How To Think About AI and Work, Post COVID-19

When work is unpredictable, humans win. The coronavirus emergency is showing how the best artificial intelligence augments, rather than replaces, human skills.

There are very real limits to how effective AI can be in tackling the coronavirus pandemic. AI relies on data to learn and the world’s data has been completely disrupted by the novel coronavirus. The impact on the accuracy of AI—particularly AI that relies on supervised learning techniques—must surely be significant. 

During past disruptions (the dot com bust, the 2008 financial crisis), only one or two industries were primarily affected. But the pandemic has affected every industry, in every country, in every corner of the world. AI tools can help with rapid adjustment of traditional models, namely forecasting models. But decision processes require adjustment so that people understand new interdependencies and complexities. This will require the ultimate marriage of AI and human expertise. 

Humans thrive on unpredictability

In 2016, as Intelligentsia Research, we conducted our own research because we wanted to understand the key drivers of human skills and how they may be replaced. We found that, even though machines indeed met or exceeded human capabilities in many areas, there was one common factor in the research where artificial intelligence was no match for humans: unpredictability. This is exactly what we have now and likely we will for some time yet.

Where a job requires people to deal with lots of unpredictable things and messiness — unpredictable people, unknown environments, highly complex and evolving situations, ambiguous data—people will stay ahead of robots. Whether it’s creative problem solving or the ability to read people, if the environment is fundamentally unpredictable, humans have the edge. 

We found four themes where jobs for humans will thrive:

  • Human interaction and “people”—jobs that require people to interact with people in situations that require empathy to be combined with action, where a person makes a decision about another person’s decision and where deciding on the best course of action or evaluating an individual is highly context-dependent. This includes jobs that rely on strong interpersonal skills like chief executives, school psychologists, social work teachers, and supervisors of a variety of trades.
  • Analysis and “numbers”—jobs that require adept treatment of data, require dealing with ambiguous data and jobs where the task is one of both wrangling with numbers but also needing to display wisdom in the data at the same time. These are jobs that apply math to business problems, like economists, management analysts, and treasurers.
  • Hazards to human health—jobs where the puzzle of determining the best path forward is a complex and uncertain mix of new toxins, pathogens, and environmental, economic and psychological factors. This includes human health-related jobs, like allergists, immunologists, and microbiologists and other environmentally-oriented professions such as toxicology.
  • In-situ physical spaces and structures—jobs that involve fitting or designing in the physical world and manage the uncertainties and challenges that arise between the design ideal and the world, like engineers and environmental scientists.

While AI can learn and adjust rapidly, we should expect that all AI models will exhibit less accuracy than before the crisis. This means human expertise will be vital. It will also be critical that humans are visibly accountable for decisions. Humans judge machines differently than they judge other humans. Humans judge humans by their intentions, while they judge machines by the consequences. 

The implications of this principle are far reaching. It means that people using AI need to be able to intuit the human intent behind it. It means that humans are forgiven for mistakes, as long as their intentions are good, while machines are not forgiven if a decision results in an unfair outcome, even if this outcome was accepted as possible right from the outset. Humans can take risks in ways that machines cannot. 

We believe that there are important signs about the future of work that this crisis reveals. 

AI is about helping people, not replacing them

Many hospitals and essential services are using robots instead of people. But does this mean that jobs are being automated away? Not necessarily. A recent survey of the role of robots in the pandemic response conducted by researchers at Texas A&M shows that robots either perform tasks that a person can’t do or do safely, or take on tasks that free up responders to handle the increased workload. 

“The majority of robots being used in hospitals treating COVID-19 patients have not replaced health care professionals. These robots are teleoperated, enabling the health care workers to apply their expertise and compassion to sick and isolated patients remotely.” 

AI-enabled surveillance of workplaces will be inevitable

Everyone wants to get back to work. But how can this be done safely? We see two routes; physical proximity surveillance and remote productivity surveillance. 

For example, Landing AI has developed an AI-enabled social distancing detection tool that detects if people are keeping a safe distance from each other by analyzing real time video streams from the camera. While developed for a manufacturing environment, it isn’t difficult to imagine such physical surveillance tools deployed in office environments along with nudging that helps remind workers to stay at a safe distance and practice high standards of personal hygiene. In fact, it’s quite possible that legal liability concerns make it a certainty that employees are required to opt in to some form of digital tracking before they return to work. In the event that someone becomes ill, employers need to be able to support contact tracking.

Remote productivity tracking is growing faster than ever. Employee surveillance tools that were once used in relatively narrow ways and focused on specific industries (such as to detect insider trading in the finance industry or for time tracking in consulting businesses) are increasingly being adopted by companies that have sent employees home to work during the pandemic crisis. It’s difficult not to see these surveillance tools become more ubiquitous, passive in how they collect data and powerful.

The biggest opportunities are for AI to support human cognition

In 2016 we found that the most interesting new product opportunities were in management and planning. The opportunities that combine high value-add and large market opportunities include functions like managing financial resources, monitoring resources, directing subordinates, developing objectives, and providing advice.

Planning under uncertainty is difficult and we need AI that supports human cognition, including accounting for our natural biases. For example, humans struggle to understand exponential growth. Our brains have a linearity bias – we tend to see change in linear terms and struggle to comprehend the magnitude of exponential growth.

There are many reasons that the USA wasn’t prepared for the pandemic but this feature of our cognition is part of the story. Countries that have previously dealt with SARS know what exponential feels like; they have been through the emotional conditioning required to mobilize quickly and have been able to act ahead of a visible appearance of catastrophe.

AI has a role to play. Because humans are good at considering our own cognitive strategies — something Tom Griffiths calls meta-reasoning — there are opportunities to develop AI that acts as a “cognitive crutch.” AI thinks in multiple dimensions, is able to handle exponential growth, so can help us think differently about the world. AI can show us alternate futures in ways that can overcome our cognitive limitations and motivate us to act differently.

And connection

In 2016, we found that the highest value-add AI opportunity was in communicating. The best opportunities to add value were in augmenting a human’s need to communicate through AI that can listen, speak, and have the social perceptiveness required to communicate.

The current crisis emphasizes communication and connection. We need to speed up processes that require humans to communicate, plan and manage under uncertainty. AI that supports this by automating mundane or repetitive activities, allowing humans to spend more time on things that machines fail to do or that humans don’t want machines to do, will be in demand. People who know when to step in, know how to motivate others in a variety of situations and contexts and who can show leadership by expressing their own unique human needs will be prized.

Human connection is a complicated thing. It requires each person to have the agency to act, to choose to connect, to actively reach out. The deepest connections require each person to show up, to be vulnerable, to risk something. This requires each person to have empathy, try to understand the other and then to work together to solve problems. This will be the skill that becomes most-prized in the workplace.

Perhaps that is how we will look back on this crisis. As we build anew, it takes humans to make decisions because people will not accept poor outcomes from a machine. It will take human intelligence, working in partnership with AI, to lead in an unpredictable post-COVID-19 world.

Photo by Christopher Burns on Unsplash

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