2.1. Theoretical considerations regarding welfare

Animals experience welfare, even if their welfare can be different in important ways from human welfare. From the perspective of the theory of welfare, it is indefensible to assume that animal welfare only matters insofar as humans are willing to pay for it. If we consider that the social planner’s objective is to consider either (a) all preferences or (b) all the positive and negative valenced states that individuals experience (depending on whether welfare is understood in terms of preferences or in terms of hedonic states), then both humans’ and animals’ welfare should matter directly. Given this, animal welfare is intrinsically valuable, implying that methods are needed such as those outlined in this paper for valuing animal welfare intrinsically. As one among many examples of arguments for the view that animal welfare matters intrinsically, consider the argument from species overlap (Horta Reference Horta2014). In brief, it is very difficult to identify any trait that would explain why all human welfare has intrinsic worth, whereas animal welfare does not. There are, of course, many features that may explain why human welfare matters more than animal welfare, but that is not the issue at hand here. Instead, the question is whether there is any trait that could explain why, say, a dog’s being in pain only matters insofar as a human cares about it, whereas that does not appear to be true for a human’s being in pain. In particular, it is implausible that humans’ WTP to avoid pain is the crucial trait, as, first, many humans have no WTP (infants, those with severe cognitive disabilities, people in comas etc.) and for any extended sense of “WTP,” such as being willing to work to avoid pain, animals have WTP in that sense. Therefore, it seems like a mere prejudice – often called “speciesism” – to insist that human welfare matters intrinsically and animal welfare does not (see also Singer, Reference Singer2023; Espinosa & Treich, Reference Espinosa and Treich2023b; Blackorby et al., Reference Blackorby, Bossert and Donaldson2005; Singer, Reference Singer1975).

2.2. Internal consistency within economics, policy and benefit–cost frameworks

Second, apart from the concerns just listed, a fully anthropocentric position is dubious from within the logic of mainstream economics and policy. One way to appreciate this point is to recognize that many animals have preferences over outcomes, and there is nothing within economics that explains why the preferences of this subset of individuals should be ignored, just as there was never an economic logic to ignoring the preferences of people in an earlier time based on their race, gender, or other factors. (The same point applies if welfare is understood in terms of hedonic states.)

It may be tempting to argue that animals lack some feature that is necessary for having welfare in the sense that is relevant to economic analyses. For instance, someone might argue that animals have zero WTP – or cannot even entertain the question of their WTP – and so are not market agents. Therefore, one might conclude that animals do not meet an essential condition for having welfare. However, neither condition is relevant to having welfare. Just as analyses should include the health and well-being impacts to individual Americans who happen to have zero WTP (e.g., if they do not earn wage incomes at any point during their life), so too the health and well-being impacts to animals must also be included. Likewise, the needs of those with limited cognitive abilities cannot be dismissed simply on the grounds that those individuals are not market agents. In cost–benefit analyses, monetary units are only one of the possible numeraires that economists take for interpersonal welfare comparisons. While economists often use changes in WTP to assess changes in welfare, their primary objective is to assess changes in welfare, which both humans and animals experience. So, the well-being impact of our actions on animals should be monetized in a way that incentivizes us to respect the actual well-being value of harm to animals (Budolfson, Reference Budolfson2023).

3.1. Animal QALYs

The objective of a QALY is to express two important dimensions of welfare with a single unit: namely, the quality and quantity of life. In the QALY framework, losing one QALY can be seen either as losing 1 year of perfect health or losing half of the maximum quality of life over 2 years, allowing for the straightforward conversion of one kind of welfare impact into the other. An AQALY has the same objective and provides the same expressive power. Such a tool is essential because human decisions affect both the quality of animals’ lives and the total amount of life lived. For example, if chickens are bred to grow more slowly, they have lower incidences of keel bone fractures than conventional chickens (which are bred to reach slaughter weight very rapidly). However, precisely by virtue of being (relatively) slow-growing, such chickens spend more time in intensive rearing facilities. So, if a policymaker decides to incentivize rearing slow-growth chickens, it will improve some aspects of welfare, but it may set back other aspects of welfare and will alter the lengths of animals’ lives. To express the total welfare impact of this policy change, therefore, we need to combine changes in the quality and quantity of life.

