bufbupa
Joined 10 years ago
Joined 10 years ago
Here's the strawman: The text-based watermarking is going to be done procedurally instead of generatively. Maybe they add some sequence of zero-width Unicode characters to all generated text at certain intervals. Then, there is effectively no false positive possible (because humans would [effectively] never type such sequences of unicode naturally). It may survive some editing (depending on how you select/edit the characters), and it's possible to be stripped (false negatives).
It's the loss of understanding. When you make something, you gain a deeper appreciation for the nuance of all that is required to breath life into it. When you outsource understanding to another (agent, contractor, w/e), you're losing the nuanced understanding of the creation.
>After all, you create the prompts, don't you? You said you were proud of doing things. Isn't that doing a thing?
This feels like the difference between putting together an ikea futon and building a hand-hewn table from logs. The fidelity of your understanding is different depending on how deeply you're engaging. But not felling and drying your own timber doesn't mean you can never make something from dimensional lumber.
I'd take the author's word "making" to mean something more like "having enough understanding of the implementation of the task, that you could recreate the output without recourse to the same set of tools".
Tested against their examples:
>I had a new front deck put in [by a contractor]
As a consequence of this addition, did you learn enough about decks so that you could you reproduce this feat if no contractor were available? If no, you didn't make the deck. If yes, you were probably watching/helping the whole time, and you can claim (at least partial) makesmanship.
> any more than using a hammer to drive nails does.
If you didn't have access to the hammer, could you still accomplish the task of attaching two boards together with a nail? Likely yes, use a rock. It's harder, but the understanding of driving the nail is transferable to other implements.
> What if I had an AI-powered hammer and asked it to hit a nail for me? What's the difference? But at that point, I can't say that I hammered it.
This one contradicted his compiler example. He says that he did write the Fibonacci program, even if the AI-powered compiler translated it to assembly. So by similar reasoning, you can claim you hammered a nail with an AI hammer, so long as you understood the aspects of hammering which the AI took care for you to such a degree that you could reproduce the effects even in the absence of the AI hammer.
The crux of the tension is around "what did you learn from the implementation of this task". If you learned enough to reproduce the objective without the assistance of AI (perhaps much slower), then you can claim the high fidelity understanding that came from making. If you didn't internalize anything, and the AI/contractor managed complexity on your behalf, then the output was commissioned, not made.
I think where people get worked up about this, is that it's not easy to tell what understanding other folks are taking away from their AI usage. It does seem like a bifurcating event where some people are going to net gain understanding of their world due to these new tools, while others will net lose understanding.
- term limits for congress
- voter day national holiday
- if budget isn't balanced all members of congress become ineligible for election
- repeal citizens united (maybe covered by op)
- and change all fines/tickets to paid in human hours of community service rather than money
It also makes for much more fungible developers. Instead of having a few key engineers that know the system inside and out, that knowledge is encoded in markdown throughout the project, allowing new devs to ramp up by asking questions against the codebase and tracing the history of reasonings that led to the shape/implementation that exists today. It's like having near exhaustive design docs & documentation with change tracking included.
While it seems likely that developers will become more fungible (replaceable) going forward, I think being able to operate at this layer of abstraction & still having the capacity to drop down to the nitty gritty implementation details will make strong devs more valuable, rather than less.
Part of the issue is that you're presupposing a uniform definition of success. Different cultures have different priorities, and not everyone wants to spend 80 hrs a week in the office to climb the ladder and become a millionaire. Some cultures prioritize family/social relationships, sports, or a connection with nature. Unsurprisingly, these different cultures can often be racially affinitized. Sure, most people wouldn't mind being rich, but many do mind the hustle often accompanying that form of success.
I think part of what you describe around momentum holds merit, but I don't think affirmative action goes about the remedy in a constructive manner. It's fighting racism with more (albeit different) racism. You turn it into a zero sum game where your political posturing can be more valuable than your work contributions. That incentive structure is degenerative for all parties.
> If you grow up in a wealthy family, you've got easy access to great education, mentors, role models, capital, etc. If you grow up in a poor family you have way less of all of this.
Genuinely curious, would you support an initiative to shuffle all babies between families at birth? Your argument seems to be "who you're raised by gives an unfair advantage in life, and we should correct for this societally". It seems to me that a random shuffle would equally distribute any inherent bias relative to generational momentum.
The best advice I can muster is "be the change you wish to see in the world". Giving up hope is just passing the buck. You'll never have the whole world on your side, but you also don't need it to be.
I'd say that bias is only an issue if it's unable to respond to additional nuance in the input text. For example, if I ask for a "male nurse" it should be able to generate the less likely combination. Same with other races, hair colors, etc... Trying to generate a model that's "free of correlative relationships" is impossible because the model would never have the infinitely pedantic input text to describe the exact output image.