Insights from the IFC Conference: Learning for the Jobs of Tomorrow


The IFC 8th Global Private Education Conference was held last week in Cape Town, South Africa which had the theme of ‘Learning for the Jobs of Tomorrow’, bringing together leaders impacting education from across the globe — a total of 370 participants, from 238 organizations, in 50 countries. I had the privilege of attending as the Chief of Staff of Nova Pioneer, an organization aiming to empower African youth to be the innovators and leaders of the 21st century.

Keynote speaker Gary Bolles (Chair for the Future of Work at Singularity University) highlighted trends in exponential technologies like AI and the dramatic impact they will have on both what future will look like and what future learning models must necessarily put more focus on to prepare students to succeed. Other sessions covered a range of related topics, including how foundational education models can evolve related to both the “what” and the “how” of learning, how a range of alternative learning providers and associated credentials can make the employment market more efficient, and how all stakeholder groups can remain agile in optimizing the education to employment pipeline.

Among the plethora of intriguing ideas and insights shared across the different conference sessions, I walked away with a few main reflections on the future of learning:

1. Evolution & Interdependence Among Stakeholder Groups

When considering the challenges that relate to an individual student/job seeker successfully progressing through the education to employment pipeline, there are numerous stakeholder groups that may impact the success of that student: K-12 education providers, higher education institutions, other education to employment initiatives, other nano-degree learning programs, the government, and employers themselves.

When we say the education “system” must evolve to adapt to the world of workforce automation, what we are really saying is that each of these individual stakeholder groups must evolve — and for each of them, that evolution may look different. For example:

  • K-12 Education Providers — can focus more on empowering students to succeed in an ever-evolving and ever-more-automated workforce by focusing on skills that are more “uniquely human” such as problem-solving, adaptability, creativity and empathy
  • Higher Education Institutions — can adapt more quickly to how to best equip students with the skills they need by creating tighter feedback loops with employers
  • Employers — can re-design their organizational structures to have humans working alongside technology to work in the most efficient way, but can also look beyond college degrees to focus on the skills that really matter and how to best test for them

One challenge in each of these stakeholder groups successfully evolving though is that many of them are interdependent on each other in a way that creates sub-optimal outcomes. For example, the vast majority of employers continue to focus on college degrees as a primary requirement for job readiness, despite their track record of an inability to consistently deliver optimal skill sets (not to mention their relative lack of accessibility). Continuing further back down the education lifecycle, the vast majority of universities continue to focus on test scores that incentivize K-12 education providers to put a disproportionate focus on test scores in a way that gives them less time to spend on innovative new models building the uniquely-human skills described above.

These interdependencies between education to employment stakeholders have created an inefficient gridlock, where none of the groups is operating in a way that allows the system as a whole to reach its optimal outcome — which is each student being most effectively prepared to succeed in the workforce and add maximum value to the economy. In order for the education system to successfully evolve, we must figure out how to breakthrough this gridlock.

2. The Valuable Role of a Central Facilitator

One dynamic that makes the challenge of designing the future of learning even more complex is that we don’t just have to solve the skills gap once. We have to be able to solve it over and over again. The exponential pace by which the workforce will evolve will mean that the education system itself will not only have to continue to evolve as well, but also do so at an increasingly faster pace. Therefore, agility of the system is crucial.

A second dynamic that is important to consider in this future state is the ability for the different stakeholder groups (mentioned above) to have some degree of a common language, including not only what skills are, but what proficiency in those skills looks like. This alignment would allow different stakeholder groups to be able to quickly and effectively communicate around the skills that are necessary in the workforce and how those skills can be developed through a combination of traditional and alternative learning providers. One company present at the conference, Degreed, was founded partially out of the dissatisfaction that college degrees are the only credential in the world that are universal; their aim is to change that by creating a lifelong learning platform that recognizes the diverse set of learning outcomes each job seeker builds over their lifetime that should be considered by employers.

When considering these dynamics together, it begs the question of whether there should be a “central facilitator” of sorts that acts as the connective tissue between job seekers, employers, and learning providers, and if so, what this player should look like (e.g., public vs. private? An aggregation of organizations or one large company?) A central facilitator could not only establish a common language among stakeholders, but also communicate (even proactively) where skills gap exist (or may exist) based on the skills that employers are demanding and the skills that job seekers are exhibiting and/or learning programs are providing.

