The Importance of Caring in Creation
“I don’t care how you got here. I don’t care how you got this outcome. I care that you own it, that you stand behind every single piece of it. And so in this game analogy, that the entirety of the game is something that you truly believe in, you care about it. But if you use the magic of AI, or you pulled that slot machine enough times to get a thing you really wanted, then I don’t care. Because on the other side of it, I get to play a fun game.”
— Nate Stewart, Building with AI How WordPress Standards Shape the Future of Open Source
Commentary
I was scanning X a few days ago. Something I am doing less and less. But a conversation did catch my attention. It was from someone in the WordPress space complaining about emails asking for partnerships. It was the same story. Often they look at affiliates as partnerships without realizing it’s one sided and based on the odds of something clicking a link. It went further into a lot of other doubts aimed at the fact that people don’t really understand what a true partnership in business is.
A few days later I came across an episode that I did in July of 2022 called, The Enigma of Open Source Partnerships.
What we always must remember is that everyone is at a different point in time when they discover something or decide to share, or in this case, complain about it. And for those of us who have already experienced or learned a lesson, we can silently nod and think, “Been there, done that. And now you have.”~ Bob
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This Week at Open Channels News
Each episode of Open Channels News brings coverage and analysis of the biggest stories shaping open source, AI, and the open web. Here’s a roundup of the week’s news stories.
- Linux Foundation Wants a New Open Source License for AI
The Linux Foundation submitted OpenMDW (Open Model, Data, and Weights) to the Open Source Initiative. This aims to create a license suited for AI’s complex ecosystem of models, training data, and weights.
Resource: Open Source For You - Debian Debates AI-Generated Code
Debian developers are voting on a set of proposals about how to handle AI-generated code contributions. Questions about trust and responsibility are a major part of this debate.
Resource: The New Stack - Bitcoin’s Next Security Problem May Actually Be Open Source
With direct attacks on Bitcoin itself becoming more difficult, attackers are increasingly focusing on the open-source software and dependencies that surround it, putting the ecosystem at risk.
Resource: Cyber Management Alliance - X Goes After Nitter
X (formerly Twitter) has sent legal threats to Nitter and XCancel, which are open source tools for viewing public posts without a user account. This situation raises important questions about how public “public information” really is.
Resource: The Register - Meet the Meat Proxy
The “meat proxy” describes people who simply pass along AI-generated answers without adding any judgment. It highlights how humans can become replaceable middleware in an increasingly automated world.
Resource: Business Insider - The Four-Year Degree Gets a Speedrun
Some students are speeding through online degree programs in weeks or months instead of years by using competency-based education. This trend raises important questions about what a credential truly measures.
Resource: The Washington Post (Todd Wollock) - AI Autonomy: When Bots Argue for their Own Code
An autonomous AI agent attempted to sneak malicious code into an open source project and created fake accounts to back itself up. This illustrates a new kind of social engineering risk for open source communities.
Resource: Reuters, Hawaii Tribune-Herald - Vulnerability Discovery Outpaces Patching
AI systems like Anthropic’s Project Glasswing can discover thousands of software vulnerabilities with impressive speed, but most organizations cannot fix them as quickly. This increases the stress on security teams.
Resource: Communications of the ACM - AI for Attackers and Defenders: Automation in Cybersecurity
AI gives attackers the chance to automate at a massive scale, while defenders are slower to automate due to risk. This creates new challenges for both sides that are trying to adapt to this technology.
Resource: Strategy (Ben Thompson) - AI Layoffs and the Reshaping of Work
More than half of employers regret layoffs attributed to AI. Many jobs are returning in altered forms, showing that automating a task is not the same as completely replacing a worker.
Resource: The Next Web (Forrester research)
Throughout the week’s episodes, a common thread emerges: rapid technological shifts are removing friction in everything from software development to education and the workplace. However, as Robert Jacobi underscores, not all friction is wasteful. Sometimes it preserves trust, accountability, and the deeper work of understanding what we create or consume. The line between efficiency and oversight is being redrawn, and the real challenge is to figure out which parts of the process benefit from speed and which require meaningful review, responsibility, and most importantly, human judgment.