For example, QALY scores are in some cases based on surveys that employ a time tradeoff method. For instance, to assess the impact of a broken femur in terms of some quantity of life, respondents are asked when they would be indifferent between having a broken femur and sacrificing some amount of life at full health. If respondents would, on average, sacrifice 3 months of life to avoid this injury – 25% of a year – then, over the course of a year, the welfare of an individual with such an injury could be represented by 0.75 QALYs.

Animals, of course, cannot report the tradeoffs they would accept, which means that AQALYs cannot be computed via the same methodology. It is, therefore, a significant challenge to analyze animal welfare in a framework that is precise enough to make it implementable over a large set of situations but that is encompassing enough such as to take into account the specificities of different species. One first step is to adapt traditional animal welfare assessment frameworks. Espinosa (Reference Espinosa2023), for instance, demonstrates how the Five Freedoms framework – which is one of the most widely used models of animal welfare worldwide and is recognized by the World Organisation for Animal Health – can be used for this purpose. The Five Freedoms framework evaluates animal welfare along five dimensions: (i) freedom from hunger/thirst/malnutrition, (ii) freedom from fear/distress, (iii) freedom from physical discomfort, (iv) freedom from pain/injury/disease and (v) freedom to express normal patterns of behavior. Espinosa (Reference Espinosa2023) defines a scale of animal welfare that accounts for the number of violation points for each of these freedoms. Then, Espinosa and Treich (Reference Espinosa and Treich2023a) integrate the instantaneous welfare over the animal’s lifetime on this scale to define AQALY scores for animals.

It would be possible to define similar AQALY scores using other animal welfare tools, such as Alonso and Schuck-Paim’s (Reference Alonso and Schuck-Paim2021) pain-track method, which distinguishes four categories of animal pain and observable symptoms of their presence. With such a tool, it is possible to quantify the amount of time that animals spend in pain, to define tradeoff relationships between pain categories and then to define corresponding AQALY scores.

However, while widely used and historically significant, the Five Freedoms framework has some well-known limitations, the most frequently noted of which is that it limits attention to negative welfare states to the exclusion of positive welfare states. That is, the best welfare state that the framework acknowledges is one without the violation of any of the freedoms, which could still be a state that is far worse than the best welfare state available to the animal in question. The same problem afflicts the pain-track method, which focuses even more narrowly on pain, even to the exclusion of all other negative affective states. This particular limitation is usually understood as a reason to use the so-called Five Domains framework (Mellor & Reid, Reference Mellor and Reid1994) or the Welfare Quality framework (Blokhuis, Reference Blokhuis2008), the details of which are not important here, but both of which remedy this particular issue. The methods that Espinosa (Reference Espinosa2023) develop, however, can readily be adapted to such alternative welfare frameworks.

An attractive feature of the AQALY approach is that it allows researchers to explore welfare states that are considered worse than death (Weinstein et al., Reference Weinstein, Torrance and McGuire2009). As Espinosa and Treich (Reference Espinosa and Treich2021) show, many people believe that the lives of some animals in intensive production systems are not worth living. As a result, preventing those animals from coming into existence may improve social welfare overall. Policies that affect both the number and the quality of lives are difficult to discuss as they imply non-trivial tradeoffs discussed in population ethics (see Section 4.1). However, quantifying the welfare of animals on both positive and negative sides of a welfare scale can provide estimates that can be used to make these tradeoffs explicit.

