What did we learn from working from home during Covid?

Lena Anayi, John Lewis and Misa Tanaka

Since the onset of Covid-19, firms and workers have adopted and adapted to new working arrangements, which involved some workers primarily or exclusively working from home (WFH). What lessons – if any – can be drawn from this experience to inform future of work? A previous blog post examined how WFH might affect productivity. This blog post reviews more recent research on the experience of WFH during Covid, and considers what can be learnt about the impact of WFH on time use, workplace interactions and productivity.

Continue reading →

Using machine learning to understand the mix of jobs in the economy in real-time

Arthur Turrell, Bradley Speigner, James Thurgood, Jyldyz Djumalieva and David Copple

Recently, economists have been discussing, on the one hand, how artificial intelligence (AI) powered by machine learning might increase unemployment, and, on the other, how AI might create new jobs. Either way, the future of work is set to change. We show in recent research how unsupervised machine learning, driven by data, can capture changes in the type of work demanded.

Continue reading “Using machine learning to understand the mix of jobs in the economy in real-time” →