RESEARCH ARTICLE Open Access
Overcoming Barriers to Cross-cultural Cooperation
in AI Ethics and Governance
Seán S. ÓhÉigeartaigh1,2&Jess Whittlestone1&Yang Liu1,2&Yi Zeng2,3&
Zhe Liu2,4
Received: 3 January 2020 /Accepted: 22 April 2020
#The Author(s) 2020
Abstract
Achieving the global benefits of artificial intelligence (AI) will require international
cooperation on many areas of governance and ethical standards, while allowing for
diverse cultural perspectives and priorities. There are many barriers to achieving this at
present, including mistrust between cultures, and more practical challenges of coordi-
nating across different locations. This paper focuses particularly on barriers to cooper-
ation between Europe and North America on the one hand and East Asia on the other,
as regions which currently have an outsized impact on the development of AI ethics
and governance. We suggest that there is reason to be optimistic about achieving
greater cross-cultural cooperation on AI ethics and governance. We argue that misun-
derstandings between cultures and regions play a more important role in undermining
cross-cultural trust, relative to fundamental disagreements, than is often supposed. Even
where fundamental differences exist, these may not necessarily prevent productive
cross-cultural cooperation, for two reasons: (1) cooperation does not require achieving
agreement on principles and standards for all areas of AI; and (2) it is sometimes
possible to reach agreement on practical issues despite disagreement on more abstract
values or principles. We believe that academia has a key role to play in promoting
cross-cultural cooperation on AI ethics and governance, by building greater mutual
understanding, and clarifying where different forms of agreement will be both neces-
sary and possible. We make a number of recommendations for practical steps and
initiatives, including translation and multilingual publication of key documents, re-
searcher exchange programmes, and development of research agendas on cross-cultural
topics.
Keywords Artificial intelligence .AI ethics .AI governance .Cross-cultural cooperationhttps://doi.org/10.1007/s13347-020-00402-x
Seán S. ÓhÉigeartaigh and Jess Whittlestone contributed equally to this work.
*Seán S. ÓhÉigeartaigh
so348@cam.ac.uk
Extended author information available on the last page of the articlePhilosophy & Technology (2020) 33:571 –593
/Publishedonline:15May2020
1 Introduction
Artificial intelligence has been identified as a key suite of technologies for many
countries worldwide, in large part motivated by its general-purpose nature
(Brynjolfsson and McAfee 2014 ). AI technologies, and machine learning techniques
in particular, are being fruitfully applied to a vast range of domains, including language
translation, scientific research, education, logistics, transport and many others. It is clear
that AI will affect economies, societies and cultures profoundly at a national, interna-
tional and global level. This has resulted in increasing attention being paid to both AI
ethics: questions about how we should develop and deploy AI systems, given their
potential impact on wellbeing and other deeply held values such as autonomy or
dignity; and to AI governance: the more practical challenge of ensuring the ethical
use of AI in society, be that through regulation, governance frameworks, or ‘softer ’
approaches such as standards and ethical guidelines.1
Cross-cultural cooperation will be essential for the success of these ethics and
governance initiatives. By ‘cross-cultural cooperation ’, we mean groups from different
cultures and nations working together on ensuring that AI is developed, deployed, and
governed in societally beneficial ways. In this paper, we focus in particular on
cooperation extending across national boundaries. Examples include (but are not
limited to) the following: AI researchers from different countries collaborating on
projects to develop systems in safe and responsible ways; establishing networks to
ensure that diverse global perspectives can feed equally into international discussions
about the ethical issues raised by AI; and involving a range of global stakeholders in the
development of practical principles, standards, and regulation. By encouraging cross-
cultural cooperation, we do not necessarily mean that all parts of the world should be
subject to the same norms, standards, and regulation relating to AI, or that international
agreement is always needed. Identifying which issues will need global standards or
agreements, and where more cultural variation is needed, is itself a key challenge that
will require cooperation to address.
Cross-cultural cooperation is important for several reasons. First, cooperation will be
essential if AI is to bring about broad benefits across societies globally, enabling
advances in one part of the world to be shared with other countries, and ensuring that
no part of society is neglected or disproportionately negatively impacted by AI. Second,
cooperation enables researchers around the world to share expertise, resources, and best
practices. This enables faster progress both on beneficial AI applications, and on
managing the ethical and safety-critical issues that may arise. Third, in the absence of
cooperation, there is a risk that competitive pressures between states or commercial
ecosystems may lead to underinvestment in safe, ethical, and socially beneficial AI
development (Askell et al. 2019 ; Ying 2019 ). Finally, international cooperation is also
important for more practical reasons, to ensure that applications of AI that are set to
cross-national and regional boundaries (such as those used in major search engines or
1AI ethics and governance are closely related: governance proposals are often a practical response to
recognized ethical issues, and ethical frameworks can be an important starting point for developing policy
and regulation. Especially as AI ethics becomes more practical —developing principles and guidelines around
the ethical use of AI in society —it starts to blend into some of the ‘softer ’governance approaches. Throughout
this chapter, we will therefore often use ‘AI ethics and governance ’as a broad term to refer to the whole
process of identifying ethical issues, codifying them, and implementing them through governance measures.S. S. ÓhÉigeartaigh et al. 572
autonomous vehicles) can interact successfully with a sufficient range of different
regulatory environments and other technologies in different regions (Cihon 2019 ).
Drawing on the insights of a group of leading scholars from East Asia and Europe,2
we analyse current barriers to cross-cultural cooperation on AI ethics and governance,
and how they might be overcome. We focus on cooperation between Europe and North
America on the one hand and East Asia on the other. These regions are currently
playing an outsized role in influencing the global conversation on AI ethics and
governance (Jobin et al. 2019 ), and much has been written recently about competition
and tensions between nations in these regions in the domains of AI development and
governance, especially in the case of China and the USA. However, our discussion and
recommendations have implications for broader international cooperation around AI,
and we hope they will spur more attention to promoting cooperation across a wider
range of regions.
As AI systems become more capable and their applications more impactful and
ubiquitous, the stakes will only get higher. Establishing cooperation over time may
become more difficult, especially if cross-cultural misunderstandings and mistrust
become entrenched in intellectual and public discussions. If this is the case, then the
earlier a global culture of cooperation can be established, the better. Cultivating a
shared understanding and deep cooperative relationships around guiding the impacts of
AI should therefore be seen as an immediate and pressing challenge for global society.