Finally, a limitation is that this proposed AQALY framework attempts to measure animal welfare, encompassing aspects beyond health alone. Consequently, it is not entirely analogous to the QALY framework and rests on distinct foundations. In particular, QALYs are a health measure, not a welfare measure and health is just one component of welfare (i.e., it is possible to be at full health without being at full welfare). So, the value of an AQALY for a given species could be more precisely understood as a year of full human welfare adjusted by the welfare potential of that species. However, we have no measures of a year of full human welfare. So, for the sake of producing some estimate of the value of an AQALY (a welfare measure, of which health is one component), the methodology proposed here is to use the value of a QALY (a health measure). Since the value of a year of full human welfare is greater than the value of a QALY, this suggests that we are underestimating the value of an AQALY, that is, providing a conservative estimate. The examples below, which use the monetary equivalent of one QALY to assign monetary equivalents to the welfare of animals measured in AQALYs may therefore be more precisely interpreted as lower-bound estimates.

3.2. Welfare potential

Given AQALYs, the task now is to find a way to convert between AQALYs and (human) QALYs. The conceptual innovation here is to understand the link between these units using welfare potentials. An animal’s welfare potential is a measure of how good and bad the life of an individual of a given species can be relative to a human; equivalently, it is a measure of the amount of welfare that the animal can generate relative to a human. More concretely, suppose that it is possible to assess a human’s welfare on a 0-1 scale, as QALYs purport to do using health as a proxy, and that it is possible to assess an animal’s welfare on a 0-1 scale.Footnote ³ A welfare potential is an estimate of the relationship between these scales: it is a means for expressing the relationship between, say, a 0.5 on the animal scale and some number on the human scale. Presumably, this variable will vary considerably by species based on their respective cognitive capacities, understood broadly to include, among other things, their affective and social abilities. Perhaps a 0.5 on a chimpanzee scale is within an order of magnitude of the same value on a human scale – that is, at least 0.05. However, perhaps a 0.5 on a gecko’s scale is orders of magnitude lower – say, 0.00005.

Broadly, there are two methods that have been proposed for estimating welfare potentials. The first is an adaptation of the time tradeoff methodology that is used to estimate the impact of various diseases on human health. In the health context, this involves surveying individuals to determine when they are indifferent between some amount of time with a health burden and living some number of years fewer than they otherwise would (Lugnér & Krabbe, Reference Lugnér and Krabbe2020). In the present context, extending this method to animals would involve surveying people to determine when they are indifferent between an additional year of healthy human life and some number of years as an animal of a given species (Bruers, Reference Bruers2023). If people judge that it would take several years of life as a chimpanzee to be worth sacrificing an additional year of healthy human life, then this provides some reason to think that the intrinsic value of chimpanzee experience is lower than that of human experience by a corresponding amount.

There are, of course, challenges associated with this approach. For example, it is difficult to determine how, exactly, to interpret the tradeoffs that people report. For instance, to what degree do humans prefer being human for non-prudential reasons – that is, reasons unrelated to welfare, but due to, say, status quo bias, anthropocentrism or what Franz de Waal (Reference De Waal1999) calls “anthropodenial,” which is, roughly, the knee-jerk rejection of various cognitive capacities to animals? Since humans have never been pigs, they do not necessarily know how pigs experience the world; as a result, their self-reports may have little evidential value with respect to the intrinsic value of living as a pig versus alternatives.

Likewise, even if respondents limit their attention to prudential considerations, not all of them will be relevant to welfare potential, making it difficult to control for yet more possible confounds. For instance, if respondents are asked how many years of life they would sacrifice to avoid becoming a pig, they might reflect on the risk of swine flu, with the result that the incidence of that disease – and not just welfare potential – would be reflected in their answer.

