Note: This is the second article in a two-part series on the Jamie Merisotis book, “Human Work in the Age of Smart Machines,” concerning the use of artificial intelligence (AI) in the workplace and how the workforce will need to adapt to the challenge of working alongside smart machines.
If the transparency of credentials makes them clear to all interested parties, how do we accomplish that? Mr. Merisotis writes that the first step is to use common frameworks to define knowledge and skills.
National skill frameworks are common in the developed world outside of the United States. The European Qualifications Framework (EQF) was developed by the European Commission to make credentials comparable across all European Union (EU) member countries.
Frameworks are not the standalone solution, however. Using a common framework to build a transparent system is the answer. Mr. Merisotis writes that we can reserve flights and hotels, research and compare products and services, and access financial information, thanks to common definitions utilized by the many providers hosting that information.
According to Mr. Merisotis, a great example of a transparent credential system in action is the EU Europass. The Europass includes a standard resume template and a European skills passport that individuals can attach to their resume to document their skills and qualifications. More than 130 million Europasses have been created since 2005.
At the same time, learning pathways should not be based on credit hours earned at an academic institution, but should be based on the specific knowledge and skills people gain through formal and informal education, work, or life experience. While competency-based learning is an alternative today, Mr. Merisotis writes that competency-based pathways through learning and working will become the norm and not the exception. He further adds that our entire system of higher education is based on the belief that quality is intrinsic to the institution rather than the learning that students obtain.
Today’s consumers of higher education are gaining greater leverage in the marketplace, putting pressure on established “brands” to produce results that students want. Transparent credentials are owned by the individuals who earned them.
With transparent credentials, individuals can leverage their learning to advance their careers, do meaningful work, and build better lives. Rather than learning to work, in a world of human work, learning is working and working is learning.
But the future of work will require both the education system and the employment system to change to focus on individuals. Mr. Merisotis writes that we make that change by focusing on learning, rather than education, and on work, rather than jobs.
People working in the field of education know that the school-college-work pathway stopped being the model for most people a long time ago, according to Mr. Merisotis. Lifelong learning — the pattern of learning first, then work, then learn some more, then work and repeat — replaced it. At the same time, we continued to maintain two distinctively different systems, education and work.
The field of human work breaks down the division between learning and working. In the human work ecosystem, education and employment are tied together in unprecedented ways. Work offer opportunities for active learning that develops higher-level thinking skills and human traits.
Mr. Merisotis writes that in the new human work ecosystem, people will be worker-learners because learning and working happen together. Employers need to embrace their role as developers of talent and not expect someone else to do it. In order to incentivize employers, he writes that we need to rethink tax policy as well as accounting standards to make sure investing in people is viewed as an enterprise essential and not just a benefit to employees.
In his last chapter, Mr. Merisotis writes that we need to examine politics in order to understand the broader ways technology is changing our society. In areas where technology has disrupted the job market, voters are more likely to support candidates who call for radical change. Regions that are thriving are also regions where residents are better educated.
AI not only impacts jobs, but it also serves to direct the flow of information and shape public opinion. Thanks to AI, people are able to live in bubbles where the information that they receive reflects their existing perspectives and prejudices. The combination of big data and social media allows those who want to influence elections to do so. The best way to counter these trends is to improve and increase the education of the citizenry.
Mr. Merisotis writes that critical thinking, problem solving, and communication skills, along with ethical thinking and decision making, are no longer necessary just for those with better jobs. These traits are essential to a democratic society.
There are two serious problems for countries like the U.S. First, global literacy has to be a critical priority in a world with few boundaries, an integrated economy, and challenges requiring coordinated international responses (think COVID-19).
Second, graduates of our education system are poorly prepared to succeed in a global environment. They lack “an awareness of history, appreciation of the complexity of the biosphere, and understanding of economic trends and tensions.” For a better-educated citizenry, degrees must include global literacy as a required competency.
Mr. Merisotis concludes by writing that no one knows what will happen with the future of work. However, these four concepts are important to build into baseline changes to adapt to future trends:
- Work brings meaning to our lives.
- Human work is learning and serving as well as earning.
- As AI and other technologies automate repetitive tasks in all jobs, human work becomes less about specialized expertise in one task or set of tasks.
- Human work requires fundamental changes in our systems for earning, learning, and serving.
An optimist, Mr. Merisotis writes that everyone has a role to play in making sure that his recommended changes occur. Employers can begin by defining transparently exactly what they need in terms of the knowledge, skills, and abilities that workers need to have. They also need to assure that workers can develop their talents throughout their career and life by ensuring that everyone has access to continuous learning.
Educators will need to question almost all the assumptions that have guided the development of our current systems starting by focusing on the success of all students. Students will need to be equipped with learning that enhances their human traits, such as compassion, empathy, and ethics.
Policymakers need to scrap funding approaches that treat education and training as separate activities performed by separate systems. Philanthropies such as foundations that focus on education and workforce development should view their strategies through the lens of preparing people for human work.
Also, workers need to own their learning in the same way that people need to own their health. It’s not enough to know what credentials you have earned, but communicating what you know and can do to current and potential employers is vital.
As the CEO of the Lumina Foundation for the past dozen years, Mr. Merisotis led his organization down a number of pathways of research, experimentation, and implementation of higher education changes. I applaud him for Lumina’s role as a forward thinker in this area. If anyone could write concisely (173 pages) about a topic like human work, Mr. Merisotis would be one of my top choices.
If it isn’t clear from my brief overview — or from the book if you choose to read it — the pathway to integrate work and learning is complicated and a heavy lift for all participants. Mr. Merisotis provides a number of examples of frameworks, individual pathways, and employer pathways as possible outcomes when individuals combine work, training, and education successfully.
One of the projects sponsored by Lumina is the Degree Qualifications Profile, a learning-centered framework for what college graduates ought to be able to do after graduating with an associate, bachelor’s, or master’s degree. First developed in 2011, version 3.0 is expected to be released in early 2021. Institutions that have embraced and implemented the DQP should be able to identify the competencies and assessments required for learning and earning degrees in multiple fields.
American Public University System (APUS) was one of the early implementers of the DQP. Our decision to implement a framework like DQP was based more on a desire to demonstrate that online courses and degrees were as academically solid as face-to-face courses and degrees.
It was a heavy lift, but by embracing it as an institution, we reinforced a culture of aligning degrees with industry or graduate school expectations. At this writing, there may be approximately 800 higher education institutions that have piloted or implemented the DQP.
While the number is low compared to all colleges and universities, it’s a large number for establishing the DQP as a viable framework for transparent competency and learning objectives. Ironically, there are AI-enhanced tools that could be utilized to ingest course syllabi and objectives in order to build the DQP framework.
There are a number of risks for accomplishing the pathway that Mr. Merisotis proposes for learning and working. The two biggest risks are:
- The established higher education institutions are resistant to change, particularly quick changes.
- Some of the largest and better capitalized employers in the U.S. may have opportunities to recruit and hire employees across the globe, thereby avoiding shortages of individuals needed for human work in the U.S.
We will need alignment and commitment from employers, educators, policymakers, philanthropists and workers to make this happen. I not only recommend reading the book, but I recommend embracing it and implementing changes with the goal of embracing Mr. Merisotis’ proposed pathway. It will enhance our nation’s quality of life in ways too numerous to mention.
