> There's a divide between people who enjoy the physical experience of the work and people who enjoy the mental experience of the work. If the thinking bit is your favorite part, AI allows you to spend nearly all of your time there if you wish, from concept through troubleshooting. But if you like the doing, the typing, fiddling with knobs and configs, etc etc, all AI does is take the good part away.
I don't know... that seems like a false dichotomy to me. I think I could enjoy both but it depends on what kind of work. I did start using AI for one project recently: I do most of the thinking and planning, and for things that are enjoyable to implement I still write the majority of the code.
But for tests, build system integration, ...? Well that's usually very repetitive, low-entropy code that we've all seen a thousand times before. Usually not intellectually interesting, so why not outsource that to the AI.
And even for the planning part of a project there can be a lot of grunt work too. Haven't you had the frustrating experience of attempting a re-factoring and finding out midway it doesn't work because of some edge case. Sometimes the edge case is interesting and points to some deeper issue in the design, but sometimes not. Either way it sure would be nice to get a hint beforehand. Although in my experience AIs aren't at a stage to reason about such issues upfront --- no surprise since it's difficult for humans too --- of course it helps if your software has an oracle for if the attempted changes are correct, i.e. it is statically-typed and/or has thorough tests.
I happen to be a shareholder in EA as part of a diversified portfolio. Not that my vote matters but I'll definitely be taking PE money. +20% in one day is nothing to sneeze at.
From the other comments about EA's games, it's not like EA is that special of a company. There's always going to be some other company (not necessarily an AAA-games maker) worth putting your capital in and end up doing as well as what the hypothetical EA could do if it were not taken private. (Obviously finding such market-outperformer isn't easy but by the same argument I'm not convinced that EA would be obviously that outperformer either.)
Speaking as a C# developer, who had in the past wanted to learn F#, but never got very far. What discourages me every time:
- C#'s good enough. Nothing's stopping you from writing functionally-oriented code in C# (and I do prefer that over traditional "enterprisey" object-orientation.)
- It's relatively difficult to have a codebase that is partly in C# and F# for incrementally trying things out. (I understand this is not really F#'s fault, owing to the .NET compilation model where C# and F# compilers each produce their own assemblies. And that Microsoft hardly cares about F#, and the tooling leaves a lot to be desired - admittedly I'm spoiled by C# tooling. )
- F# having its own implementations of concepts like async, option types introduces friction with C# obviously. I get that F# async is more powerful in some ways, but then again... F#'s option type is a reference type unlike C#'s Nullable<> value type, it's hard to see what's the advantage in that other than worse performance. One almost gets the impression that F# designers don't care about performance (while C# designers do in the past few years with additions to the ecosystem like Span<T>). This makes it hard to justify coding in F# for infrastructure libraries (which is what I often do).
C# 1.0 did not have generics, period. So the standard dictionary (Hashtable†) type took keys and values typed as "System.Object". As seen in the linked documentation this class still exists in the latest .NET to this day.
Occasionally one would still encounter non-generic classes like this, when working with older frameworks/libraries, which cause a fair bit of impedence mismatch with modern styles of coding. (Also one of the causes of some people's complaints that C# has too many ways of doing things; old ways have to be retained for backwards compatibility, of course.)
> On the other hand I cannot not help thinking that this is similar to the arguments brought forward when the internet was new. How could correctness and plausibility be established if you don't have established trustworthy institutions, authors and editors behind everything?
Not long ago I had the same viewpoint as you! But thinking back now — it dates me but I definitely lived a childhood without Internet access — probably the optimistic belief before our age of "misinformation" is that, in the marketplace of ideas, the truth usually wins. Goes along with "information wants to be free" — remember that slogan?
For us that grew up learning things "the hard way" so to speak, that made perfect sense: each of us, as should have the capability to discern what is good or bad as, individual independent thinkers. Therefore, for any piece of information, there should be a high probability, in the aggregate, that it is classified correctly as to its truth and utility.
Now there's no question China has been trying to crack down on the Internet. Good luck! That's sort of like trying to nail jello to the wall. (Laughter.) But I would argue to you that their effort to do that just proves how real these changes are and how much they threaten the status quo. It's not an argument for slowing down the effort to bring China into the world, it's an argument for accelerating that effort. In the knowledge economy, economic innovation and political empowerment, whether anyone likes it or not, will inevitably go hand in hand.
I would say, what we have since learned after some 20 years, is that in the marketplace of ideas, the most charitable thing we can say that the memes with the "best value" win. "Best value" does not necessarily mean the highest quality, but rather there can be a trade-off between its cost and the product quality. Clearly ChatGPT produces informational content at a pretty low cost. The same can be said for junk food, compared to fresh food: the overall cost of the former is low. Junk food does not actively, directly harm you, but you are certainly better off not eating too much of it. It is low quality but has been deemed acceptable.
There are examples where we can be less charitable of course. We all complain about dangerous, poorly manufactured items (e.g. electronics with inadequate shielding etc.) listed Amazon, but clearly people still buy them anyway. And then, in the realm of politics, needless to say, there are many actors bent on pushing memes they want you to have regardless of their veracity. Some people on the marketplace of ideas "buy" them owing to network effects (e.g. whether they are acceptable according to political identity, etc.) in the same way that corporations continue to use Microsoft Windows because of network effects. We also probably say nowadays Clinton has been ultimately proven wrong by the government of China.
Survival of the "fittest" memes if you like: evolution does not make value judgements.
If you ask me, maybe our assumption of de-centralized truth-seeking was itself, not an absolute truth, to begin with. But it took years to unravel, as humans, collectively speaking, atrophy from disuse of the research and critical thinking skills before technology dropped the barriers of entry to producing and consuming information.
I don't know... that seems like a false dichotomy to me. I think I could enjoy both but it depends on what kind of work. I did start using AI for one project recently: I do most of the thinking and planning, and for things that are enjoyable to implement I still write the majority of the code.
But for tests, build system integration, ...? Well that's usually very repetitive, low-entropy code that we've all seen a thousand times before. Usually not intellectually interesting, so why not outsource that to the AI.
And even for the planning part of a project there can be a lot of grunt work too. Haven't you had the frustrating experience of attempting a re-factoring and finding out midway it doesn't work because of some edge case. Sometimes the edge case is interesting and points to some deeper issue in the design, but sometimes not. Either way it sure would be nice to get a hint beforehand. Although in my experience AIs aren't at a stage to reason about such issues upfront --- no surprise since it's difficult for humans too --- of course it helps if your software has an oracle for if the attempted changes are correct, i.e. it is statically-typed and/or has thorough tests.