Venue: ACL 2023

# Ethical Considerations for Machine Translation of Indigenous Languages:

Giving a Voice to the Speakers

Manuel Mager\({}^{\diamondsuit}\)   Elisabeth Mayer\({}^{\sharp}\)

**Katharina Kann\({}^{\clubsuit}\) Ngoc Thang Vu\({}^{\diamondsuit}\)**

\({}^{\heartsuit}\)AWS AI Labs    Universidad Nacional Autonoma de Mexico

\({}^{\spadesuit}\)University of Colorado Boulder  University of Stuttgart

Work done while at the University of Stuttgart.

###### Abstract

In recent years machine translation has become very successful for high-resource language pairs. This has also sparked new interest in research on the automatic translation of low-resource languages, including Indigenous languages. However, the latter are deeply related to the ethnic and cultural groups that speak (or used to speak) them. The data collection, modeling and deploying machine translation systems thus result in new ethical questions that must be addressed. Motivated by this, we first survey the existing literature on ethical considerations for the documentation, translation, and general natural language processing for Indigenous languages. Afterward, we conduct and analyze an interview study to shed light on the positions of community leaders, teachers, and language activists regarding ethical concerns for the automatic translation of their languages. Our results show that the inclusion, at different degrees, of native speakers and community members is vital to performing better and more ethical research on Indigenous languages.

## 1 Introduction

With the advancement of data-driven machine translation (MT) systems, it has become possible to, with varying degrees of quality, to translate between any pair of languages. The only precondition is the availability of enough monolingual [20]Artetxe et al. (2018) or parallel data [53, 47]There are many advantages to having high-performing MT systems. For example, they increase access to information for speakers of indigenous languages [9] and can assist revitalization efforts for these languages [6].

Research on machine translation as well as natural language processing (NLP) more generally is moving towards low-resourced setups and multilingual models. Thus, the NLP community needs to open the discussion of repercussions and best practices for research on indigenous languages (that in most cases are also low-resourced) since non-artificial languages cannot exist without a community of people that use (or have traditionally used) them to communicate.

Indigenous languages further differ from more widely used ones in a crucial way: they are commonly spoken by small communities, and many communities use their language (besides other features) as a delimiter to define their own identity [15, 2], and have in many cases also a certain degree of endangerment. Furthermore, in some cases, highly sensitive information - such as secret aspects of their religion - has been encoded with the help of their language [1]. This is why, in recent years, discussions around ethical approaches to studying endangered languages have been started [41, 42]. When we consider the past (and present) of some of the communities that speak these languages, we will find a colonial history, where research is not the exception [1]. Therefore, it is possible to trespass on ethical limits when using typical NLP and data collection methodologies [46].

In this work, we explore the basic concepts of ethics related to MT of endangered languages with a special focus on Indigenous communities, surveying previous work on the topic. To better understand the expectations and concerns related to the development of MT systems for Indigenous communities, we then conducted an interview study with 22 language activists, language teachers, and community leaders who are members of Indigenous communities from the Americas. Additionally, we also performed 1:1 dialogues with two study participants to deepen our understanding of the matter. The goal is to answer the following

research questions: _How do community members want to be involved in the MT process, and why? Are there sensible topics that are not ethical to translate, model, or collect data without the community's explicit permission? How can we collect data in an ethical way?_

Surprisingly, most survey participants positively view MT for their languages. However, they believe research on their languages should be done in close collaboration with community members. Open access to research discoveries and resources is also valued highly, as well as the high quality of the resulting translations. The personal interviews also confirmed this. Thus, our most important finding is that it is crucial to work closely with the communities to understand delicate ethical topics when developing MT systems for endangered languages.

A Spanish translation of this paper is included in Appendix C. This translation aims to share our findings with all study participants and their communities and facilitate access to a broader audience in the Americas.

## 2 Defining "Endangered Language"

Terms frequently used in NLP are _low-resource language_, _resource-poor language_, and _low-resource setting_. Those terms are not highlighting the fact that many low-resource languages are also endangered Liu et al. (2022). Instead, they emphasize the critical machine learning problem of getting a data-driven approach to perform well with a smaller-than-ideal amount of available data (or just fewer data than what has been used for other languages). In this case, algorithmic or technological innovations are needed to close the performance gap between high-resource and resource-poor languages. This further implies that being low-resourced is not a property of a language but a term that only makes sense in the context of a particular task or tasks.

In contrast, the term _endangered language_ refers to a language with a certain degree of danger for its existence.1 Endangered languages are relevant for our study, as most Indigenous languages are also endangered Hale (1992). According to the UNESCO classification, Moseley (2010) languages can be sorted into the following different categories:

Footnote 1: In this paper, we will discuss only non-artificially created languages.

* _safe_: spoken by all generations;
* _vulnerable_: restricted just to a certain domain (e.g., inside the family);
* _definitely endangered_: it has no kids that speak the language;
* _severely endangered_: only elder people speak it;
* _critical endangered_: there are only speakers left with partial knowledge, and they use it infrequently;
* _extinct_, when there are no persons able to speak the language anymore.

Languages can become endangered due to social, cultural, and political reasons; most commonly conquests and wars, economic pressures, language policies from political powers, assimilation of the dominant culture, discrimination, and language standardization Austin and Sallabank (2013). As we can see, the problem of how a language gets endangered involves factors that must be addressed in the ethical approach of any study. On the machine learning side, an additional challenge arises: data for endangered languages is not easily available (or, in fact, available at all), as these languages have limited media production (TV shows, literature, internet blogs; Hamalainen (2021). One possible source of data for these languages is already existing documents in form of books, records, and archives Bustamante et al. (2020).

## 3 Ethics and MT

### Ethics and Data

The study of endangered languages in indigenous communities has a long history, with the most prominent questions being focused mainly on the challenge of data collection Smith (2021).

One of the common forms of this is to use normative ethics (deontology). Examples of relevant guidelines include those from The Australian Institute of Aboriginal and Torres Strait Islander Studies;2 the Ethical statement of the Linguistic Society of America;3 and the DOBES code of conduct.4 These lists are the results of broad discussions 

which have taken place over decades. In this debate also, indigenous voices were inside academia raised (Smith, 2021).

But why do we have so many attempts to set up an ethical code for linguistic fieldwork? When it comes to working with human societies, there are no easy solutions for the ethical dilemmas that arise Dwyer (2006). Every situation requires a unique treatment and compromise. This is why, in addition to the creation of a framework which is as general as possible, the concrete application of such principles involves continued discussion. Dwyer (2006) suggests documenting the ethical issues and concerns which arise during the course of a research project and the way these issues are addressed, such that other researchers can learn from the experience. While a code of conduct or principles is good, it runs the risk of introducing either overly complicated - or even inadequate - regulations, relegating this needed discussion.

Overall, we can summarize those principles that appear in all suggested lists under three big themes:

* _Consultation, Negotiation and Mutual Understanding_. The right to consultation of Indigenous people is stipulated in convention 167 of the International Labor Organization Ilo (1989) and states that they "have the right to preserve and develop their own institutions, languages, and cultures". Therefore, informing the community about the planned research, negotiating a possible outcome, and reaching a mutual agreement on the directions and details of the project should happen in all cases.
* as well as any governing organizations interested in the project
- should be familiar with the history and traditions of the community. Also, it should be recommended that local researchers, speakers, or internal governments should be involved in the project.
* _Sharing and distribution of data and research_. The product of the research should be available for use by the community, so they can take advantage of the generated materials, like papers, books, or data.

Some of these commonly agreed-on principles need to be adapted to concrete situations, which might not be easy to do via a general approach. For instance, the documentation process will create data, and the ownership of this data is a major source of discussion (cf. Sections 4, 5). Here, the traditional views of the communities might contradict the juridical system of a country Daes (1993). This problem does not have a simple solution and needs to be carefully considered when collecting data.

An additional call from these sources is to de- colonize research and to stop viewing Indigenous communities as sources of data, but rather as people with their own history Smith (2021). The current divorce between researchers and the cultural units of the communities can lead to reinforcing colonial legacy Leonard (2020).

As a final remark, we want to discuss the common assumption that any Ethical discussion must end with a normative setup for a field. It reduces indigenous institutions' collective to norms that allow an individual approach to the matter Meza Salcedo (2017). This would also not allow understanding the ethical questions with their own Indigenous communal cosmovision Salcedo (2016). Therefore, in this text, we aim to open the MT ethical debate to the NLP researchers and the Indigenous communities based on inclusion and dialog.

### Ethics and Human Translation

For a successful translation, the inclusion of all participants is important, requiring their equal, informal, and understanding-oriented participation Nissing and Muller (2009). For Rachels Rachels and Rachels (1986), the minimum conception of morality is that when we give "equal weight to the interests of each individual affected by one's decision." The question is how authors' intentions relate to the source culture's obterness, with their culturally-specific values Chesterman (2001). According to Doherty (2016), "the translation process studies emerged to focus on the translator and the process of translation rather than on the end product," incorporating mixed-method designs to get objective observations. A well-documented example of the non-ethical misuse of translation is the application of translation as an instrument for colonial domination. The main aim of this colonialist vision was to "civilize the savages" Ludescher (2001). For example, the summer institute of linguistics (SIL International)5 was used for this goal 

during the 20th century in countries with Indigenous cultures, translating the Bible and trying to provoke a cultural change6 in these communities DelValls (1978); Errington (2001); Carey (2010). Of course, these practices are not new and can be found throughout history Gilmour (2007). It is essential to notice that non-ethical research can still deliver useful material and knowledge, e.g., for language revitalization Premrisrat and Malone (2003), but might inflict harm on the targeted community.

