(to me, it isn't about producing the right test -- I could think of many scenarios AI has enabled me to move faster on than I ever could without. if you don't have those scenarios, I don't know why you'd fabricate them just to prove or disprove a theory about the usefulness of something that is, well, not useful to you.)
The conclusion I've come to is that good taste has been replaced with "works; good enough". Maybe that's the end state. Maybe the end is just a bland mass of tangled code that's junky but it works. Speed over quality has always been a currency in this industry and maybe this is just the purest expression of it.
But at the end, it leaves me with my preferences and tastes and what I think is right and I feel more and more isolated. I don't think the people who are happily using AI tools are incompetent. I know they're not. I think they just are a little more in tune with how the winds are changing.
In the long run, I'm not sure how this ends. Programming is a lifelong pursuit of endless learning. When you use tools like this, your learning becomes stunted. But maybe I'm wrong. Nobody knows.
_wire_•11h ago
Due to the very diffuse statistical nature of the mapping of the input to the output, some will be experiencing extraordinary appropriate useful results while others will be experiencing crap. And due to the subjective nature of quality and quirky topographies of the internal terrains of these systems and the haphazard control protocols, the spread of resultant value (so to speak) of these appliances may not be understandable as a normal distribution. Scenarios we might judge as lying close to each other on the input terrain may generate very peculiar bumpy results of output terrain.
One of the most damning considerations of this technology is that gross uncertainty about result quality may be manipulated by the appliance maker leading to wild patterns of exploitation without any prospect of accountability.
As there's no pretense of formal function, there can be no verification, and so there's no methodology for determining quality: a presumably working appliance may appear reliable until it isn't with no way to understand the inflection. Those with insider control and information can game customers with no chance of accountability, but the system can't be understood.
The problem with magic beans is guessing what they'll grow into.
Meanwhile, the seismic movement of business towards these private and completely mysteries silos of "knowledge" (which is a grotesque misnomer) may arrive at dead ends from which they can't retreat.
This is a far greater danger than a malicious bot because a great migration into the dead end is not just well under way, but regarded as a brilliant prospect which we must run into at all deliberate speed.
m3047•10h ago
So that people know what we mean. There's also Wikipedia: https://en.wikipedia.org/wiki/Normal_distribution