Nicolas Delon & Duncan Purves (New York University) on interventions to reduce animal suffering
Channel: Radio-CRÉ
Date: 03/11/2017

“Technological interventions to reduce wild animal suffering”

Most people believe that suffering is intrinsically bad. In conjunction with contingent facts about our world and a few plausible moral principles, this yields an obligation to reduce or eliminate suffering, except when doing so would violate a more stringent moral requirement. We ought to refrain from causing pain, and we ought to prevent or relieve pain, except when pain is necessary for the achievement of some greater good.

The prevalence of suffering is clearest, some have argued, when we consider the lives of wild animals, both in terms of scope and magnitude. If we accept the moral principle that we ought, pro tanto, to reduce the suffering of all sentient creatures, regardless of species membership, and the prevalence of suffering in the wild (through disease, starvation, parasitism, predation, disproportionate infantile mortality, etc.), then we seem committed to the existence of an obligation pro tanto to prevent this suffering. Call this surprising conclusion the Problem of Wild Animal Suffering (WAS).

As proponents of WAS reduction/elimination argue, it’s not just utilitarians who are committed to these claims. That’s because everyone should believe that suffering is intrinsically bad and that a state of affairs containing less suffering is, other things being equal, better than a state containing more. The Problem is also partly independent of competing values such as the values of species, biodiversity, naturalness or wildness. Most who advocate the reduction of WAS argue that, even if we were to give some weight to such values, no plausible theory should—without undue partiality, inconsistency or implausibility—resist the conclusion that WAS is overridingly important. Yet the Problem clearly pits some animal ethicists against the desiderata of most environmentalists. 

There have been many attempts to solve the Problem without committing oneself to systematic interventions in nature. Authors have appealed to the distinction between negative and positive duties, demandingness, created vulnerability, or constitutive group membership. Here we set those aside and accept the pro tanto desirability of a world with reduced WAS—we also set aside rights- and/or welfare- based issues (e.g., related to sterilization, culling, tagging, monitoring). Our focus is on epistemic difficulties with implementing technological interventions designed to reduce WAS, such as genetic engineering, healthcare, population control, or habitat design. 

We argue that such interventions, when scaled up to meet the actual demands of WAS, are epistemically fraught, and hence morally impermissible. The Problem is, in other words, largely intractable. We choose to focus on the case of genetic engineering, in particular ‘CRISPR’ technology that could be used to alter predator and/or prey behavior and experiences and the reproduction strategies of ‘r-selected’ species.

We defend the negative thesis that we are not justified in thinking that existing proposals to reduce WAS would in fact do so. Call this the epistemic problem. We also defend the positive thesis is that, to justify interventions to prevent WAS, we need to develop metrics and models that predict the effects of interventions on biodiversity, ecosystem functioning, and animals well-being. The positive thesis, however, might also be limited by an epistemic problem. The partial indeterminacy and extreme complexity of the ecological processes (e.g., trophic chains, genetic drift, migrations, and other aspects of population dynamics) captured by our current models and those we can hope to construct make the potentially cascading effects of massive technological interventions to reduce WAS unpredictable. The problem is compounded by the rate, magnitude and contingency of global climate change and its range of possible scenarios, as well as by a poor empirical record of successful past experiments and predictions.

Caméra et montage : Marc-Antoine Plouffe