Footnote 5: The role of SIL is controversial, and can not be summarized with one single statement. In our approach, we only refer to the role played related to cultural change. In many cases, the communities that got religious texts translated were already Christiians, given previous colonization actions. However, there are also cases, where non-christian communities had Bibles and other religious texts translated into their language, with missionary aims. This triggered community divisions. For example, the translation of the religious texts to Wixarika Fernández (2022). This also happened in the Community of Zoquipan (in the Mexican state of Nayarit), where Christiians, using the SIL-translated Bible, triggered an internal conflict in the community (the first author is part of this community). For the interested reader, we also recommend Dobrin (2009) introductory article.

### Ethics and _Machine_ Translation

In the context of NLP research, the speakers are not directly involved when a model is trained Pavlick et al. (2014). In contrast, the data collection processes Fort et al. (2011) and human evaluation Couillault et al. (2014) directly interact with the speakers and, therefore, have central importance regarding ethics. This is also true for the final translation service, which will interact with the broad public.

Data collection is the first and most evident issue when it comes to translation. Modern neural MT systems require a large amount of parallel data to be trained optimally Junczys-Dowmunt (2019). One way to obtain data is from crowd-sourcing Fort et al. (2011). However, this kind of job can be ill-paid and might constitute a problem for the living conditions of the workers Schmidt (2013). Also, data privacy is not trivial to handle. Systems must be able to filter sensitive information.

The problem of encoding biases7, like gender bias Stanovsky et al. (2019), is also an ethical concern for MT. It is also necessary to disclose the limitations and issues with certain systems Leidner Plachouras (2017).

Footnote 7: Multilingual systems refer in NLP to systems capable of translating a set of languages from and to English. In some cases, they are also able to translate between languages where English is not involved.

NLP research can also be used as a political instrument of power, where we can observe mutual relationships between language, society, and the individual that "are also the source for the societal impact factors of NLP" Horvath et al. (2017). In this way, NLP translation can be applied as an instrument to changing the culture of minorities as in traditional translation (cf. Section 3.2). So colonizers used translation as means of imperial control and expropriation Cheyfitz (1997); Niranjana (1992). The asymmetry of power is the cause of domination, where subaltern cultures being flooded with "foreign materials and foreign language impositions" is a real danger for minority cultures Tymoczko (2006). Schwartz (2022) discuss the need to decolonize the scientific approach of the NLP community as a whole, expressing the need for researchers to be cognizant of the history and the cultural aspects of the communities which use the languages they are working with. Additionally, he proposes that our research should have an obligation to provide some benefit from our studies to the communities, an obligation of accountability (and therefore be in direct contact with their governing organizations), and an obligation of non-maleficence. The fact that many translation systems nowadays are multilingual8 also result in more multi-cultural challenges Hershcovich et al. (2022).

Footnote 7: For example, Wikarika memes: [https://www.fa](https://www.fa) cebook.com/memeswixarika2019, Quechua speaking group: [https://www.facebook.com/groups/711230846397383/](https://www.facebook.com/groups/711230846397383/) 

binding the state to the responsibility to translate all official pages, documents, laws, etc., to indigenous languages. This has not been implemented, and this case is a highly valuable application case for machine translation to assist human translation. However, our findings also apply to speech-to-text translation and speech-to-speech tasks that would cover all languages, even with no written tradition.

## 4 The Speakers' Opinions

It is important to include the opinion and vision of speakers of endangered languages in NLP research, especially for topics such as MT. Therefore, we conduct a survey study with 22 language activists, teachers, and community leaders from the Americas. Importantly, our primary goal is not only to gather quantitative input on the ethical questions regarding MT for their languages but also to collect qualitative input by asking them to expand on their answers. Additionally, we also perform an interview with a subset of two participants of the initial interview study.

### Study Design

We focus our study on the Americas,10 selecting the following communities: Aymara, Chatino, Maya, Mazatec, Mixe, Nahua, Otomi, QuechuA, Tenek, Tepehuano, Kichwa of Otavalo, and Zapotec. We want to note that our study does not aim to represent a general opinion of all Indigenous tribes, nor is it a final general statement on the issue. It is a case study that surfaces the opinions of specific groups of speakers of Indigenous languages. Furthermore, the views of the interviewed individuals are their own and do not necessarily represent the view of their tribes, nations, or communities.

Footnote 10: Different parts of the world have very different levels of wariness, not just from colonial history but precisely due to interactions with field workers.

Quantitative and Qualitative aspectsFor the quantitative study, we used a survey. Surveys are a well-established technique to be used with Indigenous communities with an extensive history and are used and documented by classics like Edward Taylor, Anthony Wallace, Lewis Henry Morgan. This is also true for well-recognized Mexican (Indigenous engaged) social anthropologists Jimenez Ramos (1985); Alfredo and Alberto (1978).

For the qualitative part, we revisit existing positional papers and articles of Indigenous researchers and activists. Additionally, we use open questions in the survey, allowing extending the pure quantitative view to a qualitative one. Finally, we performed two 1-to-1 interviews with an activist (Mixe) and a linguist (Chatino).

Participant RecruitmentWe contact potential participants online in three ways. Our first approach is to establish communication through the potential participants' official project websites or public online accounts. This includes e-mail, Twitter, Facebook, and Instagram pages. Our second approach is to directly contact people in our target group with whom at least one of the co-authors has already established a relationship. Finally, we also published a call for participation on social media and check if the volunteers belong to our target group. The goals of our research, as well as the reach and data handling, are explained directly to each participant and are also included in the final form. We do not gather any personal information about the participants, like name, gender, age, etc. All study participants are volunteers.

QuestionnaireOur study consists of 12 questions. The first three questions are rather general: they ask for the tribe, nation, or Indigenous people the participant belongs to if they self-identify as an activist, community leader, or teacher, and for their fluency in their language. The remaining questions target data policies, inclusion policies, benefits and dangers of MT systems, and best research practices. The full questionnaire is available in the appendix. The questions are available in English and Spanish, but only one form has been filled in English, while the rest has been completed in Spanish. Therefore, the authors have automatically translated all comments which are shown in this paper.

### Results

The results of the study can be seen in Figure 1. Additionally, we also discuss the open answers to each question to provide more insight.

Inclusion of Native Speakers and Permissions to Study the LanguageFigure 1(a) shows that 77.3% of the participants report that their community has no restrictions regarding the sharing of their language with outside people. The comments for this question show that many participants are proud of their language and heritage: "We are supportive and share our roots. Proud of who visits us" We even find stronger statements against the pro 

hibition to share: "No one has the right to restrict the spread of the language". However, there also do exist communities with restrictions. Thus, we conclude that researchers cannot assume by default that all Indigenous groups would agree to share information about their language or would be happy about research on it.

Benefits and Dangers of MT SystemsFigure 1(b) shows that a strong majority of our participants think that an MT system for their language would be beneficial. However, there is also an important number of people who see at least some degree of danger. In this case, we need to look at the participants' comments to understand their worries. First, we find that a main concern for the participants is the translation quality. The fear of inadequate translations of cultural terms is also important. In Table 2, we can see a set of comments that illustrate these fears. One interesting comment refers to the fear of standardization of the participant's language, which could lead to a loss of diversity. In the same table, we can also see the benefits the participants expect, mostly in education and in elevating the status and usefulness of their languages.

Table 1 shows some answers to the open question on possible topics that might cause damage to the community. Most answers could not identify any possible topic that could be dangerous. However, the second most frequent answer was related to religion. Some answers are worried that ancient

Figure 1: Study performed on 22 participants that are members of Indigenous communities from the Americas.

 

ceremonial secrets could be revealed. Others also show worries about the influence of Western religions. This brings us to the question if the Bible (Christodouloupoulos and Steedman, 2015; McCarthy et al., 2020; Agic and Vulic, 2019) is suited to use as our default corpora for MT, when an indigenous language is involved. Finally, also few answers expressed that the usage of indigenous languages in the internal organization of the community could be in danger with MT systems. In contrast, figure 1(c) shows the topics that that most positive evaluation registered: everyday talks (15), science and education (14), culture and traditions (14), and medicine and health (14).

Participation of Members of Indigenous Communities in ResearchFigure 1(d) shows that our study participants think it is important to include people from the targeted communities in research projects. This confirms the experience in linguistics, where they found a similar pattern (Smith, 2021) (see SS3.1). It is important to note that only one answer was stated that official permission is needed to perform the study. In the comments, the right of consulting was mentioned, together with the advantages of involving community members in research: "It is preferable [to integrate people from the community] to obtain a good system, and not just to have approximations, because only the members of the culture know how the language is used."; "So that the vocabulary is enriched and some words that do not exist are not imposed."; "Carry out activities where the community can be involved, win-win.".

Data Usage and Translation QualityRegarding data ownership and accessibility, we find diverse sets of responses. First, Figure 1(e) shows many different opinions. Overall, we can say that a strong feeling exists that data should be publicly available. However, when it comes to the property of the data, opinions are more diverse. Surprisingly, an important number of participants (\(17\%\)) think that the external research group should own the data. Nevertheless, a higher number of participants think that the data should be owned by the community (\(29.4\%\)), and 20.6% thinks it should be owned by the speakers who participate in the research. This is a difficult topic, as traditional norms and modern law systems interact (cf. Section 3.1). In the comments, we find sad examples of mistrust in academic institutions. For example, one comment talks about previous problems of their tribe, as recordings and other material taken by linguists is not accessible to them: "Wary of academic institutions since we currently have issues accessing recordings that belong to academics and libraries and are not publicly accessible." However, in general, we see a wide range of opinions: "The work of the few who take linguistic identity seriously should be valued", "It could be public but always with the endorsement and consent of the community." This diversity demonstrates that there is a need for researchers to have a close relationship with the communities to understand the background and the aims of each particular case.

