Time Poverty and the Invisible Load of Care

I pointed out on social media a few days ago that we don’t talk enough about the very real issue of time poverty in response to a ridiculous article that stated AI would give people too much “free” time and leisure. The article was ridiculed enough so I won’t share it here, but it’s clear the author has never been a care giver nor understands the absurd underlying notion implying that time does not belong to us in the first place.

Interestingly enough a somewhat related item appeared yesterday about the Invisible Load, the tasks and systemic issues that create burdens for care giving women. Rula Health took a survey of women in 30 cities and found that 81% said they are frequently overwhelmed by the hidden labor of keeping track of family needs and managing responsibilities.

We have discussed the importance of time previously, but what was super interesting about this snapshot was seeing how much of the responsibility burdens were tied to transportation and access. Managing appointments, managing kids’ social lives, grocery and supply runs require movement and access. If not proximate, they likely contribute a larger share to time poverty, especially for the transport insecure.

This work is unpaid and as Melissa and Chris Bruntlett note in their book Women Changing Cities, it doesn’t show up in formal statistics. Our GDP measurements don’t accurately measure this work. From a transportation planning standpoint, trip purpose pie charts only go so deep into what trips are for and who makes them. Invisible indeed.

But it doesn’t have to be. Cities could survey people just like Rula Health and come up with solutions to what is now made invisible. In other parts of the world they have already. In Bogota they’ve set up Care Blocks to provide more proximate services to care givers. In Barcelona, the Superblock set up improves on public health outcomes and according to one study that could mean a reduction in premature deaths by 700 every year.

Perhaps LLMs and AI will do a lot of things, but some things aren’t likely to be offloaded to a machine, especially if we didn’t note its impact in the first place.

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