’s Several People Are Typing
blog, Matt Haughey
summarizes a recent talk by Ken Norton
on How to have meetings that don’t suck.
All of it is good, but two points jump out for me:
Your calendar doesn’t make you important and shouldn’t postpone decisions. Ken knows firsthand that an overloaded calendar can delay progress. He was once in charge of 20 designers and engineers on a long-term project, but he spent most days in senior leadership meetings. When he’d return to his desk at 5pm, he’d be swarmed by his team asking him to approve designs and make decisions that were holding the project up. When he realized they’d been waiting hours for him to arrive, he knew missed deadlines were likely due to his own overbooked schedule.
Declare calendar bankruptcy. Want to reboot your old meeting culture? Rip the Band-Aid off by picking a date in the future when absolutely every meeting on every calendar is canceled in a company, and only ones deemed most necessary and important can return. It’s not easy, but it’s a good way to reset expectations and introduce a new, more healthy meeting culture.
ON THE FUTURE OF WORK
released a comprehensive report on the future of work, Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation
. My detailed review will have to wait, but I scanned McKinsey’s own summary
and got the gist [emphasis mine]:
Our new research estimates that between almost zero and 30 percent of the hours worked globally could be automated by 2030, depending on the speed of adoption. We mainly use the midpoint of our scenario range, which is automation of 15 percent of current activities. Results differ significantly by country, reflecting the mix of activities currently performed by workers and prevailing wage rates.
The potential impact of automation on employment varies by occupation and sector (see interactive above). Activities most susceptible to automation include physical ones in predictable environments, such as operating machinery and preparing fast food. Collecting and processing data are two other categories of activities that increasingly can be done better and faster with machines. This could displace large amounts of labor—for instance, in mortgage origination, paralegal work, accounting, and back-office transaction processing.
It is important to note, however, that even when some tasks are automated, employment in those occupations may not decline but rather workers may perform new tasks.
Automation will have a lesser effect on jobs that involve managing people, applying expertise, and social interactions, where machines are unable to match human performance for now.
And the most headline grabbing guesstimates:
Upcoming workforce transitions could be very large
The changes in net occupational growth or decline imply that a very large number of people may need to shift occupational categories and learn new skills in the years ahead. The shift could be on a scale not seen since the transition of the labor force out of agriculture in the early 1900s in the United States and Europe, and more recently in in China.
We estimate that between 400 million and 800 million individuals could be displaced by automation and need to find new jobs by 2030 around the world, based on our midpoint and earliest (that is, the most rapid) automation adoption scenarios. New jobs will be available, based on our scenarios of future labor demand and the net impact of automation, as described in the next section.
However, people will need to find their way into these jobs. Of the total displaced, 75 million to 375 million may need to switch occupational categories and learn new skills, under our midpoint and earliest automation adoption scenarios.
I will be writing something more in depth on their analysis as soon as possible. But the takeaway is stark: more than 500 million (and perhaps a billion?) workers could be automated out of their jobs or occupations.
I have to say that McKinsey is taking a strong otherist
position here; this is not waving away the potential for major impact by saying it’s just another technology wave
. This is acknowledging that AI is unlike other technologies because it emulates and outruns human cognition. Contrast that with Cognizant
claims I wrote about earlier this week