Hide table of contents

I thought this overview of 2024 from the Bulletin of the Atomic Scientists might be of interest to people[1]. You can read the full statement (with more detailed data) as a PDF here.

Some quotes:

In 2024, humanity edged ever closer to catastrophe. Trends that have deeply concerned the Science and Security Board continued, and despite unmistakable signs of danger, national leaders and their societies have failed to do what is needed to change course. Consequently, we now move the Doomsday Clock from 90 seconds to 89 seconds to midnight—the closest it has ever been to catastrophe. Our fervent hope is that leaders will recognize the world’s existential predicament and take bold action to reduce the threats posed by nuclear weapons, climate change, and the potential misuse of biological science and a variety of emerging technologies.

The countries that possess nuclear weapons are increasing the size and role of their arsenals, investing hundreds of billions of dollars in weapons that can destroy civilization. The nuclear arms control process is collapsing, and high-level contacts among nuclear powers are totally inadequate given the danger at hand. Alarmingly, it is no longer unusual for countries without nuclear weapons to consider developing arsenals of their own—actions that would undermine longstanding nonproliferation efforts and increase the ways in which nuclear war could start.

Daunting biological threats

The off-season appearance and in-season continuance of highly pathogenic avian influenza (HPAI), its spread to farm animals and dairy products, and the occurrence of human cases have combined to create the possibility of a devastating human pandemic. Supposedly high-containment biological laboratories continue to be built throughout the world, but oversight regimes for them are not keeping pace, increasing the possibility that pathogens with pandemic potential may escape. Rapid advances in artificial intelligence have increased the risk that terrorists or countries may attain the capability of designing biological weapons for which countermeasures do not exist.

 

Leaders around the world could reduce the biological threats facing humanity, and thereby move the hands of the Doomsday Clock away from midnight, by:

  • Increasing surveillance of disease in humans, animals, and plants and sharing the results with all nations.
  • Establishing knowledgeable authorities and experts to provide trustworthy up-to-date information about diseases of concern and their movement throughout the world.
  • Increasing the reporting of changing disease patterns as the climate changes and updating preparedness, surveillance, response, recovery, and mitigation plans accordingly and immediately.
  • Slowing the proliferation of high-containment laboratories and establishing norms for the use and acquisition of biological material.
  • Dismantling active biological weapons programs.
  1. ^

    I'm no expert and I haven't fact checked any of this. Let us know if you think anything here is inaccurate or misleading!

14

0
0

Reactions

0
0
Comments1


Sorted by Click to highlight new comments since:

It would be useful if there was a clock / measure / indicator like this, but for AI risk. Seems like a good way to communicate hard-to-grasp existential risks to the general public.

Curated and popular this week
 ·  · 12m read
 · 
Economic growth is a unique field, because it is relevant to both the global development side of EA and the AI side of EA. Global development policy can be informed by models that offer helpful diagnostics into the drivers of growth, while growth models can also inform us about how AI progress will affect society. My friend asked me to create a growth theory reading list for an average EA who is interested in applying growth theory to EA concerns. This is my list. (It's shorter and more balanced between AI/GHD than this list) I hope it helps anyone who wants to dig into growth questions themselves. These papers require a fair amount of mathematical maturity. If you don't feel confident about your math, I encourage you to start with Jones 2016 to get a really strong grounding in the facts of growth, with some explanations in words for how growth economists think about fitting them into theories. Basics of growth These two papers cover the foundations of growth theory. They aren't strictly essential for understanding the other papers, but they're helpful and likely where you should start if you have no background in growth. Jones 2016 Sociologically, growth theory is all about finding facts that beg to be explained. For half a century, growth theory was almost singularly oriented around explaining the "Kaldor facts" of growth. These facts organize what theories are entertained, even though they cannot actually validate a theory – after all, a totally incorrect theory could arrive at the right answer by chance. In this way, growth theorists are engaged in detective work; they try to piece together the stories that make sense given the facts, making leaps when they have to. This places the facts of growth squarely in the center of theorizing, and Jones 2016 is the most comprehensive treatment of those facts, with accessible descriptions of how growth models try to represent those facts. You will notice that I recommend more than a few papers by Chad Jones in this
LintzA
 ·  · 15m read
 · 
Introduction Several developments over the past few months should cause you to re-evaluate what you are doing. These include: 1. Updates toward short timelines 2. The Trump presidency 3. The o1 (inference-time compute scaling) paradigm 4. Deepseek 5. Stargate/AI datacenter spending 6. Increased internal deployment 7. Absence of AI x-risk/safety considerations in mainstream AI discourse Taken together, these are enough to render many existing AI governance strategies obsolete (and probably some technical safety strategies too). There's a good chance we're entering crunch time and that should absolutely affect your theory of change and what you plan to work on. In this piece I try to give a quick summary of these developments and think through the broader implications these have for AI safety. At the end of the piece I give some quick initial thoughts on how these developments affect what safety-concerned folks should be prioritizing. These are early days and I expect many of my takes will shift, look forward to discussing in the comments!  Implications of recent developments Updates toward short timelines There’s general agreement that timelines are likely to be far shorter than most expected. Both Sam Altman and Dario Amodei have recently said they expect AGI within the next 3 years. Anecdotally, nearly everyone I know or have heard of who was expecting longer timelines has updated significantly toward short timelines (<5 years). E.g. Ajeya’s median estimate is that 99% of fully-remote jobs will be automatable in roughly 6-8 years, 5+ years earlier than her 2023 estimate. On a quick look, prediction markets seem to have shifted to short timelines (e.g. Metaculus[1] & Manifold appear to have roughly 2030 median timelines to AGI, though haven’t moved dramatically in recent months). We’ve consistently seen performance on benchmarks far exceed what most predicted. Most recently, Epoch was surprised to see OpenAI’s o3 model achieve 25% on its Frontier Math
Omnizoid
 ·  · 5m read
 · 
Edit 1/29: Funding is back, baby!  Crossposted from my blog.   (This could end up being the most important thing I’ve ever written. Please like and restack it—if you have a big blog, please write about it). A mother holds her sick baby to her chest. She knows he doesn’t have long to live. She hears him coughing—those body-wracking coughs—that expel mucus and phlegm, leaving him desperately gasping for air. He is just a few months old. And yet that’s how old he will be when he dies. The aforementioned scene is likely to become increasingly common in the coming years. Fortunately, there is still hope. Trump recently signed an executive order shutting off almost all foreign aid. Most terrifyingly, this included shutting off the PEPFAR program—the single most successful foreign aid program in my lifetime. PEPFAR provides treatment and prevention of HIV and AIDS—it has saved about 25 million people since its implementation in 2001, despite only taking less than 0.1% of the federal budget. Every single day that it is operative, PEPFAR supports: > * More than 222,000 people on treatment in the program collecting ARVs to stay healthy; > * More than 224,000 HIV tests, newly diagnosing 4,374 people with HIV – 10% of whom are pregnant women attending antenatal clinic visits; > * Services for 17,695 orphans and vulnerable children impacted by HIV; > * 7,163 cervical cancer screenings, newly diagnosing 363 women with cervical cancer or pre-cancerous lesions, and treating 324 women with positive cervical cancer results; > * Care and support for 3,618 women experiencing gender-based violence, including 779 women who experienced sexual violence. The most important thing PEPFAR does is provide life-saving anti-retroviral treatments to millions of victims of HIV. More than 20 million people living with HIV globally depend on daily anti-retrovirals, including over half a million children. These children, facing a deadly illness in desperately poor countries, are now going
Relevant opportunities