paint the process as pitting humans against machines.
It was in this context that I submitted a chapter idea last year to The AI Book (forthcoming from Wiley in April; available for pre-order right now) for consideration on the topic of the future of work and enhanced cognition. I make the case that the human vs. machine polemic is problematic and counter-productive. It is much more rational to cower in fear of a deadly virus than to fear automated processes that humans create, train, and have the capability to control. AI systems provide significant opportunities for human to think smarter and faster when they team up with a machine.
A wide range of analytical process automations deliver “enhanced cognition” that enables knowledge workers to read smarter and connect the dots faster by subcontracting to automated machine learning algorithms the often tedious task of reviewing large reams of material.
I know this from personal experience. My company’s patented, automated platform (the PolicyScope) daily assesses large amounts of public policy data every day in order to deliver to platform users analysis of daily global activity represented quantitatively in terms of charts and graphs. Users are literally smarter because their entry point is at a farther point in the analytical production line compared with individuals would are still spending significant parts of their day scanning email newsletters, media stories, and research reports. They read smarter and connect the dots faster. And that is just in Phase I.
My chapter for The AI Book concludes with suggestions on how policymakers and business leaders can – and should – prepare the workforce for the coming shift in workflow processes so that more people can benefit from the analytical revolution. It assumed a world where the transition to enhanced cognition was gradual. It did not countenance a pandemic.
By the time The AI Book is available in April, much of the advanced world will have been working remotely for at least two months.
Nearly everyone is a knowledge working right now. It is impossible to perform any job right now – from store clerk to truck driver to doctor to analyst -- without access to good information about government policy and health threats.
Small companies are scrambling to help their employees navigate this environment. Larger companies may have a sophisticated communications infrastructure in place, but the impact of information overload paired with not-irrational fears regarding disease transmission and urgent customer needs means increased demand for technology and automation that can ease the cognitive burden on individuals while increasing their efficiency.
COVID19 requires companies to accelerate their adoption of AI technologies that can help their employees operate remotely while delivering value to customers. Globally. The era of really alternative data has arrived, ushered in by a deadly, invisible pathogen.
Every shift in behavior, every policy shift, every sad statistic, generates a data set on which AI systems can be trained so that good solutions can be found faster in the near future.
Businesses and society will not “go back to normal” after the pandemic has peaked. Consider:
Medical professionals racing to craft a vaccine can rationally discuss research time frames in terms of months rather than years because AI systems can be deployed to collect, cleanse, and structure disease data from around the world and suggest potential solutions.
Forward-looking companies will use the vast amounts of consumer purchasing data during the panic buying early days of the pandemic to develop more advanced approaches to inventory management and supply chain diversification strategies.
Financial institutions and their regulators will use the extraordinary market volatility data as inputs for AI-devised stress tests, scenario analyses and internal risk pricing processes that reflect not only a broad range of potential outcomes but also reflect the fact that despite high volatility and steep losses markets for the most part remained resilient.
Geopolitical strategists can deploy AI systems trained on COVID19 disease transmission data and trade flow shifts to identify evolving cross-border economic and political relationships nearly in real time.
Central banks and fiscal authorities will train their AI systems using financial flow data (both at the wholesale and the consumer level) to identify the next generation of optimal monetary policy and liquidity policy structures, possibly executed through central bank digital currencies which may rely on blockchain technologies.
The unprecedented delays in meeting first quarter regulatory reporting and accounting deadlines will incentivize companies and their regulators to accelerate development of automated compliance processes executed at least in part with the assistance of AI systems that can recognize which exposures belong on which form.
The massive disruptions to daily and business life globally will inspire (or require) people to take advantage of artificial intelligence and other analytical automations so that they are better prepared to handle the next set of challenges.
To be sure, these advances create their own risks. The most important of these at the policy level are with respect to personal data privacy and potential abuse by authoritarian governments. At the individual level, disruption can be wrenching. Skill sets will need to improve rapidly. My chapter in the AI Book suggests a few ways to address these issues.
The good news is that humans are good at adapting. We learn. We can use the data from the current disruption to teach AI systems to help us analyze difficult situations faster and better.
BCMstrategy, Inc. is an early stage technology company that uses patented processes to measure public policy risks globally and daily through the PolicyScope toolkit. During April 2020, due to the severity of the pandemic, access to all PolicyScope tools are available free of charge. To start seeing global public policy reaction functions regarding COVID19 and other policy issues using objective, transparent data, contact us today.