2 The Role of North America, Europe, and East Asia in Shaping
the Global AI Conversation
North America, Europe, and East Asia in particular are investing heavily in both
fundamental and applied AI research and development (Benaich and Hogarth 2019 ;
Haynes and Gbedemah 2019 ;P e r r a u l te ta l . 2019 ) ,s u p p o r t e db yc o r p o r a t ea n d
government investment. Various analyses have framed progress on the development
and deployment of AI between the USA and China in particular through a competitive
lens (Simonite 2017 ; Allen and Husain 2017 ;S t e w a r t 2017 ), though this framing has
received criticism both on normative and descriptive grounds (Cave and ÓhÉigeartaigh
2018 ).
Scholars and policy communities in these regions are also taking deliberate and
active steps to shape the development of ethical principles and governance recommen-
dations for AI, both at a regional and global level. This is reflected in government-
linked initiatives, such as the activities of the European Union ’s High-Level Expert
Group on Artificial Intelligence, which has produced ethics guidelines and policy and
2W ec o n v e n e daw o r k s h o po nc r o s s - c u l t u r a lt r u s ti nJ u l y2 0 1 9( https://www.eastwest.ai/ ), with
representatives from UK universities (Cambridge, Bath) as well as from Chinese and Japanese universities
and initiatives (Universities of Hong Kong, Peking, Fudan, Keio, and the Berggruen Institute China Center
and the Chinese Academy of Sciences). These representatives have been heavily involved in AI ethics and
governance conversations and collaborative projects across Europe, North America, and Asia. This paper
draws on insights from this workshop, which focused particularly on the role of academia in building cross-
cultural trust in AI. We do not suggest that the regions represented are the only ones that matter in this
conversation, nor that the members present can be considered to represent the diversity of views and expertise
in the regions they are based in. However, we feel that this small step in establishing a network was of value,
and generated useful insights and ground to build on. The workshop was held under Chatham House Rule.Overcoming Barriers to Cross-cultural Cooperation in AI Ethics and... 573
investment recommendations as its first two publications3; the UK Government ’s
commitments to ‘work closely with international partners to build a common under-
standing of how to ensure the safe, ethical and innovative deployment of Artificial
Intelligence ’(May 2018 ); and the Chinese Government ’s similar commitment to
‘actively participate in global governance of AI, strengthen the study of major interna-
tional common problems such as robot alienation and safety supervision, deepen
international cooperation on AI laws and regulations, international rules ’(China State
Council 2017 ). North America, Europe, and East Asia are each also contributing
disproportionately towards international AI standards work ongoing in fora such as
the International Organization for Standardization (ISO),4the Institute of Electrical and
Electronics Engineers (IEEE),5and the Organization for Economic Co-operation and
Development (OECD).6
The prominence of North America, Europe, and East Asia is further seen in the
leadership and composition of multi-stakeholder and nongovernmental initiatives such
as the Partnership on AI,7the Future Society,8the International Congress for the
Governance of AI,9and the Global Partnership on AI (Hudson 2019 ).10A large
majority of the most prominent conferences on AI ethics and governance have taken
place in these regions, including the US-based Beneficial AI conference series,11the
Beijing Academy of AI Conference series,12the Beijing Forum,13the US-based
Artificial Intelligence, Ethics, and Society conferences,14governance and ethics work-
shops attached to the leading machine learning conferences, and many more.
This combination of:
a. technological leadership in North America, Europe, and East Asia;
b. the outsized role of these regions in shaping the global ethics and governance
conversation; and
c. the underlying tension introduced by progress being framed through a competitive
lens, and a perception of disagreements on fundamental ethical and governance
issues
leads us to focus on the barriers that exist to productive intellectual exchange and
cooperation between these regions and cultures in particular. A full analysis of cross-
3Available here: https://ec.europa.eu/digital-single-market/en/high-level-expert-group-artificial-intelligence
4North American, European, and East Asian countries account for 22 out of 28 participating countries in the
AI standards committee ( https://www.iso.org/committee/6794475.html )
5E.g. see committee membership of the IEEE ’sEthically Aligned Design AI principles document:
https://standards.ieee.org/content/dam/ieee-standards/standards/web/documents/other/ec_bios.pdf
6E.g. see participant membership of the OECD Expert Group on AI (AIGO) https://www.oecd.org/going-
digital/ai/oecd-aigo-membership-list.pdf
7https://www.partnershiponai.org/partners/
8https://thefuturesociety.org/our-team/
9https://icgai.org/icgai-members/
10Formerly the International Panel on AI, initiated by Canada and France (not to be confused with the
Partnership on AI) ( https://www.canada.ca/en/innovation-science-economic-development/news/2019/05
/declaration-of-the-international-panel-on-artificial-intelligence.html )
11https://futureoflife.org/beneficial-agi-2019/
12https://mp.weixin.qq.com/s/tAGOoqqA6ods9uaigWE7uA
13http://newsen.pku.edu.cn/news_events/news/global/9133.htm
14https://www.aies-conference.com/2020/S. S. ÓhÉigeartaigh et al. 574
cultural cooperation on AI ethics and governance, which is outside the scope of this
paper, must consider the roles of all nations and cultures, given that the domain of
impact of AI technologies is truly global. It will be particularly important for further
work to address the inequalities in power and influence that are emerging between
technology-leading nations and those to which these technologies are being exported
(Lee 2017 ), and the responsibility of technology-leading nations to include and em-
power those nations in global governance and ethics conversations.
3 Barriers to Cross-cultural Cooperation on AI
Despite the emergence of several international alliances in AI ethics and governance,
many barriers remain to achieving real cross-cultural cooperation on the norms,
principles, and governance frameworks that should guide how AI is developed and
used.
Mistrust between different regions and cultures is one of the biggest barriers to
international cooperation in AI ethics and governance. At present, there is a particular
environment of mistrust between scholars, technologists, and policymakers in the USA
and China.15This culture of mistrust is underpinned by both:
a. a history of political tensions between these two powerful regions that has
increased significantly in recent years, and is currently contributing to the compet-
itive framing of AI development as a ‘race’between ‘Eastern ’and‘Western ’
nations.16
and
b. the divergent philosophical traditions upon which these regions are founded,
leading to a perception of significant and irresolvable value differences between
‘Western ’and‘Eastern ’cultures on key issues such as data privacy (Larson 2018 ;
Horowitz et al. 2018 ;H o u s e r 2018 ).
A range of recent technological and political developments may also be contributing to
this mistrust, including concerns about the public and political influence of technology
giants in the USA (Ochigame 2019 ); perceptions of and reactions to the Chinese Social
Credit score system (Chorzempa et al. 2018 ;S o n g 2019 ); and concerns about conten-
tious uses of AI technologies, with notably controversial examples including the use of
AI in immigration control (Whittaker et al. 2018 ), criminal risk assessment in the USA
(Campolo et al. 2017 ), and in tracking communities such as the Uighur Muslim
15This perception of mistrust was highlighted throughout the July workshop. Several participants reported
being aware of or present at workshops focused on geopolitical implications of Chinese AI progress in which
Chinese participants were excluded and events at which ‘what should be done about China ’(from a Western
perspective) was raised as a key concern.
