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AI and Ethics (2025) 5:2165–2174
https://doi.org/10.1007/s43681-024-00545-z
ORIGINAL RESEARCH
The ethico‑politics ofdesign toolkits: responsible AI tools, frombig
tech guidelines tofeminist ideation cards
TomaszHollanek1
Received: 17 May 2024 / Accepted: 30 July 2024 / Published online: 8 August 2024
© The Author(s) 2024
Abstract
This paper interrogates the belief in toolkitting as a method for translating AI ethics theory into practice and assesses the
toolkit paradigm’s effect on the understanding of ethics in AI research and AI-related policy. Drawing on a meta-review of
existing ‘toolkit-scoping’ work, I demonstrate that most toolkits embody a reductionist conception of ethics and that, because
of this, their capacity for facilitating change is limited. Then, I analyze the features of several ‘alternative’ toolkits–informed
by feminist theory, posthumanism, and critical design–whose creators recognize that ethics cannot become a box-ticking
exercise for engineers, while the ethical should not be dissociated from the political. This analysis then serves to provide
suggestions for future toolkit creators and users on how to meaningfully adopt the toolkit format in AI ethics work without
overselling its transformative potential: how different stakeholders can draw on the myriad of tools to achieve socially desir-
able results but reject the oversimplification of ethical practice that many toolkits embody.
Keywords Toolkits· Guidelines· AI ethics· Responsible AI· Critical design· Feminist design
1 Introduction
In the late 2010s, AI professionals appeared ‘aware of the
potential importance of ethics in AI,’ but were left with ‘no
tools or methods for implementing ethics’ in their work [24,
p. 2148]. It is in response to this apparent lack of appropri-
ate resources that researchers have started to investigate the
needs of industry practitioners [16] and analyze potential
strategies for translating the theory of AI ethics–conceptions
of accountability, fairness, transparency, trustworthiness,
and justice, among other ideas and values–into AI develop-
ment and deployment practice [22]. To meet the pronounced
need for ‘tools for implementing ethics’ in AI, numerous
teams in industry, academia, and civil society organizations
have started to release various kinds of toolkits for respon-
sible, ethical AI.
The OECD’s Catalogue of Tools and Metrics for Trust-
worthy AI is the biggest collection of such tools, toolkits,
guidelines, frameworks, and standards–meant to ‘help
AI actors develop and use trustworthy AI systems and
applications that respect human rights and are fair, trans-
parent, explainable, robust, secure and safe’ [26]. Some
of the tools included in the Catalogue are categorized as
technical, intended for machine learning engineers and data
scientists, to help, for instance, with assessing the quality
of the data used to train a given model; some are proce-
dural, guiding those who oversee the development process
to, for example, conduct an assessment of the end product’s
impact on human rights; and some are educational, introduc-
ing development teams to concepts such as ‘trustworthiness’
and explaining how they relate to specific design decisions.
While the OECD repository was created to help disseminate
already available toolkits for ethical AI and allow for their
classification and comparative analysis, I refer to it at the
outset because it points to the diversity of formats adopted
by different teams in response to the challenge of translat-
ing AI ethics theory into responsible AI practice: ranging
from interactive, web-based applications, to static docu-
ments featuring checklists, sets of instructions, or lists of
issues to consider, aiming to intervene at different stages of
the development process and targeting different stakeholder
groups. Despite the classification system proposed by the
OECD, we lack a clear and consistent definition of a ‘toolkit’
in AI ethics research and practice, or how it differs from
a ‘method,’ a singular ‘tool,’ or ‘guideline.’ Since terms
* Tomasz Hollanek
th536@cam.ac.uk
1 Leverhulme Centre fortheFuture ofIntelligence, University
ofCambridge, Cambridge, UK
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2166 AI and Ethics (2025) 5:2165–2174
such as ‘responsible’ ‘ethical,’ ‘trustworthy,’ or ‘human-
centered,’ are also used largely interchangeably in the AI
ethics discourse, for the purposes of this paper an AI ethics
toolkit refers to any type of document, product, or website
whose explicit aim is to facilitate change in the ways in
which AI systems are designed, deployed, or governed and
to ensure that the results of development lead to desirable
social consequences.
The OECD Catalogue also serves as a poignant illustra-
tion of what we could call the ‘toolkittifcation’ trend in AI
ethics [15]. If only a few years ago there seemed to be a lack
of relevant tools and resources for producers of AI systems
to consider ethics throughout development, now, at the time
of writing, the OECD collection features more than seven
hundred toolkits that promise to facilitate precisely the dif-
ficult work of translating AI ethics theory into practice.
Despite various critiques of the toolkit format as a method
for addressing complex ethico-political questions in design
[3, 15, 23, 29], the sheer number of available responsible
AI toolkits attests to the dominance of the toolkit seen as a
tangible, operationalizable, and effective instrument of eth-
ics for technology design–a means to an ‘ethical’ end.
