This project idea suggests expanding an existing dataset curated by Luke Muehlhauser, which focuses on global priorities like existential risks and technological progress. Currently, the dataset lacks comprehensive metrics related to animal suffering (both in factory farms and the wild) and threats from bioengineered pathogens. Addressing these gaps could help researchers, policymakers, and effective altruists make better-informed decisions when comparing interventions or allocating resources.

Expanding the Dataset

The expansion would focus on three key areas:

• Factory-farmed animals: Annual population estimates by species and region, sourced from databases like FAO and industry reports.
• Wild animals: Global population estimates weighted by proxies for sentience, such as neuron counts or cognitive complexity, to assess moral significance.
• Emerging biothreats: Historical or projected data on fatalities caused by bioengineered pathogens, including lab leaks or bioterrorism incidents.

The output would be a structured and interoperable dataset designed to integrate with Muehlhauser’s existing work, along with a methodological note explaining data sources and assumptions.

Key Stakeholders and Execution

Potential beneficiaries include animal welfare organizations, biosecurity experts, and researchers who rely on quantitative data for analysis. One way this could be executed is in phases:

1. Start with factory farming data from publicly available sources (MVP).
2. Collaborate with neuroscientists and ecologists to estimate neuron-based metrics for wild animals.
3. Partner with biosecurity researchers to compile anonymized data on bioengineered pathogens without revealing sensitive details.

The dataset would likely be a public good, possibly funded by grants or institutional partnerships rather than monetization.

Comparative Advantages

Unlike existing datasets—such as FAOSTAT (livestock numbers), Animal Welfare Institute reports (U.S.-centric welfare conditions), or the Global Catastrophic Risk Institute’s biosecurity datasets—this effort would uniquely combine insights on both animal suffering and emerging technological risks within one interoperable framework. This allows for cross-cause prioritization, such as comparing the impact of reducing factory farming versus preventing engineered pandemics.

By refining these gaps, the expanded toolkit could enable more nuanced ethical and policy decisions while minimizing controversy through transparency in methodology.