16As Ess ( 2005 ) notes, the terms ‘Eastern ’and‘Western ’are not unproblematic, and are more products of
colonialization than accurate terms for diverse nations and cultures. However, the terms continue to be used
widely in the literature as shorthand for many of the broad cultural differences that are relevant to this paper;
we therefore use the terms while being cognisant of their limitations.Overcoming Barriers to Cross-cultural Cooperation in AI Ethics and... 575
minority in China (Mozur 2019 ). Adversarial rhetoric from political and defence
leaders in the USA also contributes to this tension. Recent examples reported in the
media include stating intentions to ‘be the threat ’of AI17; comments focused on the
‘otherness ’of China as an adversary,18amid broader concerns regarding Chinese
technological progress as a threat to US global leadership (Jun 2018 ). A continued
exacerbation of this culture of mistrust could severely undermine possibilities for global
cooperation on AI development and governance.
In addition, it is unclear how far existing cross-cultural collaborations and alliances
can go to shape the behaviour of actors that are as globally dominant as the USA, China,
and the large multinational corporations based in these countries. Even if AI ethics
frameworks can be agreed on in principle by multi-stakeholder groups, for example, it
will be far from straightforward to implement them in practice to constrain the behaviour
of those with disproportionate power to shape AI development and governance.
Another challenge for effective cooperation is balancing the need for global coop-
eration with the need for culturally and geographically sensitive differentiated ap-
proaches (Hagerty and Rubinov 2019 ). It is crucial we avoid a situation where one
or two nations simply try to impose their values on the rest of the world (Acharya
2019 ). In certain specific domains, for example where AI is being used to support the
delivery of healthcare, different cultures may perceive tradeoffs very differently
(Feldman et al. 1999 ), and it may be not just possible but necessary to implement
region-specific standards and governance. AI systems will also have different impacts
as they are deployed in different cultural regions, which may also require different
governance approaches (Hagerty and Rubinov 2019 ).
For some aspects of AI development and governance, however, cooperation will be
much more crucial. For example, some potential uses of AI technologies in military
contexts, such as in automated targeting and attack, could impinge upon human rights
and international humanitarian law (Asaro 2012 ). Another concern is that by automat-
ing aspects of information gathering, decision-making, and response in military arenas,
the potential for unwanted escalation in conflict situations may increase due to events
occurring and requiring responses faster than is compatible with effective human
judgement and oversight (Altmann 2019 ). In both these cases, there may be individual
military advantages to nations pursuing the technology; but in the absence of interna-
tional agreements and standards, the overall effect may be destabilizing.19International
agreement will also be of particular importance for all cases in which AI technologies
are developed in one region, but used or deployed in a different region. A key challenge
for cross-cultural cooperation will therefore be to identify the areas where international
agreement is most important, and distinguish these from areas where it is more
appropriate to respect a plurality of approaches.
17‘Plenty of people talk about the threat from AI; we want to be the threat. ’US Deputy Secretary of Defence
Patrick Shanahan in an email to Department of Defence employees (Houser 2018 )
18At a security forum in Washington D.C. in 2019, Kiron Skinner, the director of policy planning at the State
Department, was quoted as saying about China ‘This is a fight with a really different civilization and a
different ideology and the United States has not had that before ’and‘It’s the first time that we will have a great
power competitor that is not Caucasian ’(Gehrke 2019 ).
19Similarly, a range of challenges in digital security, a domain likely to be affected by AI (Brundage et al.
2018), are likely to be greatly exacerbated in the absence of agreed upon international cybersecurity practices
and standards (UN General Assembly 2015 ).S. S. ÓhÉigeartaigh et al. 576
There are also more practical barriers to cooperation between nations: language
barriers, lack of physical proximity, and immigration restrictions put limits on the
ability of different cultures and research communities to communicate and collaborate.
Furthermore, despite science being a global enterprise, the language of scientific
publication remains predominantly English.
4 Overcoming These Barriers to Cooperation
While cross-cultural cooperation in AI ethics and governance will be genuinely
challenging, we suggest that there are steps that can be taken today to make progress,
without first needing to tackle the greater problems of finding consensus between
cultures on all fundamental ethical and philosophical issues, or resolving decades of
political tension between nations.
4.1 Building Greater Mutual Understanding, Including Around Disagreements
Mistrust between nations is a serious concern for the future of AI ethics and gover-
nance. However, we suggest that this mistrust is at least partly fuelled by misunder-
standings and misperceptions, and that a first step towards building greater cross-
cultural trust must therefore be to identify and correct important misperceptions, and
enhance greater mutual understanding between cultures and nations.
It would be easy to assume that the main barrier to building trust between East and
West around AI is that these regions of the world have very different fundamental
values, leading them to different —perhaps conflicting —views of how AI should be
developed, used, and governed from an ethical perspective. While value differences
between cultures certainly exist, claims about how those differences manifest often
depend on unexamined concepts and entrenched assumptions, and lack empirical
evidence (Whittlestone et al. 2019 ). The idea that ‘Eastern ’and‘Western ’ethical
traditions are fundamentally in conflict also oversimplifies the relationship between
the two. There are many different philosophical traditions that might be referred to
under either heading: there are, for example, many important differences between
relevant philosophical perspectives across China, Japan, and Korea (Gal 2019 ), and
the values and perspectives of ‘Western ’philosophy have changed a great deal over
time (Russell 1945 ). More broadly, ethical and cultural values in both regions are in
constant evolution, as captured by projects such as the World Values Survey20and the
Asian Barometer.21
Differences in ethical and cultural traditions and norms across regions are often
assumed to underpin contrasting governance approaches. For example, privacy is often
seen as an issue for which significant value differences exist between East and West,
leading to a perception that laxer regulation and controls exist on data privacy in China
compared with the USA and Europe. However, such claims are often made in very
broad terms, without substantive evidence or analysis of how significant these differ-
ences are or how they manifest in practice (Ess 2005 ; Lü Yao-Huai 2005 ). This leads to
20http://www.worldvaluessurvey.org/wvs.jsp
21http://www.asianbarometer.org/Overcoming Barriers to Cross-cultural Cooperation in AI Ethics and... 577
misunderstandings in both directions. First, there are significant differences between
the USA and Europe on both conceptions of privacy (Szeghalmi 2015 ) and regulations
that relate to privacy (McCallister et al. 2018 ). These are often missed in Chinese
perceptions of Western societies, which tend to focus just on the USA.22Second,
Western perceptions of data privacy in China may be outdated: Lü Yao-Huai ( 2005 )
highlighted as early as 2005 that the relevant literature on information ethics was much
younger in China than in the USA, but was evolving quickly and in a manner
significantly informed by Western scholarship. A range of papers and reports from
Chinese scholars and policymakers have highlighted the importance of data privacy in
AI ethics and governance (Beijing Academy of Artificial Intelligence 2019 ; Ying 2019 ;
Zeng et al. 2018 ;D i n g 2018b ). Principles around protecting individuals ’data privacy
are also beginning to be borne out in regulatory action in China; over 100 apps have
been banned by the government for user data privacy infringements, with dozens more
being required to make changes relating to data collection and storage.23This is not to
suggest that there are not meaningful differences in values, norms, and regulations
relating to data privacy between these countries, but that such differences have often
been oversimplified and are not well understood.