The main objectives of this paper are, then, to interrogate
the belief in toolkitting as a viable method for reorienting
AI practice towards socially desirable goals and to assess
its effect on the understanding of ‘ethics’ in AI research
and policy; to analyze the features of several toolkits whose
creators recognize that the conception of the ethical that
presupposes the toolkits’ creation can never be truly dis-
sociated from the political, while ethics cannot be turned
into a box-ticking exercise for engineers; and to provide
recommendations for future toolkit creators and users on
how to meaningfully adopt the toolkit format in ethical AI
work without overselling its transformative potential. In Part
2, I start by exploring the ethico-political assumptions that
underly most ethical AI toolkits. Through a meta-critique of
toolkits (drawing on a review of existing ‘toolkit-scoping’
work), I demonstrate that a reductionist conception of eth-
ics, seemingly dissociated from politics, that informs most
efforts at reshaping AI development standards, results in the
creation of toolkits whose capacity for facilitating change
and challenging the status quo is limited. Then, in Part 3,
I analyze several ethical AI toolkits that have emerged as
alternatives to those most widely adopted in industry–tool-
kits that draw on intersectional feminist critique, posthuman
theory, and decolonial theory, and that remain absent from
the OECD Catalogue and unaccounted for by the ‘toolkit-
scoping’ papers that inform the meta-critique of the toolkit
‘landscape’ in Part 2. I refer to these ‘alternative’ toolkits to
argue that the role that toolkits may play in reorienting tech-
nology design towards socially desirable outcomes relates
to their potential for facilitating power-sensitive conversa-
tions between different stakeholder groups and epistemic
communities. Finally, in the concluding section, referring
to broader theories and critiques of toolkitting as a method
for structuring the design process, I suggest how different
stakeholders can draw on the myriad of available tools, rang-
ing from big tech companies’ guidelines to feminist design
ideation cards, to achieve positive, socially desirable results,
while rejecting the oversimplification of ethical practice
and technosolutionism that many responsible AI toolkits
embody.
2 The ethico‑politics ofAI ethics toolkits
2.1 Analyzing thetoolkits ‘landscape’
It is precisely because of the abundance of ethical AI tool-
kits–overwhelming for any design team in search of an
appropriate tool or guideline–that ‘toolkit-scoping’ has
become a sub-genre of AI ethics scholarship. Numerous
articles aim to analyze various aspects of ‘the landscape’
of ethical AI toolkits to uncover trends in what is already
available and highlight what is still missing. Some studies
examine the convergences of the values, principles, and
goals–across institutions, sectors, countries, or regions–that
the toolkits foreground as crucial to ensuring that AI devel-
opment is carried out responsibly [4, 11, 19, 20, 30]. Some
analyses focus on the question of the toolkits’ usability [21,
24, 32] or compare the toolkits’ formats and the methods
they introduce to their intended users [5, 31]. Other surveys
reveal consistencies in how the toolkits’ creators envision the
work of ethics in AI design: what traditions of ethics, if any,
the toolkits draw upon [4, 12, 13, 35]; what stage of develop-
ment this work is meant to be carried out at [4, 5]; and which
stakeholder groups are to be involved in the process [5, 12].
While these studies adopt different analytical angles and
use distinct selection criteria for ethical AI toolkits to be
taken into consideration, collectively–as I will explain in
what follows–they point to several, consistent categories of
shortcomings in the design of the toolkits themselves. To
prepare a systematic meta-critique of the AI ethics toolkits
landscape, I looked for academic papers published in 2019
or later, presenting the findings of reviews or surveys of
at least twenty responsible/ethical/trustworthy AI guide-
lines/toolkits/tools. I searched several databases (Google
Scholar, the ACM Digital Library, Web of Science, SSRN,
and arXiv) by terms such as ‘AI guidelines,’ ‘AI toolkits,’ ‘AI
ethics toolkit review,’ ‘ethical ML toolkit review,’ and vari-
ations of these. Eight papers met the criteria for inclusion
in the meta-critique [4, 5, 13, 19, 20, 24, 30, 35]; two other
articles [11, 12] that did not come up in the database search
but were cited by nearly all the initial eight papers were also
included in the meta-critique collection. Three other papers
repeatedly showed up in the search [21, 31, 32], but did not
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2167AI and Ethics (2025) 5:2165–2174
meet all the criteria for inclusion, as they present in-depth
comparative analyses of a smaller number of toolkits.
The primary goal of the meta-critique is to reveal that,
despite the sheer number of available options, most ethical
AI toolkits are informed by the same set of ethico-political
assumptions–ideas about ethical reasoning as it relates to
the conceptions of agency, power, and individual as well
as collective responsibility–that negatively impact the tool-
kits’ potential to reorient practice towards socially desirable
outcomes. When surveying the papers for consistencies in
what the papers’ authors highlight as limiting the toolkits’
positive influence on design practice and in what they rec-
ommend to future toolkit creators, I considered the follow-
ing questions: What conceptions of ‘ethics’ do the toolkits
refer to, explicitly or implicitly? Which values, principles,
or goals do the toolkits foreground as key to responsible
AI development that they promise to facilitate? Whom do
they address as the agents of change? To what extent is the
transformation of practices–that the toolkits are meant to
enable–envisioned as a matter of individual responsibility of
designers? Are stakeholders other than designers accounted
for? If so, do the toolkits present any methods for engaging
these stakeholders?
