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80,000 Hours has updated it's career review on working at an AI company, originally written in June 2023. Here's Claude's summary of the main changes:
Key differences:
- Tone and stance:
- The newer article adopts a more cautious and nuanced tone overall.
- It places greater emphasis on the potential downsides and risks of working at frontier AI companies.
- The updated version is more explicit about the possibility of contributing to harm.
- Categorization of companies:
- The original article refers to "leading AI labs" like OpenAI, Google DeepMind, and Anthropic.
- The newer article uses the term "frontier AI companies" and includes additional companies like Meta, Mistral, and xAI as contenders.
- Discussion of specific roles:
- The updated article provides more detailed information about different types of roles within AI companies and their potential impact.
- It more clearly distinguishes between roles aimed at reducing catastrophic risks and those that primarily accelerate AI progress.
- Career capital considerations:
- While both articles mention career capital benefits, the newer one explores potential downsides more thoroughly, such as the risk of changing one's views due to the work environment.
- Company responsibility:
- The updated article places more emphasis on assessing the responsibility of individual companies and provides specific examples of concerns (e.g., events at OpenAI).
- Alternatives and recommendations:
- The newer article provides more concrete alternatives to working at frontier AI companies, including government initiatives and non-profit research organizations.
- It offers more specific advice on how to mitigate downsides if one does choose to work at a frontier AI company.
- Ethical considerations:
- The updated version delves deeper into the ethical implications of working on AI capabilities and the potential for contributing to catastrophic risks.
- Current context:
- The newer article includes more recent events and developments in the AI field, reflecting the fast-moving nature of the industry.
Overall, the updated article presents a more complex and cautious view of working at frontier AI companies. It maintains that these roles can be high-impact, but it places greater emphasis on the potential risks and the need for careful consideration before taking such positions.
This seems like a significant shift in tone, but there doesn't seem to be any acknowledgement that this is the case
Curated and popular this week
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Note: I am not a malaria expert. This is my best-faith attempt at answering a question that was bothering me, but this field is a large and complex field, and I’ve almost certainly misunderstood something somewhere along the way.
Summary
While the world made incredible progress in reducing malaria cases from 2000 to 2015, the past 10 years have seen malaria cases stop declining and start rising. I investigated potential reasons behind this increase through reading the existing literature and looking at publicly available data, and I identified three key factors explaining the rise:
1. Population Growth: Africa's population has increased by approximately 75% since 2000. This alone explains most of the increase in absolute case numbers, while cases per capita have remained relatively flat since 2015.
2. Stagnant Funding: After rapid growth starting in 2000, funding for malaria prevention plateaued around 2010.
3. Insecticide Resistance: Mosquitoes have become increasingly resistant to the insecticides used in bednets over the past 20 years. This has made older models of bednets less effective, although they still have some effect. Newer models of bednets developed in response to insecticide resistance are more effective but still not widely deployed.
I very crudely estimate that without any of these factors, there would be 55% fewer malaria cases in the world than what we see today. I think all three of these factors are roughly equally important in explaining the difference.
Alternative explanations like removal of PFAS, climate change, or invasive mosquito species don't appear to be major contributors.
Overall this investigation made me more convinced that bednets are an effective global health intervention.
Introduction
In 2015, malaria rates were down, and EAs were celebrating. Giving What We Can posted this incredible gif showing the decrease in malaria cases across Africa since 2000:
Giving What We Can said that
> The reduction in malaria has be
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"Part one of our challenge is to solve the technical alignment problem, and that’s what everybody focuses on, but part two is: to whose values do you align the system once you’re capable of doing that, and that may turn out to be an even harder problem", Sam Altman, OpenAI CEO (Link).
In this post, I argue that:
1. "To whose values do you align the system" is a critically neglected space I termed “Moral Alignment.” Only a few organizations work for non-humans in this field, with a total budget of 4-5 million USD (not accounting for academic work). The scale of this space couldn’t be any bigger - the intersection between the most revolutionary technology ever and all sentient beings. While tractability remains uncertain, there is some promising positive evidence (See “The Tractability Open Question” section).
2. Given the first point, our movement must attract more resources, talent, and funding to address it. The goal is to value align AI with caring about all sentient beings: humans, animals, and potential future digital minds. In other words, I argue we should invest much more in promoting a sentient-centric AI.
The problem
What is Moral Alignment?
AI alignment focuses on ensuring AI systems act according to human intentions, emphasizing controllability and corrigibility (adaptability to changing human preferences). However, traditional alignment often ignores the ethical implications for all sentient beings. Moral Alignment, as part of the broader AI alignment and AI safety spaces, is a field focused on the values we aim to instill in AI. I argue that our goal should be to ensure AI is a positive force for all sentient beings.
Currently, as far as I know, no overarching organization, terms, or community unifies Moral Alignment (MA) as a field with a clear umbrella identity. While specific groups focus individually on animals, humans, or digital minds, such as AI for Animals, which does excellent community-building work around AI and animal welfare while
this is really awesome to see!