Another example of differing perceptions are those surrounding China ’ss o c i a lc r e d i t
score (SCS) system. The SCS has been discussed with great concern in Western media,
policy circles, and scholarship, and presented as an example of Orwellian social control
by the Chinese government (Botsman 2017 ; Pence 2018 ), representative of a culture
and government with profoundly different values to the West (Clover 2016 ). However,
both Chinese and Western sources have argued that there are significant misunder-
standings surrounding the SCS. Multiple scholars have pointed out that the SCS is not
designed to be a single unified platform that rates all 1.4 billion Chinese citizens (as is
often supposed), but rather a web of individual platforms with latitude for different
interpretations, with social credit scores mostly given by financial institutions (as
opposed to a big data-driven comprehensive rating) (Mistreanu 2019 ; Sithigh and
Siems 2019 ). Song ( 2019 ) notes that many of the measures in the SCS are designed
to tackle issues such as fraud and corruption in local government. Chorzempa et al.
(2018 ) also highlight that ‘many of the key components of social credit, from blacklists
to widespread surveillance …already exist in democracies like the United States. ’
China ’s SCS is likely to evolve significantly over time, and there are likely to be
genuine reasons for concern both in terms of present and future implementation.
However, a much clearer cross-cultural understanding of how the SCS works, is being
used, and is impacting Chinese citizens, would allow dialogue on relevant ethics and
governance issues to progress more constructively.
Given the lack of shared knowledge and discourse that has existed historically
between regions such as the USA, Europe, and China, it is not surprising that many
22This was a misperception noted by multiple Chinese scholars at the aforementioned July workshop.
23In November 2019, the Chinese Ministry of Public Security banned 100 apps that failed to meet standards
on individuals ’data privacy; the body has investigated 683 apps in 2019 (National Cyber Security Advisory
Centre 2019 ). In addition, in December 2019, the Chinese Ministry of Industry and Information Technology
released a list of 41 apps that would have to make changes to comply with data regulations by the end of 2019
(Ministry of Industry and Information Technology of the People ’s Republic of China 2019 ). In July 2018,
China ’s Shandong Province brought a major case relating to infringement of personal information against 11
companies (Ding 2018c ).S. S. ÓhÉigeartaigh et al. 578
misperceptions exist between them. We should therefore be wary of jumping too
quickly to assume intractable and fundamental disagreements. Misunderstandings
clearly exist in both directions: analyses of public opinion survey data suggest, for
example, that both American and Chinese populations hold various misperceptions
about the other nation ’s traits and characteristics (Johnston and Shen 2015 ). As
mentioned above, in China, the diversity of Western societies is also often
oversimplified down to a single pattern of American life. At the same time, the USA
and Europe have historically struggled to understand China (Chen and Hu 2019 ),
evidenced for example by repeated failures to predict China ’s liberalization (or lack
thereof) or periods of economic growth (The Economist 2018 ;C o w e n 2019 ;L i u 2019 ).
Language barriers present a particular difficulty for Western nations in gleaning what is
happening in China in terms of AI development, ethics, and governance (Zhang 2017 ;
Ding 2019 ). As Andrew Ng points out in a 2017 interview in the Atlantic: ‘The
language issue creates a kind of asymmetry: Chinese researchers usually speak English
so they have the benefit of access to all the work disseminated in English. The English-
speaking community, on the other hand, is much less likely to have access to work
within the Chinese AI community ’(Zhang 2017 ). For example, Tencent released a
book on AI strategy (Tencent Research Institute et al. 2017 ) which includes deep
analysis of ethics, governance, and societal impacts, but has received relatively little
English-language coverage (Ding 2018a ). Even on empirical matters such as level of
Chinese public investment in AI research and development, widely reported figures in
the USA may be inaccurate by an order of magnitude (Acharya and Arnold 2019 ).
The recently published Beijing AI Principles (Beijing Academy of Artificial
Intelligence 2019 ) and similar principles developed around the world (Cowls and
Floridi 2018 ) in fact show substantial overlap on key challenges (Zeng et al. 2018 ;
Jobin et al. 2019 ). The Beijing Principles make clear reference to the key concepts and
values which have been prominent in other documents, including that AI should
‘benefit all humankind ’; respect ‘human privacy, dignity, freedom, autonomy and
rights ’;a n db e ‘as fair as possible, reducing possible discrimination and biases,
improving its transparency, explainability and predictability. ’In addition, both the
Beijing AI Principle s, and the National Governance Principles of the New AI, China ,
call for openness and collaboration, with the latter encouraging ‘cooperation across
disciplines, domains, regions, and borders ’(Laskai and Webster 2019 ). However,
nations with different cultures may interpret and prioritize the same principles differ-
ently in practice (Whittlestone et al. 2019 ), which may be a further source of misun-
derstanding. We cannot simply assume, for example, that ‘Western ’cultures value
privacy more highly than ‘Eastern ’ones; instead, we need a more nuanced understand-
ing of how privacy may be prioritized differently when it comes into conflict with other
important values, such as security (Capurro 2005 ). Similarly, although it is important to
recognize that many cultures value autonomy, it is equally important to understand the
different connotations and philosophical assumptions underpinning this value in dif-
ferent contexts (Yunping 2002 ).
