crank.report

User Generated Content and the Fediverse: A Legal Primer from the Electronic Frontier Foundation via Pluralistic: Daily links from Cory Doctorow

For people hosting instances, however, it can also mean some legal risk. Fortunately, there are some relatively easy ways to mitigate that risk – if you plan ahead. To help people do that, this guide offers an introduction to some common legal issues, along with a few practical considerations.

Embracing My Butch Identity Was a Challenge, Here’s Why by Ro White

On one of many occasions when I was stopped by the TSA, an agent demanded to know what was “strapped to my chest.” “My boobs,” I said. “I’m wearing a bra.” Strangers regularly ask me what my gender is or ask leading questions to reveal my “true” identity. My life is a never-ending “It’s Pat!” sketch, and it’s only funny sometimes.

HTTPS explained with carrier pigeons by Zanin Andrea

Any activity you do on the Internet (reading this article, buying stuff on Amazon, uploading cat pictures) comes down to sending and receiving messages to and from a server.

This can be a bit abstract so let’s imagine that those messages were delivered by carrier pigeons.

Tokyo’s Urban Planning Secrets Revealed in New Book by Max Zimmerman

It’s based on the idea that systems and phenomena, through local interactions of their parts, can create orders. The classic example would be the flocking behavior of birds, in which you can see clearly the formations but there is no bird leading it.

#links #fediverse #gender #explainer #urbanplanning

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Anti-marketing by Andy Matuschak

If you make anti-marketing the goal, then interesting challenges become a positive thing: fodder for public conversation, not something to be swept under the rug.

My Information Operating System Part 1: Reading by Kyle Stratis

My goal when reading is to generate knowledge and insights that can be connected with knowledge and insights derived from other sources. That is a mouthful to say that I want to integrate information from something I read and connect it to my existing knowledge.

Why are there so many minor scales by Ethan Hein

The minor-key world is more complicated than the major-key world. But that also makes for a lot of musical variety. Let’s dig in!

Levels of Racism: Systemic vs Individual – Anti-racism Resources – Research Help at Fitchburg State University via D. Elisabeth Glassco on Mastodon

We pledge to provide access to information, resources, and programming that works towards dismantling the racist systems on which our country has been built, as well as the many other insidious forms of inequality that persist in our society.

#links #marketing #pkms #music #anti-racism #libraries

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Whether it was Gap Khakis, Patagonia vests, or Allbirds, the counter-cultural ethos that applauded individuality has been replaced by herd thinking. In Silicon Valley, we use a better marketing term for herd: team. One of the biggest trends of the past twenty years has been the rise of corporate swag. Wearing a Google t-shirt, an AirBnB backpack, or a logo-festooned Hydra bottle are all symbols of belonging to a herd called “work.” These logos advertised where you worked and thus gave you a place in Silicon Valley’s social hierarchy.

As the technology industry became the cultural zeitgeist, it became necessary to advertise to the world that you were part of the tech set. And the easiest way to do so is through uniforms. And I don’t mean uniform in the strictest sense, just as pinstripes and bold red suspenders were the look for traders and bankers in the heyday of Wall Street. By embracing a uniform, we are echoing being part of the tribe. Uniform is a great leveler, and it shows what team you are on. It is a symbol of power, affiliation, and hierarchy. Its underlying ethos: us versus them.

From Sometimes a shoe is not just a shoe.

#thisworld

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Image Credit: A DALL-E 2 generated image of a person standing in a field, painted in an abstract style

In ChatGPT and the Imagenet Moment Benedict Evans writes:

… a generative ML system could make lots more ‘disco’ music, and it could make punk if you described it specifically enough (again, prompt engineering), but it wouldn’t know it was time for a change and it wouldn’t know that punk would express that need. When can you ask for ‘something raw, fresh and angry that’s a radical change from prog rock?’ And when can a system know people might want that? There is some originality in creating new stuff that looks like the patterns we already have, but the originality that matters is in breaking the pattern. Can you score that?

