Links

Ketan Joshi analysed Google's latest sustainability report, which details enormous increases in energy consumption, which is not good news given we're in a climate crisis.

Adding up the numbers, Joshi says the increase isn't due to people manually prompting Gemini, but likely associated with the fact Google's search engine shows AI results by default:

GenAI’s climate harm comes from the system design, such as Google’s AI overview triggering constantly whether users want it or not

(From: Google’s exponential path to climate-wrecking digital bloat – Ketan Joshi)

They could choose to try and have the reverse effect, by designing it like the Spice Girls would: triggering GenAI-abled functionality only when users really, really want it.

Jo Lindsay Walton argues for Assured Interventions (AI), things that actually can contribute to the climate transition reliably:

massive and delicious demand-side mitigation of meat methane, nationalise LDAR for fugitive emissions, stop deforestation with community rights and loss and damages funding, ban cryptocurrency

(From: Why we need “AI” for climate transition | by Jo Lindsay Walton) (sadly on Medium, but it's a great piece)

Three findings from this week's UN report on AI vs climate crisis:

🌿 Majority of AI energy use (80-90%) is not in training models, but in day-to-day use.

🌿 Generating an image is 1450⨉ more energy intensive than text, generating video much worse.

🌿 We need to monitor water and land footprint, as well as carbon.

(From: Rising Emissions, Depleting Water and Vanishing Land—UN Scientists: AI Is Threatening Natural Resources for Billions | United Nations University)

The WebKit team responded to WebMCP in standards-positions.

What stood out to me:

When a site's actions are hard for an agent to use, that is a gap in the page's own semantics, and the fix, in our opinion, is to close it in the platform's shared layers (HTML and ARIA), where the user, assistive technology, and agents all benefit. Describing those actions a second time as JavaScript tools would not deliver the reliability it promises: the agent still selects and interprets a tool from its natural-language name and description, which the specification itself concedes are ambiguous and unverifiable, with "no guarantee that a WebMCP tool's declared intent matches its actual behavior."

(From: WebMCP · Issue #670 · WebKit/standards-positions)

Another reason to disallow LLM contributions in open source projects would be that it gets in the way of the project nurturing “new, confident, trustworthy contributors“, says (even) Simon Willison:

It doesn't matter if the LLM helps you submit a perfect PR to Zig - the time the Zig team spends reviewing your work does nothing to help them add new, confident, trustworthy contributors to their overall project.

(From: The Zig project's rationale for their firm anti-AI contribution policy)

(via Cassandra)

Of course kids are bypassing age verification:

Kids used to draw on their faces for fun. Now, they're doing it to play Roblox.

(From: Mustache Mischief: Kids Bypass UK's Digital Age Barriers - CNET)

In another great piece about what LLM usage actually means in the workplace beyond promise of ‘efficiency’ and ‘profit’, Dave Rupert notes:

I’d rather have a human-to-human conversation with you, not a chat with Claude by proxy. What Claude said is an okay chunk of “anecdata”, but it’s not a substitute for our working relationship.

(From: I don't want a screenshot of your Claude conversation - daverupert.com)

As part of my work for the W3C's Advisory Board (AB), I co-wrote a short overview of reasons why or why not to use LLMs in the standards process.

My own personal opinions are a bit more extreme than what is captured here, and that's fine, the goal of this document is to capture what the AB mostly agrees on when it comes to usage of these tools. We wanted to be balanced, too, which is why a sceptic (me) and an enthusiast (Elena) decided to collaborate on it.

As we wrote:

we want to highlight considerations around different ways in which LLMs can be useful or problematic when it comes to leveraging them in standards work at W3C.

(From: Use of Large Language Models in Standards Work)

My opinion on "Artificial Intelligence" | ./axel.leroy.sh) gives an overview of developer's Axel Leroy's thought process on the question whether to use LLMs at work.

Dave wrote a great piece about friction, and Matthias pointed out something rather important that followed from this:

The frictionless version of creative work isn’t faster creative work. It’s no creative work at all.

(From: The Shape of Friction · Matthias Ott)

I could not agree more. Bringing in experience and judgment (and, imo, intentions) is what makes works meaningfully creative, removing that leaves us with very little left.