Likewise, depending on how we interpret the tradeoffs that people report, it may be difficult to convert those tradeoffs into estimates of welfare potential. To continue with the example mentioned above, if it is plausible that status quo bias or “anthropodenial” explains some amount of people’s preference to live human over animal lives, then the strength of such biases must be quantified so that the appropriate discount rate can be applied. Otherwise, the time tradeoff method will underestimate the animals’ welfare potentials. By contrast, if it is plausible that anthropomorphism explains some amount of people’s preference to live animal lives – where humans are mistakenly attributing human-like (and welfare-relevant) traits to animals – then the time tradeoff method will overestimate animals’ welfare potentials. It could work out that such a bias is more prevalent for some animals than others; for instance, based on familiarity and affection, people may overestimate dogs’ welfare potentials relative to pigs’, despite there being few objective differences between these animals’ cognitive capacities.

The second methodology bypasses these questions by focusing on proxies that, in one way or another, bear more directly on how well or poorly an animal’s life can go. For instance, given the assumption that there is some important relationship between the increased functionality and processing power associated with larger brains and welfare potential, it is possible to define a function from neuron counts in certain brain regions to welfare potential, resulting in a single score per species that can be used to make interspecies welfare comparisons (Budolfson & Spears, Reference Budolfson, Spears and Fischer2019). Alternatively, it is possible to incorporate a wide range of neurophysiological, cognitive and behavioral traits into more complex multidimensional proxies that can be aggregated to produce a single overall welfare potential score (Fischer, Reference Fischer2024). These approaches parallel the way economists already try to capture complex phenomena by combining several proxies (e.g., assessing human development through proxies like education level, wealth and longevity).

There are predictable challenges here as well. First, proxy selection poses several problems. On a purely theoretical level, there is the difficulty of establishing a relationship between the proxy in question and differences in welfare potentials. Neuron counts, for instance, do not matter in themselves; they are important because they are associated with key intellectual and affective capacities that may bear on welfare potentials. However, the empirical evidence suggests that those capacities do not scale linearly with the total number of neurons that animals possess. So, it is important to specify brain regions and perhaps other proxies that bear closer relationships to the capacities of interest, as discussed in Budolfson and Spears (Reference Budolfson, Spears and Fischer2019).

On a more practical level, there is the challenge of identifying proxies for which data are available across a sufficiently wide range of decision-relevant species. There is surprisingly little research on many species of clear relevance to decision-makers, as demonstrated by Fischer (Reference Fischer2024). This makes it difficult to identify proxies that are both welfare-relevant and sufficiently well-studied to be of use to current decision-makers who need to make interspecies welfare comparisons.

Second, after the hurdle of proxy selection, there is the challenge of proxy aggregation. Again, on a purely theoretical level, there is the difficulty of establishing a relationship between sets of proxies and differences in welfare potentials. Consider a method for estimating welfare potentials that involves a wide range of proxies. The simplest aggregation strategy is additive: take the scores across all the proxies, sum them and divide by the total possible score to produce a welfare potential estimate. However, it could be that some nonlinear relationship between proxies and welfare potential estimates is more appropriate, requiring some more complex function.

Likewise, on a more practical level, there is the challenge of navigating uncertainties about proxy possession. How, if at all, should a proxy aggregation strategy correct for a lack of empirical clarity about whether animals possess certain cognitive traits, such as mental time travel (the capacity to replay past experiences and imagine hypothetical future experiences)? Any proposal will need to navigate this issue.

Though these challenges are hardly insignificant, they are not obviously worse than the ones that prior research programs have faced. In those cases, and presumably in this one, all methods require care in their development, interpretation and use. Moreover, they will often work better in tandem than alone, as agreement between them is one source of evidence that they are tracking genuine differences between the taxa of interest. (Indeed, it may be possible to combine their separate welfare potential estimates – each of which is sensitive to specific assumptions – into composite, “meta” scores that reflect our best “all things considered” judgments given various methodological uncertainties.) Finally, it is important to recall that these methods and others are primarily intended to provide inputs to sensitivity analyses, making it possible to determine whether decisions do, in fact, turn on the uncertainties involved in generating these estimates. In some cases, they will. In other cases, it may turn out that any plausible way of generating welfare potential estimates has the same practical implications, in which case decision-making is simplified.

