Incorporating Animals as Stakeholders in ICT: Towards Truly Inclusive

Digital Sustainability

Roberto Vergallo

1 a

and Luca Mainetti

2 b

Department of Information Sciences and Technologies, Pegaso Digital University, Piazza Trieste e Trento 48, Napoli, Italy

Department of Innovation Engineering, University of Salento, via per Monteroni 165, Lecce, Italy

Keywords:

Sustainability, Digital Ethics, Wildlife, Biodiversity, Vegan Software, Animal Rights.

Abstract:

The digital revolution has driven unprecedented technological advancements, transforming modern life and

addressing global challenges. However, while sustainability efforts in Information and Communication Tech-

nology (ICT) are addressing environmental issues like energy consumption and carbon footprints, the ethical

implications for non-human animals remain largely unexplored. This position paper calls for a redeﬁnition of

sustainability in ICT to include animal welfare as a core principle. We argue that animals should be recog-

nized not only as indirect stakeholders impacted by technological progress but as direct beneﬁciaries of ethical

digital practices. For the ﬁrst time, we propose the concept of vegan digital product, also introducing an in-

terdisciplinary methodological framework that prioritize animal welfare in digital design and policy-making.

Particularly, the framework incorporates animal welfare as a scope-based non-functional requirement in ICT

projects, including a draft for quantitative metrics based on the Value of Statistical Life (VSL).

1 INTRODUCTION

The digital revolution has transformed every aspect

of modern life, driving innovation and creating un-

precedented opportunities. However, its impacts

on non-human animals remain largely unexamined.

While sustainable software engineering has signif-

icantly adapted to minimize environmental impacts

like energy and carbon footprints, yet the broader eth-

ical impacts on animal life are frequently overlooked.

The deployment of large-scale digital infrastructures

potentially compromises animal habitats through land

use for data centers, pollution from extracting and dis-

posing of rare minerals, and disturbances from elec-

tromagnetic ﬁelds and digital devices. Additionally,

technologies meant to enhance productivity, such as

in smart farming, perpetuate exploitation by treating

animals merely as resources rather than sentient enti-

ties deserving of ethical consideration.

At a time when public awareness and empathy for

animal suffering are on the rise – as in the food, fash-

ion, and entertainment industries – the lack of focus

on animal welfare within the domain of ICT is both

striking and concerning. There is the urgent need

https://orcid.org/0000-0003-3560-806X

https://orcid.org/0000-0001-9387-9277

to broaden the concept of sustainability in the digital

domain to include compassion and fairness towards

all sentient beings. This includes developing ethical

frameworks that integrate animal welfare into digital

design and deployment, exploring the impact of digi-

tal infrastructures on animal habitats, and showcasing

case studies of animal-friendly ICT applications.

This position paper seeks to address these gaps by

advocating for a redeﬁnition of sustainability frame-

works to incorporate animal welfare as a core princi-

ple in digital and technological development. Specif-

ically, it calls for the recognition of animals not

merely as indirect stakeholders affected by technolog-

ical progress but as direct beneﬁciaries who deserve

thoughtful consideration and ethical respect. Central

to this vision is the concept of ”vegan digital product,”

an innovative approach that align digital innovation

with the principles of non-violence and animal wel-

fare. The objective is to foster an interdisciplinary dis-

course that bridges technological advancements with

ethical imperatives.

To help digital companies report their efforts in

mitigating animal suffering, in this paper we propose

using the Value of Statistical Life (VSL) metric to

quantify the life value of sentient animals affected by

ICT products. Additionally, we draw inspiration from

established frameworks, such as the Software Carbon

Vergallo, R. and Mainetti, L.

Incorporating Animals as Stakeholders in ICT: Towards Truly Inclusive Digital Sustainability.

DOI: 10.5220/0013431100003953

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 14th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2025), pages 147-154

ISBN: 978-989-758-751-1; ISSN: 2184-4968

147

Intensity (SCI) speciﬁcation and the Greenhouse Gas

(GHG) Protocol, to introduce a novel methodological

framework structured around a scope-based division.

The rest of the paper is structured as follows. Sec-

tion 2 reports a multidisciplinary review on the rele-

vant literature. Section 3 includes our position state-

ment. Section 4 summarizes our contribution and

sketches future research directions.

2 RELEVANT LITERATUE

The lack of consideration for the dignity and welfare

of sentient animals is evident both in global agendas

and in the digital sector. For instance, the United Na-

tions Sustainable Development Goals (SDGs) prior-

itize reducing inequalities, but only among humans.

Animals are mentioned brieﬂy in Goal 2.5, and even

then, only in a utilitarian context: to limit the risk of

extinction for species deemed vital to human survival.

