The most important technologies and research disciplines for wild animal welfare

Wild animal suffering is most likely the biggest chunk of suffering in the world in the foreseeable future. Luckily there are important emerging technologies and research disciplines that help improve the welfare of all animals in nature.

The three most important technologies to improve wild animal welfare

  1. Cultured meat

A lot of suffering and rights violations in the world is caused by predation. Carnivores need animal protein to survive, but with cellular agriculture we can produce meat without animals. Cellular agriculture, based on cell and tissue engineering, allows us to produce meat that is necessary for carnivores, using cells instead of entire animals. Cultured meat can be fed to predators, starting with the carnivores under our care, such as carnivorous pets (cats, dogs) and predators in wildlife rescue centers. Research in cellular agriculture is underfunded because of vested interests in traditional (livestock) agriculture. Therefore, as a first step, the research and development of cultured meat can be supported.

  1. Gene drives

If we help animals in the wild, saving them from predators, parasites or diseases, animal populations with a high reproduction rate (so called r-strategists) might expand too quickly. This results in more resource competition. To control those populations, we need to limit their fertility. Gene drives (e.g. using CRISPR-Cas9 gene editing technology) allow to propagate genetic traits (such as fertility) throughout a population. With gene drives we do not need to perpetually interfere with wild animals’ liberties: a one-time intervention, releasing a gene drive, is sufficient (see Johannsen, K. (2017). Animal Rights And The Problem Of R-strategistsEthical Theory And Moral Practice, 20(2). 333-345.) As a first step, the research and development as well as the governmental regulatory framework of applications of gene drives can be supported.

  1. Artificial intelligence

If we intervene in nature with vaccines, antibiotics, antiparasitics, cultured meat and gene drives, we need to be aware of harmful flow-through and spillover effects. To study those indirect side-effects, we need advanced computer modelling with artificial intelligence (AI) and machine learning. AI-capacity is developing at a fast pace; perhaps faster than AI-safety. Therefore, as a first step, the research in AI-safety can be supported.

The three most important research disciplines to improve wild animal welfare

  1. Ecological modelling

The biggest concern about interventions in nature to improve wild animal welfare, is the problem of indirect flow-through and spillover effects that can be harmful to other, non-targeted sentient beings. Ecological modeling is necessary to understand the complex processes in food webs and ecosystems and to avoid those harmful side-effects.

  1. Animal physiology

The biggest cause of wild animal suffering is the r-reproduction strategy, where an animal gets a lot of offspring and a few of those offspring experience long healthy lifespans. Child mortality rates of wild animals are very high. If we want to increase the ratio of animals who have long healthy lifespans, we need to control their fertilities. In the short run, animal physiology is necessary to develop new contraceptives such as immunocontraception, adapted to different animal populations. In the long run, we can think of gene drives to control populations.

  1. Ethology and neurobiology

The biggest uncertainty facing wild animal suffering, is the degree of animal sentience. We do not yet know how consciousness is generated, which living beings are conscious, how much they experience positive and negative feelings and how strong their subjective preferences are. Preferences can be revealed by studying animal behavior under natural conditions, so we need ethology to estimate the strengths of an animals’ preferences. A huge body of scientific evidence indicates that consciousness is generated by nervous systems, so we need neurobiology to estimate the levels of consciousness of sentient beings.

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