2.2 Meta‑critique ofAI ethics toolkits: thetoolkits’
limitations
In this section, I present the results of the meta-critique of
the toolkits landscape, pointing to several types of limi-
tations that determine the outcomes of most attempts at
‘toolkittifying’ AI ethics. These limitations relate to: the
toolkits’ foundational ‘deficiencies,’ reflective of the omis-
sions in the lists of values and principles they are meant
to help translate into practice; a reductionist, technosolu-
tionist conception of ethics–seemingly dissociated from
politics–that most toolkits embody; and the co-optation of
concepts and methods derived from critical studies of design
and technology (such as participatory or inclusive design)
decontextualized in ways that foreclose their meaningful,
power-sensitive implementation in the AI development
process.
The majority of responsible AI toolkits carry founda-
tional ‘deficiencies’ because they are bound to reflect the
limitations of the lists of values and principles that underlie
their creation. While most toolkits feature values such as
accountability, privacy, trustworthiness, or fairness [11, 19,
20], the ideals and goals of solidarity, or the prioritization
of human co-flourishing as opposed to ‘radical individual-
ism’ [19], environmental sustainability, or the commitment
to minimizing the negative effect of technological develop-
ment on the environment [19, 20], as well as labor rights
or the rights of children [20] are consistently omitted. Sev-
eral studies also highlight how design values and principles
statements–that the toolkits are supposed to help translate
into action–frame the quest for responsible AI as a universal,
species-wide concern, failing to acknowledge that the val-
ues in question might be interpreted differently around the
globe, and that the available lists of principles exclude the
values prioritized by societies and groups underrepresented
in mainstream AI ethics–as embodied by ethical AI toolkits
[12, 19, 20].
We could argue that most ethical AI toolkits incorporate
a reductionist conception of ethics because far too often
they frame ethical practice as a matter of compliance with
already existing standards and regulations–on the part of
developers/designers/data analysts–rather than an inquiry
into the motivations behind development, or an analysis of
wider, socio-environmental consequences of technological
production. Several studies emphasize the ‘technosolution-
ist’ character of ethical AI toolkits, as the majority of avail-
able tools approach ethical reasoning as directly translatable
into immediate technological and procedural ‘fixes’ [13, 35]
to the already established development pipeline. Informed
by this form of technosolutionism, the majority of toolkits
for ethical AI not only overlook the full complexity of the
decision-making processes at play [24], but also leave no
space for questioning the justifiability of starting a given
development project in the first place. It is precisely this
focus on what is immediately and visibly ‘fixable’ at the
product development stage that results in the toolkits’ failure
to prompt the questioning of business strategies behind par-
ticular technical decisions [4, 12], as well as to draw atten-
tion to–and provide guidance on mitigating–the undesirable,
indirect social and environmental costs of technology devel-
opment [13, 20, 30].
Numerous toolkits and guidelines gesture towards the
need for ‘inclusion’ of diverse ‘stakeholders’ in design as a
matter of ensuring that development leads to desirable out-
comes. These calls for stakeholder engagement, however,
often point to external experts, such as lawyers [12], rather
than those minoritized stakeholder groups who bear the
brunt of the new technologies’ harmful impacts–stakehold-
ers referred to (problematically, but suggestively) as ‘voice-
less’ in one toolkit-scoping paper, a category comprising
both the ‘[t]raditionally marginalized groups with limited
voice in society’ and ‘the environment’ [5, p. 412]. Several
studies emphasize that even the toolkits that do prescribe
minoritized stakeholders’ participation in the design process
fail to account for–and help navigate through–the difficulties
of facilitating power-sensitive conversations between those
who are already present at the metaphorical design table
and those whose voices have been excluded or ignored in
the past [5, 35]. This constitutes an especially concerning
limitation of the available toolkits, since the calls for par-
ticipatory technology design, when approached this way, are
more likely to encourage ‘participation-washing’ rather than
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2168 AI and Ethics (2025) 5:2165–2174
‘participation as justice’ [33]: a genuine attempt to actively
include, not extract insights from, minoritized stakeholder
groups. Indeed, even when ethical AI toolkits operational-
ize the language of social justice, this is more likely to be a
sign of corporate co-optation of the critical terminology than
that of genuine commitment to aligning business and design
processes with the goals of equitable human co-flourishing
and environmental sustainability – the normative ends of the
critical work from which the terminology derives [12, 33].
2.3 Meta‑critique ofAI ethics toolkits:
recommendations forfuture toolkit makers
As I demonstrated in the previous section, consistent pat-
terns of critique emerge in various surveys evaluating ethi-
cal AI toolkits, pointing to several types of limitations in
the design of the toolkits themselves. These toolkit-scoping
reviews also converge on a set of recommendations for
future toolkit creators.