Biodiversity appears to be the sole objective humanity

assigns itself when discussing animal protection. ICT-

related frameworks, such as the IEEE Recommended

Practice for Assessing the Impact of Autonomous and

Intelligent Systems on Human Well-Being (Commit-

tee, 2020), address biodiversity in terms of endan-

gered species, protected habitats, and forest preserva-

tion. However, this perspective excludes farmed ani-

mals, which remain relegated to utilitarian roles under

the same indicator (2.5) of the UN SDGs. Similarly,

the Corporate Digital Responsibility (CDR) white

(Shaw et al., 2024) paper deﬁned as “a set of prac-

tices and behaviors that help an organization use data

and digital technologies in ways that are perceived as

socially, economically, and environmentally respon-

sible,” mentions biodiversity but avoids any reference

to ”animals” or ”breeds”. This reveals a glaring omis-

sion in addressing the dignity of non-human animals,

both at a global level and within the digital sector.

The ethical neglect of animal welfare contrasts

with philosophical insights and scientiﬁc evidence.

(Hanna and Kazim, 2021) explores the Kantian the-

ory of human dignity to argue that not all humans

are “real persons,” and that it is possible for animals,

such as pets, to qualify as persons. This philosoph-

ical stance is further supported by scientiﬁc decla-

rations. The 2012 Cambridge Declaration on Con-

sciousness (Low et al., 2012) recognized that many

non-human animals possess neurological substrates

that generate consciousness, enabling them to expe-

rience emotions. The 2024 New York Declaration on

Animal Consciousness

expanded this view, afﬁrm-

https://sites.google.com/nyu.edu/nydeclaration/

ing that all vertebrates and many invertebrates likely

possess consciousness. These ﬁndings emphasize the

need to rethink human-animal relationships. Never-

theless, ethical treatment of animals should not hinge

solely on their consciousness, as their dignity exists

independently of their cognitive capacities.

The effects of digitalization on animals are signif-

icant, both in terms of their objectiﬁcation and neglect

in the face of technological side effects. For example,

digital farming has raised serious ethical concerns.

Neethirajan’s work (Neethirajan, 2021; Neethirajan,

2023) explores the objectiﬁcation of animals in mod-

ern farming systems, where the farmer’s role shifts

from caretaker to supervisor, emphasizing efﬁciency

through real-time monitoring and predictive analyt-

ics. This shift, while technologically advanced, re-

duces direct human-animal relationships and raises

questions about animal welfare. Neethirajan advo-

cates for integrating ethical frameworks like Respon-

sible Research and Innovation (RRI) (Burget et al.,

2017) to ensure digital livestock farming technologies

align with societal values, prioritizing the well-being

of animals alongside sustainability.

Urbanization, often viewed as a driver of smart

cities and digital advancements, also has indirect ef-

fects on animal welfare. Studies have long shown

that urbanization reduces natural capital and biodiver-

sity, as noted in (De Montis et al., 2021). McKinney

(McKinney, 2008) reviewed over 100 studies on ur-

banization’s effects, ﬁnding that species richness de-

creases with increasing urbanization, particularly in

highly urbanized areas. The aggregate global impacts

of urban expansion are expected to require signiﬁ-

cant policy changes to mitigate biodiversity loss (Seto

et al., 2012). While sustainable city development em-

phasizes environmental aspects, animal welfare is no-

tably absent from its objectives (Rabelo et al., 2017).

Another controversial aspect of digitalization is

the widespread use of biologging devices, such as

GPS and satellite trackers, to study animal behavior.

While these tools have advanced ecological research

(Hussey et al., 2015; Kays et al., 2015), they often im-

pose physical burdens on animals, leading to behav-

ioral changes or reduced survival rates (Duda et al.,

2018). Research tends to focus on technological im-

provements, like energy efﬁciency of devices (Stroia

et al., 2020), rather than addressing their impact on

animal well-being. Similarly, electromagnetic radia-

tion from mobile phone towers and devices has been

linked to adverse effects on animal health, behavior,

and reproduction. Studies have documented popu-

lation declines in bats and other species near phone

masts (Gauthreaux Jr, 1985; Balmori, 2009).

The controversial impacts of digitalization on an-

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148

imal welfare extend to other applications, such as

drones disrupting wildlife (Rebolo-Ifr

an et al., 2019;

Wallace et al., 2018), land usage of data centers

(Kshetri and Voas, 2024; Judge, 2021), mobile apps

facilitating the consumption of animal-derived prod-

ucts (Lohmann et al., 2024), and the environmental

toll of increased energy demands to power algorithms

and digital systems (Belkhir and Elmeligi, 2018; Ver-

gallo and Mainetti, 2024; Vergallo et al., 2024a; Ver-

gallo et al., 2024b). This body of research under-

scores the critical gaps in global and digital policies

regarding animal welfare. By failing to integrate com-

passion and dignity into the framework of sustainabil-

ity, current approaches neglect the moral and ethical

considerations necessary to ensure the well-being of

all sentient beings.