As discussed above, the quality of the final system is an important concern for many participants. In Figure 1(f) we can see that publishing an experimental MT system is also controversial. The possibility of using an experimental system is liked by \(54.8\%\) of our participants, which is slightly higher

\begin{table}
\begin{tabular}{l l}  & **Can you think of any dangers to the language and culture, if so, which?** \\ \hline There are cultural linguistic concepts that are only understood in our native language. & \\ The existence of so many variants would make the project little or not profitable and would lead the “experts” to an attempt to standardize language, which would be a tremendous mistake. & \\ There are cultural elements that must be taken into account. & \\ They could undoubtedly distort the proper use of the language. & \\ \end{tabular}
\end{table}
Table 1: Some answers to the open question on possible dangers of MT for indigenous languages.

 

than the number of participants who are against this (\(45.5\%\)). Some opinions against it are in line with earlier worries about incorrect translations of cultural content: "Something that is devoid of structure and cultural objectivity cannot be made available to the public" and "...damage would be caused to the language and its representatives since the learners would learn in the wrong way." Most people with a positive opinion agree that an initially poor system could be improved over time: "If it could be improved and corrected, that would be excellent."

## 5 Discussion

In Section 3 we survey the ongoing debate on ethics in documentation, translation, and MT, before presenting an interview study in Section 4. Now we discuss some the most important issues we have identified in the last section in more depth.

Need for Consultations with CommunitiesPrevious experiences Bird et al. (2020); Liu et al. (2022) as well our study highlight the need for consultation with Indigenous communities when performing research involving their languages11. In some cases, the minimal expressed requirement is to inform speakers about new technological advances. Feedback and quality checks are also crucial for MT systems and important to the members of the communities. This consultation should include intercultural dialog as it has been a central instrument in the decision-making of indigenous communities Beauclair (2010). We recommend doing this by integrating community members into the loop while, of course, giving them the credit they deserve.

Footnote 11: An example of a community engaged fieldwork is Czaykowska-Higgins (2009)

Legal systems vs. Traditional Views of Communual Knowledge OwnershipLegal systems and, with that, copyright laws vary by country. However, legal rules are sometimes in conflict with the traditional views of Indigenous people Dwyer (2006). Thus, when working with Indigenous communities, we recommend discussing and agreeing upon ownership rights with annotators or study participants prior to starting the work to find an arrangement everyone is happy with. We would also like to point out that, according to our case study, a general feeling is that data and research results need to be accessible to the community speaking the language. This contradicts the practice of some documentation efforts that close the collected data to the public and even to the speakers of the community Avelino (2021). Some participants in our study even suggest the usage of Creative Commons CC12 for data. However, the use of CC might not be the best licensing option, as it not designed specifically for the needs of Indigenous. Finally, whenever collected data are used for commercial usage, special agreements involving financial aspects are crucial.

PermissionsSome communities require that a permit from their governing entity be obtained when someone, not a member, wants to study their language. This might be difficult as sometimes there is no central authority. Figuring out from whom to get permission can be challenging in such scenarios. However, as we see in this study, many communities do not require this permission. A promising project that aims to simplify this topic is the KP labels13. It is a set of labels that communities can use to express their permissions and willingness to cooperate with researchers and external projects.

Footnote 12: [https://creativecommons.org/licenses/](https://creativecommons.org/licenses/)

Personal DataFrom the free-text answers, we further learn that, for many speakers, using their own language in their daily environment helps them protect their privacy: Their conversations can only be understood by their family or close environment. This concern of data handling is, however, also valid for other languages.

Concerns about Private Information of the CommunityThe previous point can further be extended to assemblies and other organizational meetings, where the language barrier is used to keep their decisions or strategies private. This is one worry that the communities have with MT and the possible topics that might be harmful for them. Some communities also have general concerns about sharing their language with people that do not belong to them (e.g., the Hopi Dictionary controversy Hill (2002)). For this case, it is important not to approach this issue from a Western legal point of view and go towards traditional internal governance practices and norms and consultation with the communities.

Religion and the BibleRegarding problematic domains for MT, multiple survey participants men 

tioned religion. This is quite relevant for the NLP community, as the broadest resource currently available for minority languages is the Bible. As seen in Section 3.2, the colonial usage of translation of religious texts Niranjana (1990) is precisely the origin of these detests. Thus, we recommend that NLP and MT researchers use the Bible carefully, through a consultation process, and consider its impacts. Nevertheless, without a close relationship with each community (e.g., in a massive multilingual MT experiment), the recommendation is to void using the Bible.

Footnote 15: [https://indigenousinsnovate.org/downloads/indigenous-knowledge-and-data-gourance-protocol_may-2021.pdf](https://indigenousinsnovate.org/downloads/indigenous-knowledge-and-data-gourance-protocol_may-2021.pdf)

Technology and data SovereigntyHaving technology for their own languages is well seen by most study participants. However, we also find a strong wish to participate directly in the development of MT systems. This requires more inclusion of Indigenous researchers in NLP. Therefore, training Indigenous researchers and engineers is an important task that we recommend should be valued more highly by the NLP and MT communities. We are aware that existing inequalities cannot be removed immediately or in isolation, but everyone can be supportive.16 The creation of a collaborative process is a proposal emerging from the communities themselves: "Technology as Tequio; technological creation and innovation as a common good" Aguilar-Gil (2020). However, it is not possible to build contemporary data-driven NLP technologies without data. And this opens the discussion regarding Data Sovereignty. First, it is important to mention that the communities have the right to self-determination, and this includes the data that they create. Applying this sovereignty to data refers to having control over the data, knowledge17 and cultural expressions that are created by these communities. As discussed in this paper, it is important to reach agreements with the communities through consultations and direct collaborations. This includes the licensing and ownership of the final data products.

Footnote 16: Tech sovereignty is a central topic for the Natives in Tech conference in 2022: [https://nativesintech.org/conference/2022](https://nativesintech.org/conference/2022)

Footnote 17: See [https://indigenousinnovate.org/downloadloads/indigenous-knowledges-and-data-gourance-protocol_may-2021.pdf](https://indigenousinnovate.org/downloadloads/indigenous-knowledges-and-data-gourance-protocol_may-2021.pdf)

Our Findings and Previous WorkFinally, we want to relate our findings to similar discussions in prior work. Most previous concerns and suggestions related to including and consulting people from the communities Bird (2020); Liu et al. (2022) are aligned with the wishes and desires of the participants in our study. The inclusion of community members as co-authors Liu et al. (2022) should not be an artificial mechanic but more a broad inclusion process, including data and technology sovereignty. This is also aligned with the community building aimed at by Zhang et al. (2022). Additionally, we should consider that there might exist problematic topics and not underestimate the importance of high-quality translations.

## 6 Conclusion

In this work, which is focused on ethical challenges for MT of Indigenous languages, we first provided an overview of relevant ethical approaches, ethical challenges for translation in general, and more specific challenges for MT. Afterward, we conducted a case study, for which we interviewed \(22\) Indigenous language activists, language teachers, and community leaders from the Americas. Our findings aligned with previous findings regarding the need for inclusion and consultation with communities when working with language data. Additionally, our participants expressed a surprisingly strong interest in having MT systems for their languages but also concerns regarding commercial usage, cultural and religious misuse, data, and technological sovereignty. We ended with specific recommendations for the NLP and MT communities, but even more important, an open discussion framework for the indigenous communities.

### Acknowledgments

We want to thank all community members, linguists, and language activists who participants in our study. We will also thank the reviewers for their valuable comments and Heriberto Avelino for his useful insights. This project has benefited from financial support to Manuel Mager by a DAAD Doctoral Research Grant.

### Limitations

This study is restricted to the Americas. Therefore the results from this paper can not be generalized, as different indigenous communities or nations might have different pasts. Also, all opinions expressed by the interviewed people are exclusively personal and in should not be interpreted as the general stand of the communities. As discussed in the paper, the main aim of this work is 

not to provide a normative for MT researchers. We rather provide a set of questions and open topics that should be considered when performing MT work with indigenous languages. Nevertheless, we also provide general and broad non-normative recommendations that should be carefully applied to the concrete case of each community.

## Ethical statement

To ensure the ethics of this work, we followed well-recognized ethical codes: The Australian Institute of Aboriginal and Torres Strait Islander Studies ( AIATSIS)16 and the DOBES code of conduct17. As a result, all participants were well informed about the intent of this work, our aims, and the complete anonymization of their answers. Moreover, this work was done with indigenous leadership (as suggested by AIATSIS).

Footnote 16: [https://aiatsis.gov.au/sites/default/files/2020-10/aiatsis-code-ethics.pdf](https://aiatsis.gov.au/sites/default/files/2020-10/aiatsis-code-ethics.pdf)

Here we list the ethical issues we found while working on this work and how we try to minimize their impact. First, we were concerned with the data protection of the participants in this study. As for this study, no personal data is required. Therefore, we decided to remove any questions containing any information that could reveal the identity of the participants. Second, as our study aims to get substantial input from the communities, we decided to leave as many open questions as possible and consider the available comments section of each question. All participants were informed about the goals of this project and participated in a free and informed way. To give proper recognition to the participants of this study, we offer an option to be included in the acknowledgment section.

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## Appendix A Questionnaire

The following questions, together with their answers are listed in this section.