If most ethical AI toolkits overlook the values of solidar-
ity (or human co-flourishing) and environmental sustainabil-
ity, as well as other values and principles prioritized by com-
munities underrepresented in mainstream AI ethics, then the
solution to these foundational ‘deficiencies’ appears to lie in
engaging with the ethical and epistemological frameworks
from which the missing values originate when designing
new toolkits. Future toolkit creators are encouraged to con-
sider, for instance, feminist ethics, ethics of care, decolonial
theory, and Indigenous epistemologies [4, 35]–a recommen-
dation that echoes a growing number of calls for AI ethicists
to draw on relational philosophies in their work [6, 9]. This
suggestion for future toolkit makers also points to a belief
inscribed in the toolkit as a means of ‘reforming’ dominant
design practices: a belief that, by exposing themselves to
‘alternative’ ethical and epistemological positions, toolkit
makers might conceive of ‘alternatives to the dominant para-
digm of the toolkit’ [35, p. 16], and that, by developing such
alternatives, they might then enable a wider shift in design
without requiring–and this is key–individual designers or
design teams, the intended users of most responsible AI tool-
kits, to directly engage with these positions.
Since most responsible AI toolkitsembody a reduction-
ist understanding of ethics–with the checklist as its primary
‘instrument’ [13]–the recommendation for future toolkits
makers is to adopt different formats that reflect the complex-
ity of ethical reasoning in design, accounting for the indirect
social and environmental costs of AI development. To depart
from the technosolutionism implicit in most available tool-
kits, new, alternative toolkits are supposed to prompt design
teams to draw on non-technical expertise and to consult with
representatives of groups that are most likely to experience
the negative consequences of AI development [5, 13, 35]–to
only then consider and implement strategies for mitigating
the undesirable impact. This second set of recommenda-
tions also points to another, somewhat paradoxical feature
of the toolkit conceived as a means of transforming design
practices: while toolkits are meant to make the difficult,
often uncomfortable critical work of assessing and mitigat-
ing socio-environmental harms of technology development
more easily executable, the format of the toolkit itself should
never make the task at hand appear straightforward and free
from friction. A good toolkit, it seems, should reflect, rather
than reduce, the full complexity of the process of identify-
ing and addressing ethical challenges in design–even if the
toolkit aims to facilitate this process by giving it structure.
Finally, as the majority of available toolkits fails to guide
development teams through the exercise of meaningfully
including the so-called ‘voiceless’ [5]–or, more appropri-
ately, ignored or silenced–stakeholders in design ideation
and testing, and to enable participation as justice, future
toolkit makers are encouraged to create toolkits that ‘struc-
ture the work of AI ethics as a problem for collective action’
[35, p. 17] undertaken not only by professional designers
within technology companies, but also the communities
most likely to be impacted by AI. The recommendation
for future toolkit makers is to create toolkits that not only
make designers already present at the ‘design table’ aware
of broader power dynamics that either enable or foreclose
ethical technology design but also, and more importantly,
empower a wider array of stakeholders to challenge these
preexisting relations, as well as verbalize their needs and
demand change [5, 30, 35]. A good, effective design toolkit
in this framing is supposed to lead stakeholders through the
challenges of building new systems responsibly and, simul-
taneously, building new movements–within and outside of
tech companies–that make attempts at transforming design
practices both possible and consequential. The vision that
emerges from this final set of recommendations is that of
the toolkit as a means of structuring the design process and
affecting political change–approaching responsible technol-
ogy development not only as a matter of ethics but also, and
perhaps more importantly, that of politics.
3 The wider landscape ofAI ethics toolkits
3.1 Toolkitting otherwise
Although the toolkit-scoping articles that informed my
meta-critique of the toolkit ‘landscape’ collectively point to
the need for ‘alternatives’ to the dominant paradigm of the
ethical AI toolkit as if such alternatives were not available,
in Part 3 I refer to examples of toolkits produced by critical
design theorists and practitioners that constitute precisely
such alternatives–alternatives excluded by the OECD data-
base and all the toolkit-scoping papers that informed my
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2169AI and Ethics (2025) 5:2165–2174
meta-critique of the toolkits ‘landscape’ in Part 2. Draw-
ing on interventions in intersectional feminism, decolonial
theory, post-development studies, and posthuman theory,
among other fields, critical design scholars point out that
universalist approaches to design, practices that aim to
streamline and standardize the design process and its prod-
ucts, in reality cater to the dominant groups in society and
thus ‘erase certain groups of people, specifically those who
are intersectionally disadvantaged or multiply burdened
under white supremacist heteropatriarchy, capitalism, and
settler colonialism’ [8, p. 19]. To deliver socially (and
environmentally) desirable outcomes, design practice, they
argue, can no longer be conceived of as ‘an expert-driven
process focused on objects and services within a taken-for-
granted social and economic order’ [10, p. 53] but instead
must be reimagined from the standpoint of those marginal-
ized and minoritized groups. For this reorientation to hap-
pen, practices and methods that are ‘participatory, socially
oriented, situated, and open ended and that challenge the
business-as-usual mode of being, producing, and consum-
ing’ [10, p. 53] should be brought to the fore. This is pre-
cisely what the ‘alternative’ toolkits that I focus on in this
section aim to achieve.
