Kevin Lacker

Karma: 45

Kevin Lacker 21 Nov 2020 6:20 UTC
7 points
on: AGI Predictions
I suspect this question is misworded:
Will there be a 4 year interval in which world GDP growth doubles before the first 1 year interval in which world GDP growth doubles?
Do you mean in which world GDP doubles? World GDP growth doubles when it goes from, say, 0.5% yearly growth to 1% yearly growth.
Personally, I suspect world GDP is most likely to next double in a period after a severe war or depression, so you might want to rephrase to avoid that scenario if that isn’t what you’re thinking about.

Kevin Lacker 23 Jun 2022 20:44 UTC
6 points
on: Nonprofit Boards are Weird
I think you actually do not have very much power as a board member. During normal operations, you can give advice to the CEO, but you have no power beyond the “access to the CEO”. If the CEO resigns or is being forced out, you briefly have an important power, but it is a very narrow power, the ability to find and vote in a replacement CEO.
The position is very public and respected so it may feel like “a lot of power” but quite often even a mid level employee at the organization has more real power over the direction of the company than a board member does.

Kevin Lacker 21 Nov 2020 0:38 UTC
6 points
on: Persuasion Tools: AI takeover without AGI or agency?
I believe there already is a powerful AI persuasion tool: the Facebook algorithm. It is attempting to persuade you to stay on Facebook, to keep reading Facebook so that their “engagement” metrics are optimized. Indeed, many of the world’s top AI researchers are employed in building this tool. So far it is focused much more on ranking than on text generation, but if AI text generation improves to the extent that it’s interesting for humans to read, I would expect Facebook to incorporate that into newsfeed. AI-generated “news summaries” might be one area that this happens first.

Kevin Lacker 17 Nov 2020 7:52 UTC
6 points
on: Propinquity Cities So Far
Isn’t this what real estate developers do? You buy up some land somewhere that is a combination of inexpensive and desirable, like Dallas or Jacksonville. Then you attract people by building housing there. The land is cheap, you just have to move to the exurbs in a red state. You can set up a homeowners association with a wide variety of rules, although I suspect that the optimal ones may be closer to the way homeowners associations currently operate, rather than the decisionmaking procedures you propose here. But it has been a flexible enough process to build things like carless cities or cities aimed at the needs of senior citizens.

Kevin Lacker 20 Nov 2020 0:58 UTC
LW: 5 AF: 2
AF
on: Inner Alignment in Salt-Starved Rats
Now, for the rats, there’s an evolutionarily-adaptive goal of “when in a salt-deprived state, try to eat salt”. The genome is “trying” to install that goal in the rat’s brain. And apparently, it worked! That goal was installed! And remarkably, that goal was installed even before that situation was ever encountered!
I don’t think this is remarkable. Plenty of human activities work this way, where some goal has been encoded through evolution. For example, heterosexual teenage boys often find teenage girls to be attractive and want to get them naked, even before they have ever managed to do it successfully, without a true conscious understanding of their eventual goals. Or babies know to seek out nipple-shaped objects, before they have ever interacted with a nipple.

Kevin Lacker 21 Nov 2020 0:32 UTC
3 points
on: Hiding Complexity
I don’t think the metaphor about writing code works. You say, “Imagine a company has to solve a problem that takes about 900,000 lines of code.” But in practice, a company never possesses that information. They know what problem they have to solve, but not how many lines of code it will take. Certainly not when it’s on the order of a million lines.
For example, let’s say you’re working for a pizza chain that already does delivery, and you want to launch a mobile app to let people order your food. You can decompose that into parts pretty reasonably—you need an iOS app, you need an Android app, and you need an API into your existing order management system that the mobile apps can call. But how are you going to know how many lines of code those subproblems are? It probably isn’t helpful to think about it in that way.
The factoring into subproblems also doesn’t quite make sense in this example: “Your team still has to implement 300k lines of code, but regardless of how difficult this is, it’s only marginally harder than implementing a project that consists entirely of 300k lines.” In this case, if you entirely ignore the work done by other teams, the Android app will actually get harder, because you can’t just copy over the design work that’s already been done by the iOS team. I feel like all the pros and cons of breaking a problem into smaller parts are lost by this high-level way of looking at it.
My null hypothesis about this area of “factored cognition” would be that useful mechanisms of factoring a problem into multiple smaller problems are common, but they are entirely dependent on the specific nature of the problem you are solving.

Kevin Lacker 20 Nov 2020 7:04 UTC
3 points
in reply to: DirectedEvolution’s comment on: Should we postpone AGI until we reach safety?
We could in theory try to kill all AI researchers (or just go whole hog and try to kill all software engineers, better safe than sorry /s).
I think this is a good way of putting it. Many people in the debate refer to “regulation”. But in practice, regulation is not very effective for weaponry. If you look at how the international community handles dangerous weapons like nuclear weapons, there are many cases of assassinations, bombing, and war in order to prevent the spread of nuclear weapons. This is what it would look like if the world was convinced that AI research was an existential threat—a world where work on AI happens in secret, in private military programs, with governments making the decisions, and participants are risking their lives. Probably the US and China would race to be the first one to achieve AGI dominance, gambling that they would be able to control the software they produced.

Kevin Lacker 11 Nov 2020 21:19 UTC
3 points
on: Ongoing free money at PredictIt
I started the process to accept this free money, but once I read enough of the fine print I bailed. Basically, if PredictIt is taking a 5% cut of my withdrawals, then I’m going to lose money if it so happens that I can’t get enough of this contract. It feels more like even-money gambling, where I lose if the PredictIt market happens to lose liquidity by the time they verify me, and I win if I actually fill out all the forms in time. If there were more money at stake, maybe I’d work a bit harder to jump through all the hoops, but it just isn’t worth it to riskily earn $20.

Kevin Lacker 20 Nov 2020 0:43 UTC
1 point
in reply to: otto.barten’s comment on: Should we postpone AGI until we reach safety?
You can change the world, sure, but not by making a heartfelt appeal to the United Nations. You have to be thoughtful, which means you pick tactics with some chance of success. Appealing to stop AI work is out of the political realm of possibility right now.

Kevin Lacker 19 Nov 2020 7:45 UTC
0 points
on: Should we postpone AGI until we reach safety?
It seems like there is very little chance that you could politically stop work on AGI. Who would you appeal to—China, the U.S., and the United Nations would all have to agree? There just isn’t anywhere near the political consensus necessary for it. The general consensus is that any risk is very small, that it’s the sort of thing only a few weirdos on the internet worry about. That consensus would have to change before it makes any sense to ask questions like, should we postpone all AGI research indefinitely. I think we need to accept that worry about AGI is a fringe belief, and therefore we should pursue strategies that can have an impact despite it being a fringe belief.