As AI gets better and better at repeating patterns that exist. As we get better at producing prompts – what Evans calls ‘prompt engineering’. As AI starts getting integrated in tools in ways we don’t even notice. As all that happens, we and how do we identify the places we need human intervention? And not just to retain unique value or to increase the amount of interesting hard work we do, but so that we are not building a future based on our past. Because, you know what? That past is full of exploitation, extraction, and oppression. Many would argue the very AI works is an example. It’s intelligence is built off the work of others in a mass consumption way.

So, what does this mean for civil society? How do we take advantage of the technology, influence the system, and judge the output?

1. Algorithm detectives. We need an independent body who reviews the tools – algorithms, the training of AI – so that we can be clear about the patterns we are learning from and the ways we promote the responses.
2. Use AI to identify patterns of injustice. This will require excellent prompt engineers who are asking and asking and asking and then sharing the results.
3. Illuminate what is missing. If AI is trained on available massive data, we need to show what and who is missing from that data. And we have to find ways to include it. Sometimes that will come from technical means – refining, adding, training – and sometimes it will come from advocacy. It must be intentional.
4. Use the tools. We can’t just opt out. Usage shapes the tools. We have to use them and aggregate our learnings with the goal of improving our own efficiency and shaping the tools themselves. And let’s normalize it. Don’t hide that the you turned the grant question into an AI prompt.
5. Build context. That’s what struck me about the quote above: context is something’s humans have in a hyper local way. We can adjust, disregard, slow down or speed up what AI generates for us based on the context. We can identify places where the pattern is wrong for reasons of justice and equity. We have the context and the experience.

#areas #AI

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“Part of the job of making change is working to make sure a bad story doesn’t get in the way of good facts.” This is good advice from Seth Godin. And it is so hard. Especially when teams of well trained humans are well funded to make excellent stories to elicit actions and those stories are based on lies.

To really accomplish this we have to:

1. Prioritize access to data and the tools and humans to find the insights in the data. The Data Innovation Lab at Tech Impact is doing interesting work in this area.
2. Help people interrogate the stories put in front of them. This is some of the work IREX does.
3. Give teams skills in developing engaging narratives based on truth and that debunk lies. TechSoup’s teams in Europe have done tremendous work in this area.
4. Create media outlets, forums, and campaigns that get this out into the world. Unfortunately, I don’t have a good example of this.

That’s, of course, still too simple. It requires funding and infrastructure and it has to start with the data.

#data #narratives #civilsociety

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Hacker News published a link to an opinion piece by Paul Krugman on blockchain. In it Krugman writes:

A blockchain is a digital ledger associated with an asset, recording the history of transactions in that asset — who bought it from whom and so on. The asset could be a digital token like a Bitcoin, but it could also be a stock or even a physical thing like a shipping container. Ledgers, of course, are nothing new. What’s distinctive about blockchains is that the ledgers are supposed to be decentralized: They aren’t sitting on the computers of a single bank or other company; they’re in the public domain, sustained by protocols that induce many people to maintain records on many servers.

These protocols are, everyone tells me, extremely clever. I’ll take their word for it. The question I’ve never heard or seen satisfactorily answered, however, is, “What’s the point?” Why go to the trouble and expense of maintaining a ledger in many places, and basically carrying that ledger around every time a transaction takes place?

Krugman’s answer and the Hacker News comment consensus is: Nothing. At best, it’s a solution is search of a problem.

I don’t agree. I think it’s a solution in search of a user interface. The first people grokked, if it all, is bitcoin. Because, money. But that’s not all:

• PolicyKit is a peer-to-peer community governance and moderation project.
• ProofMode – ProofMode – Verified Visuals creates a chain of custody around evidence such as photos.
• Starling Labs creates a historical ledger.
• Acorn | Open Source P2P Project Management for Software Teams reimagines project collaboration in a serverless environment.

Can these problems be solved in other ways? Of course. Is blockchain and interesting way to solve these: yes.

In a world where billionaires can disrupt social communications by buying a platform, war and its crimes continue to be perpetrated, and government records are removed from public view, decentralized tools using a ledger can help us maintain the past, understand the present, and collaborate into the future.

#area #technology #blockchain

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