I think AI wins against people when we start using KPIs in an industrial view of software like defects / LOC, decomposability, etc), or possibly even maintainability / understandability of a codebase. Gosh, even since the 1980s expert systems were already out-performing entire doctors' boards in diagnosing issues in patients so clearly technical performance in KPIs isn't the only measure by which we adopt technology in society.
When it comes to judgment calls for technical decisions, a lot of interesting innovations appear to come from rejecting conventions / averages in favor of a different set of constraints as a trade-off because we challenge the assumptions we make about the demands being asked of a solution / product. I'm thinking in the constellation of the apocryphal Steve Jobs quote about rejecting asking horse riders what they want because if we asked them they'd ask for a more reliable horse.
Maybe I'm misunderstanding you but I believe I'd disagree with your first point on the perceived lower skill roles with higher design / creative requirements. I've seen a lot of the software industry being software factories rather than something closer to craftsmanship or even proper ABET-style engineering and AI is indeed better than the manually written slop that was encouraged in low-creativity / low-innovation environments such as QA and a lot of infrastructure engineering like defining CI pipelines. It seems reminiscent of the waves that hit industries like coal mining and manufacturing in the US except at a much faster rate and with different driving and resisting forces in automation.
Programmer / engineer compensation in the US market at least has been looking bimodal for at least 12 years now and the first one looks even more devastated in terms of labor than the big tech companies based upon (lack of) job postings and from browsing my connections on LinkedIn.
The demand exploded as so many business cases for computing and automation arose partly because the application of them helped suppress job growth in other areas while also attracting investor capital during heavy deregulation / liberalization trends so it's difficult to attribute any change to an effect in isolation. Let's not forget the old myopic sounding quote where someone thought the global market for computers was maybe $50 million or some other laughably small number.
The issue that hasn't been addressed with the latest wave of computing hype is whether enough new jobs for displaced workers can arise during a time when people are experiencing such economic turmoil and political strife where new jobs or other means of letting people find a way to have gainful employment in society when institutions are so weak now and everyone across professions is being worked to an early grave from sheer stress alone. This resembles Japan or Korea although the US and Canada I can't imagine having the same kind of social drivers although many trends from them are showing up in youth demographic trends. And frankly as I see it a large number of current social problems are from the past 50+ years of the decline of blue collar jobs in developed economies being accessible to as many people and the lack of a competition-driven economy as much as an extractive one in most OECD countries.
It's not like he was going to be a Congressional staffer nor working at a newspaper. But if he was on-call for a lot of his career that'd be kind of amusing
This is sounding eerily similar to how the setup for a Cyberpunk TTRPG scenario. "Militech hired mercenaries raid Militech facilities wearing Arasaka uniforms to make it look like Arasaka did it?"
This is HN, we can use an analogy of TCP window size or UDP packet size in an underlying high latency medium and the receiver and sender have very high processing costs. So perhaps solving the unloading and loading logistics is also worth optimizing for like we did almost for free in computing space? But because we don't have ballpark numbers of each terribly well we're going to have some difficulties with a valid non abstract system design discussion.
Many gun proponents seem to think of them like most people do knives when knives have many, many domestic purposes beyond killing things that have a life. Same things with cars given there's many things cars can do besides get people and things from place to place.
One of the core problems we have in software engineering is the longstanding philosophical problem around creation of cohesive, consistent, objective mental models of inherently subjective concepts like identifying a person, place, etc. Look at the endless lists of falsehoods programmers (tend to) believe about any topic.
You’re right that LLMs specifically have no guarantees about accuracy nor veracity of the text they generate but I posit that that’s the same with people, especially when filtered through the socialization process. The difference is in the kind of errors machines make compared to ones that humans make.
It’s frustrating we’re using anthropomorphic concepts like hallucinations when describing LLM behaviors when the fundamental units of computation and thus failures of computation are so different at every level.
> The difference is in the kind of errors machines make compared to ones that humans make.
There's another difference, and that is that other humans can learn and study that mental model (which is why "readable code" is a goal — the code is a physical manifestation of the model that you, the programmer, has to learn), and then the model can be tweaked and taught back to the original programmer, who can then think of that tweak in the future. Programming is inherently (in most cases) a collaborative art, because you're working with people to collectively develop a mental model and refine it, smoothing it down until (as Christopher Alexander said) there are no misfits between the model and the domain.
This is what amorality means to me in the context of socioeconomics. It operates in an area of reduced dimensionality to economic value because no other value can be agreed upon in trade between cultures. It doesn’t care if a piece of art, nature or human invention is genuinely novel, rare, irreplaceable, invaluable, etc. unless it can be converted into materializable economic value that is itself subjective and present oriented so that we can plan for our future selves about resources as a proxy.
Both ideas can be true. It’s not on their radar because despite their popularity in consumer space they can’t find a business purpose that aligns with their self interests that require such user information. If I’m running a free podcast, in contrast, I might be happy anyone’s even bothering to visit and listen to what I have to say compared to who they are and whether I can assign a monetary value to their attention because spending money on something without clear, intentional, measurable ROI is anathema to our predominant modus operandi in business
When it comes to judgment calls for technical decisions, a lot of interesting innovations appear to come from rejecting conventions / averages in favor of a different set of constraints as a trade-off because we challenge the assumptions we make about the demands being asked of a solution / product. I'm thinking in the constellation of the apocryphal Steve Jobs quote about rejecting asking horse riders what they want because if we asked them they'd ask for a more reliable horse.
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