1. **How do you consider yourself** 1. Leader of your town or community 2. Language activist 3. None of the above 4. Other, explain
2. **To what degree do you speak your mother tongue (indigenous / native / native)** 1. Perfectly 2. Fairly good, but with shortcomings 3. I speak with difficulties 4. I don't speak it but I do understand 5. I am not a speaker of the language, but I know some words
3. **What people / tribe / nation do you belong to?** 1. Open Question
4. **In your town / nation / tribe there is some restriction to share your language with people outside your community** 1. Yes 2. No 3. It depends Comment the question
5. **On a scale from 1-5, how dangerous do you think an MT system would be?** * 1 - Not dangerous 

- Dangerous Comment the question
6. **What advantages would you see with an automatic translation system** * Open ended Comment the question
7. **What dangers would you see in a machine translation system:** * Open ended Comment the question
8. **What topics would you see as positive in which automatic translation can be carried out (there may be several options)** 1. Medicine and health 2. Medicinal plants 3. Religion and sacred songs 4. Tales and literature and non-sacored songs 5. Laws 6. Commercial matters 7. Talk everyday 8. Science and education 9. Culture and traditions 10. others
9. **What would you see as damaging topics that should not be machine translated?** * Open question
10. **What would you think of a system with poor translation quality?** * Not to be used or made available to the public * It would be good, to see the progress and be able to help correct it
11. **To create translation systems we need data (text in the native language aligned with text in the foreign language). These data should:** 1. Be public and without restrictions 2. Be owned by an organ of the community or town. 3. Be the property of the research group that compiled it 4. Be the property of the speakers who made the translation
12. **In a machine translation project** 1. Any team of researchers in the world can produce systems 2. It is preferable to integrate community members 3. Only community members should work on it 4. Only with express permission of the community body 5. These investigations should not be carried out

## Appendix B Complete answers of the open questions

All questions refer to the ones enumerated in appendix A. In table 5 we present the complete results for the open question 6. In table 3 we present the complete results for the open question 7. In table 4 we present the complete results for the open question 9.

 



\begin{table}
\begin{tabular}{|p{14.2pt}|p{390.8pt}|p{56.9pt}|}  & Original & English Translation \\ \hline  & Que ventajas tendria un sistema de traduccion automatica para su idioma? & What dangers would you see in a machine translation system (for indigenous languages): \\ \hline
1 & Seria practico pero confuso, por las variantes (aprox. mas de 30 variantes) & It would be practical but confusing, because of the variants (approx. more than 30 variants) \\
2 & Facilitaria el aprendizje para los ajenos a la lengua y entender cada une do les nativos la forma estructura de sus excritura. & It would facilitate learning for those foreign to the language and for each of the natives to understand the structure of their writing. Easy access \\
3 & Facil acceso & Easy access \\
4 & La unificacion de la lengua & The unification of the language \\
5 & La ventaja de que las personas que no lo hablan, puedan comunicarse con la gente monolingue & The advantage that people who do not speak it can communicate with monolingual people \\
6 & Ninguna. & None \\
7 & La dispersion del aprendizaje de este & The dispersion of the learning of this \\
8 & Tal vez un aporte de modernidad a la comunidad, preservación de la lengua nativa. & Perhaps a contribution of modernity to the community, preservation of the native language. \\
9 & Con respeto a los derechos linguistics su difusion pertinecia & With respect to linguistic rights its dissemination relevance \\
10 & Facilitaria la ensénanza porque se tendria muchas herramientas de appoyo. & It would facilitate teaching because it would have many support tools. \\
11 & Conocer una aproximacion de los significados & Know an approximation of the meanings \\
12 & Ayudaría a las personas que no hablan o ya no hablan el idioma Popti’, ayudaria a los niñ ones en las escuelas para aprender el idioma. & It would help children in schools to learn the language. \\
13 & Contribuirifa al uso social de nuestro idioma & It would contribute to the social use of our language \\
14 & El uso de traductorores automáticos en espacios como hospitalales, oicinas de gobierno, etc. & The use of automatic translators in spaces such as hospitals, government offices, etc. \\
15 & Contribuirita al Status de las lengunas indigenas y quiza tambien Corpus. & It would contribute to the Status of indigenous languages and perhaps also Corpus. \\
16 & Solo seria util para concer vocabulario y pequenas frases quizás. & It would only be useful to learn vocabulary and small phrases perhaps. \\
17 & haacer la lengua mas visible y mas accesible a personas fuera de la comunidad de habla & make the language more visible and more accessible to people outside the speaking community \\
18 & Mantener la lengua a través del tiempo y la distancia & hold the tongue through time and distance \\
19 & Mucha ventaja para las personas que han estado interesados en aprender este idioma. & Much advantage for people who have been interested in learning this language. \\
20 & nos avdardaria a normalizar la presencia del kichwa en und medio actual de comunicacion. & It would help us to normalize the presence of Kichwa in a current means of communication. \\
21 & These are great for interview videos or audio. I don’t see anything wrong with this. & \\
22 & Ayudar aprender nuestra lengua & Help learn our language \\ \end{tabular}
\end{table}
Table 3: Answers for the open question 6 (see §A). All translations are automatic translations with human editing. If the original is in English, we leave the translation field blank.





\begin{table}
\begin{tabular}{p{14.2pt}|p{390.8pt}|p{56.9pt}|p{71.1pt}}  & Original & English Translation \\ \hline  & **Podria****usted****commentar sobre algun posible probelema que podria generar un sistema de traduccion automatic para su idioma?** & **What dangers would you see in a machine translation system** \\ \hline
1 & Por la variedad de la Lengua, algunas palabras significan diferente, no es recomendable un diccionario estandara para la lenguia, si por variante. Los conceptos culturales. En su defecto hay concepto slingtistiucles vultraales que solo se entienden en la lengua nativa. De igual forma, encontraremos conceptos apenos a nuestra lengua que no son traducibles. Falta de recursso de informacion & Due to the variety of the language, some words mean differently, a standard dictionary for the language is not recommended, if by variant. Cultural concepts. Failing that, there are cultural linguistic concepts metr are only understood in the native language. In the same way, we will find concepts foreign to our language that are not translatable. Lack of information resources The people of each region cling to their own variant It cannot be strictly understood as dangerous, but it is a bit difficult because there are many variants The denaturation of the language. Being a language where nouns do not prevail, articles and some prepositions are lacking, in addition to being agglutinative, the work is much more complicated than in other languages. In addition, the existence of so many variants would make the project unprofitable or unprofitable and would lead the "experts" to attempt to standardize speech, which would be a tremendous mistake. It would help to learn the language. None, in fact we have progress and an international community (Peru, Bolivia, Argentina y Chile) of Aymara formed with this objective. There are some words that cannot be translated, because by doing so they lose their meaning, in addition to the fact that this language has other spellings that are absent in the consonantal and vowel system of Spanish (which is like the reference for everything that is done). In addition to the fact that the O’dam language is agglutinative, the correspondences between words or sentences will not always be one to one because the words in O'dam are long and can mean a whole sentence. It is an agglutinative langauge. Take culture into account, there are cultural elements that must be taken into account None Not culturally and linguistically adequate That for “practically” the use of automatic translators is prioritized instead of learning the language. They could undoubtedly distort the proper use of the language. Quechaus is a contextual language. the previous question is very ambiguous, dangerous in what sense, for its speakers? for the linguist? ... a problem that could arise is that not the entire speech community agrees to make the language available to everyone The first thing is that there is no special keyboard It would be a bit difficult to translate Chol automatically, since it is a complex language and sometimes it is only understood by seeing, being or knowing the context of the speech. none As long as the community is involved. \\ \end{tabular}
\end{table}
Table 4: Answers for the open question 7 (see §A). All translations are automatic translations with human editing. If the original is in English, we leave the translation field blank.





\begin{table}
\begin{tabular}{|l|p{142.3pt}|p{142.3pt}|} \hline  & Original & English Translation \\ \hline  & **Que temas veria usted como perjudiciales en los que no se debería realizar traduccion automática para su lengua?** & **What would you see as damaging topics that should not be machine translated?** \\ \hline
1 & Ninguno & None \\
2 & Leyes, medicina y salud, ciencia, cuestiones mercantiles, religion y canciones sagradas, & Law, medicine and health, science, business matters, religion and sacred songs, Laws the bad words I do not see any problem in the translation of all sides topics Nine90 Nin90 Nin90 Nin9

Spanish Version: _Consideraciones eticas para la traduccion automatica de lenguasi indigenas: dar voz a los hablantes Incliumos una traduccion del texto original en ingles, para facilitar la discusion del mismo en los pales de habla hispana del continuete Americano. A si mismo esta traduccion nos permite comparir los resultados de nuestra investigacion con los participantes de las entrevistas y encuestas. La traduccion fue realizda con Ayuda de un sistema de tradiccion automatica (Google Translate) y mejorada con edicion manual. Todas las referencias son elnazadas al original en ingles._

ResumenEn los altlimos anos, la traduccion automata se ha vavelto muy exitosa para los pares de idiomas con altos recursos. Esto tambien ha despertado un nuevo interes en la investigacion sobre la traduccion automatica de idiomas de bayos recursos, incluidos los idiomas indigenas. Sin embargo, estos ultimos estan profundamente relacionados con los grupos indigenas que los halban (o solian hablar). La recopilacion de datos, modelar y desplegar sistemas de traduccion automatica da como resultado nouevas cuestiones eticas que deben abordarse. Motivados por esto, primero examinamos la literatura existente sobre las consideraciones eticas para la documentacion, la traduccion y el processariento general del lenguaje natural para las lengunas indigenas. Posteriormente, realizamos y analizamos un estudio de entrevistas para arrojar luz sobre las posiciones de los lideres comunitarios, maestros y activistas linguistics con respecto a las preccupaciones eticas sobre la traduccion automatica de sus idiomas. Nuestros resultados muestran que la inclusion, en diferentes grados, de hablantes nativos y miembros de la comunidad es vital para realizar una mejor investigacion y mas etica sobre las lenguas indigenas.