3 POSITION STATEMENT

This paper advocates for embedding vegan principles

into the design and development of software systems

and ICT products in general. By particularly aligning

software development practices with the core prin-

ciples of vegan philosophy, this approach promotes

a shift towards ethical, inclusive, and compassionate

technology development, both in the ends and in the

means. The adoption of these principles calls for a

fundamental rethinking of how we deﬁne and mea-

sure digital sustainability, emphasizing metrics that

account for the welfare of non-human animals.

Through a comprehensive framework that in-

cludes the integration of vegan philosophy into ICT

design, the establishment of a precise deﬁnition of ve-

ganism for the digital realm, and the proposal of ac-

tionable metrics to evaluate animal-friendly practices,

this position aims to redeﬁne ethical digital technol-

ogy. By doing so, it not only challenges prevailing

paradigms of sustainability in ICT projects but also

aligns software development with other industries.

In the following sections, this position is articu-

lated in detail, starting with the philosophical under-

pinnings of incorporating vegan principles into digital

products, including a formal deﬁnition of vegan ICT

system and concluding with proposed metrics for as-

sessing alignment with this vision.

3.1 Integrating Digital Technologies in

the Vegan Philosophy

The Vegan Society, established in 1944, deﬁnes veg-

anism as ”a philosophy and way of living which seeks

to exclude – as far as is possible and practicable – all

forms of exploitation of, and cruelty to, animals for

food, clothing or any other purpose; [...]”

. This deﬁ-

nition highlights that veganism extends far beyond di-

etary choices, encompassing a broader commitment

to eliminating animal exploitation in all forms, in-

cluding production processes. It is clear, therefore,

that reducing veganism to a dietary pattern is overly

simplistic. The philosophy fundamentally opposes

the exploitation of animals in every context, whether

in large-scale industrial systems or small, localized

practices, reﬂecting the principle that every life mat-

ters equally.

Despite this uniﬁed foundation, the vegan move-

ment remains diverse in its motivations. Indi-

viduals adopt veganism for different reasons, of-

ten grouped into three primary categories: ethical

concerns, environmental sustainability, and personal

health. While substantial literature already supports

the positive impacts of veganism on both the envi-

ronment (Scarborough et al., 2023)(Gonz

alez-Garc

ıa

et al., 2018)(Aleksandrowicz et al., 2016)(Ruini et al.,

2015) and human health (Selinger et al., 2023)(Satija

and Hu, 2018)(Pistollato and Battino, 2014), the con-

cept of vegan digital product proposed here is rooted

in the anti-speciesist dimension of the philosophy.

Our position grounds digital products develop-

ment in ethical vegan principles, in order to advocate

for a paradigm where the creation, deployment, and

operation of digital technologies actively reject prac-

tices that harm non-human animals. This approach

aligns with the broader philosophical framework of

veganism, seeking to ensure that technology devel-

opment reﬂects compassion and fairness towards all

sentient beings. Similar to other non-food industries,

such as textiles (Lamarche-Beauchesne, 2023) and

medicine (Rodger, 2022), which have already estab-

lished deﬁnitions of vegan products or adopted vegan

practices in their production processes, we propose a

corresponding deﬁnition for the ICT industry:

A vegan digital product, technology, or software

is one that incorporates – as far as is possible and

practicable – fairness toward non-human animals

as a core non-functional requirement, applying this

principle not only to the ﬁnal aims and applications

but also to every stage of its lifecycle, including

design, development, testing, deployment, and main-

tenance.

To help identify direct and indirect causes of

unfairness toward animals in digital systems, enhance

transparency, and provide utility for various types

of ICT organizations, ethical policies, and business

https://www.vegansociety.com/go-vegan/deﬁnition-

veganism

Incorporating Animals as Stakeholders in ICT: Towards Truly Inclusive Digital Sustainability

149

goals, we adopt an approach inspired by existing ini-

tiatives such as the Greenhouse Gas (GHG) Protocol

and ISO 14064 standard

. Speciﬁcally, we introduce

three scopes of reporting:

• Scope 1: Direct Discrimination. This oc-

curs when an organization provides ICT systems

speciﬁcally designed to control non-human ani-

mals with the sole objective of improving the ex-

ploitation outcomes of both farmed and wild an-

imals to meet human needs such as food, cloth-

ing, cosmetics, and healthcare. Examples include

smart farming technologies, biologging devices,

and software applications that perpetuate discrim-

ination against animals.

• Scope 2: Indirect Disturbance. This accounts

for the environmental modiﬁcations caused by

digital systems merely by their operation or exis-

tence, while neglecting their impact on wildlife.

