https://doi.org/10.1037/a0026699

https://doi.org/10.1037/bul0000131

Past research has a eugenicist bias because early statisticians were eugenicists seeking evidence for the ideas. I would argue that’s why the social determiners research is valuable to help offset that.

Where it fails me though is exactly when I’m doing something novel like developing a new model or trying to develop some new method to process data. I’ve tried many times to one shot these ideas with detailed descriptions of what I want, how I’d like to generate abstractions, etc and it almost always ends up changing what I want to what I can only describe as something which better matches its training data. It often quietly changes key details that means that I have to delete the whole thing and start over. Just today this happened. On this level of task I’ve found that my workflow and pace of iteration hasn’t really changed at all in the last year. I still have to go and explain in detail on a function by function level what I want in much the same way I did a year ago. While that’s obviously a harder task, it seems to me like the task this whole long term exponential argument hinges on. I obviously could be wrong and maybe LLM with eval loop will do all of this for us but it seems still quite bad at anything without a clear definition of “good”.

I’m personally much more concerned about autonomous weapons, surveillance, and people plugging these things into places they don’t belong to avoid responsibility than I am the general possibility of these models being smarter than me in every way but obviously I could be wrong on this and am just using it incorrectly, hence the question.

I would argue the best way to safeguard against long-term threats is to start by focusing on the issues that already exist. If you can offset the health risks of local datacenters or issues of unequal distribution of wealth by creating a more equal society right now then you’re already on the path to handling these long term issues. To me, this distant focus only distracts from the already present issues and conceals effective policy in this moment. We do need to safeguard against AI risk and it’s already here. Don’t even get me started on the havoc which recommendation systems have caused in society in the last 15 years which we still don’t call AI because it doesn’t speak.

Tl;Dr: These essays can feel disingenuous because:

1) AI risk is already present without exponential growth. The exponential growth argument often feels like a distraction from the fixes we could put in to fix the current issues that are already here.

2) The people stating this argument often have billions of dollars to gain if it comes true. While they may be altruistic, I also don’t see them doing all that much to fix the issues that people are already claiming exist and instead continue onwards on their path by justifying that they are the only ones responsible enough to handle it if the super intelligence does arrive. By continuing down that path, if that day ever does arrive they’ll have ensured the existence of a system which is unable to handle it.

I see this move as an attempt to stifle 2 by hiding 3. It seems like a bet that if we don’t focus on the global issues (like a collapsing current) then much of the political power behind climate change disappears since we are frankly quite lucky in the US to have a beautiful, and largely clean environment/air. Grassroots movements and politically powerful messages are likely an annoyance for those who want to keep doing business as usual since it benefits them to do so. Not trying to make a strong claim that our current response to climate change or what anyone in particular is doing is right or wrong but it seems clear that climate change is a powerful message that pushes for much grander scale changes than most people are comfortable with especially those with strong private interests in ignoring it.

[1] https://arxiv.org/pdf/2211.04533 [2] https://www.nature.com/articles/s41586-025-09631-6 [3] https://www.biorxiv.org/content/10.1101/2025.03.09.642245v1

I would argue the organizational tricks exist more for the benefit of the worker than the org itself. The “powerless software engineers” there wanted the excuse to accept the huge salary for very easy work. The organizational tricks don’t fool anyone it’s a favor to the workers at these companies. They exist specifically to ease the cognitive dissonance just enough continue doing your job so you can get paid as much as you want without having to take guilt home with you. I’d say the same is true of my friends in the aerospace defense world. Do you really think they can’t put two and two together and understand that their “flight stabilization module” isn’t going to be used to blow up some school in another country?Your argument is just giving these people the ease of conscious which they want.

On the decision front as well I’d say most of the actual decisions in my org were not actually being made by C-Suite level or even executives. The managerial class at these companies are playing a totally different game than engineers. All the managers care about is that they have good metrics to show their boss so they can get promoted before the person on their sister team. I didn’t interact with a single person above VP and on my projects (as a recent grad mind you) I couldn’t even get my product manager to make a decision on how my product should be implemented. Everyone in the managerial class in these large companies largely exists to provide the illusion that you have no power. Meanwhile they have no idea what anyone in their org is actually working on and as long as they get a nice number to show their boss at the end of the quarter they won’t bother looking too closely.

I think we’re going to have a reckoning in the near future where we’re going to have to come to terms with the fact that the surveillance state which we’re scared of has been designed and built by the “powerless” engineers. The world is too complex for executives to actually have any understanding of what’s being done beneath them. There is SO MUCH room for the average engineer to shape their work in a more positive direction but that would actually require taking ownership over their work and risk some mental connection to its implementation. The average big tech employee already exists on the precipice of too much cognitive dissonance so they can’t afford to try and change anything otherwise they’d be convinced to give up their mid 6 figure salary while already having a larger net worth than 99% of the world will achieve in their lifetime. You cannot equate the life of a software engineer at a large company with the struggle of the working class in any meaningful way. Having a large mortgage is not at all similar to living paycheck to paycheck with variable hours at multiple jobs.

I’m being a bit brutal here I know but I’m so tired of people making excuses for themselves and others for living a life devoid of responsibility. If what I’m saying has struck a chord with anyone who is in a similar spot as I was, I’d suggest strongly questioning your position in the world. I have since found a different career path where I have clear ownership over my work and direction and am much happier now. I’m not fixing the world or anything and took a huge paycut but I agree with the outcome of job and am actually willing to work hard without resentment. I also applaud those who fight against the indifference of their coworkers in these companies since I know they exist. If every worker took responsibility for their output I promise you the parasitic Google or Meta as we know it would not exist. We are not the victims here. If we were desperate coal miners, I’d agree with you, but we are a class of workers with a level of financial flexibility, education, and freedom in our work most of the world has never been able to dream of. The success of these companies exists in how much responsibility they can put in the hands of their engineers who ultimately make most of the meaningful decisions whether they’re willing to admit it or not.