Category: Links (page 1 of 183)

Almhouses as a way forward for social housing

While I’m aware of medieval almshouses, I didn’t know they were still a thing. It’s great that there’s more being built now than in Victorian times, and I hope this kind of approach, along with co-operative housing, becomes even more of a thing.

It looks like they could be particularly useful for helping everything from ending rough sleeping, to stopping premature deaths in old age from poverty.

Almshouses are the oldest form of social housing in the world: the oldest foundation still in existence dates from about 990. Legally, historically and socially unique – exempt from right to buy legislation and so remaining as a permanent part of the community once gifted – there are 30,000 throughout the UK, providing affordable housing for more than 36,000 residents.

They are owned and managed by a network of more than 1,600 independent charities, and nearly all market towns in the UK have at least one almshouse. In some rural areas, they are the only provider of affordable, community housing.

In a time of a severe shortage of affordable rental accommodation, almshouse charities have long been trying to get attention from philanthropists and the government to make the case that their role is more vital than ever – that they should be put at the forefront of the community housing concept, providing an “exemplar housing model”.

Now, a new research project, the Almshouse Longevity Study from Bayes business school, has given extra ammunition to their call finding that those fortunate enough to live in an almshouse receive a longevity boost of almost two and a half years – equating to an extra 15% of future life for someone aged in their early 70s.

Despite not looming large in the public’s awareness, more almshouses are being built today than have been since the Victorian era; while most are for elderly people, some have no age restrictions and are able to accommodate families, people with disabilities and key workers.

[…]

Paul Mullis, the chief executive of the Durham Aged Mineworkers’ Homes Association, the biggest almshouse charity in the UK, agreed. “Our residents know they can look forward to tomorrow because the things that make people’s lives worth living haven’t changed in the 1,000 years that almshouses were created to target: community, safe and secure housing, a sense of purpose.”

Meredith Whittaker on AI doomerism

This interview with Signal CEO Meredith Whittaker in Slate is so awesome. She brings the AI ‘doomer’ narrative back time and again both to surveillance capitalism, and the massive mismatch between marginalised people currently having harm done to them and the potential harm done to very powerful people.

What we’re calling machine learning or artificial intelligence is basically statistical systems that make predictions based on large amounts of data. So in the case of the companies we’re talking about, we’re talking about data that was gathered through surveillance, or some variant of the surveillance business model, that is then used to train these systems, that are then being claimed to be intelligent, or capable of making significant decisions that shape our lives and opportunities—even though this data is often very flimsy.

[…]

We are in a world where private corporations have unfathomably complex and detailed dossiers about billions and billions of people, and increasingly provide the infrastructures for our social and economic institutions. Whether that is providing so-called A.I. models that are outsourcing decision-making or providing cloud support that is ultimately placing incredibly sensitive information, again, in the hands of a handful of corporations that are centralizing these functions with very little transparency and almost no accountability. That is not an inevitable situation: We know who the actors are, we know where they live. We have some sense of what interventions could be healthy for moving toward something that is more supportive of the public good.

[…]

My concern with some of the arguments that are so-called existential, the most existential, is that they are implicitly arguing that we need to wait until the people who are most privileged now, who are not threatened currently, are in fact threatened before we consider a risk big enough to care about. Right now, low-wage workers, people who are historically marginalized, Black people, women, disabled people, people in countries that are on the cusp of climate catastrophe—many, many folks are at risk. Their existence is threatened or otherwise shaped and harmed by the deployment of these systems…. So my concern is that if we wait for an existential threat that also includes the most privileged person in the entire world, we are implicitly saying—maybe not out loud, but the structure of that argument is—that the threats to people who are minoritized and harmed now don’t matter until they matter for that most privileged person in the world. That’s another way of sitting on our hands while these harms play out. That is my core concern with the focus on the long-term, instead of the focus on the short-term.

Source: A.I. Doom Narratives Are Hiding What We Should Be Most Afraid Of | Slate

Playing the right game

Thanks to Laura for pointing me towards this post by Simone Stolzoff. There’s so much to unpack, which perhaps I’ll do in a separate post. It touches on reputation and credentialing, but also motivation, gamification, and “value self-determination”.

Extracting yourself from the false gods of vanity metrics is hard, but massively liberating. It starts with realising small things like you don’t actually need to keep up a ‘streak’ on Duolingo to learn a language. But there’s a through line from that to coming to the conclusion that you don’t need to win awards for your work, or the status symbol of a fancy car/house.

I interviewed over 100 workers—from kayak guides in Alaska to Wall Street bankers in Manhattan—and met several people who achieved nearly every goal set out for them, only to realize they were winning a game they didn’t enjoy playing.

How do so many of us find ourselves in this position, climbing ladders we don’t truly want to be on? C. Thi Nguyen, a philosopher and game design researcher at the University of Utah, has some answers. Nguyen coined the term “value capture,” a phenomenon that I came to see all around me after I learned about it. Here’s how it works.

Most games establish a world with a clear goal and rankable achievements: Pac-Man must eat all the dots; Mario must save the princess. Video games offer what Nguyen calls “a seductive level of value clarity.” Get points, defeat the boss, win. In many ways, video games are the only true meritocratic games people can play. Everyone plays within clearly defined boundaries, with the same set of inputs. The most skilled wins.

Our careers are different. The games we play with our working hours also come with their own values and metrics that matter. Success is measured by how much money you make—for your company and for yourself. Promotions, bonuses, and raises mark the path to success, like dots along the Pac-Man maze.

These metrics are seductive because of their simplicity. “You might have a nuanced personal definition of success,” Nguyen told me, “but once someone presents you with these simple quantified representations of a value—especially ones that are shared across a company—that clarity trumps your subtler values.” In other words, it is easier to adopt the values of the game than to determine your own. That’s value capture.

There are countless examples of value capture in daily life. You get a Fitbit because you want to improve your health but become obsessed with maximizing your steps. You become a professor in order to inspire students but become fixated on how often your research is cited. You join Twitter because you want to connect with others but become preoccupied by the virality of your content. Naturally, maximizing your steps or citations or retweets is good for the platforms on which these status games are played.

Source: Playing a Career Game You Actually Want to Win | Every