Daniel Araya, PhD
From the proliferation of sharing platforms like Airbnb and Uber to the advent of blockchain networks and advanced robotics, the nature of work is changing.
Much of this change is grounded in artificial intelligence (AI).
AI is now the basis for a wide range of mainstream technologies including web search, medical diagnosis, smart phone applications, and most recently, autonomous vehicles.
According to MIT researchers, we are moving into a “Second Machine Age” in which advanced technologies have begun automating work across multiple industries. Studies on automation vary but researchers at the University of Oxford suggest that as much as 57 percent of jobs in OECD countries could be automated over the coming decades. In fact, researchers at Gartner indicate that as many as one-third of all jobs could be converted into software and robots by as early as 2025.
Given the inherent capacity of technology to automate labor, it stands to reason that developing the right kinds of learning and development (L&D) systems is now fundamental to the future of work. As Gartner explains, the need to use current and emerging technologies is now a driving force of change across industries. Unfortunately, too few companies understand the compensatory investment needed to offset these challenges.
When anything mentally routine or predictable can be reduced to an algorithm, it signals the need for a profound shift in our learning systems. Beyond basic skills and capacities, advanced competencies that build on networked collaboration, digital fluency, and creative innovation will become increasingly critical to economic growth and mobility.
According to Gartner, AI bots will power 85 percent of customer service interactions by 2020 and drive as much as $33 trillion in annual economic growth. Building on this assessment, PwC forecasts that chat bots will significantly reduce the costs of hiring by adding sentiment analysis and computational linguistics, accelerating the selection process. Of course all of this hinges on reducing bias in the design and evolution of algorithmic systems.
What is obvious is that the proportion of stable and routine jobs in manufacturing and service industries is declining. Even as the proportion of non-routine jobs and higher cognitive skills is expanding. This interpretation of labor trends is supported by research in Europe as well. According to a report by the British think tank Nesta, creative work remains the only strategic response to automation and robotics. To be sure, creative occupations are simply more resistant to automation.
Following this line of reasoning, Richard Florida argues that creativity is the defining principle of our age. In his view, waves of “creative destruction” now challenge basic assumptions about the management of our society and its institutions.
One of the key questions we face today is with regard to how corporate L&D systems can leverage AI to augment human labor. Beyond the bureaucratic systems of the Industrial Age, workers today must be better prepared to leverage technology to solve complex real-world challenges. Beyond rigid curricula we are witnessing a fundamental shift in power toward personalized learning.
Leveraging machine learning systems, corporate L&D systems will need to increasingly focus on “experience design,” and “design thinking,” to more closely align with experimental and data-driven work flow solutions. The enormous amount of data that AI collects and analyzes can provide significant insights toward the evolution and creation of customized learning programs.
Rather than framing L&D in terms of the needs of routine labor, corporate learning system will need to bridge the creative capacities of workers with advanced computational technologies in the evolution of “augmented intelligence”. This is a move from scalable efficiency to scalable learning. It is also a shift in mindset from expertise or “knowing” to learning as Design Thinking.
As we move from the Information Era into the Augmented Era, demand is growing for a profound shift of focus in learning and workforce development. Rather than assuming that the purpose of L&D systems is simply the transfer of fixed knowledge, Design Thinking facilitates the development of the entrepreneurial dispositions and skills necessary to adapt to rapid social and technological change.
What this means is that corporate L&D systems will need to pivot from professional training to personalized learning in the context of autonomous creativity and problem-solving. This is precisely the distinctive advantage of companies like IDEO, Apple, and Google. Design Thinking embodies basic principles first described by Nobel Prize laureate Herbert Simon: Empathize with users, define user needs, ideate, prototype, and finally test solutions.
At the heart of Design Thinking is the cultivation of curiosity, in order to challenge assumptions and find solutions. Put differently, Design Thinking is a methodology for solving problems using the kinds of strategies that designers use. The value of Design Thinking is that it augments human capabilities alongside the impressive capabilities of intelligent machines. Design Thinking utilizes elements from the digital designer’s toolkit: empathy, experimentation, and intuition to arrive at innovative solutions.
Even as AI is forecast to match and even exceed human capabilities across a range of skills, it is also predicted to augment labor. Knowledge workers who can leverage technology to evolve creative work and learning through Design Thinking will have a competitive advantage in this new era. The simple truth is that even as computers excel at many logical functions, they are simply not as efficient or effective as human beings at tasks requiring flexibility and judgment.
The value of computers to human cognitive capabilities is their capacity to augment human intelligence, especially the uniquely human capacity for design and innovation. The ever-growing integration of human intelligence, neural networks and cloud driven big data is driving changes in the nature of L&D. By replacing workers who do routine, technical tasks, for example, AI will accelerate the comparative advantage of workers with complementary skills: problem solving, leadership, empathy and creativity.
As Deloitte’s Global Human Capital Trends report explains, in order to increase productivity L&D systems must decrease complexity. This means putting employees at the center of learning in the context of Design Thinking. More concretely it means leveraging AI and other disruptive technologies to empower workers to creatively locate and solve problems as they arise.
We stand on the precipice of a Fourth Industrial Revolution. Beyond (1) steam, (2) electricity, and the (3) microchip, this Fourth Industrial Revolution is being powered by Big Data, machine learning, and automation. Just like previous technological revolutions, work will be adapted to new needs, new markets and new learning systems.