Introduction
A self-conscious view of the relevance, direction, and impact of our work has
accompanied information system (IS) research almost from its inception [
1–4
] and
continues to this day [
5
]. Most prominently, Benbasat and Zmud [
3
] escalated these
concerns into a comprehensive discussion about the very identity of IS research. Their
reasoning was that a dominant design in the form of common core of constructs and
relationships was necessary for IS research to mature and gain relevance (i.e., cognitive
legitimacy) with important stakeholders (e.g., governing bodies, public organizations,
etc.). After all, how convincing and relevant can IS research be when it cannot
demonstrate a consensus around its core concepts? This stance sparked a controversial
and still unresolved discussion about the nature and direction of IS research [
4
]. To this
day, the discourse on this topic remains controversial with different perspectives
coexisting and competing [
5
].
This paper strives to broaden the discourse by focusing on the moral dimension of
IS research. Here, we follow in the footsteps of Walsham [
6
], who has already argued
for the need to reframe the discourse about the nature and identity of IS research and to
reconsider its values and vision in the form of a strong ethical agenda:
Architects want to build better buildings, medics want to help people live longer and
healthier lives, engineers want to build more effective technological systems to
improve efficiency and artists want to stimulate our subtler senses with their work.
IS scholars and practitioners should be concerned with how to use ICTs to help make
a better world, where everybody has the opportunity and capability to use
technologies to make better lives for themselves, their communities and the world in
general. [
6
]
Most importantly, emphasizing the ethical agenda of IS research has the virtue of
providing a common ground on which most scholars should be able to unite. No matter
what topics, concepts, theories, or methods IS scholars investigate or make use of, we
should all be able to agree on the desire to be relevant and have a positive impact on
the world [
6
]. Thus, focusing on the ethical dimension and agenda of IS research
provides new opportunities for reframing the debate on IS identity as well as IS impact
and may help to move it closer towards resolution.
Towards this goal, we extend Walsham’s initial work by starting to investigate the
foundational question that an ethical agenda for IS research poses: how can we most
effectively improve the world with IS research? As a first step, we turn to Effective
Altruism (EA) [
7
] for an expert perspective on this topic. EA is a growing global
movement and research program focused on the deceptively simple-seeming question:
How can we do the most good with the resources we have? EA advocates for an open,
scientific mindset when considering moral questions [
8
] and, since its inception, the
EA movement has curated a rapidly growing body of knowledge focused on the key
considerations that should be kept in mind when one tries to effectively improve the
world [
7–12
]. Thus, we argue that EA is a key reference discipline that should be
considered when an ethical agenda for IS research is discussed.
The rest of the paper is structured as follows. First, we provide a short overview of
EA and its key concepts and considerations. Second, we frame IS research in terms of
EA and discuss how it could be informed by two key ideas from EA. Third, we conclude
with a short discussion and outlook.
2
A Short Overview of Effective Altruism
Historically, the EA movement can be traced back to the philosophical arguments of
the philosopher Peter Singer [
13
], who observed that humans are often in a great
position to help avoid unnecessary suffering (e.g., by giving to effective charities) but
somehow neglect to do this (e.g., due to cognitive biases). For example, while most
people who walk by a shallow pond and see a drowning child would hurry to its rescue
even at great cost to themselves, far fewer people would give a comparable amount of
money to effective charities who could save the equivalent of the drowning child in a
developing country. According to Singer [
13
], there is no morally relevant difference
between the two situations and, thus, we ought to be impartial [
14
] and help in both
cases. Since then, more and more people have taken Peter Singer up on his challenge
to give morality a bigger role in their lives and united around what was to become the
central question of EA: How can we do the most good with the resources we have?
