If you think the profession has enough time to organize reasonable unions, you’re an optimist. Pessimists are changing careers altogether as we speak.
Either way it’s been a fun ride.
Either way it’s been a fun ride.
Personally I don't think they're a great fit for the software industry where the nature of the job and the details are continuously changing as technology evolves.
The fundamental point of the union is to be able to negotiate as a group. That is valuable regardless of the industry.
- paternity leave
- overtime
- not having to answer a call or email outside of work hours
- workman’s comp / short/long-term disability for issues with my back or wrists or eyes or…
- about 100 more things
I wonder if there is a difference in context that explains why we might disagree. I'm in Australia where I think it's politically easier to "add" broad top level protections for all workers than it would be in the US.
It's not just the labor regulations holding Europe back, it's the lack of funding due to not having a unified European digital market.
Netflix Europe needs to have 20+ licensing deals. Selling across Europe at a large scale requires interactions with 20+ legal teams. Language and cultural barriers kill a lot of things.
How do US giants thrive in Europe, then?
Because they come in directly giant-sized based on growth in the US. They either ignore European legal compliance until sued or pay peanuts for them to handle all the legal aspects.
I wrote this up a bit ago in my essay fragments collection. It's rough and was just a thought I wanted to get down, I'm unsure of it, but it's at least somewhat relevant to the discussion here:
LLM or LLM-adjacent technology will never take over the execution of work in a way that approaches human where humans continue to guide (like PMs or C-suite just "managing" LLMs).
The reason is that spoken language is a poor medium by which to describe technical processes, and a well-enumerated specification in natural language describing the process is at-least synonymous with doing the work in skilled applications.
For example, if someone says to an LLM: Build a social media app that is like Tinder but women can only initiate.
... this is truly easily replicatable and therefore with little real business value as a product. Anything that can be described tersely that is novel and therefore valuable unfortunately has very little value practically because the seed of the short descriptor is sort of a private key of an idea itself: it will seed the idea into reality by labor of LLMs, but all that is needed for that seed's maturation is the original phrase. These would be like trade secrets, but also by virtue of something existing out there, its replication becomes trivial since that product's patterns are visible and copyable.
In this way, the only real outcome here is that LLMs entirely replace human labor including decision making or are tools to real human operators but not replacements.
Consider "Uber, but for X"
This wasn't a thing you could deploy as a term pre-Uber.
I'm not sure what this means for your analogy, but it does seem important. Somehow branding an idea reifies a ... callable function in? ???
Maybe something like (just spitballing)
The specification-length needed for a given idea isn't fixed - it's relative to available conceptual vocabulary. And that vocabulary expands through the work of instantiation and naming things?
Which maybe complicates the value story... terseness isn't intrinsic to the idea, it's earned by prior reification work?
Hmm
Basically it seems that "Like Tinder but" is doing a lot of lifting there... and as new patterns get named, the recombination space just keeps expanding?
Yeah, this feels right. It's like a process of condensing: new ideas brought to life condense metaphors into more compact forms and so make language more dense and expressive. This idea reminds me of Julian Jaynes's description of metaphor condensation in Origin of Consciousness.
A lot of hard work goes into novel products, but once that work has been proven, it is substantially more trivial for human or machine to copy. Groping around in the darkness of new, at the edge of what-could-be is difficult work that looks simple in hindsight to others who consider that edge a given now.
> The specification-length needed for a given idea isn't fixed - it's relative to available conceptual vocabulary. And that vocabulary expands through the work of instantiation and naming things?
Yeah, I think that naming and grouping things, then condensing them (through portmanteau construction or other means) is an underrated way to learn. I call this "personal taxonomy," and it's an idea I've been working on for a little bit. There is just tremendous value in naming patterns you personally notice, not taking another person's or group's name for things, and most importantly: allow those names to move, condense, fall away, and the like.
I left out a piece of my fragment above wherein I posit that a more constrained form of natural language to LLMs would likely lead to better results. Constraining interaction with LLM to a series of domain-specific metaphors, potentially even project specific givens, might allow for better outcomes. A lot of language is unspecific, and the technical documents that would truly detail a novel approach to an LLM require a particularly constrained kind of language to be successful where ambiguity is minimized and expressiveness maximalized (legal documents attempt at minimal ambiguity). I won't go into details there, I'm likely poorly reiterating a lot of the arguments that Dijkstra made here:
https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667...