Given the rich history of misunderstanding between nations, to build greater cross-
cultural cooperation, we should start by focusing on identifying those misperceptions
most relevant to AI ethics and building greater mutual understanding of where more
substantive disagreements exist and are likely to impact governance approaches. In
doing so, it is worth distinguishing explicitly between disagreements pertaining toOvercoming Barriers to Cross-cultural Cooperation in AI Ethics and... 579
ethics as opposed to governance issues, since it may sometimes be possible for groups
to agree on the same governance principles despite justifying them with different
ethical assumptions, as we will discuss later. It may also be helpful to distinguish
between misunderstandings that pertain directly to AI (such as misperceptions of other
countries ’investment in technology, or misinterpretation of data protection laws) and
those that pertain to broader societal, political, or philosophical matters that are more
indirectly relevant to AI, as they may require different approaches to resolve.
Acknowledging the role of misunderstandings does not, of course, imply that all
matters of intercultural tension in AI ethics and governance are fundamentally based on
misunderstandings. Deep and fundamental disagreements across regions will remain on
a range of issues, including those relating to the relationship between the individual,
society, and the state; the level and nature of integration between civil, private, and
military sectors; and various specific matters of social policy. However, focusing
initially on reducing misunderstandings will aid in establishing more clearly where
these fundamental differences exist, while at the same time identifying contexts in
which sufficient agreement exists for fruitful cooperation. Doing so is a crucial first step
towards addressing the broader challenges of cross-cultural cooperation on AI ethics
and governance.
4.2 Finding Ways to Cooperate Despite Disagreements
Even where important differences of view on AI ethics, governance, and broader
societal issues exist, forms of agreement and cooperation can still be possible.
As mentioned earlier, a key outstanding challenge for AI ethics and governance is
identifying those areas where cross-cultural agreement on norms, standards, or regula-
tion is crucial, and where different interpretations and approaches are acceptable or
even desirable. This is precisely the kind of challenge which itself requires cross-
cultural cooperation: the delineations must be informed by diverse cultural perspectives
on the impacts of AI in different contexts, and the needs and desires of different
populations. Indeed, this approach is reflected in the National Governance Principles
of the New AI, China , which includes the recommendation to ‘Launch international
dialogue and cooperation; with full respect for each country ’s principles and practices
for AI governance, promote the formation of a broad consensus on an international AI
governance framework, standards, and norms ’(Laskai and Webster 2019 ).
Regional and cultural differences on the abstract level of ethical assumptions and
high-level principles are also not necessarily a barrier to agreement on more concrete
norms and governance. If it were impossible to reach any practical agreement without
consensus on fundamental ethical issues, many important international agreements —
such as the Nuclear Weapons Ban Treaty —would not have been possible. The notion
of an ‘incompletely theorized agreement ’in legal scholarship (Sunstein 1995 ), de-
scribes how it is often possible for people who disagree on fundamental or abstract
matters to nonetheless agree on specific cases —and that this is central to the function-
ing of law as well as of a pluralistic society more broadly. Several authors in the
literature on intercultural information ethics have promoted the related idea of aiming to
arrive at an ‘overlapping consensus ’(Rawls 1993 ), where different groups and cultures
may have different reasons for supporting the same norms and practical guidelines
(Taylor 1996 ; Søraker 2006 ; Hongladarom 2016 ). For example, Taylor ( 1996 )S. S. ÓhÉigeartaigh et al. 580
discusses how we have managed to ground internationally shared norms of human
rights in different cultural traditions. While Western philosophies differ substantially
from others such as Buddhism in how much importance they give to the human agent
and its unique place in the cosmos, both seem to end up grounding the same norms of
human rights.
Wong ( 2009 ) criticizes this idea that intercultural information ethics can arrive at
shared norms with different justifications, suggesting that this risks making norms too
‘thin’, devoid of all normative content. Søraker ( 2006 ) acknowledges a similar objec-
tion to this ‘pragmatic ’approach to information ethics: that it may result in agreements
that are fragile due to not being sufficiently grounded in substantive normative content.
However, in line with Søraker ’s own response to these objections, we believe that the
aim of ‘overlapping consensus ’should be to arrive at shared norms and practical
guidelines which are in fact more robust by virtue of being endorsed and justified from
a range of different philosophical or normative perspectives. This should be distin-
guished from a situation where one culture uses pragmatic arguments to attempt to
force their own values upon others, or where several cultures reach agreement but for
reasons with little normative content, which, we agree with Wong, would be
concerning. Taylor ’s example of human rights being supported by multiple philosoph-
ical perspectives appears to demonstrate the plausibility of this kind of well-
substantiated overlapping consensus.
Indeed, we suggest that finding areas of overlapping consensus on norms and
practical guidelines may be much more important for ensuring the benefits of AI than
aiming for global consensus on a shared set of fundamental values —an aim which
underpins many recent proposals.24Consensus on high-level ethical principles does not
necessarily mean they are well-justified (Benjamin 1995 ), and the best way to arrive at
more robustly justified norms, standards, and regulation for AI will be to find those that
can be supported by a plurality of different value systems.
4.3 Putting Principles into Practice
Even where it is possible to improve mutual understanding and arrive at shared
governance approaches in theory, some might object that it will still be difficult to
influence the development and use of AI in practice, especially since to do so requires
influencing the behaviour of powerful states and companies that have little incentive to
cooperate.
Although a full discussion of the complex power dynamics between states, compa-
nies, and other actors on issues relevant to AI ethics and governance is beyond the
scope of this paper (and worthy of further research), we briefly explain why we do not
think this barrier undermines our proposals. While challenging, historical precedent
suggests that it is possible for public and academic alliances to influence the behaviour
of powerful actors on issues of global importance. There is evidence to suggest that
broad, cross-cultural ‘epistemic communities ’—i.e. networks of experts in a particular
domain —can be particularly effective at supporting international policy coordination
24For example, Floridi et al., 2018 present a ‘unified framework ’; Awad et al. 2018 talk about ‘developing
global, socially acceptable principles for machine ethics ’; Jobin et al. 2019 set out to investigate ‘global
agreement ’on what constitutes ethical AI.Overcoming Barriers to Cross-cultural Cooperation in AI Ethics and... 581
(Haas 1992 ). For example, a community of arms control experts helped shape coop-
eration between the USA and Russia during the Cold War by creating an internationally
shared understanding of the problem of nuclear arms control (Adler 1992 ), and the
ecological epistemic community managed to successfully coordinate national policies
to protect the stratospheric ozone layer (Haas 1992 ).
The commitments of large companies and even nations around AI have already been
influenced by combinations of employee activism, international academic research, and
campaigning. A notable example is in the application of AI in military contexts.
