This year’s Cyber Monday was the single biggest online shopping day in US history, with $6.6 billion in sales. Focusing solely on e-commerce misses a key storyline, as Fast Company suggests. It profiles companies thinking creatively about brick-and-mortar experiences and how they differentiate from Amazon. Target, for example, is focusing on its exclusive house brands to build market share, to promising results:
Cat & Jack [a Target children’s brand] customers, for example, spend 50% more in surrounding kids’ retail areas. … Most significantly, Target’s consumer research has shown that its brands have become a “trip driver”: People come to the store for Cat & Jack as much as they do for essentials like laundry detergent or bread or milk.
Technology companies are living up to their transformative promises, argues economist Tyler Cowen, citing GDP growth and low inflation. Cowen’s recent Bloomberg column echoes the assessment he made at our recent G100 meeting:
The tech companies have shown that their radical model of low price, high market share, high quality rapid expansion will keep them profitable for a long time to come. That’s big news but not the kind of information connected to a discrete event, so it receives less attention than President Donald Trump’s latest antics or the progress of the Republican tax bill. Still, I suspect this is the missing piece of the puzzle that helps explain the Goldilocks scenario for the macroeconomy.
Over the next 15 years, automation could lead to 21 new job categories and 21 million roles, replacing 19 million eliminated positions, per a new study from Cognizant’s Center for the Future of Work. More on these new roles from The Wall Street Journal:
“Man-machine teaming managers” will be needed to ensure machines and human workers collaborate in a way that maximizes results, the study says, while “cyber city analysts” will see that municipalities’ digital systems and processes function smoothly. On the low-tech end of the spectrum, the study describes rising demand for “walker-talkers,” gig workers who answer calls to assist and provide companionship for a growing elderly population as people live longer.
As machines teach themselves to solve increasingly complex problems, researchers find they can no longer explain exactly how these machines develop and refine their algorithms. The nascent field of X.A.I, or explainable AI, seeks to address the disconnect between human and machine decision-making and enable machines to translate their own workings – even as their computing processes move beyond human comprehension. Drawing on work by DARPA and Google, The New York Times explains the stakes:
In many arenas, A.I. methods have advanced with startling speed; deep neural networks can now detect certain kinds of cancer as accurately as a human. But human doctors still have to make the decisions — and they won’t trust an A.I. unless it can explain itself.
What can youthful countries like Nigeria, Indonesia, and Vietnam teach us about the tech-enabled gig economy? Anne-Marie Slaughter, CEO and President of New America, explores work platforms in dynamic informal markets:
Flexibility and uncertainty define informal markets in developing countries. Those lucky men and women who have formal jobs (less than 40%) often have “side hustles” through which they sell their time, expertise, network, or ideas to others in an effort to hedge against an uncertain labor market. A Nigerian saying – “you have a 9 to 5, a 5 to 9 and a weekend job” – aptly describes the environment of layered work. The same pattern is starting to emerge in developed countries.