While Part 2 served as a meta-critique of the ‘landscape’
of responsible AI toolkits, Part 3, rather than a comprehen-
sive survey of ‘alternatives,’ is an analysis of two toolkits
informed by broadly understood critical design theory. The
first, the Intersectional AI Toolkit [17], is a website created
by the artist and scholar Sarah Ciston in 2021 and main-
tained–thanks to its wiki-style format–by a community of
contributors; it comprises downloadable design ideation
workshop materials and short explainers on both intersec-
tional feminism and machine learning for non-experts. The
second, the Notmy.ai website [25], is an ongoing attempt at
developing ‘a feminist toolkit to question AI systems’ [34]
by the Brazilian feminist organization Coding Rights, led by
the researcher and activist Joana Varon in partnership with
the activist Paz Peña, gathering resources such as instruc-
tions on how to investigate the harms perpetuated by AI
systems already in use and design ideation cards helping
marginalized stakeholders to conceive of new technologies
and systems.
The meta-critique of the toolkits landscape revealed that
future toolkit makers are consistently encouraged to consider
‘alternative’ philosophical foundations–feminist ethics and
decolonial theory, among others–as the basis for AI eth-
ics toolkittification projects; the two selected toolkits stem
precisely from such ‘alternative’ foundations. The Intersec-
tional AI Toolkit, as the name suggests, explicitly draws
on intersectional feminist critique to ensure that ‘queer,
antiracist, antiableist, neurodiverse, feminist communi-
ties’ can bring to bear on what kinds of systems are seen as
desirable. The Notmy.ai Toolkit departs from the assumption
that ‘decolonial feminist approaches to life and technolo-
gies are great instruments to envision alternative futures and
to overturn the prevailing logic in which A.I. systems are
being deployed.’ In my reading of the ‘alternative’ toolkits,
I elucidate what these toolkits do differently as a result of
their creators’ ethico-political commitments–how the tool-
kits restructure the relationships between different actors
involved in the design process and between individual tools
and methods to ensure that their adoption leads to socially
desirable outcomes, where the understanding of the desir-
able is tied to the goals of social justice. I aim to ‘distill’ the
qualities of the ‘alternative’ toolkits that could, potentially,
inform the design (or re-design) of other AI ethics toolkits.
3.2 Multiplying thesites ofintervention
Remarkably, the primary goal of the alternative toolkits
is to gather people not tools. The Notmy.ai Toolkit prom-
ises to ‘build bridges’ between different activist groups,
including organizations defending women’s and LGBTIQ+
rights, to collectively voice objection against the use of AI
in specific domains (for instance, to manage access to pub-
lic services) and to facilitate the process of co-imagining
alternative applications that empower, rather than harm,
vulnerable groups. The Intersectional AI Toolkit, a com-
munity-maintained repository of collaboratively produced
materials–an explicit reference to ‘the 90s zine aesthetics
and politics’–similarly aims to bring together ‘some of the
amazing people, ideas, and forces working to re-examine
the foundational assumptions built into these technologies’;
it does so not toalign different stakeholders’ views or needs,
but rather to facilitate conversations and ‘engage tension.’
The alternative toolkits thus depart from the premise that
responsible technological development is not a matter for
technology executives or design leads to ‘solve’ internally;
that it is conditional on the involvement of civil society and
minority rights organizations; and that it is only through
surfacing friction–potential conflicts between the interests of
these different groups–that ethical practice becomes possi-
ble. The toolkits constitute ‘alternatives’ to the ‘mainstream’
ones analyzed in Part 2 precisely because, through their stag-
ing of collective deliberation and attending to conflict, they
attempt to repoliticize both ‘ethics’ and ‘design’–by contrast
with AI ethics toolkits that approach certain challenges, such
as those related to ‘algorithmic bias,’ as technical, rather
than deeply ethico-political.
One of the tools from the Notmy.ai collection, the Oppres-
sive AI Framework, in particular illustrates how toolkittifi-
cation of AI ethics can serve to reinscribe the political into
‘ethical’ tech design–ensuring that the understanding of
ethical practice in this context is not limited to interrogating
particular design decisions but rather extends to questioning
broader socio-political arrangements that make only some
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2170 AI and Ethics (2025) 5:2165–2174
AI development projects appear realizable or desirable, and
to whom. The Oppressive AI Framework introduces users
to feminist theory-informed ‘categories of harms,’ such as
‘embedded racism’ or ‘colonial extraction,’ perpetuated by
AI. Accompanied by real-life examples of AI applications
in South America analyzed through the Framework, the tool
demonstrates how users can examine injustices related to AI
development and deployment as a basis for seeking redress
and questioning the justifiability of certain AI projects.
Toolkittification in this framing does not foreclose avail-
able options by turning ‘ethics’ into a finite list of actions to
be carried out and ticked off during development, but rather
leads to their multiplication, where a decision not to design
or deploy a given system is also considered viable.
