Jacob Peacock 🔎

Research Advisor at Stanford focused on improving animal welfare. Quantitative social scientist & ex-computational biologist. Open science and anti-speciesism.

[Jacob Peacock 🔎 @JacobPeacock1]

Predict the future for animals and win $3,400. My tip: 7% chance of US plant-based meat reaching 10% marketshare by 2031 is too high sadly...
https://t.co/VwwVI6wprT

[Jacob Peacock 🔎 @JacobPeacock1]

Careful, mechanistic thinking re:effects of AI on cultivated meat: https://t.co/ekxjfy5lNT

I enjoyed consulting as an expert reviewer on this report. If your work would benefit from thoughtful, critical and and speedy technical review, please reach out!

[Jacob Peacock 🔎 @JacobPeacock1]

@PracheeAC Thanks! I'll have to give Zenodo a try at some point, and that makes sense re:IMRAD

[Jacob Peacock 🔎 @JacobPeacock1]

@niplav_site @tyler_m_john Interesting, I'll check out the paper in more detail!

[Jacob Peacock 🔎 @JacobPeacock1]

@tyler_m_john It's ez to believe that using only round percentages is less accurate, but I'm more curious whether the added precision itself was accurate. 2/2

[Jacob Peacock 🔎 @JacobPeacock1]

@tyler_m_john Agree with your general take here, but have always questioned the rounding studies specifically. IIRC, they took 1%-precision forecasts and rounded them, but I'd rather see random reassignment to a different percentage in the same range? (Eg, 95% -> 91%) 1/

[Jacob Peacock 🔎 @JacobPeacock1]

@IshanKhire @datagenproc Thank you!

[Jacob Peacock 🔎 @JacobPeacock1]

@IshanKhire @datagenproc Probably more similar to Global Burden of Disease and definitely involving some modeling. I'd expect start initially mostly desk research, but do more fieldwork later on to improve models; eg, collecting more representative shrimp and fish weights.

[Jacob Peacock 🔎 @JacobPeacock1]

@dcshiller I'll give a listen, very cool!

[Jacob Peacock 🔎 @JacobPeacock1]

Instead: "Please briefly describe how you used LLMs in preparing your responses, with links to transcripts where practical."

[Jacob Peacock 🔎 @JacobPeacock1]

I see two LLM policy mistakes in hiring processes all the time:

1. Total ban on LLMs. Using an LLM for spellchecking, searching your own past writing for reference, or answering factual experience questions should absolutely be permissible. 🧵

[Jacob Peacock 🔎 @JacobPeacock1]

2. Requesting transcripts. Linking to a ChatGPT or Claude transcript is great—if you used that tool. Your best applicants are using extensions, skills, context and agents that won't meaningful appear in a transcript. And do you really want to read reams of transcript anyway?

[Jacob Peacock 🔎 @JacobPeacock1]

@peterwildeford Curious what set-up you're using for data analysis work? I used to default to jupyter notebooks, but haven't found ergonomic LLM integrations, so I just have a ton of scripts like the before-jupyter times

[Jacob Peacock 🔎 @JacobPeacock1]

Final week to apply to join the Animal Charity Evaluators Board! Deadline March 1st.
https://t.co/ylDeb4dZAM

[Jacob Peacock 🔎 @JacobPeacock1]

.@AnimalCharityEv is looking for new board members! Join me and a talented group of leaders to guide ACE's work to identify highly cost-effective animal charities. Apply by March 1st.
https://t.co/ylDeb4dZAM

[Jacob Peacock 🔎 @JacobPeacock1]

Made my first podcast appearance on @veganreportshow, hosted by Rayane Laddi. Seth Green and I talk AI, MAHA, nudges, social desirability bias, and more: https://t.co/tscguHnCw6

[Jacob Peacock 🔎 @JacobPeacock1]

@alexolegimas Exciting, I'll plan to be there!