Yes, thanks for the reminder. I have long (incorrectly) thought pond loach is just one species, until Ryan pointed out that there are at least 4 (but seems like only two are commercially popular). 

From what I learned, even though mud carp should be the biggest used fry for mandarin fish feed, many other species such as other carps and tilapia are also used in significant amounts. But in terms of cause priortization/conceptualization, grouping them together makes perfect sense!

Yes feeder fish for mandarin fish is a big category. But my understanding is that many species' fry are used, including pond loaches (rarely though, I believe). I am not sure the majority of them are one species (i.e. mud carp). 

Also, since we need to count fry to come up with a few trillion figure for feeder fish for mandarin fish, we also need to count pond loach numbers by the fry stage. Estimates of pond loach survival rates from fry to sellable fish vary widely, from 2% to 10%. Given that the number of pond loach slaughtered each year is roughly 10B, that's ~100B-500B pond loaches slaughtered each year. 

Yeah, maybe mud carp or some other species is no.1, but I am guessing it is also possible pond loach is still no.1 or close.

Thanks for asking, here are some ideas I personally wish funders would consider at least investigating. The epistemic status of some of these ideas is not great, and I never attempted any robust analysis on the expected values of these potential interventions/causes, but I hope they are worth investigating. 

• Stop/slow down the development of remotely controllable insects (not just for AW reasons; such a tech can be misused for surveillance, military uses, and bioterrorism)
• Stop the spread of caged broiler systems, particularly in African countries, and other LMICs.  
• Help the most (probably) farmed fish on earth (in terms of number of individuals, counting from actual quantities sold), pond loaches, who suffer from mortality rates like 20-80%, stressful and long transports, and long, excruciating slaughters.
  • FWI is investigating potential interventions, both on the on-farm condition, and slaughter
• Using "Virtual Control Groups" to reduce the number of animals used in the control groups in preclinical studies and basic research
  • think about it, the control group should be similar across different experiments using the same strain of animal. But animals in the control arm also suffer, because they have to be captivated in small spaces, eat boring food, fed "vehicle chemicals" meant to carry the drug in the test arm, and also have their blood drawn. So the idea is: why don't we reuse historical control group data (it's more complicated than that, but that's the spirit)
• Building an LLM-based agent that can allow regulators and drug discovery researchers to have an easy-to-use AI agent with a text-based chat interface (credit to Alexandra Hammond, who developed the idea with me). This idea specifically tackles the problem that many regulators, and some researchers, are reluctant to use ML/DL models that can predict toxicities of chemicals to replace animal tests because there are too many different models, with each of them working for only a narrow range of chemicals. This idea also partly solves the "blackbox concern" excuse used by some regulators to not adopt AI alternatives to animal tests. This idea might be achievable from two different architectures, or the combination of them
  • Allow the LLM-based agent to access and utiliize various ML/DL models that can be found online, open-sourced, and either teach researchers and regulators how to apply them to certain kinds of chemicals, or even just give the prediction directly in the chat.
  • Train a multi-modal LLM, with one of its modes being toxicity data.
• It seems to me that many alt-protein companies, particularly cultivated meat ones, are interested in using AI to take their research to a new level. But since each of these companies data are proprietary, none of them can get their models to become a large model. What if we fund an open-source large database for alt proteins which everyone can use to train models to help their work. Or maybe we even just fund both the database and the training of a "large-altpro-model".
• AI to help wild animal welfare. A particular intervention that might serve many values, such as signalling effect, signposting, experimentation, and piloting, is to use AI-controlled drones that can identify animals who are in serious injuries or diseases so bad that it means they will not survive for long (and will die from starvation, dehydration, being eaten alive, or multiple organ failures). The drone would have the capability to euthanize the animal on the spot, preferably with methods that would not leave a trace (e.g. if a chemical was used, it has to be non-toxic to at least predators and scavengers nearby). The design is to try to make sure there is as little counterfactual impact on the situation, other than the alleviation of suffering by killing the animal sooner
  • Note: My original idea was to even limit the use case to animals with broken spines or multiple broken limbs so that counterfactually, not even the location of the death would differ.
• Supporting the research of using AI-controlled drones, preferably of insect sizes, for investigating cruelty in factory farms
  • Of course, don't use remote-controllable insects.
  • The idea could be expanded to investigating any animal cruelty cases
  • Controversial and risky, socially, politically, and legally

Thank you for the post!

Animals are not one issue

I have long wished to write or see an EA forum post about this. Thanks for doing it!

I don't understand the negative karma for a comment that has 5 agreement votes to 0 disagreement. I wonder if some of you can explain the reason for agreeing but downvoting this?

Thank you for the great post! I don't have comments right now on your subject matter, but want to provide a bit of information about my region.

and then trying to steer the conversation as quickly as possible back towards safer, intuitive examples, like malaria nets, lead poisoning, factory farms, biosecurity, etc.

In China, my sense is that factory farming is not a "safe" option when it comes to explaining EA, cause prioritization, etc to non-EAs or even new EAs. On the other hand, for some reason, AI seems to be much more "safe" than factory farming. 

Spare billions of chickens from cages by preventing the expansion of broiler chicken cages in East and Southeast Asia. [Short-term]

Thank you for the post! I am glad that this is on the radar! (broiler cages in particular, but also in general, thwarting the growth of certain industries or practices)

Thank you for this very helpful post. I am insipred to reflect on my often muddled and repetitive writing style, and then improve.

Do you know if the Centre for Biomedical Ethics was consulted?

I am trying to ask. I will PM you when I get an answer. 

It would also be very interesting to know how the university and IRB approval worked here. 

I will try to investigate too.

Please feel free to email me to keep in touch. Or add me on linkedin.

Clarification: They commissioned the YLL School of Medicine, particularly the Life Science Institute, to validate the idea of using CL1 to build datacentres. Of course they won't commission a centre for bioethics to do that.