3.3. A monetization method for animal welfare

Together, AQALYs and welfare potential estimates provide a method for monetizing animal welfare. Again, the method is to extend existing methods for monetizing human QALY impacts, where the key additions are two conceptual innovations: first, a method for generating AQALYs from traditional welfare assessment tools in animal welfare science; second, a method for converting AQALYs into human QALYs. With these tools in hand, it becomes possible to express the intrinsic value of animal welfare impacts in monetary terms.Footnote ⁴

Suppose, for instance, that the lives of egg-laying hens in small conventional battery cages can be improved by switching to larger cages. If, for instance, the improvement in each hen’s life from switching cages would be scored as 0.25 AQALYs, then welfare potentials can be used to convert that improvement into (human) QALYs. Consider one of the simplest welfare potential metrics – cortical neuron counts – where the ratio of the average number of forebrain neurons in a chicken brain to the average number of forebrain neurons in a human brain is taken to represent chickens’ welfare potential (i.e., ~61M/~21B; Olkowicz et al., Reference Olkowicz, Kocourek, Lučan, Porteš, Fitch, Herculano-Houzel and Němec2016; Herculano-Houzel, Reference Herculano-Houzel2009). Then, a year of egg-laying hen life in conventional battery cages is equivalent to ~0.0007 (human) QALYs (0.25 AQALYs × 0.0029 welfare potential score, representing the hypothesis that one fully healthy chicken life year = 0.0029 fully healthy human life year). This estimate can then be converted into a currency using standard methods. For example, assuming a human QALY is valued at $580,000, then the implied intrinsic animal welfare value of switching to the larger cages is $420.50 per chicken.

Note that policymakers might also be interested in capturing the heterogeneity in animal welfare within a single species when considering the policies to implement. As for humans, a policy can have heterogeneous effects on individuals because they live in different welfare situations. For instance, forcing farms not to slaughter their broilers before 80 days is beneficial for some animals and detrimental to others. As for QALY scores, animals might experience negative welfare such that additional days at the farm might be detrimental. On the contrary, chickens in some organic farms might experience positive welfare such that a longer lifetime would be associated with a greater lifetime overall utility.

This method could also be used in cost–benefit contexts to compute break-even points. Let us consider for instance the case of animal experimentation where a research team is willing to undertake an experiment on primates. If the medicine is successful, the researchers expect this medicine to save about one out of three persons affected by a rare disease. The team expects that X humans would take the medicine per year, which would add three QALYs per person. They consider that their experiment will necessitate 20 chimpanzees to appropriately estimate the medicine’s effect size, and they believe that the experiment has ultimately 10% of being successful (i.e., a successful test on chimpanzees and then a successful test on humans). Last, imagine that the welfare of the primates taking part in the experiment would be substantially reduced and worsened by the experiment such that the welfare impact is estimated to be about −8 AQALY for each chimpanzee and that the utility potential of a primate is 0.85. A central question for the ethics committee is to decide whether the experiment is worth running. It must evaluate whether the benefits of running the project exceed the costs. The costs are given by: 20 (number of chimpanzees) times 0.85 (utility potential) times −8 (AQALYs per chimpanzee), which is equivalent to 136 human QALYs. The yearly expected benefits are 0.10 (chances of success) × 1/3 (chances of recovery) × X (number of humans that would take the medicine each year) × 3 (number of QALYs gained per cured human), namely 0.1 X human QALYs. Assuming a discount rate of 5%, the expected benefits are 0.1X/0.05 = 2X human QALYs. Thus, the ethics committee could decide to validate the experiment only if 2X > 136, that is, if there are strictly more than 68 humans that would take the medicine per year.

