Hi Itamar That sounds great — I’d be happy to connect

Thanks for the kind words! I am glad you found the tool useful.

A quick update: we’ve now expanded the system so it doesn’t just quantify negative affective experiences, but also positive ones. Because of this broader scope, the new version is called Hedonic-Track GPT, and it is gradually replacing the earlier Pain-Track GPT.

We may need to update this article soon so readers are directed to the most current tool. In the meantime, you can find the link to the Hedonic-Track GPT here:

https://chatgpt.com/g/g-cpXxeWtgg-hedonic-track

Thank you very much for this thorough analysis and for the constructive comments.
Cynthia will address the points related to the results of the study, while I’ll focus here on the methodological aspects.

One of the most important points you raise touches on the core of the Welfare Footprint Framework itself: we recognize that inferring the affective states of other beings is enormously challenging—both in scope and depth. This task can never be complete; it will always require revisions and corrections as new evidence becomes available. The Welfare Footprint Framework is, in essence, an attempt to structure this challenge into as many workable, auditable pieces as possible, so that the process of inference can be progressively improved and openly scrutinized.

You are absolutely right that several painful conditions in chickens were not included in this initial analysis. This was a conscious decision—not because those harms are unimportant, but because we had to start with a subset that we judged to be among the most influential and best documented. The framework is designed precisely so that others can build upon it by incorporating additional conditions, refining prevalence estimates, or reassessing intensities. In that sense, this work should be seen as a living model, not a closed dataset.

Regarding the concern about the lack of use of high-quality statistical techniques, our approach is pragmatic. Where robust statistical analyses are feasible—such as in estimating prevalence or duration—they are of course welcome and encouraged. But in areas where measurement is currently impossible—most notably the intensity of affective states—we deliberately avoid mathematical sophistication for its own sake. No amount of elegant equations can compensate for the fact that subjective experience is, for now, beyond direct measurement. What we can do is gather convergent evidence from different sources - e.g. behavior, physiology, neurology, evolutionary reasoning - and generalize that evidence into transparent, revisable estimates, and make every assumption explicit so that others can challenge and adjust them.

As for the legitimacy of this approach, we believe that, while imperfect and always improvable, quantifying affective experiences is vastly more informative than relying solely on indirect indicators such as mortality. Animals can live long, physically healthy lives that are nevertheless filled with frustration, chronic pain, fear, or monotony—forms of suffering invisible to metrics that focus only on death or disease. By directing efforts toward gathering as much evidence as possible to infer the intensity and duration of each stage spent in negative and positive affective states, we can begin to capture what actually matters to the animal.

The framework has also evolved since this analysis was first produced. At that time, we focused primarily on negative affective states, but we have now extended the methodology to include Cumulative Pleasure alongside Cumulative Pain. Positive affective states are now being systematically quantified using the same operational principles, creating a fuller picture of animal welfare.

Finally, we are developing an open, collaborative platform where Pain-Tracks and Pleasure-Tracks can be published, discussed, and iteratively improved by the broader scientific community. Each component of a track—for example, the probability assigned to a certain intensity within a phase of an affective experience—could be challenged and refined, potentially even through expert voting or consensus mechanisms. The aim is to make welfare quantification transparent, dynamic, and collective rather than proprietary.

Thanks again for putting our work under the microscope—this is exactly what it needs. The Framework is meant to evolve, and feedback like yours helps it grow in the right direction.

Thanks Vasco. I’d like to clarify that Disabling Pain is also a severe/intensive level—think of it as the kind of crippling back pain or intense headache that prevents any enjoyment or productivity. And our project study found that moving a hen from a furnished cage to a cage-free aviary prevents, on average, hundreds of hours of Disabling Pain during her laying life. Specifically, transitioning to cage-free systems avoids approximately 275 hours of Disabling pain ( https://welfarefootprint.org/laying-hens).

Additionally, as argued in the book, the estimates for Excruciating Pain were extremely conservative (i.e. Cumulative Pain in both cage systems is likely higher than estimated). We'll have full estimates soon, once 'The Welfare Footprint of the Egg' is released.

Thanks, Vasco. I think we’ve clarified where our frameworks diverge—you prioritize maximizing expected welfare, assuming that equivalences across intensities are possible once the time component is introduced (an assumption I don’t share), whereas I tend to emphasize minimizing the most intense forms of suffering. Both approaches have their merits, but they naturally lead to different prioritizations. Perhaps we can just agree to disagree on this point.

Vasco, thank you for inviting me to look at your post. Here are some considerations .

Point 1: Uncertainty in Hedonic Capacity for Primitive Organisms
 Our recent EA Forum  post  explores the question of hedonic capacity for primitive organisms like ants, termites, and nematodes. I personally believe there are weak biological grounds—whether in neurological capacity or in behavioral prioritization needs—to support the view that these species can reach high‑intensity suffering levels, which are our primary ethical concern. Therefore, in my view, the suffering a an ant or a nematode can experience is not comparable to what a pig, cow, or chicken can, making the former not a moral priority.