This sort of multiplication is what sets the ‘alternative’
toolkits apart from the ‘mainstream’ ones. In her Cloud
Ethics, Louise Amoore points to the distinction between an
encoded ethics, delineating what humans or algorithms can
or cannot do, and a relational ethics–an ‘ethics of the orien-
tation one has to oneself and to others’ [1, p. 165]–to argue
it is the latter that we should consider to determine what
constitutes ‘responsible’ technology design. This approach
to ethics, what Amoore calls cloud ethics, does not aim to
encode rules for human designers or algorithms, but rather
attend to how algorithms devise their own ethical patterns
and how these patterns impact the ways in which we relate
‘to ourselves and to others’ [1, p. 6]. While most ethical AI
toolkits embody the former approach (as the meta-critique
of the toolkits landscape confirms), the alternative toolkits
give an indication of what relational ethics might look like
in technology design practice: how we can give this kind
of critical work structure, while rejecting formulaicity and
reductionism implicit in most attempts at AI ethics toolkitti-
fication. For Amoore, cloud ethics in practice would take on
the form of ‘a crowded court in the sense that my approach
multiplies the possible sites of intervention and respon-
sibility’ [1, p. 25]; we could say that, in their attempt to
gather people, not only tools, the alternative toolkits aim to
convene precisely the kind of ‘crowded court’ that Amoore
gestures towards. In contrast to the ‘mainstream’ toolkits,
however, the ‘alternative’ toolkits not only underscore the
importance of assembling a diverse array of voices to widen
participation in AI design but also, and more importantly,
offer insights into how such conversations can be staged in
a power-sensitive way.
3.3 Facilitating power‑sensitive conversations
To allow for meaningful, power-sensitive inclusion of
diverse stakeholders in the ‘crowded court’ of design, the
alternative toolkits prioritize empowering the so-called
‘voiceless’ (or, more appropriately, silenced) stakeholders
to formulate and communicate their concerns, needs, and
ideas for development. While the Intersectional AI Toolkit
offers accessible resources on coding and machine learning
principles for non-experts, the Notmy.ai Toolkit directs users
to the Oracle for Transfeminist Technologies, a deck of tarot-
styled cards prompting players to consider values such as
‘solidarity,’ ‘decoloniality,’ ‘multispeciesm,’ or ‘socio-envi-
ronmental justice’–to co-imagine how AI could be applied
in a desirable future ‘where technologies are designed by
people who are too often excluded from or targeted by tech-
nology in today's world.’ Designers often work with card-
based tools to scope ideas [28] and indeed there are cards
decks that introduce professionals to Kimberlé Crenshaw’s
intersectionality framework to help them question who it
is they are designing for, highlighting intersecting charac-
teristics such as race, age, gender, or disability to support
designers in thinking critically about the intended users of
their products (see: [18]). However, by catering specifically
to those typically excluded from the design process but dis-
proportionately impacted by technological development, the
Intersectional AI Toolkit and the Notmy.ai Toolkit not only
encourage the interrogation of who constitutes the generic
‘user’ at the center of design but also, and more importantly,
challenge and expand the understanding of the ‘designer.’
By providing their target audience with an introduction to
the technical principles behind machine learning and to the
capabilities and limitations of AI, as well as by encouraging
the reimagining of AI from the standpoint of marginalized
groups, the toolkits aim to ensure that ‘inclusive’ practices
lead not to further extraction of insights from the most vul-
nerable in society but rather to the redistribution of power
at the metaphorical design table.
This is not to suggest that the alternative toolkits would
not prove beneficial to those who already have a seat at the
table. Most toolkits aimed at advancing diversity, equity,
and inclusion (DEI) in AI development focus on persuading
those in positions of power of the value, including direct
financial value, of inclusivity in AI design [15]. Rather than
merely providing information on the benefits of diversity
in design, alternative toolkits for business decision-makers,
software engineers, or design leads could function as train-
ing grounds for cultivating what design theorist Ahmed
Ansari refers to as ‘epistemic humility’–a ‘sensitivity to
difference’ that, as he argues ‘design research and practice
need, in order to move toward making [a more just and equi-
table] world possible’ [2, p. 19]. The Oracle cards aim to
nurture precisely this kind of sensitivity by guiding play-
ers to ‘reflect on who you are’ instead of ‘pretending that
you are someone else and you know what they need’; they
pose questions like ‘What body do you inhabit? Where
are you situated? What privileges and burdens accompany
your body and surroundings?’–and make clear that these
are fundamental to ethical design practice. It is precisely
because of this function–prompting critical introspection
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
2171AI and Ethics (2025) 5:2165–2174
and the acknowledgment of partiality of knowledge on the
part of the toolkit users–that the alternative toolkits could
be said to provide ground for translation between differ-
ent stakeholder groups. Translation should be understood
here in terms of Donna Haraway’s work on feminist epis-
temologies: translation as ‘always interpretive, critical, and
partial’ and, as such, enabling ‘power-sensitive, not plu-
ralist, “conversation[s]”’ [14, p. 589]. It is this conception
of translation, as enabling power-sensitive conversations,
that underlies the design of the alternative toolkits and that
departs from the misapprehension of participatory methods
as tactics for fulfilling visible diversity quotas.