One existing company that seems in a particularly good position to play this role of a central facilitator is LinkedIn — given their work connecting job seekers, employers, and learning programs (particularly after their acquisition of At the IFC Conference, I had the opportunity to ask the Head of R&D for LinkedIn Africa about LinkedIn’s role as a central facilitator during a panel Q&A, which you view at the 55:30 mark of this video.

3. Automation’s Impact on the Global Talent Marketplace

Though I thought speakers and panelists at the IFC Conference did an excellent job speaking to the different ways different education stakeholder groups can evolve to better prepare for the onset of workforce automation, one critique I had was not focusing enough on the reality that despite efforts from all those stakeholder groups, there remains the significant possibility that a significant portion of the global workforce is displaced from their current roles in the economy (even if just temporarily).

One dynamic that was pointed out during the conference that relates to this assertion is the fact that different geographies (countries, states, etc.) will be impacted by automation in different ways, largely influenced by the breakdown of activities in within a geography’s economy and how that breakdown relates to the type of activities that are more or less susceptible to automation. In Mexico for example, there are millions of people still working in manufacturing roles that are extremely susceptible to automation, making their economy (and the individuals in it) even more at risk.

One trend also covered at the conference that does offer some hope in response to this risk is the decreasing amount of friction between global talent markets — that is, if demand (from employers) for a particular set of skills is present in one region, and supply (from job seekers) of that skill set is present in another region, the global economy is getting better at matching that supply and demand, which in theory may slightly lessen the blow of automation to particular regions.

Andela was the most notable company present at the conference that is actively contributing to breaking down barriers in the global talent marketplace. The company’s model involves training software developers across Africa and providing global technology companies access to this talent, while the individuals remain in their home countries. This is just one example of how barriers can be reduced in the global 21st economy, and it is a huge opportunity for players in the global economy to explore how the success of Andela can be replicated in other industries and geographies.

The Robots are Coming: An Introduction

1. The Scenario

As you pull up to LaGuardia airport, you hop out of the Uber that transported you, along with two other Manhattanites who set across the table from you in the car, which was quite spacious in the absence of a driver.

You head to the Delta check-in desk, where a computer prompts you to look directly into the camera above the screen. After the facial recognition technology kicks in, a check mark pops up on the screen along with your SkyMiles rewards number and prompts you to put your checked bag on the conveyor belt. At the security checkpoint, you make your way to the TSA Pre-Check line, and after the 10-second full body and baggage scan, a green light appears to signal you are free to proceed.

Finally on the plane, you order an orange juice and a decaf coffee from the television on the seatback in front of you, and about thirty seconds later, the two drinks emerge on the armrest next to you. Just under an hour later, a robotic voice comes on over the intercom to update you on the local temperature in Boston and the updated arrival time of the autonomous Boeing 717.

As you are getting into the aisle to depart the plane, you motion to the family in the row behind you that they can go in front of you. On a Monday morning in a previous life, you may not have been as generous with your time, but hey, you don’t have anywhere to be today. You don’t have a job.

But then again, neither does anyone else.

2. The Issue

The accelerating rise of artificial intelligence, robotics, and other exponential technologies threatens to disrupt the workforce as we know it, with millions of jobs at risk of either partial or complete automation. The potential disruption could result in anything from, taking a conservative view, a drastic shift in the the makeup of the type of tasks humans perform in an economy and the associated skill sets that will be required from them, to at worst, a significant proportion of the global population being displaced by automation to the point of long-term mass unemployment across all industries and regions.

Some skeptics may rightfully point out that ill-founded stories of robot-induced mass unemployment have been threatened to be on the horizon for decades, from former US President Lyndon Johnson, who in the 1960’s warned of an impending “cybernation revolution” that would result in widespread unemployment, all the way back to John Maynard Keynes in the 1930’s who predicted an imminent “disease” of “technological unemployment” that would have a dramatic impact on the economy.