Today, EA is a rapidly developing, and global movement of diverse people driven
by the desire to effectively improve the world [
15
]. EA has started to integrate research
and considerations from philosophy with other disciplines, most prominently,
economics to provide a sound foundation for this endeavor [
7, 10, 12
]. Due to the scope
and complexity of this work, only a short overview of major considerations can be
presented and discussed in this paper. We follow the EA Concepts website [
12
] in
structuring this overview and, thus, focus on considerations emerging from general
features of the world and how these impact ethical decision-making.
2.1
General Features of the World
EA highlights, amongst others, three general features of the world, which are deemed
highly relevant to ethical decision-making, namely, capacity to feel pleasure and pain,
future considerations, and variation in cost-effectiveness [
12
].
Capacity to Feel Pleasure and Pain. The creation of pleasure and avoidance of pain
is generally considered to be an important value in all plausible theories of value that
underpin systematic moral considerations [
12
]. Thus, it is highly relevant to understand
and/or determine to what degree pleasure and pain can be experienced by beings that
may be affected by one’s actions. Three major positions can generally be discerned in
the philosophic and scientific discourse, namely, only humans feel pleasure and pain,
only sufficiently advanced animals feel pleasure and pain, or the capacity to feel
pleasure and pain is substrate-independent and may arise in non-animal subjects as
well [
12
]. For example, while most people hold that only sufficiently advanced animals
feel pleasure and pain, some people argue, for instance, that sufficiently advanced
artificial intelligence (e.g., in the form of computer simulations of people) could have
similar experiences to biology-based beings [
16
]. It is obvious that one’s position on
this question may greatly alter the moral weight associated with a given action and,
thus, EA generally argues for deliberate engagement with this challenge.
For example, recognizing the possibility that conscious artificial intelligence may be
created accidentally and unwittingly exposed to large amounts of suffering would likely
influence the development and research of IS which could conceivably exhibit this
property. However, it is also important to note that the recognition of other beings’
capacity to experience does not necessarily imply that all beings’ experiences need to
be of equal importance in one’s considerations [
12
].
Future Considerations. The observable value of any action today is determined by
what happens in the future [
12
]. For example, on the one hand, if a large meteor was
going to hit earth and wipe out humanity in a few years’ time that would considerably
decrease the value of work done to combat climate change [
12
]. On the other hand, if
one sees future people as morally relevant and considers that in a positive (post-human)
future [
17
] most people who will have ever lived have not yet been born. This would
imply that all actions which help to positively shape the future are of overwhelming
importance [
18
]. More specifically, if one accepts these premises, it is plausible that the
most important thing about actions today are their long-run consequences in the far
future (e.g., via indirect flow-through effects) [
18, 19
]. Thus, EA generally advocates
for the importance of future considerations even on present-day ethical
decisionmaking [
18, 19
]. Of particular interest in this context are potentially transformative
technologies such as artificial intelligence, genetic engineering, atomically precise
manufacturing and methods of interstellar space travel [
12
] which are all interlinked
with IS and, thus, relevant fields of IS research. New technologies can not only radically
improve the world but also create new risks that may even lead to human extinction
[
20, 21
].
Variation in Cost-Effectiveness. According to the best estimates resulting from
empirically grounded cost-effectiveness analyses [
11, 22
] there are significant
variations in the cost-effectiveness of interventions focused on improving the world
[
23, 24
]. For example, the most cost-effective intervention focused on reducing the
suffering caused by HIV/AIDS (education of high-risk individuals) is estimated to be
around 1,400 times cheaper than the least cost-effective intervention (surgical treatment
for Kaposi’s sarcoma). This means that for the cost of treating one Kaposi’s sarcoma
about 1,400 high-risk individuals can be prevented from contracting HIV/AIDS
through the means of education [
23
].
Although such cost-effectiveness estimates are inherently uncertain due to the
variety in influencing factors and overall complexity and entanglement of the modern
world, the magnitude of observed differences in cost-effectiveness estimations suggests
that significant variation in cost-effectiveness exists to a reasonable degree of
confidence and is likely a general feature across focus areas [
22–24
]. Consequently, in
the light of general constraints on available resources, EA argues for a moral imperative
to use the resources available wisely and in a cost-effective manner [
23
].