For instance, the energy consumption of ICT

technologies pollutes the air due to fossil fuel

combustion, harming the habitats where animals

live. Other examples include land use changes

for building data centers and communication net-

works, or to mine rare earths needed for hard-

ware parts, electromagnetic pollution from com-

munication infrastructure, and drones disrupting

or confusing natural migration processes.

• Scope 3: Other Indirect Sources of Discrimi-

nation. These arise from activities of the com-

pany but originate from sources not owned or di-

rectly controlled by it. Examples include Cloud

services, the embodied impact of hardware and

other digital procurement activities.

Figure 1 illustrates the integration of the three

scopes into the phases of an iterative Software De-

velopment Life Cycle (SDLC). This model, chosen

as an example, provides a framework for understand-

ing how the potential impacts on non-human animals

manifest across different stages of software develop-

ment. The iterative SDLC consists of six phases:

planning, requirements, analysis & design, imple-

mentation, testing, and evaluation, with a recurring

feedback loop that includes operations and mainte-

nance (incorporating deployment). Each phase plays

a distinct role in shaping the lifecycle of a software

product.

Scope 1 is most relevant in the requirements and

analysis & design phases, as well as during evalua-

tion. The requirements phase, where system objec-

tives are deﬁned, is particularly susceptible to incor-

https://ghgprotocol.org/

https://www.iso.org/standard/66453.html

Figure 1: Mapping between Iterative SDLC phases and

scopes of animal exploitation in IT projects.

porating specist thinking. During this phase, deci-

sions can establish goals or speciﬁcations that directly

target or marginalize non-human animals. Similarly,

the analysis & design phase solidiﬁes these require-

ments into concrete plans and system architectures,

embedding any discriminatory assumptions into the

foundation of the system. In the evaluation phase, the

focus on assessing whether the system meets its goals

often perpetuates these same specist frameworks, fur-

ther reinforcing direct discrimination. Scope 2 aligns

with the implementation and operations & mainte-

nance phases. In these stages, the long-term environ-

mental and ecological effects of digital systems are

most apparent. The implementation phase involves

the creation of software and hardware, often consum-

ing signiﬁcant energy and resources, contributing to

environmental changes that may disrupt wildlife. Op-

erations & maintenance, which includes deployment,

extends these effects into the product’s lifecycle, as its

ongoing operation and maintenance require continued

resource consumption, infrastructure support, and po-

tential ecological disturbances. Scope 3 is tied to the

value chain, explicitly addressing both upstream and

downstream impacts. In the planning phase, upstream

effects occur through material acquisition and pre-

processing, where dependencies on supply chains or

third-party technologies can inadvertently harm non-

human animals. Downstream impacts become evi-

dent during the operations & maintenance phase, as

the use of external services like cloud providers or

digital procurement contributes to additional indirect

harm.

3.2 Quantitative Reporting

The aim of this section is to propose a quantitative

methodology for reporting the extent of animal ex-

ploitation or neglect in IT projects. Such reporting

can serve multiple purposes: documenting the impact

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150

of technology on animals to customers or buyers, as-

sessing the effectiveness of mitigation strategies, driv-

ing decision-making processes, and showcasing com-

mitment to addressing these concerns.

Quantitatively measuring levels of animal suffer-

ing is usually a matter of veterinary (Morton, 2023)

and behavioral neuroscience (Singer, 1990) research,

often with regards to experimental animals (Honess

and Wolfensohn, 2010). In this position paper we

suggest to adopt and adapt an existing metric from

the economic sector which is the Value of Statistical

Life (VSL) (Schelling, 1968)(Hirshleifer, 1970)(Vis-

cusi, 1993)(Viscusi, 2019). VSL is an economic mea-

sure used to quantify the monetary value individuals

place on reducing the risk of mortality. It is not the

value of an individual life but rather the aggregate

willingness to pay (WTP) of a population to reduce

the risk of one statistical death. VSL is widely ap-

plied in cost-beneﬁt analyses to evaluate public poli-

cies in areas such as health, environmental protection,

and workplace safety, and it has been widely adopted

to evaluate the impact of lockdown and other mea-

sures during the Covid-19 pandemic. The methodol-

ogy typically derives its estimates from observed mar-

ket behavior (e.g., wage-risk trade-offs in labor mar-

kets) or stated preferences in hypothetical scenarios.

In many studies the value also includes the quality of

life and the expected life time remaining. VSL can

vary between regions (Liu et al., 2022). For instance,

in the United States, recent estimates suggest a value

of approximately 7.2 million USD. In Europe, VSL

values differ by country, with Switzerland showing a

value of about 9.4 million USD, while the median in-

ternational value is around 1.3 million USD.