4.1. Population ethics

Policies that influence animal welfare frequently have impacts on the total number of animals in existence. Consider policies related to meat consumption, animal testing, or biodiversity conservation, for instance – all these policies alter the sizes of different animal populations. Now, let us assume (as we do in this paper) that animals possess intrinsic value. When the number of individuals with intrinsic value varies, we are in a variable population case. In the population ethics literature, it is widely recognized that variable population cases can give rise to difficult moral dilemmas. Common social welfare functions (SWFs) like total utilitarianism have counterintuitive consequences under variable populations, the most famous of which is the so-called “repugnant” conclusion (Blackorby et al., Reference Blackorby, Bossert and Donaldson2005; though see Zuber et al., Reference Zuber, Venkatesh, Tännsjö, Tarsney, Stefánsson and Steele2021). (Attempts to avoid such conclusions have their own problems – e.g., the so-called “sadistic” conclusion; see Arrhenius, Reference Arrhenius2000.)

The foundation of BCA lies in the Kaldor–Hicks principle – namely, the potential Pareto improvement concept. Yet, the Pareto concept typically operates within the framework of a fixed population. Similarly, the QALY or DALY approaches typically consider a fixed population as they do not assess the impact of adding or subtracting lives. More than two decades ago, Broome (Reference Broome2000) wrote: “What is the value of adding a person to the world? I know of no cost–benefit analysis in practice that has taken account of this value.” The key point we aim to emphasize here is that integrating animal welfare into policymaking will only make it more important to confront the intricate issue of population ethics in BCA.

4.2. Equity

One of the primary challenges in BCA revolves around addressing equity concerns (Adler, Reference Adler2012). The consideration of animal welfare introduces new dimensions to these equity issues. In practice, equity is often tackled through the use of equity weights that typically reflect disparities in income. However, considering that animals do not have income, we must adopt a different approach. One possibility is to calculate these weights as a reflection of differences in utilities and using an SWF. Yet, this raises several difficult questions. For instance, what axioms should guide the development of a multispecies SWF (Zuber et al., Reference Zuber, Spears and Budolfson2023)? Which attributes should we consider when evaluating utilities? What does “priority for the worse-off” mean when comparing multiple species? How can we appropriately account for instances of negative well-being? The list of open questions in this domain is extensive.

Deeper challenges may even arise when comparing different species (Fleurbaey & Leppanen, Reference Fleurbaey and Leppanen2021). While some animals like elephants and horses live for decades, many bird species live only for a few years. There are even smaller species with extremely brief lifespans. Comparing lifetime welfare, we risk undervaluing these short-lived creatures, which may seem unfair. So, should we normalize lifetime welfare to a species standard? Or should we accept that some kinds of animals can, by virtue of living longer, have better lives than others (Vallentyne, Reference Vallentyne2005; Kagan, Reference Kagan2019)? There is an additional complication here related to farmed animals, where it is unclear whether the “species standard” should be given by production timelines (i.e., the time to slaughter) or by the natural lifespan. If the former, then many farmed animals are not made worse off simply by having their lives cut short; if the latter, then raising and slaughtering animals for food results in significant losses of AQALYs.

4.3. Uncertainty

Another common challenge within BCA pertains to the treatment of uncertainty. Again, the consideration of animal welfare introduces another layer of complexity here. As highlighted in our earlier discussion, the subject of animal welfare is notably intricate, with numerous uncertainties yet to be resolved. The welfare potentials of many species remain unknown (Fischer, Reference Fischer2024), this is unlikely to change in the short-term, and there will still be high uncertainty about animals’ welfare potentials for a long time. Uncertainty also concerns ethical aspects such as determining whether an animal’s life is worth living or not. The main challenge here lies in explicitly incorporating this scientific uncertainty into the decision-making process and evaluation practices. For instance, some experts argue for the adoption of the precautionary principle when determining which species possess sentience (Birch, Reference Birch2017). This seems sensible but, in practice, how can we account for this specific precautionary premium in BCA?