2.2
Ethical Decision-Making
Ethical decision-making is the study of how to make the decisions with the information
that is available based on what one values [
12
]. It can be separated into idealized ethical
decision-making, focused on applying standard decision theory to ethical problems, and
practical ethical decision-making, focused on pragmatic approaches to ethical
decision-making that try to make idealized ethical decision-making more tractable and
applicable in real world contexts [
12
].
Idealized Ethical Decision-Making. In idealized ethical decision-making the behavior
of perfectly rational ethical agents is studied [
12
]. Due to the expansive body of
knowledge in this field and the length restrictions of this paper, we simply summarize
that idealized ethical decision-making consists of three general branches, namely,
epistemology (how to form beliefs given available evidence?), ethics (what is
valuable?), and decision theory (how to reach a decision given values and believes?)
[
12
]. EA advocates for the study of idealized ethical decision-making to inform and
guide practical ethical decision-making.
Practical Ethical Decision-Making. In practical ethical decision-making, decisions
are generally structured in terms of problems, interventions, and focus areas [
12
]. A
problem is something true about the world, which, if it stopped being true, would
improve the world [
12
]. For example, “people dying from malaria” would be a problem.
Interventions are attempts to solve or make progress on problems [
12
]. For example,
“distribution of bednets” would be an intervention aimed at solving “people dying from
malaria”. A focus area is a bundle of (inter)related problems that make up a broad field
of inquiry [
12
]. For example, “global health” would be a focus area, which would
include the problem “people dying from malaria” but also other related problems such
as “people suffering from neglected tropical diseases”.
The benefit of distinguishing between problems, interventions, and focus areas is
that it allows for a structured approach to identify the best opportunities for doing good.
Given the vast range of opportunities out there and the limited amount of resources
available, it is necessary to engage in some form of triage or prioritization. Assessing
the relevance of focus areas allows for a rough mapping of the overall problem space
in terms of likelihood of containing great opportunities for doing good, which, in turn,
allows for the prioritization of more in-depth investigations and engagement.
Importantly, EA strives to be cause neutral and is open to focus on any focus area as
long as it is likely to lead to cost-effective ways to improve the world [
14, 25
].
To facilitate this assessment of focus areas, the importance, tractability,
neglectedness, (ITN) framework has emerged as a useful tool within the EA movement
[
12
]. The ITN framework holds that a focus area is more likely to contain great
opportunities for doing good the more important (the more important the problem, the
higher the payoff), tractable (the more tractable the problem, the less resources need to
be invested), and neglected (the more neglected the problem, the higher is the expected
marginal utility of additional resources) it is. The three aspects are defined by the
following questions [
12
]:
• Importance: What is the scale of problems in the area? If all problems in the area
could be solved, how much better would the world be?
• Tractability: How solvable are the problems in this area?
• Neglectedness: How much is already being done in this area?
These questions can then be assessed, either, qualitatively or quantitatively, which
allows for a very rough estimation of the expected value of directing additional
resources into a focus area. Given the recognition of marginal utility [
26
] assessments
of focus areas are highly context specific and may change over time. At the moment,
mainstream thinking in EA generally recognizes three major focus areas on which the
movement as a whole is focusing, namely, global poverty and health, animal welfare,
and improving the long-term future [
27
]. However, personal fit and obligations may
rightfully push individual EAs or subgroups within EA to engage in and explore other
focus areas [
28
].
On the level of specific interventions, practical ethical decision-making is generally
built around cost-effectiveness or cost-benefit estimates. When faced with resource
constraints investing resources cost-effectively is simply the most effective thing to do.
A challenging topic in cost-effectiveness analyses is the inherent uncertainty but
overwhelming importance of long-term consequences [
18, 19
]. Within EA there is
currently no consensus on how to solve this challenge. Thus, personal judgements
become an important factor in choosing the most promising interventions [
28
].