### Introduccion

Con el avance de los sistemas de traduccion automatica (MT) basados en datos, se ha vavelto possible, con diversos grados de calidad, traducir entre cualquier par de idiomas. La unica condicion previva es la disponibilitad de suficientes datos monolingues [18, 2] o paralelos [40, 37]. Hay muchas ventajas de tener sistemas de traduccion automatica de lato rendimiento. Por ejemplo, aumentan el accoso a la informacion para los habitantes de idiomas indigenas [56] y pueden apvador en los efuerzos de revitalizacion de estos idiomas [56].

La investigacion sobre la traduccion automatica, asi como el procesamiento del lenguaje natural (NLP), en general, se esta moviendo hacia entornos de bajas recursos y modelos multilingues. Por lo tanto, la comunidad de NLP necesita abrir la discusion sobre las repercusiones y las mejores practi-cas para la investigacion en lenguas infigenas (que en la mayoria de los casos tambien son de bajos recursos) y que las lenguas naturales no pueden existir sin una comunidad de personas que usan (o ban usado tradicionalmette).

Los idiomas indigenas difieren ademas de los mas utilizados de una manera crucial: son commente holalados por pequenas comuniddades, y muchas comuniddades usan su idioma (adenas de otras caracteristicas) como un delimitador para definir su propia identifad [9, 20], y tienen en muchos casos tambien un cierto grado de peligrosidad. Ademas, en algumos casos, informacion altamente confidencial, como aspectos secretos de su religion, ha sido codificada con la ayuda de su idioma [56]. Esta es la razon por la que, en los alltimos anos, se hen iniciado debates sobre enfoques eticos para estudiar lenguas en peligro [21, 22]. Cuando consideramos el passado (y presente) de algunas de las comunidades que hablan estos idiomas, encontraremos una historia colonial, donde la investigacion no es la excepcion [57]. Por lo tanto, es posible traspasar los limites eticos cuando se utilizan metodologias tipicas de recomplicacon de datos y NLP [56].

En este trabajo, explormos los conceptos basicos de etica relacionados con la MT de lenguas en peligro de extincion con un enfoque especial en las comunidades indigenas, examinationo trabajos previos sobre el tema. Para comprender mejor las expectativas y precupaciones relacionadas con el desarrollo de sistemas de MT para las comunidades indigenas, luego realizamos un estudio de entrevistas con 22 activistas linguisticos, profesores de idiomas y lideres comunitarios que son miembros de comunidades indigenas de America. Ademas, tambien realizamos dialogos 1:1 con dos participants del estudio para profundizar nuestra compression del asuto. El objeiro os responder las siguientes prepuntas de investigacion: ?_Como quien partic 

_ipar los miembros de la comunidad en el proceso de traduccion automatica y por que? ??? !Hay temas sensibles que no son eicos para traducir, modeler o recopilar datos sin ?el permiso explicito de la comunidad? ?? Como podemos recompilar datos de manera etica?_

Sorprendentemente, la mayoria de los participantes de la encuesta ven positivamente la traduccion automatica de sus idiomas. Sin embargo, creen que la investigacion sobre sus idiomas debee realizarse en estrecha colaboracion con los miembros de la comunidad. El acceso abierto a los descubrimientos y recursos de investigacion tambien se valora mucho, asi como la alta calidad de las traducciones resultantes. Las entrevistas personales tambien lo confirmaron. Por lo tanto, nuestro hallazgo mas importante es que es fundamentaltrabajar en estrecha colaboracion con las continuades para comprender temas eticos delicados al desarrollar sistemas de traduccion automatica para lengunas en peligro de extincion.

### Definiendo "lenguaje en peligro"

Los terminos que se usan con frecuencia en la NLP son _lenguaje de bajos recursos_, _lenguaje de pocos recursos_ y _configuracion de bajos recursos_. Esos terminos no resaltan el hecho de que muchos idiomas de bajos recursos tambien estan en peligro (Liu et al., 2022). En cambio, enfatizan el problema critico del aprendizaje automatico de lograr que un enfoque basado en datos funcione bien con un cantidad de datos disponible menor a la ideal (o simplemente menos datos que los que se han usado para otros idiomas). En este caso, se necessitan innovaciones algoritmicas o technologicas para cerrar la brecha de rendimiento entre los lenguajes de muchos recursos y los de pocos recursos. Esto implica ademas que tener pocos recursos no es un propiedad de un idioma singo un termino que solo tiene sentido en el contexto de una teraea o tareas en particular.

En contraste, el termino _lenguaje en peligro_ se freire a un idioma con cierto grado de peligro para su existencia.18 Los idiomas en peligro son relevantes para nuestro estudio, va que la mayoria de los idiomas indigenas tambien estan en peligro (Hale, 1992). Segun la clasticiscacion de la UNESCO, los idiomas en peligro (Moseley, 2010) se pueden claisificar en las siguientes categorias diferentes:

Footnote 18: En este documento, discutiremos sololo los idiomas creados no artificialmente.

* _saltudables_: halbaldo por todas las genericones;
* _vatherable_: restringido solo a un determinado dominio (es decir, dentro de la familia);
* _defintivamente en peligro_: no tiene ninos que hablen el idioma;
* _en grave peligro_: solo lo hahlan las personas mayores;
* _peligro crtico_: solo quedan habitantes con conocimiento parcial, y lo usan con poca frecuencia;
* _extinto_, cuando ya no haya personas capaces de hablar el idioma.

Los idiomas pueden estar en peligro debido a razones sociales, culturales y politictas; mas commentente conquistas y guerras, presiones economicas, politicas linguisticas de los poderes polificos, assimilacion de la cultura dominante, discriminancion y estandarizzacion linguistica (Austin and Sallabank, 2013). Como podemos ver, el problema de como un lengua se pone en peligro involucra factores que deben ser abordados en el enfoque ecico de causalquier estudio. Por el lado del aprendi azie automatico, surge un desafrio actional: los datos de los idiomas en peligro no estan facilmente dispionbles (o, de hecho, no estan disponibles en absoluto), ya que estos idiomastienen una produccion de medios limitada (programas de television, literatura, blogs de Internet; Hamalainen, 2021). Una posible fuente de datos para estos idiomas son los documentos y existentes en forma de libros, registtors y archivos (Bustamante et al., 2020).

### Etica y MT

Etica y datosEl estudio de las lenguas en peligro en las comunidades indipensa tiene un larga historia, y las preguntas mas destacadas se centran principalmente en el desafio de la recognizable de datos (Smith, 2021).

Una de las formas comunes de esto es usar la etica normativa (deontologia). Ejemplos de pautas relevantes incluyen las del Instituto Australiano de Estudios de los Aborigenes e Isenos del Estecho de Torres;19 la Declaracion etica de la Soc 

cidad Linguistica de America;20 y el codigo de conducta DOBES.21 Estas listas son el resultado de amplias discusiones que han tenido lugar durante decadas. En este debate tambien, las voces indigenas se alzaron dentro de la academia (Smith, 2021).

Footnote 23: [https://www.linguisticsociety.org/content/lsa-revised-ethics-statement-approved-july-2019](https://www.linguisticsociety.org/content/lsa-revised-ethics-statement-approved-july-2019)

Pero, cpor que tenemos tantos intentos de establecer un codigo etico para el trabajo de campo linguistico? Cuando se trata de trabajar con sociedades humanas, no existen soluciones faciles para los dilemas eticos que surgen (Dwyer, 2006). Cada situacion requiere un trato y compromiso unico. Por eso, ademas de la creacion de un marco lo mas general posible, la aplicacion concreta de tales principios implica una discusion continua. Dwyer (2006) sugiere documentar las cuestiones y preoccupaciones eticas que surgen durante el curso de un proyecto de investigacion y la forma en que sabordan estas cueestiones, de modo que otros investigadores puedan aprender de la experiencia. Si bien unc codigo de conducta o Principios es bueno, corre el riesgo de introducir regulaciones demasiado complicadas, o incluso inadecualas, relegando esta neccesaria discussion.

En general, podemos resumir los principios que apareccen en todas las listas sugeridas bajo tre grandes temas:

* _Consulta, Negocicacon y Entendimiento Mutuo_. El derecho a la consula de los peueblos indispensable esta estipalado en el convenio 167 de la Organizacion Internacional del Trabajo (Ilo, 1989) y establece que "tienen derecho a preservar y desarrollar sus propiais institicones, idiomas y culturas". Por lo tanto, informar a la comunidad sobre la investigaciion planificada, negocair un posible resultado y llegar a un acuerdo mutuo sobre las direcciones y los detalles del proyecto debe ocurri en todos los casos.
* _Respeto a la culura local y participacion_. Como cada comunidad tiene su propia cultura y vision del mundo, los investigadorres, assi como cualuquer organizacion gubernamental interesada en el proyecto, deben estar familiarados con la historia y las tradiciones de la communidad. Ademas, se debe recomendar que investigadores locales, oradores o gobiernos internos se involucren en el proyecto.
* _Compartir y distribuit datos e investigaciones_. El producto de la investigacion debe estar disponible para su uso por parte de la comunidad, para que puedan abrovechar los materiales generados, como documentos, libros o datos.

Algunos de estos principios commentente accordados estan abiertos a un acuerdo deben adaptarse a situaciones concretas, lo que podria no ser facil de hacer a traves de un enfaque general. Por ejemplo, el proceso de documentacion Creara datos, y la propiedad de estos datos es una fuente importante de discusion (cf. Secciones 4, 5). Aqui, los puntos de vista tradictionales de las comuniddades pueden contradecir el sistema juricloo de un pais (Daes, 1993). Este probema no tiene una solucion simple y debe considerarse cuidadosamineet al recopilar datos.