As an additional motivation for using VSL, we

highlight that this metric is already employed by

industry leaders in the ﬁeld of sustainability. For

instance, the marginal operating emissions provider

WattTime utilizes it in their ”health damage” data sig-

nal, expressed in V SL/MWh

. This signal estimates

the harm to human health caused by emissions from

electricity generation, based on the electricity con-

sumed at a speciﬁc time and location. As a mere ex-

ample, the health signal for the US ranged in 10 − 60

$/MWh during 2021

To provide greater precision, we propose dis-

tinguishing between the Value of Statistical Human

Animal Life (V SHAL, where V SL = V SHAL) and

the Value of Statistical Non-human Animal Life

(V SNAL). In alignment with the ethical principles

https://watttime.org/data-science/data-signals/health-

damage/

Source: own elaboration of data obtained from a spe-

cial agreement with WattTime.

underlying this work, we posit that the value of a hu-

man life is equal to the value of any other animal life,

weighted by an optional index of sentience to each

animal species, i.e.:

V SNAL = α · V SHAL (1)

The index of sentience (α) should be set to 1 for

non-human animals with cognitive and sensory ca-

pacities qualitatively comparable to those of humans

(e.g., mammals, birds, cephalopods). However, other

animals, such as those lacking a central nervous sys-

tem or a brain, while still deserving of ethical con-

sideration, may have a lower capacity for experienc-

ing physical and emotional suffering. The assump-

tion in Eq. 1 does not strictly follow the technical

deﬁnition of VSL, which is inherently anthropocen-

tric and grounded in economic evaluations. Instead,

it reﬂects a philosophical stance that all sentient be-

ings hold intrinsic and equal value, providing an ethi-

cal foundation for the measurements proposed in this

work. Moreover, we acknowledge that some inter-

pretations may argue for V SHAL to exceed V SNAL,

citing factors such as differences in life expectancy

or body size. For readers who ﬁnd it challenging to

adopt the equality presented in Eq. 1, the equation

could alternatively be applied as an upper-bound es-

timate. This approach would still align with the core

objectives outlined at the beginning of this subsection

while accommodating varying perspectives. More-

over, we remind that VSL already varies among hu-

man animals born in different countries, still being

considered a valid indicator.

Deﬁning N

as the number of animals impacted

by activities in Scope 1, then it follows that the non-

human animal life damage D for Scope 1, in monetary

unit (e.g. USD), is:

Scope1

= N

· V SNAL [USD] (2)

This term is designed to weigh heavily in the ﬁ-

nal computation, as it carries the cost of all beings

whose discrimination is supported by the digital sys-

tem. Moreover, given the turnover of animals in the

locations where the system is applied, this metric is

bound to grow proportionally over time.

Damage for Scope 2 involves all the indirect ef-

fects on an estimated number of animals N

whose

habitats are modiﬁed due to digital activities. This

impact can be decomposed into ﬁve key dimensions:

air, water, soil and habitat loss, plus radiation effects:

• A (air): The air breathed by N

animals gets

polluted by GHG derived from energy produc-

tion needed to run the digital system. The

damage is quantiﬁed using the health signal

(V SNAL/MW h), reﬂecting the indirect harm

caused by reduced air quality.

Incorporating Animals as Stakeholders in ICT: Towards Truly Inclusive Digital Sustainability

151

• W (water): The availability and quality of water,

essential for the survival of N

animals, are al-

tered due to the water consumption and contam-

ination associated with ICT operations. For ex-

ample, cooling processes in data centers may de-

plete local water sources or discharge heated or

polluted water into ecosystems. The damage is

calculated by assessing the deviation from base-

line water needs (W

baseline

) and the cost in terms

of VSNAL for affected animals.

• S (soil): The quality and availability of soil that

animals depend on are impacted. This in-

cludes contamination from improper disposal of

electronic waste, and land degradation. The dam-

age is calculated by evaluating the area of soil af-

fected (S

area

) and the resulting harm to the depen-

dent animal population (VSNAL).

• H (habitat): The construction of data centers,

communication networks, and other ICT infras-

tructure such as drones and satellite ground sta-

tions directly impacts the living conditions of

animals. This includes the deforestation or

conversion of natural landscapes into industrial

zones, leading to displacement, reduced access to

resources, and increased vulnerability to predators

or environmental changes. The damage is cal-

culated by assessing the total area of habitat lost

area

) and the number of displaced or affected an-

imals, weighted by their dependency on the spe-

ciﬁc habitat type. The impact is then expressed in

terms of VSNAL per affected population.

• R (radiation): Electromagnetic interference from

ICT assets, such as cell towers, communication

networks, and drones, affects wildlife. For ex-

ample, migratory species and animals that rely on

natural electromagnetic ﬁelds for navigation (N

)

can experience disorientation, stress, or disrupted

life cycles. The damage is quantiﬁed based on

the affected species and populations, with mea-

surement units reﬂecting electromagnetic expo-

sure levels (e.g., µT) and the corresponding im-

pact on animal welfare (VSNAL).

