LearnerShape and the Future of Work

Hello, world! This is the LearnerShape blog. LearnerShape was founded in 2019 (based upon ideas developed since 2017) to compute learning pathways for future jobs, using robust data science. We are funded by a grant from Innovate UK (the UK government innovation funding body) and private investors.

We intend this blog to focus on the education technology ecosystem addressing the ‘future of work’ — including issues of reskilling (training people for new jobs) and upskilling (augmenting skills for changing job requirements) — although we are likely to wander into related areas that interest us, including the edtech sector more generally, and data science (including artificial intelligence and machine learning). This first post briefly describes the core problem that we are solving.

The future of work problem, and the challenge of reskilling and upskilling in particular, is widely recognised. Professor Klaus Schwab, founder of the World Economic Forum, is widely credited with coining the term ‘Fourth Industrial Revolution’, the technology-driven upheaval that individuals and organizations are currently experiencing, involving a rapidly-changing jobs market. There have been widespread forecasts of job losses due to these changes, although others believe that new technologies will create as many jobs as they eliminate — influential reports on these issues include those from PwC and the World Economic Forum.

We don’t have a crystal ball, or a strong view on the size of job losses or gains, yet we are convinced that there is effective certainty of substantial change in the workplace. This is already occurring. Many companies have already realised that determined action is needed to address these challenges. For example, Amazon announced in July 2019 that it will spend $700 million through 2025 to retrain about 100,000 US employees. About two years earlier, AT&T announced that it will spend about $1 billion to retrain a similar number of workers — nearly 40% of its workforce. In large part these programs are driven by the simple observation that it is more effective to retrain existing workers for new skills and new jobs, compared to extensive and disruptive hiring and firing.

LearnerShape’s mission is to help organizations and individuals to address these challenges by identifying likely future skill gaps, and building learning pathways to fill those gaps. Our services are intended to meet the needs of both organizations and individuals.

There are many other companies, from startups to mature players, working to address future of work challenges. This level of attention is welcome, because addressing this problem will require a complex ecosystem — and a huge amount of innovation will be needed. As stated succinctly by one of our earliest supporters, a startup CEO, “no one has cracked this problem”.

Our solution is based on robust principles and technology. We depend upon the trust of customers and learners in high-quality, unbiased learning recommendations, based upon a deep understanding of how humans learn. And we have a conviction that there is a huge opportunity to leverage advances in machine learning and data science to improve the quality of our recommendations. The technical and business details of our solution are confidential for now. Please sign up for our mailing list to receive more information!

Maury Shenk
Co-Founder & CEO, LearnerShape