New releases

This post was written by Benjamin Todd in his personal capacity and originally posted on benjamintodd.substack.com.

Today robots barely have the dexterity of a toddler, but are rapidly improving.

If their algorithms and hardware advance enough to handle many physical human jobs, how quickly could they become a major part of the workforce?

Here’s some order of magnitude estimates showing it could happen pretty fast.

Robot cost of production

Today’s humanoid robots cost about $100,000, with perhaps 10,000 units produced annually. But manufacturing costs tend to plummet with scale:

For solar energy, every doubling of production was associated with a 20% decline in costs. In other industries, we see estimates ranging from 5-40%, so 20% seems a reasonable middle point.

That means a 1000x increase in production (10 doublings), should decrease costs 10x to $10,000/unit. That’s around the cost of manufacturing a car.

However, humanoid robots only use about 10% the materials of a car, so it’s plausible they could eventually become another 10x cheaper, or $1000 each.

Though, it’s also possible the elements for fine motor control remain far more difficult to manufacture. Let’s add 2x to account for that.

Robot operating costs

If a robot costs $10,000 and lasts for three years working 24/7, the hardware costs $0.40 per hour.

At $2000 each,

The idea this week: despite claims of stagnation, AI research still advanced rapidly in 2024.

Some people say AI research has plateaued. But a lot of evidence from the last year points in the opposite direction:

• New capabilities were developed and emerged
• Research indicates existing AI can accelerate science

And at the same time, important findings about AI safety and risk came out (see below).

AI advances might still stall. Some leaders in the field have warned that a lack of good data, for example, may impede further capability growth, though others disagree. Regardless, growth clearly hasn’t stopped yet.

Meanwhile, the aggregate forecast on Metaculus of when we’ll see the first “general” AI system — which would be highly capable across a wide range of tasks — is 2031.

All of this matters a lot, because AI poses potentially existential risks. We think making sure AI goes well is a top pressing world problem.

If AI advances fast, this work is not only important but urgent.

Here are some of the key developments in AI from the last year:

New AI models and capabilities

OpenAI announced in late December that its new model o3 achieved a large leap forward in capabilities. It builds on the o1 language model (also released in 2024),

This week, we’re looking back at some of our top content from the year!

Here are some of our favourite and most important articles, posts, and podcast episodes we published in 2024:

Articles

Factory farming — There’s a clear candidate for the biggest moral mistake that humanity is currently making: factory farming. We raise and slaughter 1.6-4.5 trillion animals a year on factory farms, causing tremendous amounts of suffering.

The moral status of digital minds — Understanding whether AI systems might suffer, be sentient, or otherwise matter morally is potentially one of the most pressing problems in the world.

Should you work at a frontier AI company? — Working at a frontier AI company is plausibly some people’s highest-impact option, but some roles could be extremely harmful. So it’s critical to be discerning when considering this option — and particularly open to changing course. We’ve previously written about this topic, but explored it in more depth this year while taking account of recent developments, such as prominent departures at OpenAI.

Risks of stable totalitarianism — Some of the worst atrocities have been committed by totalitarian rulers. In the future, the threat posed by these regimes could be even greater.

Nuclear weapons safety and security — Nuclear weapons continue to pose an existential threat to humanity, but there are some promising pathways to reducing the risk.

Other posts

AI for epistemics — Our president and founder,

It’s giving season! Cue excitement…or dread?

If you’re anything like me, December is a busy time. You’re wrapping up projects, reviewing the past year’s work, planning for holidays, and buying gifts. (Not to mention, drafting a newsletter!)

So “giving season” — the time of year when most charitable donations are made — may just feel like one more thing to do. But donating is one of the most important decisions you can make.

Consider that:

• If you have an average UK/US income and donate 10% of it, this year you can save a child who would otherwise have died of malaria.
• There are other cause areas where you can potentially have an even bigger impact.

Of course, the high stakes of giving can make it feel even worse to rush it, and even more daunting.

I’ve definitely struggled to live up to my ideals when faced with this. I can confirm that New Year’s Eve is not when you want to deal with details like finding a quick online payment method. And I used to be the executive director of Giving What We Can and a grantmaker for the EA Infrastructure Fund — so if you also struggle with this, you’re not alone!

My bottom line advice is: find ways to make fewer decisions. They’re stressful and time consuming.

Below are two key tips that work for me and make my giving season slightly less hectic.

The idea this week: there are no magical fixes for career burnout, but there are concrete steps that can help.

When I was in the last years of my PhD studying representations of science and technology in fiction, I started feeling tired every day. I was checked out from my research, and I had a nagging sense that I wasn’t as good at it as I used to be.

I now realise I was experiencing burnout — and these feelings are quite common.

The World Health Organisation will tell you that burnout is an occupational syndrome that results from chronic workplace stress. It’s characterised by energy depletion, increased negativity and cynicism about your job, and reduced efficacy.

In my case, I was struggling with a mismatch between my work and what I thought really mattered. I was doing a PhD to become a literature professor, but my research seemed fundamentally disconnected from what I cared about: helping with pressing world problems.

Once something feels pointless, it’s very difficult to muster the motivation to get it done.

The silver lining is that now I can use this experience to help others in my role as a career advisor. And here is one piece of advice I often give: if you can, try to find work that aligns with what you think matters. In order to do this, it’s important to first reflect on what problems you care about and how to best tackle them.

The idea this week: biosecurity experts disagree on many of the field’s most important questions.

We spoke to more than a dozen biosecurity experts to understand the space better. We let them give their answers anonymously so that they could feel comfortable speaking their minds.

We don’t agree with everything the experts told us — they don’t even agree with one another! But we think it can be really useful for people who want to learn about or enter this field to understand the ongoing debates and disagreements.

We already published the first article on their answers about misconceptions in biosecurity, and we’re now sharing three more editions, completing this four-part series:

1. AI’s impact on biosecurity

We think one of the world’s most pressing problems is the risk of catastrophic pandemics, and powerful AI could make this risk higher than ever before.

Experts generally agreed that AI developments pose new risks, but there was some disagreement on how big and immediate the threat is.

These are some key quotes from the experts on areas of disagreement:

• “AI may really accelerate biorisk. Unfortunately, I don’t think we have yet figured out great tools to manage that risk.” (Read more)
• “My hot take is that AI is obviously a big deal, but I’m not sure it’s actually as big a deal in biosecurity as it might be for other areas.”