3
What We Can Learn from Effective Altruism
Although we have only had space to present some of the basic ideas and considerations
of EA, we hope to have convinced the reader that it provides a thought-provoking lens
onto the world when compared to mainstream thinking in IS. This is not surprising,
whereas IS research emerged from pragmatic concerns with how to understand and deal
with people interacting with IT in business contexts [
2
], EA is specifically focused on
how to have a positive impact in the world [
7
]. Consequently, if IS research is striving
to increase its positive impact on the world [
5
], it seems only prudent to reflect upon
and adopt from the body of knowledge which is already available in EA. For this paper,
we have chosen to discuss two major ideas from EA, which seem especially relevant
for IS research to consider, namely, shared goals, principles and measures, and cause
neutrality and focus areas.
3.1
Shared Goals, Principles and Measures
EA movement growth is grounded in an ongoing concern with and support of
community development, which includes, but is not limited to, the development and
institutionalization of shared goals, principles and measures [
7, 8, 11
]. For example,
as Walsham [
6
] wished for IS, EA has been built around a strongly shared ethical
agenda focused on a single core goal [
7, 27
]: do the most good with the resources that
are available. Moreover, a set of shared principles (i.e., engagement for others,
scientific mindset, openness, integrity, and collaborative spirit) is prominently being
held up by major institutions in the movement [
8
] and openly celebrated at major EA
conferences. Finally, united by the common goal of finding ways to do the most good
and guided by the shared principles, EAs find it in their own best interest to develop,
establish, and update shared measures to be able to better understand, benchmark and
compare how they can do the most good [
11, 29
].
We posit that these three facets are major parts of a shared identity of EA that enables
a diverse set of people and institutions to critically but constructively engage,
coordinate, and cooperate in a wide range of focus areas. In our opinion, EA is a living
example of how shared goals, principles and measures can create a movement-wide
bond and trust that fosters cooperation even among only loosely connected individuals.
For example, it is not uncommon for EAs to personally work on one focus area where
they have expertise (or simply earn-to-give) and support work on other focus area
financially because they share the same goal and can assess and value the work done
by other EAs (e.g., due to shared measures and benchmarks). Furthermore, in such an
environment, multiple perspectives, theories, and research approaches can all coexist
and thrive if they can demonstrate in how far they address concerns which have not yet
been captured or solved by existing work because everyone is working towards the
same goal. For instance, population ethics is a highly-contested field in which several
theories co-exist but none seem completely satisfactory [
30
]. This has given rise to
several approaches that try to deal with this challenge, including the novel extension of
ethical decision-making to the conditions of moral uncertainty [
12
]. There is simply no
gain in rejecting novel or unusual approaches on nebulous grounds if they demonstrate
utility for reaching one’s own goals.
Translated to IS research this provides evidence for the view held by Walsham [
6
]
that a strong ethical agenda could provide the foundation for a more cooperative, and
impact-driven field. Moreover, EA presents us with an example of important aspects
that such a field should clarify and provide (i.e., shared goals, principles and measures).
This insight complements recent work on a systematic high impact research model
(SHIR) [
31
] which elaborated on how to build high impact IS research programs.
Whereas SHIR focuses on how to conduct a specific research program, we highlight
the importance of shared goals, principles and measures for coordinating and
prioritizing between possibly diverse research programs. For example, the article on
SHIR presents three high-impact research programs but does not attempt to quantify or
compare impact. This is not surprising because it is very challenging to compare the
impact of research programs if there are no readily shared measures between them. To
overcome this challenge, IS researchers could be advised to link their work to the UN
Sustainable Development Goals (SDG) [
32
] or human well-being [
29
] as broad
frameworks for assessing ethically-valuable impact. This could be a first step towards
more broadly shared goals, principles and measures in IS research.