However, the current wave of automation is radically distinct from these previous eras, with exponential technologies having accelerated more in the last 5 years than they have in the last 50, leading to more and more companies starting to automate not only routinely programmable tasks, but also tasks that require complex cognitive capabilities that have until recently been assumed to require “uniquely human” skills.

A detailed study by Oxford University in 2013 suggested that 47% of jobs in the economy were at risk of being automated in the next 20 years, which was one of the first smoke alarms in recent years that seemed to convince some of the general public to start paying more attention to the issue. Since then, other leading research centers have conducted a number of additional analyses with varying methodologies that have predicted similarly worrisome results. In 2016, the World Economic Forum released findings that even when accounting for the jobs that would be newly created from exponential technologies, the net impact of automation in the 15 countries studied would be 5 million jobs lost by 2020. And in 2017, the McKinsey Global Institute conducted extensive research on the potential for automation and concluded that 50% of all activities in the global economy could be automated using technologies that are already in existence today.

With more and more data-driven studies supporting the validity of this impending shift in the workforce, and more and more companies providing real word case studies by beginning to automate certain parts of their labor force, there is an emerging consensus of the large impact that automation will have on the workforce. There are significantly divergent views, however, on what exactly that impact will be, what the implications of that impact are, and what society should do about it.

While influential figures such as Bill Gates, Elon Musk, and Stephen Hawkings (prior to his passing) have infamously leaned towards the more negative side of the spectrum of the doomsday-like risk that Artificial Intelligence poses (both in the workforce and more broadly in society), others have predicted a mere shift in the workforce that results in less unemployment and more “redeployment” (that is, many jobs will be lost, but many jobs will also be created, so a large number of people will have to pivot to new occupations).

Suggestions on what society should do about this impending impact have diverged even further from a consensus, ranging everywhere from implementing a robot tax, to numerous deviations of some form of universal basic income (UBI), to ultimately fusing human brains with artificial intelligence (if you can’t beat ‘em, join ‘em?)

Whatever the result of accelerated artificial intelligence, robots, and automation, large scale impact to the workforce is imminent. And among the numerous areas in society that will likely experience domino effects of dramatic changes when such a large scale impact to the workforce occurs, the education sector may be one of the most significant. The inherent objective of education in society, in its most simplified form, is to prepare students for the workforce. Thus, if the workforce itself transforms dramatically, the education sector may have to undertake a proportionally dramatic transformation to continue to deliver on its aforementioned objective.

This imminent challenge for the education sector may prove to be incredibly difficult, especially when considering the “Skills Gap” (that is, the disconnect between the skills required in the workforce and the the skills the education sector is equipping students with) in the United States and around the world has already increased dramatically in recent years, with substantially larger changes to the workforce still on the horizon.

3. The Blog

I’m starting this blog to follow an issue that I believe will be hugely important to the future of our economy, our livelihood, and society as we know it. I’ll aim for my analysis to be evidence-based when possible, but rather than dive into technical nuances of artificial intelligence, I’ll focus more on theorizing about the broader societal implications with a healthy dose of everyday layman speculation and conjecture.

While the blog’s title and opening scenario above are intentionally provocative, painting the picture of a Hollywood-ready storyline about the complete takeover of robots in the economy, the reality is that even if we were headed towards significant unemployment, there would likely be a substantial runway time period of adoption, which is why questions like educating for the workforce of the future would still remain relevant.

Fundamentally, the guiding questions of my blog will be:

  • What impact will automation have on the workforce?
  • How will the education sector need to adjust in response to that new workforce?
  • What other implications will workforce automation have for society as a whole?

I’ll kick-off the blog by summarizing some past material that I believe is most important to a foundational understanding of the issues. From that point on, I’ll use the blog as a way to aggregate the latest research, analysis, and opinion on workforce automation and related issues, with a small dose of unsolicited commentary over the top — connecting dots, playing devil’s advocate, and posing further questions.

Though the original impetus to create a blog came from a personal desire to follow the issues around workforce automation and organize my own thoughts around its implications, my hope is that this can also be helpful to those who share similar interests and who might offer their own feedback, comments, and suggestions, as we as humanity face what I think will be the largest societal shift of our lifetime.