The summation of the aforementioned contribu-

tions gives the health damage for Scope 2:

Scope2

= D

+ D

[USD]

= (N

· V SNAL)

+ (N

· V SNAL · ∆W

used

)

+ (N

· V SNAL · S

area

)

+ (N

· V SNAL · H

area

)



· V SNAL · R

intensity



(3)

Exploding the different terms in Eq. 3 is presented

here in a conceptual manner. The formal mathemati-

cal structure, along with the methodology for collect-

ing the necessary data to feed the formula, require fur-

ther reﬁnement and validation and represent a work

in progress. Moreover, the equation assumes that the

components D

, D

, and D

are indepen-

dent. While this simpliﬁes the calculation and makes

the model more practical, it overlooks potential cor-

relations between these components. As a result, the

current model should be understood as providing an

upper bound for Scope 2. This approach ensures that

no potential impact is underestimated but calls for re-

ﬁnement in future iterations to incorporate interde-

pendencies more accurately.

Finally, the total damage falling in Scope 3 is sim-

ply the summation of the VSNAL for each external

resource r acquired by the company:

Scope3

∑

r∈R

VSNAL

[USD] (4)

Here, R denotes the set of external resources ac-

quired by the company to sustain its digital activities

(both tangible and intangible assets). Each resource

r ∈ R represents an individual component within this

set, such as hardware (e.g., servers, networking equip-

ment), software services (e.g., Cloud computing or

third-party applications), and supply chain contribu-

tions (e.g., energy procurement, subcontracted ser-

vices). The VSNAL

term quantiﬁes the impact of

each resource r on non-human animals, considering

the resource’s lifecycle from material extraction and

production to delivery and eventual usage.

It trivially follows that the total damage D is the

summation of the contributions of each scope:

D = D

Scope1

+ D

Scope2

+ D

Scope3

[USD] (5)

Inspired by the Software Carbon Intensity (SCI)

metric proposed by the Green Software Foundation

we deﬁne the Damage Intensity (DI) as the total dam-

age D normalized by a functional unit R:

DI = D per R [USD/unit] (6)

The functional unit R provides a versatile mean to

evaluate how the damage scales across different di-

mensions, making it possible to tailor the metric to

the speciﬁc context of its application. For instance,

R could represent a temporal scale (D/year), a per-

product basis, per customer, or more technical metrics

like per API call. In this way, organizations can align

the metric with their reporting frameworks.

As a ﬁnal consideration for this section, while

Scopes 2 and 3 present signiﬁcant challenges in both

measurement and mitigation, we strongly advocate

https://sci.greensoftware.foundation/

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152

for the immediate and actionable step of fully elim-

inating costs associated with Scope 1.

4 CONCLUSIONS

In this position paper, we have introduced a new di-

mension of sustainability for ICT including animals

as stakeholders throughout all phases of the lifecycle

of digital artifacts, encompassing both software and

hardware. This perspective is grounded in the recog-

nition of the sentience of non-human animals, which

are often objectiﬁed or neglected in modern digital-

ization processes. Furthermore, the ICT sector lags

behind other industries such as food, fashion, and en-

tertainment, which have already adopted innovative

market propositions aligned with animal welfare prin-

ciples. This work calls for a concerted interdisci-

plinary effort to establish a dialogue that addresses the

need for anti-speciesist technology. The key contribu-

tions of this paper are summarized as follows:

1. Multidisciplinary State-of-the-Art. We have cu-

rated and synthesized insights from key studies

across ethics, biology, energy, and computer sci-

ence, fostering a comprehensive and interdisci-

plinary foundation to promote dialogue among re-

searchers from diverse ﬁelds.

2. Deﬁnition of Vegan IT. For the ﬁrst time, to the

best of our knowledge, we have positioned the

digital sector within the broader vegan philoso-

phy, proposing a clear deﬁnition of what consti-

tutes a vegan digital product.

3. Framework Proposition. While still in its pre-

liminary stages, we have introduced a method-

ological framework that incorporates animal wel-

fare as a non-functional requirement in ICT

projects. This framework includes a division into

scopes and a draft for quantitative metrics, en-

abling ICT companies to assess and demonstrate

their commitment to animal welfare.

While this paper primarily serves as a position

piece to introduce speculative ideas, it currently lacks

an application of the proposed framework. As a re-

sult, the mathematical foundation remains at a con-

ceptual stage and requires further reﬁnement to be-

come actionable and suitable for industrial adoption.

Future work will focus on presenting numerical re-

sults to illustrate how a reference scenario could be

improved by adopting our method, thereby demon-

strating its practical impact.

