commit b69eff10374350db7e928dfab094d98327dcda61
parent b3eb79bd9347734b226b58d973c3025028fa161f
Author: Eamon Caddigan <eamon.caddigan@gmail.com>
Date: Sun, 2 Feb 2025 20:18:44 -0800
Add weeknote for 2025-W06
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diff --git a/content/posts/weeknotes/2025-w06/index.md b/content/posts/weeknotes/2025-w06/index.md
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+---
+title: "Weeknote for 2025-W06"
+description: "Constructive pessimism, technology vs. hi-tech, and open source
+machine learning"
+date: 2025-02-03T04:59:00-08:00
+draft: false
+categories:
+- Weeknotes
+---
+
+## Constructive pessimism beats false hope
+
+Do you feel like the state of the world is bad, is nearly certain to get worse,
+and that there's virtually nothing you can do to change any of it? If you
+answered yes to all three questions, I think you have a more realistic
+understanding of our circumstances than many people.
+
+But that doesn’t mean you’re off the hook! Research described in this article
+shows that those of us with a pessimistic outlook are more likely to act to
+improve our circumstances than naive optimists---as long as that pessimism
+inspires action.
+
+This article focuses on attitudes toward climate change, and back in December I
+shared it with many of my friends who share my concerns about our warming
+planet. However, the argument is also relevant in other contexts---such as the
+political environment---so it's worth reading again.
+
+[The Upside of Climate
+Pessimism](https://undark.org/2024/11/28/opinion-upside-of-climate-pessimism/)
+
+## “Technology is the active human interface with the material world”
+
+This quote comes from a essay from my favorite sci-fi author, Ursula K. Le
+Guin. It challenges nerds (like me) to remember that “technology” doesn't mean
+"high tech stuff." It's a quick read and worth your time.
+
+[A Rant About
+“Technology”](https://www.ursulakleguin.com/a-rant-about-technology)
+
+## What is an “open source” machine learning model?
+
+I loved this Mastodon post from Timnit Gebru so I'll just reproduce it right
+here:
+
+> Friends, for something to be open source, we need to see
+>
+> 1. The data it was trained and evaluated on
+>
+> 2. The code
+>
+> 3. The model architecture
+>
+> 4. The model weights.
+>
+> DeepSeek only gives 3, 4. And I'll see the day that anyone gives us #1
+> without being forced to do so, because all of them are stealing data.
+
+I made a similar point in [the "terms" I wrote]({{< ref
+"/about/index.md#copyright" >}}) for anyone who wants to scrape my site to
+train a model[^cc]. If you can't reproduce a digital artifact using the
+"sources" provided, then it's not "open source", and machine learning models
+(including large language models like DeepSeek) can't be reproduced without the
+data that trained them.
+
+[Link to Gebru's original
+post](https://dair-community.social/@timnitGebru/113909880610412733)
+
+[^cc]: I'm not naive enough to think that the people scraping the web to train
+ these models would respect my terms, but doing so would be one step toward
+ anything we could consider "ethical AI".