Point 2: The Risks of Aggregating Intensities and Durations
 You noted in one message you sent me that, as a classical utilitarian, you are indifferent between averting 1 billion animal‑years of low‑intensity suffering and 1 animal‑year of high‑intensity suffering, as long as expected welfare increases. That’s a revealing point and highlights precisely why we at the Welfare Footprint Institute believe it is not advisable to create equivalences between intensities based on duration. Aggregation of this sort, besides lacking a sound empirical basis (what is the equivalence of one hour of Excruciating Pain in Annoying Pain? one month? one million years?), can actually mask and divert attention from what some of us consider really important and of primary moral concern: minimizing high levels of Pain (namely Excruciating and Disabling, in the Welfare Footprint classification). For this reason, our methodology explicitly measures time in distinct intensity categories rather than collapsing them into a single score, using tools like the Cumulative Pain metric (see also our EA Forum piece “Short Agony or Long Ache?” ).

Point 3: Prioritizing Farmed Animals for Tractability and Capacity

 Just to reinforce a point about our focus on farmed animals: this stems not only from their clear high hedonic capacity but also from tractability—we can much more reliably intervene and measure impacts in these systems. 

This is a very thought-provoking idea—thank you Aaron for sharing it. That said, I wonder about the analogy with carbon credits, which are based on the fungibility of carbon: one ton emitted can, in principle, be balanced by one ton absorbed elsewhere. When it comes to sentient experience, things are less straightforward.

For example, if a laying hen endures 200 hours of Disabling Pain, what would it mean to “offset” that suffering? Supporting a happier life for another animal may be valuable in itself, but it doesn’t reverse or neutralize the original experience. Each animal is a distinct individual, and pain—unlike carbon—cannot be canceled by pleasure elsewhere.

From a practical standpoint too, the goal should be to ensure funding is tied as tightly as possible to direct improvements at the source of suffering. The risk of a credit market is that it can introduce a layer of abstraction, where the focus shifts from making a specific farm better to simply trading units of 'welfare' to balance a ledger.

Speaking from the perspective of the Welfare Footprint approach (apologies for the self-reference), I see real potential in identifying reforms that can prevent large amounts of intense suffering in a measurable way. For instance, if evidence shows that implementing electrical stunning in a shrimp slaughter facility could avert, say, one billion hours of Disabling Pain and one hundred thousand hours of Excruciating Pain annually—and if that reform costs $200,000—then this creates a clear and actionable opportunity to “pay to reduce time in intense pain” directly. That might align well with what you're suggesting, while avoiding some of the conceptual challenges that arise from offsetting.

Hi Toby, thank you for your kind words. I might take some time to answer, but I’m happy to continue this back-and-forth (and please feel free to challenge or push on any point you disagree with).

I believe the problem we face is practical in nature: we currently lack direct access to the affective states of animals, and our indirect methods become increasingly unreliable as we move further away from humans on the evolutionary tree. For instance, inferring the affective capacity of a reptile is challenging, let alone that of an arthropod or annelid. But when you mention the caveat “even in principle,” I feel much more optimistic. I do believe that, in principle, how affect varies can be projected onto a universal scale—so universal that it could even compare affective experiences across sentient beings on other planets or in digital minds that have developed hedonic capacity.

Despite the variety of qualitative aspects (e.g., whether Pain stems from psychological or physical origins, or signals an unfulfilled need, a threat, damaged tissue, or a desire), the goodness or badness of a feeling—its ‘utility’—should be expressible along a single dimension of real numbers, with positive values for Pleasure, negative values for Pain, and zero as a neutral point. Researchers like Michael Mendl and Elizabeth Paul have explored similar ideas using dimensional models of affect, suggesting that valence and arousal might offer a way to compare experiences across species, which supports the idea of a universal scale—though they also note the empirical gaps we still face.

So, I see this challenge as a technical and scientific issue, not an epistemological one. In other words, I’m optimistic that one day we’ll be able to say that a Pain value of, let’s say, -2.456, represents the same amount of suffering for a human, a fish, or a fly—provided they have the neurological capacity to experience this range of intensities. I recognize this is a bold claim, and given the current lack of empirical data, it’s highly speculative—perhaps even philosophical. But this is my provisional opinion, open to change, of course! :)

Not at all! I appreciate the great exchange, the challenging ideas, and the opportunity to clarify any points. Please feel free to continue discussing any aspect you think needs further clarification.

Thank you, Alfredo, for raising awareness and contributing this piece on such a critical issue. As a source of profound suffering, this devastating disease demands urgent and prioritized attention from society.