The impact of digital technologies on animal wel-

fare is unavoidable. However, minimizing this impact

to the greatest extent possible is both feasible and eth-

ically imperative. Establishing a clear standard for re-

porting the impact of digital products on non-human

animals paves the way for certiﬁcations in vegan IT,

empowering customers to make informed choices.

ACKNOWLEDGEMENTS

We thank WattTime for providing the health data.

REFERENCES

Aleksandrowicz, L., Green, R., Joy, E. J., Smith, P.,

and Haines, A. (2016). The impacts of dietary

change on greenhouse gas emissions, land use, wa-

ter use, and health: a systematic review. PloS one,

11(11):e0165797.

Balmori, A. (2009). Electromagnetic pollution from phone

masts. effects on wildlife. Pathophysiology, 16(2-

3):191–199.

Belkhir, L. and Elmeligi, A. (2018). Assessing ict global

emissions footprint: Trends to 2040 & recommenda-

tions. Journal of cleaner production, 177:448–463.

Burget, M., Bardone, E., and Pedaste, M. (2017). Deﬁ-

nitions and conceptual dimensions of responsible re-

search and innovation: A literature review. Science

and engineering ethics, 23:1–19.

Committee, I. S. (2020). IEEE Recommended Practice for

Assessing the Impact of Autonomous and Intelligent

Systems on Human Well-Being: IEEE Standard 7010-

2020. IEEE.

De Montis, A., Calia, G., Puddu, V., and Ledda, A. (2021).

Designing green infrastructure guidelines: A method-

ological approach. In Smartgreens, pages 156–163.

Duda, N., Nowak, T., Hartmann, M., Schadhauser, M.,

Cassens, B., W

agemann, P., Nabeel, M., Ripperger,

S., Herbst, S., Meyer-Wegener, K., et al. (2018). Bats:

Adaptive ultra low power sensor network for animal

tracking. Sensors, 18(10):3343.

Gauthreaux Jr, S. A. (1985). Electromagnetic inﬂuences on

birds. CL rpﬂo fC mmsindPpr orteEFLtrtr ReiwPrjc,

page 141.

Gonz

alez-Garc

ıa, S., Esteve-Llorens, X., Moreira, M. T.,

and Feijoo, G. (2018). Carbon footprint and nutri-

tional quality of different human dietary choices. Sci-

ence of the total environment, 644:77–94.

Hanna, R. and Kazim, E. (2021). Philosophical foundations

for digital ethics and ai ethics: a dignitarian approach.

ai and ethics, 1 (4), 405–423.

Hirshleifer, J. (1970). Investment, Interest, and Capital.

Prentice-Hall, Englewood Cliffs, NJ.

Honess, P. and Wolfensohn, S. (2010). The extended wel-

fare assessment grid: A matrix for the assessment of

welfare and cumulative suffering in experimental ani-

mals. Alternatives to Laboratory Animals, 38(3):205–

212.

Incorporating Animals as Stakeholders in ICT: Towards Truly Inclusive Digital Sustainability

153

Hussey, N. E., Kessel, S. T., Aarestrup, K., Cooke, S. J.,

Cowley, P. D., Fisk, A. T., Harcourt, R. G., Holland,

K. N., Iverson, S. J., Kocik, J. F., et al. (2015). Aquatic

animal telemetry: a panoramic window into the under-

water world. Science, 348(6240):1255642.

Judge, P. (2021). Prince william county environmental

report [...]. https://www.datacenterdynamics.com/

en/news/prince-william-county-environment-report-

recommend-ditching-2000-acre-data-center-plans/.

Accessed: 2024-12-25.

Kays, R., Crofoot, M. C., Jetz, W., and Wikelski, M. (2015).

Terrestrial animal tracking as an eye on life and planet.

Science, 348(6240):aaa2478.

Kshetri, N. and Voas, J. (2024). Data centers in your back-

yard? Computer, 57(1):82–87.

Lamarche-Beauchesne, R. (2023). Reviving the silenced;

deﬁning vegan fashion and classifying materials of an-

imal origin. Fashion Theory, 27(7):937–956.

Liu, J.-T., Hammitt, J. K., and Wang, J.-L. (2022). Revis-

iting the value of a statistical life: an international ap-

proach. Journal of Beneﬁt-Cost Analysis, 13(1):123–

146.

Lohmann, P. M., Gsottbauer, E., Farrington, J., Human,

S., and Reisch, L. A. (2024). Choice architecture

promotes sustainable choices in online food-delivery

apps. PNAS nexus, 3(10):pgae422.

Low, P., Panksepp, J., Reiss, D., Edelman, D.,

Van Swinderen, B., and Koch, C. (2012). The cam-

bridge declaration on consciousness. In Francis crick

memorial conference, volume 7. Cambridge England.

McKinney, M. L. (2008). Effects of urbanization on species

richness: a review of plants and animals. Urban

ecosystems, 11:161–176.