Nevertheless, it is easy to overstate the problem of uncertainty. In many cases, sensitivity tests will reveal that almost most reasonable estimates of the intrinsic value of animal welfare support a particular decision. And while it may not be obvious what range of valuations to use for various understudied species, reasonable extensions can be made from others where better information is available. In the human case, we should recall, high confidence is not required to justify using the outputs of various ways of monetizing health impacts. Instead, what matters is that these outputs are integrated into decision-making in appropriate ways (e.g., as inputs to sensitivity tests) and that the entire decision-making process has democratic legitimacy. If similar standards can be met when quantifying animal welfare, then uncertainties need not be barriers to incorporating intrinsic valuations into BCA.

4.4. Political viability and pure species discounting

The aim of this paper is to encourage research on ways of monetizing the intrinsic value of animal welfare. However, some methods for monetizing the intrinsic value of animal welfare – even if well-motivated and methodologically sound – may suggest that animal welfare is worth far more than the general population previously believed. This could result in cases where BCAs imply that animal welfare should be prioritized over human interests in ways that the public finds uncomfortable. If so, then we face difficult questions about the political prospects for public action based on non-anthropocentric valuations of animal welfare.

There are several points to make here. First, it is possible that many members of the public would be open to more animal-friendly policies than we might initially predict. For instance, a 2015 Gallup survey found that a full third of Americans said that animals should have the same rights as people (with 62% saying that animals deserve “some protection”; Gallup 2015). Surveys from Ladak and Anthis (Reference Ladak and Anthis2022) and Norwood and Murray (Reference Norwood and Murray2018) showed substantial levels of support among US consumers for banning slaughterhouses (~39–43%); Dullaghan (Reference Dullaghan2022) found less but still significant sympathy for this position (~8–20%). In the United kingdom, about 40% of the citizens hold that animal lives are worth the same as human lives (YouGov, 2021). In France, 95% of the citizens consider that animals have rights (IPSOS, 2020), and 93% of them support increased protection for animals (Harris Interactive, 2021). And perhaps most directly relevant to the question at hand, Johansson-Stenman (Reference Johansson-Stenman2018) conducted a survey that was fairly representative of the Swedish population where over 95% of respondents said that “animal suffering should be taken into account… in public decisions, even when no human beings suffer when knowing that animals suffer.”Footnote ⁵

Of course, even if the present public (in some country or region) is not willing to allow non-anthropocentric valuations of animal welfare to guide public action, that is not necessarily an argument against incorporating those valuations: some domestic BCAs completely ignore the impacts of public actions on the international community, but that is no evidence that those impacts are irrelevant to those BCAs. To the contrary, incorporating those impacts is one way, however modest, of encouraging the population to consider a wider range of consequences.

That being said, it is also possible to incorporate a pure species discounting parameter in BCA that reflects some population’s view about the relative value of, say, chicken welfare to human welfare. This would be a simple multiplier that reduces the intrinsic valuation to some lower value (as proposed, essentially, by Kagan, Reference Kagan2019). Still, a pure species discounting parameter on an intrinsic valuation of animal welfare is still importantly different from a straightforwardly anthropocentric valuation approach: the former still allows some amount of animal welfare to outweigh human interests, while the latter may involve a function where animal welfare has diminishing marginal value to the point that, in relatively high stakes cases for humans, animal welfare never outweighs human interests. Applying a pure species discounting parameter is, therefore, a possible compromise between an intrinsic and an anthropocentric valuation that may improve political viability in the short run. At the same time, pure species discounting that is calibrated only to political feasibility would not have a fundamental social welfare justification. Instead, it would be motivated only by practical considerations, just as pure time discounting of future human welfare that is calibrated only to the political feasibility of climate change policy does not have a fundamental social welfare justification.

With this in mind, it may be normatively important to consider ways of incorporating animal welfare into democratic decision-making that more closely reflect its undiscounted value. Some work has already been done in this vein – for example, Zuolo (Reference Zuolo2020) and Magaña (Reference Magaña2023), which represent different views about the relationship between the Rawlsian idea of public reason and animals’ interests – but much more is still required.