The alternative toolkits make clear that ‘responsible’ AI
can only take shape through such conversations. As they
aim to empower those whose voices usually do not bring to
bear on business and design decisions behind tech develop-
ment and to guide those in positions of power to cultivate
epistemic humility as the basis for ethical work, the tool-
kits give an indication of how such conversations should be
structured to ensure that pre-existing power relations do not
foreclose the positive effect of participatory and inclusive
practices. Unlike most AI ethics toolkits that lack concrete
guidance on meaningful ‘stakeholder involvement,’ the alter-
native toolkits–precisely because they focus on ensuring that
conversations in these new design constellations are power-
sensitive–point to how participation can become the means
for reorienting design towards justice, how participation
understood this way is justice.
3.4 Foregrounding theneed for‘ongoingness’
ofethics work
If the toolkits facilitate the process of questioning and
restructuring the relationship between users and designers
on a broader scale, this process is mirrored in the design
of the toolkits themselves. The Intersectional AI Toolkit is
‘showing rough edges and edit marks, in the belief that no
text is final, all code can be forked, and everything is bet-
ter with friends.’ As a wiki page where users can trace the
evolution of different sections, the Toolkit not only invites
users to become co-designers, to comment on and remix
content, but also to delve into the project’s archive–making
the process of toolkittification itself transparent and open-
ended. Similarly, the Notmy.ai Toolkit emphasizes that the
tools it contains are not to be seen as ‘written in stone’ but
rather as ‘a work in process,’ and that depending on when
and where they are used, they will be ‘re-shaped according
to the particular context and its oppressions.’ The Toolkit
also actively invites users to directly contribute to its toolkit-
tification project, to collaboratively develop new applica-
tion cases, and to provide feedback on individual tools and
the Toolkit as a whole. The alternative toolkits thus make
clear that the ownership over the tools and resources they
gather is dispersed, that they belong to the community that
has helped to co-create them–the community they aim to
foster and empower; that ethics work demands negotiation
and conversations, and that it rests in making these negotia-
tions and conversations visible; and that no tool or toolkit
is ever finalized–that ethics work must remain continuous,
‘in progress.’
The alternative toolkits thus indicate that the process of
toolkittification must itself be seen as open-ended, a forever
ongoing negotiation of the ethics and politics that should
shape practice. Indeed, as the creator of the Intersectional
AI Toolkits emphasizes, responsible AI cannot be defined
by a ‘singular ethic or aesthetic–but rather a meta-ethics of
multiplicity and intersubjective relations’ [7, p. 5]. In this
perspective, toolkittification–the creation, selection, and uti-
lization of toolkits–does not imply foreclosure, simplifica-
tion, or reductionism; rather, it fosters multiplicity, negotia-
tion, and collective mobilization. It becomes an exercise in
meta-ethics of design, challenging assumptions about who
has the authority to design and where interventions should
extend beyond the design process itself. Toolkittification in
this framing is not only an expression of care for how tech-
nologies are made but also how they are imagined and who
gets to partake in that imagining. And it is within this mir-
roring between the design of the toolkits themselves and the
kind of design they aim to facilitate that lies a hint of what
we can glean from the alternative toolkits to understand the
broader process of toolkittification in AI ethics: how produc-
ing and using toolkits may help designers achieve socially
desirable results without the oversimplification of ethical
practice that many toolkits embody.
4 Towards aconclusion:
aftertoolkittication
In this article, I have drawn on the meta-critique of the AI
ethics toolkit landscape to demonstrate that that the ethico-
political assumptions that underpin most endeavors to ‘kit-
tify’ AI ethics also limit the resulting toolkits’ potential
for facilitating change in how new technologies are con-
ceived, developed, and deployed. These limitations, as I have
argued, are tied to several categories of suggestions on how
to improve toolkits put forward by AI ethics researchers. The
meta-critique of the toolkit landscape reveals that toolkit
makers are urged to address the foundational ‘deficiencies’
of existing toolkits by incorporating ‘alternative’ ethical
and epistemological frameworks, such as feminist ethics
or indigenous epistemologies. It emphasizes that toolkits
should reflect, rather than simplify, the full complexity of
the process of identifying and addressing ethical challenges
in design, while still providing structure to this process. It
also advocates for toolkits that encourage the participation
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
2172 AI and Ethics (2025) 5:2165–2174
of a wider array of stakeholders, enabling them to articu-
late their needs and demand change in how technologies are
developed and adopted. Finally, the meta-critique also points
to the need for reframing responsible technology design as a
matter of collective action–the need for reinscribing politics
into the ethics of AI.