Concerns over the use of AI in warfare have been the subject of high-profile campaigns
by experts across academia and civil society internationally, such as those involved in
the International Committee for Robot Arms Control (ICRAC) and the Campaign to
stop Killer Robots. These campaigns played a leading role in establishing discussion on
lethal autonomous weapons (LAWs) at the United Nations Convention on Certain
Conventional Weapons (CCW; the body that hosted negotiations over the banning of
cluster munitions, blinding laser weapons, and landmines) (Belfield 2020 ). Ninety
countries have put forward statements on LAWs, with most doing so at the CCW;
28 countries support a ban (Campaign to Stop Killer Robots 2018 ).25In 2018, over
4000 Google employees signed a letter protesting Google ’s involvement in the Penta-
gon’s Project Maven, a military project exploring the use of AI in footage analysis
(Shane and Wakabayashi 2018 ), and a number resigned (Conger 2018 ). Several other
campaigning groups, comprised of scholars and researchers from the USA, Europe,
Japan, China, Korea and elsewhere, released public articles and letters supporting the
concerns of the Google practitioners (ICRAC 2018 ).26Google subsequently announced
it would not renew its contract on Project Maven, and would not bid on a $10 billion
Department of Defence cloud computing contract (Belfield 2020 ).
More broadly, international academic and civil society input has played a significant
role in shaping principles that are likely to form the basis for binding regulation in years
to come. For example, the European Commission ’s white paper On Artificial Intelli-
gence - A European Approach to Excellence and Trust (European Commission 2020 )
lays out ‘policy options for a future EU regulatory framework that would determine the
types of legal requirements that would apply to relevant actors, with a particular focus
on high-risk applications ’(European Commission 2020b ).This document was strongly
influenced by the work of the European Union ’s High-Level Expert group on Artificial
Intelligence, comprising 52 European experts from across academia, industry, and civil
society.27Similarly, the US Department of Defence has formally adopted ethical
principles on AI (US Department of Defense 2020 ), after 15 months of consultation
with US-based academic, industry, and government stakeholders, and has hired staff to
implement these principles (Barnett 2020 ). While in both cases the groups consulted
were region-specific, the degree of alignment and overlap between principles
25China supports a ban on use of fully autonomous weapons on the battlefield, but not their production and
development. The USA, Russia, UK, Israel, and France oppose a ban. (Kania 2018 )
26An open letter was released by the International Committee for Robot Arms control and signed by over
1000 scholars and researchers, and members of the Campaign to Stop Killer Robots wrote public articles and
letters to company leaders supporting the concerns of the Google petitioners: https://www.stopkillerrobots.
org/2019/01/rise-of-the-tech-workers/
27Information on process and composition available at: https://ec.europa.eu/digital-single-market/en/high-
level-expert-group-artificial-intelligenceS. S. ÓhÉigeartaigh et al. 582
developed in different regions suggests the insights and recommendations are substan-
tially informed by interaction with broader epistemic communities from other regions.
This suggests that insights gained from cross-cultural cooperation and consensus can
meaningfully feed into regulatory frameworks at a regional and national level.
5 Recommendations
Academia has an important role to play in supporting cross-cultural cooperation on AI
ethics and governance: both through research into where and what kinds of cooperation
are most needed, and by establishing initiatives to overcome more practical barriers to
cooperation. Our discussion in this paper raises many questions that will require diverse
academic expertise to answer, including questions about what important mispercep-
tions most hinder cooperation across regions; where international agreement is needed
on AI ethics and governance; and how agreement might be reached on specific
governance standards despite differences on ethical issues. Academic communities
are also particularly well-suited to building greater mutual understanding between
regions and cultures in practice, due to their tradition of free-flowing, international,
and intercultural exchange of ideas. Academics can have open conversations with
international colleagues in a way that is often challenging for those working in industry
or government, and two academics from different parts of the world can productively
collaborate even if each has strong criticisms of the other nation ’s government and/or
companies.
The following recommendations indicate a number of specific steps that academic
centres, research institutions, and individual researchers can take to promote cross-
cultural understanding and cooperation on AI ethics and governance. Some excellent
work is already ongoing in each of these areas. However, we believe that the pace at
which AI is being deployed in new domains and regions calls for a greater focus within
the academic community on building cross-cultural bridges and incorporating cross-
cultural expertise within a wider range of ethics and governance research projects.
Develop AI Ethics and Governance Research Agendas Requiring Cross-cultural
Cooperation Greater cross-cultural collaboration on research projects will play a cru-
cial role in building an international research community that can support international
policy cooperation (Haas 1992 ).
An example of a research project that might be well-suited to such collaboration is to
conduct comparative foresight exercises exploring differences in how both positive
visions and prominent concerns about AI ’s impact on society vary across cultures. This
could help with developing a more global vision for what we hope to both achieve and
avoid in AI development, which could guide more practical discussions around ethics
and governance frameworks. There may be particularly valuable opportunities for
consensus generation around avoidance of particular negative outcomes; safety and
security are fundamental to human cultures worldwide, and so developing agreements
to avoid threats to these may be an easier starting point. However, the authors feel that
it is important not to neglect positive visions, as the opportunity for scholars across
cultures to co-create shared positive futures may represent an excellent way to delve
into nuances within shared values.Overcoming Barriers to Cross-cultural Cooperation in AI Ethics and... 583
It would also be particularly valuable to explore the ongoing and expected impact of AI
on developing countries, in collaboration with experts from these countries. Such research
should aim to ensure that decisions to deploy technology in developing nations are made
with the guidance of local expertise in such a way as to empower local communities
(Hagerty and Rubinov 2019). On a more practical level, international research groups
could productively work together to develop frameworks for international sharing of
research, expertise, and datasets on AI safety, security, and avoidance of societal harm.
Collaboration between researchers from multiple regions and cultures will also be
essential to further research on the topic of cross-cultural cooperation itself. Our
discussion in this paper, especially in section 4, has pointed to many research areas
in need of further exploration, including the following:
&Exploring, identifying, and challenging perceived cross-cultural differences in
values, assumptions, and priorities relevant to AI ethics and governance, on
multiple different levels, including28the following:
–Analysing similarities and differences in technology ethics across different philo-
sophical traditions, and exploring how these may affect AI development, deploy-
ment, impacts, and governance in practice;
–Exploring the empirical evidence behind claims of key value differences between
cultures. For example, a project might identify and explore perceived value
differences between Eastern and Western cultures relevant to AI governance, such
as those relating to data privacy, the role of the state vs. the individual, and attitudes
towards technological progress;
–Understanding regional differences in practical priorities and constraints relating to the
use of AI in society, and the implications of these differences for AI research and
development.