Un Ilamado adicional de estas fuentes es descolonizar la investigacion y dejar de ver a las comuniddades infigenas como fuentes de datos, sino como personas con su propia histororia (Smith, 2021). El divorcio actual entre los investigadores y las unidades culturales de las comuniddades puede llevar a reforzar el legado colonial (Leonard, 2020).

Como concentario final, queremos discutir la suposicion comun de que cualquier discusion etica debe terminar con una configuracion normativa para un campo. Esto reducira la trducción de toma de decisiones colectivas de los pueblos indigenas a normas que permitan un abordaje individual del asunito (Meza Salcedo, 2017). Esto lampoco permitira comprender las cuestiones eticas con su propia cosmovision indigenous comunal (Salcedo, 2016). Por lo tanto, en este texto pretendemos abrir el debate etico de la MT a los investigadores de la NLP va las comuniddades indigenas a partir de la inclusion y el dialogo.

Etica y _Traduccion humana_ Para una traduccion exitosa, la inclusion de todos los participantes emportante, requiriendo su particpicapacin equitativa, informal y orientada a la compression (Nissing and Muller, 2009). Para Rachels and Rachels (1986), la conception minima de la moralidad es que cuando damos "igual peso a los intereses de cada individivo afectado por la decision de uno". La pregunta es como las intenciones de los autores se relacionan con la otreda de la cultura de origen, 

con su valores culturalmente especificos (Chesterman, 2001). Segun Doherty (2016), "los estudios del proceso de traduccion surgieron para centralre en el traductor y el proceso de traduccion en lugar del producto final", incorporando disenos de metodos mixtos para obtener observaciones objetivas. Un ejemplo bien documentado del mal uso no etico de la traduccion es la aplicacion de la traduccion como instrumento para la dominacion colonial. El principal objetivo de esta vision colonialista era "civilizar a los salvajes" (Ludescher, 2001). Por elejemplo, el instituto linguistico de verano (ILV)22 se utilizo para este objetivo durante el siglo XX en paises con culturas indigenas, traduciendo la Bibilia y tratando de provocar un cambio cultural23 en estas comunidades (DelValls, 1978; Errington, 2001; Carey, 2010). Por supuesto, estas practicas no son nuevas y se pueden encontrar a lo largo de la historia (Gilmour, 2007). Es escencial tener en cuenta que la investigacion no etica aun puede brindar material y conocimientos ttiles, por epimplo, para la revitalzacion del idioma (Premsirrat and Malone, 2003), pero podria causar dano a la comunidad objetivo.

Footnote 22: ILV se describe a si mismo como “.., una organizzación muidial sin fines de lucro basada en la fe que trabaja con connuladdes locales de todo el mundo para desrarollar soluciones linguístas que amplien las posibilitados de una vida mejor. . Las principales afeas de contribucion de SIL son la traducción de la Bibilia, la alafhetizacion, le educación el descarrollo, la inversigacion linguisticx y las herramientias linguistics.”. [https://www.sil.org/El](https://www.sil.org/El) papel del SIL es controvertidó, y no se puede resumir en una sola declaración. En nuestro enfoque, solo nos referinos amal paper jugado en relacion coin el campio cultural. En muchcos casos, las comuniddades que incheron traducI tox testos religoisos y earn cristians, adadas las acciones de coloranizacon previas. Sin embargo, tambien hay casos en los que cumouldades no existanas tuvieron Biblias y otrostos textos religoisos traduelos a su idioma, con fines misoieros. Esto desendach gravisiones comunitaras. For eigenplo, la traduccion de los textos religisos al Wixarika (Fernandez, 2022). Esto tambien sucedio en la Comunidad de Zoquipan (en el estado mexicato de Nayariti), donde los cristanos, utilizando Ia Bibila traductida del IILV, desenedaranvon on conflicto intercomp en la comunidad (el primer autor es parte de esta comunidad). Para el lectore interesado, tambien recomendamos Dobrin (2009) articulo introductorio.

De traduccion final, que interactuara con el publico en general.

La recopilacion de datos es el primer y mas evidente problema cuandro se trata de traduccion. Los sistemas MT neuronales modernos requieren una gran cantiadd de datos paralelos para entrenarse de manera optima (Junczys-Dowmunt, 2019). Una forma de obtener datos es mediante el crowdsourcing (Fort et al., 2011). Sin embargo, este tipo de trabajo puede estar mal pagado y puede constituur un problema para las condiciones de vida de los trabajadotres (Schmidt, 2013). Ademas, la privacidad de los datos no es trivial de manejar. Los sistemas deben ser capaces de filtrar informacion confidential.

El problema de los sesgo s de codificacion24, como el sesgo de genero (Stanovsky et al., 2019), tambien es una preccupacion etica para MT. Tambien es necesario revelar las limitaciones y problemas con ciertos sistemas (Leidner and Plachouras, 2017).

Footnote 24: Tambienté es importante tener en cuenta las características tipologicas que podrian dificultar esto. Un ejemplo son los lenguajes polisiinteicos y los lenguajes sin codificacion de genero (Klavans, 2018).

Li mesvestigacion de la NLP tambien se puede utilizar como un instrumento politico de poder, donde podemos observvar las relaciones mutues entre el lenguaje, la sociedad y el individuo que "tambien son la fuente de los factores de impacto social de la NLP" (Horvath et al., 2017). De esta forma, la traduccion automatica se puede aplicar como un instrumento para cambiar la cultura de las minorias como en la traduccion tradicional (cf. Seccion 3.2). Enttonces, los colonizadores usaron la traduccion como medio de control imperial y exroppiacion (Cheyfritz, 1997; Ninranjana, 1992). La asimetaria de poder es la causa de la dominacion, donde las culturas subalternnas que se inundan con "imposiciones de materiales e idiomas extranjeros" son un peligo rael para las culturas minoritarias (Tymoczko, 2006). Schwartz (2022) discute la necesidad de descolonizar el enfoque cientffico de la comunidad de NLP en su conjunto, expressando la necesidad de que los investigadores sea conscinetes de la historia y los aspectos culturales de las comunidades que utilizan los idiomas con los que estan trabajande. Ademas, propone que nuestra investigacion de bener un obligacion de brandar algun beneficiio de nuestros estudios a las comunidades, una obligacion de rendicion de cuentas (y por lo tanto estar en contacto directo con sus organismmos rec 

tores) y una obligacion de no tener intenciones que contravengan los intereses de las comunidades. El hecho de que muchos sistemas de traduccion hoy en dia sean multilingues25 tambien resultan en mas desafios multiculturales (Hershcovich et al., 2022).

Footnote 25: Los sistemas multilinguales se refieren en NLP a sistemas capares de traducir un conjunto de idiomas desde ye hacia el ingles. En alguons casos, tambient son capaces de traducir ente idiomas donde el ingleds n o está involvadroso.

Finalmente, tambien queremos realtar la importancia de discuit los sistemas MT en una configuración de texto a texto. El uso del texto esta limitado a ciertos temas y varia de una comunidad a orta. Por ejemplo, el wixarika y el quencha, idiomas que se hablan en todas las generaciones, se usan de manera escrita principalmente en aplicacoines de mensajeria privada (como WhatsApp), pero tambien tienen una prolifica generalcaion de publicaciones en Meme y Facebook26. Inclus si una determinada comunidad no adopta amplamente la tradicion escrita, existen, como minimo, obligaciones legales de los Estados hacia las lenguas indigenas. Por ejemplo, algunas constituuciones reconocen las lenguas indigenas como lenguas niconicales (es decir, Mexico y Bolivia), obligando al Estado a la responsabilidad de traducir todas las paginas oficiales, documentos, leyes, etc., a las lenguas indigenas. Esto no se ha implementado, y este caso es un caso de aplicacion muy valioso para la traduccion automatica para avudar a la traduccion humana. Sin embargo, nuestros halazgos tambien se aplican a la traduccion de voz a texto y a las tareas de voz a voz que cubririan todos lio diomas, incluso sin tradcicion escrita.

Footnote 26: Or ejemplo, los memes vivariak: url-[https://www.facebook.com/memeswixarika?19](https://www.facebook.com/memeswixarika?19), grupo de habla quechua: [https://www.facebook.com/groups/711230846397383/](https://www.facebook.com/groups/711230846397383/)

### Las opiniones de los ordaores

Es importante incluir la opinion y la vision de los habitantes de lenguas en peligro de extincion en la investigaciion de la NLP, especialmente para temas como la MT. Por lo tanto, Ilevamos a cabo un estudio de encuesta con 22 activistas linguisticos, maestros y lideres commitarios de America. Es importante destacar que nuestro objetivo principal no es solo recopilar informacion cuantitativa sobre las preguntas ecicas relacionadas con la traduccion automatica para sus idiomas, singo tambien recompillar informacion cualitativa al pedirles que amplien sus respuestas. Ademas, tambien realizamos una entrevista con un subconjunto de dos participantes del estudio de entrevista inicial.

### Diseno del estudio

Enfecamas nuestro estudio en el continente Americano,27 seleccionando las siguientes comuniddades: asymara, chatino, maya, maatecco , mixe, nahua, otomi, quechua, tenek, telephone, kichwa de Otavalo y zapoteco. Queremos senalar que nuedstro estudio no pretende representar una opinion general de todos los pubelos indigenas, ni es una declaracion general final sobre el tema. Es un estudio de caso que anlora las opiniones de prugos especificos dehalantes de lenguas indigenas. Ademas, las opiniones de las personas entrevistadas son propias y no representn necesariamente la opinion de sus tribus, nacinoes o cumulidades.

Footnote 27: Dérentes partes del mutdo itenen niveles muy diferentes de consciencia, no solo por la historía colonial sino precisamente por las interacciones con los trabjadotes de campo.