These suggestions would certainly resonate with many
critical design theorists and practitioners. This is because
the limitations of AI ethics toolkits identified in the meta-
critique might relate not to the challenges of translating the
theory of ethics into AI development practice specifically,
but to the pitfalls of toolkittifcation as a means of reform-
ing design generally: a form of myopia that toolkittifca-
tion embodies. Precisely in response to this critical view
of toolkittification, Ansari has argued that we do not need
toolkits ‘nor their “universal” definitions of design thinking
or their processes’ but rather ‘new, diverse philosophies and
frameworks that are tied to local knowledge and practice,
informed by local politics and ethics’ [3, p. 428]. In Ansari’s
understanding, design toolkits reaffirm the ethico-political
assumptions underlying dominant design paradigms instead
of challenging them; the organizing logic they represent and
enforce is that of scale and repetition and thus also of eras-
ure–erasure of practices that are not suitable for scaling up,
that are situated, deeply contextual. In her essay on design
toolkits, media theorist Shannon Mattern echoes this, para-
phrasing the work of Audre Lorde, saying that ‘tools forged
through a particular politics […] might not be able to under-
mine that political regime’ [23, non pag.]. In this framing, a
toolkit as a means of structuring design activities incorpo-
rates the universalizing principles of the Western modernist
tradition–a tradition that critical design scholars, as men-
tioned earlier, aim to depart from; toolkits foreclose certain
modes of resistance to development and production because
they reflect a worldview that sees technological advance-
ment as inevitable, while disregarding modes of being and
knowing that do not ‘lend themselves to standardization,
measurement, and “kittification”’ [23].
Without questioning the underlying ethico-politics of
design toolkits (whether for AI or any other application area)
their creators are bound to repeat the mistakes that critical
design theorists and practitioners have been warning against
ever since toolkits, that initially emerged as frameworks
for ‘bringing more self-reflexivity and rigor into design-
ers’ own processes’ out of the design methods movement
of the 1960s, evolved into ‘formulaic, self-contained pack-
ages’ [3, p. 419] that they are now. However, the historical
trajectory of design toolkits that Ansari is referring to also
indicates that the belief in the toolkit as a means of facili-
tating change in design might not be entirely misguided.
Indeed, Mattern argues that precisely in the context of rapid
technological change and in contrast ‘with the machines
automatically harvesting mountains of data,’ some design
toolkits may allow for ‘a slower, more intentional, reflective,
site-specific, embodied means of engaging with research
sites and subjects’ [23]. I expanded the ‘landscape’ of AI
ethics toolkits in my discussion to include the ‘alternative’
toolkits–toolkits overlooked by other ‘toolkit-scoping’ and
‘toolkit-collecting’ projects–to demonstrate what they do
differently to enable the kind of practice that Mattern sug-
gests is still possible. Rather than facilitate the translation of
‘theory’ into ‘practice,’ these toolkits help translate between
people, between different stakeholder groups and epistemic
communities–they strive to stage power-sensitive conversa-
tions and allow for engaging tension. Instead of encouraging
inclusion measured against visible markers of ‘diversity,’
they prioritize participation as justice. They foreground
ethics work as continuous, perpetually ‘in progress,’ rather
than a finite list of issues to be resolved. The result of this
analysis is, therefore, not so much a set of clear-cut recom-
mendations for future makers and users of AI ethics toolkits
or an ‘endorsement’ of the selected ‘alternative’ toolkits,
as a renewed sense of orientation: from toolkittification as
automation, delegation, and simplification of ethics work in
design, towards toolkittification as a meta-ethics of design.
This is also to emphasize that my critical interrogation of
‘toolkittfication’ is not a call to abandon toolkits but rather
to explore and acknowledge both the affordances and limita-
tions of the modes of acting (and knowing) that toolkits, in
their multiplicity, enable and enforce. While specific types of
tools–be they ideational, educational, procedural, or techni-
cal–can help address particular aspects of broader challenges
related to responsible technology development, it is essential
to make visible what is lost in ‘translation,’ what gets obfus-
cated when toolkits are embraced as the primary response
to the demands of AI ethics, understood broadly as both a
research and regulatory space. The European Union’s newly
adopted AI Act mandates that developers assess the impact
of their AI systems on fundamental rights and values, such
as dignity, in high-risk areas of application like recruitment
and public services. This is no easy feat, and we can expect
new guidelines and toolkits to multiply to make compli-
ance with new regulation more easily executable. Thinking
critically about AI ethics through ‘toolkittification’ will help
ensure that these efforts, while much needed, do not lend
themselves to a checklist mentality and oversimplification
of the ethics work discussed in this article.
Indeed, my critique of the AI ethics toolkits landscape
was conducted concurrently with a practice-oriented project
that aimed to develop precisely such a toolkit: intended to
help development teams not only comply with the AI Act
but also adopt a pro-justice approach to design–an approach
that informs the ‘alternative’ toolkits analyzed in this article.
While a discussion of how the approach to toolkittification
as a meta-ethics of design has influenced the development
of a specific toolkit (and what compromises have been made
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
2173AI and Ethics (2025) 5:2165–2174
in the process) is beyond the scope of this paper–and will
be addressed elsewhere–the hope is that the scaffolding
proposed here, which helped our team test the limits of the
toolkit format, will also help others consider what should
become of AI ethics work after toolkittification.
Funding This work was funded by the Stiftung Mercator GmbH grant
no. 200446.
Data availability Not applicable.
Declarations
Conflict of interests No competing interests to declare.
Ethics approval and consent to participate Not applicable.
Consent for publication Not applicable.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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