&Further analysis to identify aspects of AI governance where global agreement is
needed, and differentiating these from areas in which cross-cultural variation is
either acceptable or desirable;
&Cross-cultural contribution to the development of international and global AI
standards in key domains for which these are needed; exploration of flexible
governance models that allow for a combination of global standards and regional
adaptability where appropriate;
&Exploring models and approaches for reaching agreement on concrete cases,
decisions, or governance standards despite disagreement on more fundamental or
abstract ethical issues, and identifying cases of this being done successfully in other
domains that can be translated to AI ethics and governance.
Some excellent work is already ongoing in each of these areas. However, we believe
that the pace at which AI is being deployed in new domains and regions calls for a
28Some excellent work on this question and related topics already exists in the field of intercultural
information ethics —see for example Capurro ( 2005 ,2008 ), Ess ( 2006 ), Hongladarom et al. ( 2009 )—but we
would be particularly keen to see cross-cultural research collaborations around these topics, and greater
attention paid to this work in more practical AI ethics discussions and initiatives.S. S. ÓhÉigeartaigh et al. 584
greater focus within the academic community on building cross-cultural bridges, and
incorporating cross-cultural expertise, within a wider range of ethics and governance
research projects.29
Translate Key Papers and Reports Language is a major practical barrier to greater
cross-cultural understanding around AI development, governance and ethics, as it has
been in many other areas of science (Amano et al. 2016 ). It would therefore be
extremely valuable for the burgeoning literature on AI ethics and governance, as well
as the literature on AI research, to be available in multiple languages. While many
leading Asian scholars in AI are fluent in English, many are not; and the fraction of
Western researchers fluent in Mandarin or Japanese is far lower.
Furthermore, some sources of the misunderstandings we have discussed may link to
the ways in which key documents from one region are understood and presented in other
regions. In Western media, China ’s2 0 1 7 New Generation Artificial Intelligence Devel-
opment Plan has been presented as promoting the aim of global dominance in AI
economically and strategically (Knight 2017 ; Demchak 2019 ). However, from the
Chinese perspective, national AI developmen t goals appear to be primarily motivated
by the needs of the Chinese economy and society (China State Council 2017), rather than
necessarily international com petitive superiority (Ying 2019). It appears that some trans-
lations may have led to misinterpretations of key terms and points. For example, the
original Chinese text referred to China becoming ‘a primary AI innovation center of the
w o r l db y2 0 3 0 ’(Ying 2019).30However, some English translations of the report trans-
lated this phrase as China becoming ‘the world ’s primary AI innovation center ’(e.g.
Webster et al. 2017). This was then interpreted and presented by Eric Schmidt, former
executive chairman of Google parent Alphabet, as ‘By 2030 they will dominate the
industries of AI. Just stop for a sec. The [Chinese] government said that. ’(Shead 2017).
While this evolution of wording is not substantial in one sense, it carries important
connotations; the language in the original context carries much softer connotations of
leadership and progress, as opposed to global dominance. Having multiple high-quality
translations of the most important documen ts would allow scholars to explore nuances of
language and context that may be lost in the reporting of these documents.
Producing high-quality versions of papers and reports in multiple languages also
conveys respect and an appetite to engage cross-culturally, which is likely to encourage
cooperation. High-quality translation of academic and policy materials is a challenging
and time-consuming task that we would encourage being supported and celebrated
more strongly. There is a growing body of work to be celebrated in this vein; for
example, Jeff Ding ’s translation of a range of key Chinese AI documents (Ding 2019 ),
the work of Intellisia in China on international relations, technology, and other topics,
which publishes in 5 languages ( http://www.intellisia.org/ ); Brian Tse ’st r a n s l a t i o nt o
Chinese of documents including OpenAI ’s Charter31; and New America ’st r a n s l a t i o n
of the Chinese Ministry of Industry and Information Technology ’sThree Year Action
Plan (Triolo et al. 2018 ).
29Several authors of this paper are part of an initiative that aims to support cross-cultural research of this
nature between the UK and China: https://ai-ethics-and-governance.institute/
30This specific translation was also provided to us by participants in the July 2019 workshop.
31https://openai.com/charter/Overcoming Barriers to Cross-cultural Cooperation in AI Ethics and... 585
Alternate Continents for Major AI Research Conferences and Ethics and Governance
Conferences To encourage more global participation in AI development, ethics, and
governance, we recommend that many of the leading conferences and fora on these
topics alternate between multiple continents. This has several advantages. It reduces the
cost and time commitment for scholars from parts of the world in which these
conferences do not frequently take place to participate. It avoids restrictive visa
limitations differentially affecting certain parts of the global research community. It
encourages the involvement of local organizers, who can play an effective role in
engaging local research communities who might not consider travelling far overseas for
an event. It also encourages organizers to run events multilingually rather than
monolingually.
Again, there are encouraging steps. Of AI research conferences, IJCAI took place in
Macau in 2019 and Beijing in 2013, the first two times the conference had been held in
China (although it has been held in Japan twice). ICML took place in Beijing in 2014,
and will be in Seoul in 2021, and ICLR 2020 will be held in Ethiopia, making it the first
of the top tier major machine learning conferences to be held in Africa. There are fewer
established conferences explicitly focused on AI ethics and governance since the field ’s
growth is relatively recent, but it may be particularly important for these conferences to
ensure a global presence by alternating the continent on which they are held if possible.
AI Ethics and Society, for example, is currently held in the USA due to ties to AAAI;
the importance of building an international academic community around these issues
may justify finding some way to change this. There is a burgeoning set of AI ethics and
governance conferences in China, including the Beijing Academy of AI Conference
series. There are also several existing conferences which cover topics relevant to AI
ethics and governance (even if not so explicitly centred around them), which do enable
more international participation, such as the World Summit on the Information Society
Forum (held most years in Geneva), the Internet Governance Forum, and RightsCon
(which have both been held in a range of locations historically including in South
America, India, and Africa, though neither in East Asia).32
Establish Joint and/or Exchange Programmes for PhD Students and
Postdocs Encouraging cross-cultural collaboration between researchers from different
cultures early on in their careers will help support greater cooperation and mutual
understanding as research advances. Many international fellowships and exchange
programmes exist, especially between the USA and China (e.g. the Zhi-Xing China
Fellowship and the Schwarzman Scholars programme) as well as between the UK and
Singapore (King ’s College London offers a joint PhD programme in Philosophy or
English with the National University of Singapore). To our knowledge, no such
initiatives exist explicitly focused on AI; the only initiative focused on AI ethics and
governance that we are currently aware of is the international fellowship programme
recently established by the Berggruen China Institute (Bauch 2019 ).33Establishing
more such programmes could be valuable for the future of international cooperation
32There is also a role for industry groups to play in encouraging cross-cultural collaboration through
international workshops and conferences. We highlight the work of the AI Industry Alliance as an example
of a recently established initiative in this space http://www.aiiaorg.cn/
33The Tianxia Fellowship, established by the Center for Long-term Priorities ( http://www.longtermpriorities.
org/), also includes AI safety and governance among other topics.S. S. ÓhÉigeartaigh et al. 586
around AI, and there are many existing models and initiatives from which to build and
learn.