Morton, D. B. (2023). A model framework for the esti-

mation of animal ‘suffering’: Its use in predicting and

retrospectively assessing the impact of experiments on

animals. Animals, 13(5):800.

Neethirajan, S. (2021). Ethics of digital animal farming.

Preprints.

Neethirajan, S. (2023). The signiﬁcance and ethics of digital

livestock farming. AgriEngineering, 5(1):488–505.

Pistollato, F. and Battino, M. (2014). Role of plant-based di-

ets in the prevention and regression of metabolic syn-

drome and neurodegenerative diseases. Trends in food

science & technology, 40(1):62–81.

Rabelo, A. C., Oliveira, I. L., and Lisboa-Filho, J. (2017).

An architectural model for smart cities using collab-

orative spatial data infrastructures. In International

Conference on Smart Cities and Green ICT Systems,

volume 2, pages 242–249. SCITEPRESS.

Rebolo-Ifr

an, N., Grilli, M. G., and Lambertucci, S. A.

(2019). Drones as a threat to wildlife: Youtube com-

plements science in providing evidence about their ef-

fect. Environmental Conservation, 46(3):205–210.

Rodger, D. (2022). Why we should stop using animal-

derived products on patients without their consent.

Journal of medical ethics, 48(10):702–706.

Ruini, L. F., Ciati, R., Pratesi, C. A., Marino, M., Princi-

pato, L., and Vannuzzi, E. (2015). Working toward

healthy and sustainable diets: The “double pyramid

model” developed by the barilla center for food and

nutrition to raise awareness about the environmental

and nutritional impact of foods. Frontiers in nutrition,

2:126479.

Satija, A. and Hu, F. B. (2018). Plant-based diets

and cardiovascular health. Trends in cardiovascular

medicine, 28(7):437–441.

Scarborough, P., Clark, M., Cobiac, L., Papier, K., Knup-

pel, A., Lynch, J., Harrington, R., Key, T., and Spring-

mann, M. (2023). Vegans, vegetarians, ﬁsh-eaters and

meat-eaters in the uk show discrepant environmental

impacts. Nature Food, 4(7):565–574.

Schelling, T. C. (1968). The life you save may be your own.

In Chase, S. B., editor, Problems in Public Expendi-

ture Analysis, pages 127–162. Brookings Institution,

Washington, DC.

Selinger, E., Neuenschwander, M., Koller, A., Gojda, J.,

Kuehn, T., Schwingshackl, L., Barbaresko, J., and

Schlesinger, S. (2023). Evidence of a vegan diet for

health beneﬁts and risks–an umbrella review of meta-

analyses of observational and clinical studies. Critical

reviews in food science and nutrition, 63(29):9926–

9936.

Seto, K. C., G

uneralp, B., and Hutyra, L. R. (2012). Global

forecasts of urban expansion to 2030 and direct im-

pacts on biodiversity and carbon pools. Proceedings

of the National Academy of Sciences, 109(40):16083–

16088.

Shaw, P., Price, R., Elliott, K., Copilah-Ali, J., Huntingford,

J., and Ionescu, O. (2024). White paper-corporate dig-

ital responsibility (cdr) securing our digital futures.

Corporate Digital Responsibility (CDR) Securing Our

Digital Futures, pages 1–35.

Singer, P. (1990). The signiﬁcance of animal suffering. Be-

havioral and Brain Sciences, 13(1):9–12.

Stroia, N., Moga, D., Muresan, V., and Lodin, A. (2020).

Estimating environmental variables in smart sensor

networks with faulty nodes. In SMARTGREENS,

pages 67–73.

Vergallo, R., Cagnazzo, A., Mele, E., and Casciaro, S.

(2024a). Measuring the effectiveness of the ‘batch op-

erations’ energy design pattern to mitigate the carbon

footprint of communication peripherals on mobile de-

vices. Sensors, 24(22):7246.

Vergallo, R., Errico, A., and Mainetti, L. (2024b). On the ef-

fectiveness of the’follow-the-sun’strategy in mitigat-

ing the carbon footprint of ai in cloud instances. Avail-

able at SSRN 4566638.

Vergallo, R. and Mainetti, L. (2024). Measuring the ef-

fectiveness of carbon-aware ai training strategies in

cloud instances: A conﬁrmation study. Future Inter-

net, 16(9):334.

Viscusi, W. K. (1993). The value of risks to life and health.

Journal of Economic Literature, 31(4):1912–1946.

Viscusi, W. K. (2019). Value of a statistical life. Oxford

Research Encyclopedia of Economics and Finance.

Wallace, P., Martin, R., and White, I. (2018). Keeping pace

with technology: Drones, disturbance and policy deﬁ-

ciency. Journal of Environmental Planning and Man-

agement, 61(7):1271–1288.

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