3.2
Cause Neutrality and Focus Area Selection
The idea of cause neutrality and a focus on systematic, evidence-based focus area
selection is another corner stone of the EA movement which IS research may adopt and
benefit from. Cause neutrality describes the stance that no cause (i.e., focus area) is by
any rule, definition or dogma more important than any other cause, only the
consequences of working on a cause should determine our actions [
8, 12, 14, 25
]. The
benefits of cause neutrality include that it enables the most effective use of resources
[
25
] as well as that it creates an expectation of constant adaptation and reprioritization
as new evidence is assimilated and views are updated. We argue that this facilitates
more effective coordination between individual interests as cause neutrality presents a
rational avenue to discuss allocation conflicts and mediate between them.
On the practical side of cause neutrality, EA has generally taken to the ITN
framework (see section 2.2) to operationalize cause neutral focus area selection. Similar
to how it is used in EA, the ITN framework could be used to guide IS research to focus
areas where it will likely have the biggest impact. More interestingly, even results from
its current application in EA [
27, 33
] could already be useful to IS as focus areas with
high-expected value for EAs are also likely to be focus areas where IS could have an
impact. For example, the EA focus area of global health and development provides
ample opportunities for impactful IS research (e.g., [
34
]) that can potentially improve
the lives of millions at comparatively low costs. The same goes for the other EA focus
areas, animal welfare (e.g., IS research could aim to reduce the amount of suffering
caused by factory farming), and improvement of the long-term future (e.g., IS research
could aim to improve institutional decision making and coordination with novel
ITartifacts).
Altogether, insights from EA suggest that reconsidering focus areas in IS could
substantially increase the impact of research. Although business organizations have
been the starting point for IS research [
1, 2
], it need not be its destiny. While several
researchers and initiatives have made moves towards expanding the scope and mission
of IS research [
35–37
], there is so far no clear conceptual foundation for comparing and
choosing between specific directions and focus areas in IS research. Thus, specific
initiatives may largely be directed by ambient factors such as social capital of the
researchers involved or current trends in other fields and less in logical reason and
expected value in any ethical sense. As discussed, the ITN framework can usefully
inform future IS research on how to maximize impact by focusing on the most pressing
challenges.
4
Discussion and Outlook
In this paper, we have considered EA as a reference discipline that demonstrates the
feasibility and utility of a strong ethical agenda for IS research [
6
]. We contribute to the
discourse around IS impact and identity by identifying key considerations that
impactdriven IS research should reflect upon and highlight were the existing body of
knowledge in EA may usefully inform such research. Importantly, applying EA
concepts and ideas could help IS research convert its latent comparative advantage in
investigating and shaping IT-related phenomena into often missed “real world” impact
[
6, 31
] by focusing on the most ethically-valuable opportunities. Examples for
potentially highly impactful IS topics from an EA perspective are: governance for the
save development of AGI or IS to improve institutional decision-making.
However, our work is not without limitations. While we have started to engage with
the considerations we identified, future research is needed to further investigate
possible implications for IS research and flesh out more concrete strategies of action.
Moreover, due to space limitations, we could only touch on but not fully unpack what
EA can offer to IS research. The interested reader is invited to investigate the cited
sources to get an in-depth understanding of the topic. Future research should provide
more in-depth examples and discussions to make the topic more approachable.
Considering these possibilities and limitations, we encourage other researchers to
work with us towards realizing IS research’s full potential to do good in the world. Next
steps could include, but are not limited to:
• more open discussions of core goals and values of IS research (e.g., does IS research
have a moral obligation to strive for the realization of its full potential to do good?),
• the investigation and adaptation of shared measures to IS research (e.g., investigate
if the SDG [
32
] or well-being [
29
] can be used as frameworks to compare different
focus areas, for instance, “health IT” vs. “fintech” vs. “green IT”), or
• a comprehensive application of the ITN framework to focus areas of IS research
(e.g., are there focus areas with much higher expected ethical-value than others?).