More broadly, the authors endorse the Partnership on AI ’s recommendations to
governments on establishing visa pathways, simplifying and expediting visa processes,
and ensuring just standards to support international exchange and collaboration of AI/
ML multidisciplinary experts. We emphasize that these recommendations include
experts working or seeking to work on AI ethics and governance (which sometimes
fall outside of what is classed as ‘skilled technology work ’) (PAI Staff 2019 ).
6 Limitations and Future Directions
We believe that academia has an important role to play in supporting cross-cultural
cooperation in AI ethics and governance: that it is possible to establish effective
communities of mutual understanding and cooperation without needing to resolve all
fundamental value differences, and that reducing misunderstandings and mispercep-
tions between cultures may be of particular importance.
However, we recognize that the suggestions in this paper cannot go all the way to
overcoming the many barriers to cross-cultural cooperation, and that much more work
needs to be done to ensure AI will be globally beneficial. We briefly highlight two
broad avenues of further research in support of this goal:
More Detailed Analysis of Barriers to Cross-cultural Cooperation, Especially Those
Relating to Power Dynamics and Political Tensions While analysis of historical suc-
cesses suggest that it is possible for cross-cultural initiatives around AI ethics and
governance to considerably shape how norms, standards, and regulation evolve in
practice, there are still many barriers to implementation and enforcement that we were
unable to consider in this analysis. Further research into when and how attempts to
influence globally relevant norms and regulation have been successful in the past
would be of considerable value.
We acknowledged earlier in this paper that various issues related to power relations
and political tensions likely pose significant barriers to cross-cultural cooperation,
beyond problems of value differences and misunderstandings between cultures. More
research on how these issues present barriers to cross-cultural cooperation in AI ethics
and governance would therefore be particularly valuable, helping us to understand the
limits of academic initiatives in promoting cooperation, and in what ways these
approaches need to be embedded within a broader analysis of power and political
dynamics.
Considering the Unique Challenges of Cross-cultural Cooperation Around More Pow-
erful Future AI Systems Future advances in AI, which some scholars have theorized
could have impacts as transformative as the industrial or agricultural revolutions
(Karnofsky 2016 ; Zhang and Dafoe 2019 ), may raise new challenges for global
cooperation of a greater scale than we already face. Without careful global stewardship,
such advances could lead to unprecedented inequalities in wealth and power between
technology-leading and lagging nations. Others have gone further, theorizing about the
possibility of developing systems exhibiting superintelligence (i.e. greater-than-humanOvercoming Barriers to Cross-cultural Cooperation in AI Ethics and... 587
general intelligence; Bostrom 2014 ). Such systems, due to their tremendous capability,
might pose catastrophic risks to human civilisation if developed without careful
forethought and attention to safety. It has been proposed that a key challenge for
avoiding catastrophic outcomes will be value alignment —designing systems that are
aligned with humanity ’sv a l u e s( R u s s e l l 2019 ). This would greatly increase the impor-
tance and urgency of reaching global consensus on shared values and principles, as
well as finding ways to design systems to respect values that are not shared.
Expert views differ widely on how far in the future such advances might lie, with
most predicting decades. However, developing the collaborations and agreements
necessary for an effective and coordinated response may also require decades of work.
This suggests that cooperative initiatives today must address not just the ethics and
governance challenges of current AI systems, but should also lay the groundwork for
anticipating and engaging with future challenges.
7 Conclusion
The full benefits of AI cannot be realized across global societies without a deep level of
cooperation —across domains, disciplines, nations, and cultures. The current unease
and mistrust between the USA and Europe on the one hand, and China on the other
hand, places a particular strain on this. Misunderstandings may play an important role
in fuelling this mistrust, and differences in broader societal and political priorities
frequently appear to be overemphasized or misunderstood.
At the same time, it would be naive to assume that all major ethical
principles relating to AI can be shared in full between these regions, and can
be enshrined in rules and standards. Even if this were the case, it would not be
desirable for these regions to be overly dominant in shaping the ethics and
governance of AI globally; all global communities to be affected by AI must be
included and empowered. However, efforts to achieve greater understanding
between these ‘AI superpowers ’m a yh e l pi nt w ow a y s :F i r s t l y ,b yr e d u c i n g
key tensions within the global AI governance sphere. Secondly, by providing
lessons that can contribute to ethics and governance frameworks capable of
supporting a greater diversity of val ues while allowing consensus to be
achieved where needed. For a well-functioning system of global cooperation
in AI, the challenge will be to develop models that combine both principles and
standards shaped and supported by global consensus, and the variation that
allows research and policy communities to best serve the needs of their
societies.
On a more practical level, the international AI research community, and AI ethics
and governance communities, must think carefully about how their own activities can
support global cooperation, and a better understanding of different societal perspectives
and needs across regions. Greater cross-cultural research collaboration and exchange,
conferences taking place in different regions, and more publication across languages
can lower the barriers to cooperation and to understanding different perspectives and
shared goals. With political winds increasingly favouring isolationism, it has never
been more important for the research community to work across national and cultural
divides towards globally beneficial AI.S. S. ÓhÉigeartaigh et al. 588
Acknowledgments The authors would like to thank the participants of the July 11 –12 Cross-cultural trust
for beneficial AI workshop for valuable discussions relevant to the themes of the paper, as well as Emma
Bates, Haydn Belfield, Martina Kunz, Amritha Jayanti, Luke Kemp, Onora O ’Neill, and two anonymous
manuscript reviewers for helpful comments on previous drafts of this paper.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, 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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Affiliations
Seán S. ÓhÉigeartaigh1,2&Jess Whittlestone1&Yang Liu1,2&Yi Zeng2,3&Zhe
Liu2,4
1Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK
2China-UK Research Centre for AI Ethics And Governance, Beijing, China
3Research Center for AI Ethics and Safety, Beijing Academy of Artificial Intelligence, Beijing, China
4Centre for Philosophy and the Future of Humanity, Peking University, Beijing, ChinaOvercoming Barriers to Cross-cultural Cooperation in AI Ethics and... 593

Seán S. ÓhÉigeartaigh
Jess Whittlestone
Yang Liu
Yi Zeng
Zhe Liu