**Aspectos Cuantitativos y Cualitativos** Para el estudio cuantitativo se utilizo una encuesta. Las encuestas son una tecnica bien establecida para ser utilizada con comunidades indigenous con una extensa historia y son utilizadas y documentadas por clasicos como Edward Tylor, Anthony Wallace, Lewis Henry Morgan. Esto tambien es cierto para reconocidos autropologos sociales mexicanos (indigenas comprometidos) (Jimenez and Ramos, 1985; Alfredo and Alberto, 1978).

Para la parte cuallitativa, revisamos documentos de posicion existentes y articulos de investigadores y activistas indigenas. Ademas, utilizamos preguntas abietras en la encuesta, lo que permite extender la vision puramente cuantitativa a una cualiitativa. Finalmente, realizamos dos entrevistas 1 a 1 con unactivista (mixe) y un linguusta (chatino).

**Reclutamiento de participantes** Nos pusimos en contacto con participants potenciales de tres maneras. Nuestro primer enfoque fue establecer comunicacion a travers de los stiios web oficiales del proyecto de los participantes potenciales o cuentas publicas en linea. Esto incluye las paginas de correo electronico, Twitter, Facebook e Instagram. Nuestro segundo enfoque fue contactar directamente a las personas de nuestro grippo objetvo con quigenes al menos une do les coautores yha establecido una relacion de trabajo. Por ultimo, tambien publicamos una convocatoria de participacion en las redes sociales, y morphobamos si los voluntarios perteneceen a nuestro gruppo objettivo. Los objetivos de nuestra investigacion, asf como 

el alcance y manejo de datos, se explican directamente a cada participante y tambien se incluyen en el formulario final. No recopilamos ninguna informacion personal sobre los participants, como nombre, sexo, edad, etc. Todos los participantes del estudio son voluntarios.

CuestionarioNuestro estudio consta de 12 preguntas. Las primeras tres pregnantas son generales: prepantan por la tribu, nacion o pueblo indigena al que pertenece el participante; si se identifica a si mismo como activista, lider continuario o maetstro, y por su fluidez en su idioma. Las pregnutas restantes se unfecan en politictas de datos, politicas de inclusion, beneficiios y peligros de los sistemas MT y mejores practicas de investigacion. El cuestionario completo esta disponibles en el apendice A. Las preguntas estan disponibles en ingles y espanol, pero solo se ha completado un formulario en inples, mientras que el restore se ha completado en espanol. Por lo tanto, los autores han traducido automaticamente todos los concentarios que se muestran en este documento al Ingles.

### Resultados

Los resultados del estudio se pueden ver en la Figura 1. Ademas, tambien discuitmos las respuestas abiertas a cada negunta para brindar mas informacion.

Inclusion de halhantes nativos y permisos para estudiar el idiomaLa figura 1(a) muestra que el 77,3% de los participantes informan que su connumidad no tiene restricciones con respecto a compartir su idioma con personas externas. Los commentarios para esta prespanta muestran que muchos participiantes estan orgullosos de su idioma y herencia: "Somos solidarios y comparrimos nuestras ratices. Orgullosos de quien nos visita" Incluso entornamos pronunciamientons mas fuertes contra la prohibicion de compartir: "Nade tiene derecho a restringir la difusion de la lengua". Sin embargo, tambien existen commuldades con restricciones. Por lo tanto, concliumos que los investigators no pueden asumir por defecto que todos dos grupos indigenous estarian de acuerdo en compartir informacion sobre su idioma o que estarian contentos con la investigacion sobre el mismo.

Beneficios y Peligros de los sistemas MTLa figura 1(b) muestra que une gran mayoria de nuestros participantes piensa que un sistema de traducicon automatica para su idioma seria beneficoso. Sin embargo, tambien hay un numero importante de personas que ven al menos algun grado de peligo. En este caso, necestimos mirar los comentiors do les participantes para entender sus precupaciones. En primer lugar, encontramos que una de las principales preoccupaciones de los participanteses le calidad de la traduccion. El miedo a las traduccions inadequadas de los termininos culturales tambien es importante. En la Tabla 2, podemosver un conjuncto de cometarios que ilustran estos temores. Un comcentario interessante se refere al miedo a la estandarizacion del lenguaje de los participantes, lo que podria conduciv a una perdida de diversidad. En la misma tabla, tambien podemosver los beneficiios que esperan los participantes, principalmente en educaccion y en elevar el estatus y la utilidad de sus idiomas.

La tabla 1 muestra agunas respuesta s a la pregunta abierta sobre posibles temas que podrian causar dano a la comunidad. La mayoria de las respuestas no pudieron identifier angun tema possible que pudiera ser peligroso. Sin embargo, la segunda respuesta mas frecuente estuvo relacionada con la religion. Algunas respuestas estan preocupadas de que se puedan revelar antiguos secretos ceremoniales. Otros tambien muestran preoccupiedon por la influencia de las religiones occidentales. Esto nos Ileva a la pregunta de si la Biblia (Christodoulouopoulos and Steedman, 2015; McCarthy et al., 2020; Agic and Vulic, 2019) es adecuada para usar como nuestro corpus predeterminado para MT, cuando se trata de un idioma indigena. Finalmente, tambien algunas respuestas expresaron que el uso de lenguasi infgenas en la organizacion interna de la comunidad podria estar en peligro con los sistemas de MT. En contraste, la figura 1(c) muestra los temas que registraron esa evaluacion mas positiva: charlas cotidianas (15), ciencia y educacion (14), cultura y tradiciones (14), y medicina y salud (14).

Participencion de miembros de communidades indigenas en la investigacionLa figura 1(d) muestra que los participantes de nuestro estudio piensenque es importante inclur personas de las comunidades objeitivo en los proyectos de investigacion. Esto confirma la experiencia en linguistica, donde incontratron un patron similar (Smith, 2021) (ver SS3.1). Es importante senalar que solo se indico una respuesta de que se necessita permiso oficial para realizar el estudio. En los comentarios se menciono el dereecho a la consulta, junto con las ventajas de 

involucrar a los miembros de la comunidad en la investigacion: "Es preferible [integrar a personas de la comunidad] para obtener un buen sistema, y no solo tener aproximaciones, porque solo los miembros de la cultura saben como se usa el idioma."; "Para que se enriquezca el vocabulario y no se impongan algunas palabras que no existen."; "Realizar actividades donde la comunidad se pueda involucrar, ganzar- ganar.".

**Uso de datos y calidad de traduccion** Con respecto a la propiedad y accesibilidad de los datos, encontramos diversos conjuntos de respuestas. Primero, la Figura 1(e) muestra muchas opiniones diferentes. En general, podemos decir que exsite una fuerte tendencia a favorecer que los datos deben estar disponibles publicamente. Sin embargo, cuando se trata de la propiedad de los datos, las opiniones son mas diversas. Sorprendentemente, un numero importante de participantes (\(17\%\)) piensa que el grupo de investigacion externo deberia ser el proprietario de los datos. Sin embargo, un mayor numero de participants' piensa que los datos deberian ser propiedad de la comunidad (\(29,4\%\)), y un 20,6% piensa que deberian ser propiedad de los pionentes que participanen en la investigacion. Este es un tema complejo, ya que las normas tradicionales y losistemas legales modernos interacettian (cf. Seccoion 3.1). En los commentarios entornamos tristes ejmplos de desconfianza en las instituciones academicas. Por ejempllo, un comcentario habla de los problemas previos de su tribu, ya que las grabaciones y otros materiales tomados por los linguustas no son accesibles para ellos: "Cuidade con las instituciones academicas va que actualmente tenemos problemas para acceder a las grabaciones que pertenecen a academics y bibliotecas y no son publicas.". Sin embargo, en general, vemos una amplia gama de opiniones: "Debe valorarse el trabajo de los pocos que se toman en serio la identidad linguistica", "Puede ser publico peero siempre con el aval y consentimiento de la comunidad". Esta diversidad demuestra que existe la necesidad de que los investigaderes tengan una relacion cercana con las comunidades para ententer los antecedentes y los objetivos de cada caso en particular.

Como se discutio anteriormete, la calidad del sistema final es una preccupacion importante para muchos participantes. En la Figura 1(f) podemos ver que publicar un sistema MT experimental tambien es controvertido. La posibilidad de utilizar un sistema experimental gusta a \(54,8\%\) de nuetwors participantes, que es ligeramente superior al numero de participantes que estan en contra (\(45,5\%\)). Algunas opiniones en contra estan en linea con precupaciones anteriores sobre traducciones incorrectas de contenido cultural: "Algo que esta desprovisto de estructura y objetividad cultural no es no se puede poner a disposicion del publico" y "... se causaria daño a la lengua y sus representantes ya que los estudiantes aprenderian de forma inconrecta". La mayoria de las personas con un opinion positiva estan de caverdo en que un sistema inicialmente pobre podria mejorarse con el tiempo: "Si pudiera mejorarse y corregirse, seria excelente".

### Discusion

En la Seccion 3 examiniumamos el debate en curso sobre la etica en la documentacion, la traduccion, antes de presentar un estudio de entrevista en la Seccion 4. Ahora discutimos algunos de los problemas mas importantes que hemos identificado en la ulima seccion con mas profundidad.

**Necesidad de consultas con las comunidaddes Experiencias anteriores**Bird, 2020; Liu et al., 2022) asi como nuestro estudio resaltan la necessidad de consultant con las cumuladades indigenas cuando se realizan investigaciones relacionadas con sus idiomas28. En algunos casos, el requisito mimo expresado es informar a los penentes sobre los nuevs avances tencologicos. La retroalimentacio y los controles de calcidad tambien son cruciales para los sittemas de traduccion automatica e importantes para los miembros de las comunidades. Esta consultia debe incluir el dialog intercellulara ya que ha sido un instrumento central en la toma de decisiones de las comunidades indigenas (Beauclair, 2010). Recommendamos hacer esto integrando a los miembros de la comunidad en el cielo y, por supuesto, dandoles el credito que se mereccen.

Footnote 28: Un ejempllo de un trabajo de campo comprometidó con la comunidad es Czaykowska-Higgins (2009)

**Sistemas legales versus visiones tradictionales de la propiedad del conociniento comunal Los sistemas legales y, con eso, las leyes de derechos de autor varian segun el pais. Sin embargo, las lieves a veces estan en conflicto con los puntos de vista tradicionales de los puelbos infgenas (Dwyer, 2006). Por lo tanto, cuando se trabaja con continuides indigenas, recomendamos discuit y acordar los derechos de propi 

los participantes del estudio antes de comenzar el traabajo para encontrar un arreglo con el que todos esten contentons. Tambien nos gustaria senalar que, segun nuestro estudio de caso, la sensacion general es que los datos y los resultados de la investigacion deben ser accesibles para la comunidad que habla el idioma. Esto contradice la practica de algunos esfuerzos de documentciaou que cierran los datos recopilados al poblico e incluso a los halbantes de la comunidad (Avelino, 2021). Algunos participants en nuestro estudio incluso sugieren el uso de Creative Commons (CC)29 para los datos. Sin embargo, el uso de CC podria no ser la mejor opcion de licencia, va que no esta disenado especificamente para las necesidades de los indigenas. Finalmente, siempre que los datos recopilados se utilicen para uso comercial, los acuer dos especiales que involucra aspectos financeros son cruciales.

Footnote 38: [https://www.ecativecommons.org/licenses/](https://www.ecativecommons.org/licenses/)

PermisosAlgunas cumuladdes requieren que s obtenga un permiso de su entiad gobernante cuando alguien, que no es miembro, quiere estudiar su idioma. Esto puede ser dififici yque a veeces no existe una autoridad central. Averiguar de quien obtener el permiso puede ser un desafio en tales escenarios. Sin embargo, como vemos en este estudio, muchas comuniddades no requieren este permiso. Un proyecto promoted que pretende simplificar este tema son las etiquetas KP30. Es un conjunto de etiquetas que las comunidades pueden usar para expresar sus permisos y voluntad de cooperar con investigadeores y proyectos externos.

Footnote 30: [https://localcontexts.org/labels/tracional-concomientento-etiquetas/](https://localcontexts.org/labels/tracional-concomientento-etiquetas/)

Datos personalesDe las respuestas abiertas, aprendemos ademas que, para muchos hablantes, usar su proppio idioma en su entorno diario les Ayuda a proteger su privaciidad: Sus conversaciones solo pueden ser entendidas por su familia o entorno cercano. Sin embargo, esta preoccupacin por el maneno de datos tambien es valida para otros lenguajes.

Precupaciones sobre Informacion Privada de la ComunidadEl punto anterior puede extersexe au mas a las asambleas y orras reuniones organizacionales, donde se utiliza la barrera del idioma para mantener en privado sus decisiones o estrategias. Esta es una preccupacion que tienen las compunidades con MT y los posibles temas que podrian ser perjudiciales para ellos. Algunas continuadas tambien tienen precupaciones generales acerca de compartir su idioma con personasajanas a la comunidad (por ejemplo, la controversia del Diccionario Hori (Hill, 2002)). Para este caso, es importante no abordar este tema desde un punto de vista legal occidental e iracia las practicas y normalas tradicionales de gobierno interno y la consulta con las comunidades.

La religion y la BibiliaCon respecto a los dominios problematicos para MT, varios participantes de la encuesta mencionaron la religigon. Esto es bastante relevante para la comunidad de NLP, y que el recurso mas amplio disponible actualmente para los idiomas minoritarios es la Biblia. Como so vio en la Seccion 3.2, el uso colonial de la traducción de textos religiosos (Niranjanja, 1990) es precismente el origen de estos conflictos. Por lo tanto, recomendamos que los investigadecres de NLP y MT usen la Biblia con cuidado, a traves de un processo de consula, y consideren sus impactos. Sin embargo, sin una relacion cercana con cada comunidad (por ejemplo, en un experimento masivo de MT multilingue), la recomendacon es evitar el uso de la Biblia.

Teenologia y soderania de los datosTener technologia para sus propios idiomas es bien visto por la mayoria de los participantes del estudio. Sin embargo, tambien encontramos un fuerte desco de participipar directamente en el desarrollo de sistemas MT. Esto requiere unayor inclusion de investigaderes indigenas en la PNL. Por lo tanto, la formacion de investigaderes e ingenieros infogenas e unsa tarea importante que recomendamos sea valorada mas por las comunidades de NLP y MT. Somos conscientes de que las designaldades existentes no se pueden eliminar de immediato o de forma aislada, pe rodos pueden brindar su appoyo.31 La creacion de un proceso colaborativo es una propuesta que surge de las propias comunidades: "Tecnologia como Tequio; la creacion tecnologica y la innovacion como bien comun" (Aguilar-Gil, 2020). Sin embargo, no es posible construit tenologistas contemporaneas de NLP sin datos. Y esto abre la discusion sobre la Soberania de los Datos. En primer lugar, es importante mencionar que las comunidades tienen derecho a la autodeterminacion, y esto incluye los datos que generan. Aplicar esta soberania a los datos se refire 

tener control sobre los datos, el conocimiento32 y cultural. expresiones que son creadas por estas comunidades. Como se discute en este documento, es importante llegar a cauerdos con las cumulades a traves de consultas y colaboraciones directas. Esto incluye la concesion de licencias y la propiedad de los productos de datos finales.

Footnote 31: [https://indigenousinnovate.org/downloads/indigenous-knowledge-and-data-go](https://indigenousinnovate.org/downloads/indigenous-knowledge-and-data-go)

Nuestros hallazgos y trabajos anteriores Filanmente, queremos relacionar nuestros hallazgos con discusiones similares en trabajos anteriores. La mayoria de las inquietudes y sugerencias anteriores relacionalas con la inclusion y consulta de personas de las comunidades (Bird, 2020; Liu et al., 2022) estan alineadas con los desceys van anhelos de los participantes en nuestro estudio. La inclusión de miembros de la comunidad como coautores (Liu et al., 2022) no debe ser una mecanica artificial, sino mas bien un proceso de inclusion amplio, que incluyve la soberania de los datos y la tecnologia. Esto tambien esta allineado con la construccion de la comunidad a la que apunta Zhang et al. (2022). Ademas, debemos considerar que pueden existir temas problematicos y no subestimar la importancia de las traducciones de alta calidad.

### Conclusion

En este trabajo, que se centra en los desafios eicos para la MT de las lengunas indigenas, primero brindamos una descripicion general de los enfoques eticos relevantes, los desafios eticos para la traduccion en general y los desafios mas especificos para la traduccion automatica. Luego, Ilevamos a cabo un estudio de caso, para el cual entrevistamos a activistas de lengues infgenas, profseores de idiomas y Ideres commitarios de las Americas. Nuestros hallazgos se alinearon con hallazzgos previos con respecto a la necesidad de inclusion y consulta con las comunidades cuando se trabaja con datos linguistics. Ademas, nuestros participants empresaron un interes sorprendentemente fuerte en tener sistemas de traduccion automatica para sus idiomas, pero tambien precupaciones sobre el uso commercial, el mal use cultural y religigoso, los datos y la soberania tecnologica. Terminamos con recomendaciones especificas para las comunidades de NLP y MT, pero ann mas importante, un macro de discusion abierto para las comunidades indigenas.

 



**ACL 2023 Responsible NLP Checklist+**

Footnote †: margin: The Responsible NLP Checklist used at ACL 2023 is adopted from NAACL 2022, with the addition of a question on AI writing assistance.

A For every submission: A1. Did you describe the limitations of your work? A2. Did you discuss any potential risks of your work? A3. Do the abstract and introduction summarize the paper's main claims? A4. Have you used AI writing assistants when working on this paper? Left blank. B Did you use or create scientific artifacts? Left blank. B B. Did you cite the creators of artifacts you used? Not applicable. Left blank. B2. Did you discuss the license or terms for use and / or distribution of any artifacts? Not applicable. Left blank. B3. Did you discuss if your use of existing artifact(s) was consistent with their intended use, provided that it was specified? For the artifacts you create, do you specify intended use and whether that is compatible with the original access conditions (in particular, derivatives of data accessed for research purposes should not be used outside of research contexts)? Not applicable. Left blank. B4. Did you discuss the steps taken to check whether the data that was collected / used contains any information that names or uniquely identifies individual people or offensive content, and the steps taken to protect / anonymize it? A5. Did you provide documentation of the artifacts, e.g., coverage of domains, languages, and linguistic phenomena, demographic groups represented, etc.? A6. Did you report relevant statistics like the number of examples, details of train / test / dev splits, etc. for the data that you used / created? Even for commonly-used benchmark datasets, include the number of examples in train / validation / test splits, as these provide necessary context for a reader to understand experimental results. For example, small differences in accuracy on large test sets may be significant, while on small test sets they may not be. Not applicable. Left blank. C Did you run computational experiments? Left blank. C1. Did you report the number of parameters in the models used, the total computational budget (e.g., GPU hours), and computing infrastructure used? Not applicable. Left blank.



* C2. Did you discuss the experimental setup, including hyperparameter search and best-found hyperparameter values? _Not applicable. Left blank._
* C3. Did you report descriptive statistics about your results (e.g., error bars around results, summary statistics from sets of experiments), and is it transparent whether you are reporting the max, mean, etc. or just a single run? _Not applicable. Left blank._
* C4. If you used existing packages (e.g., for preprocessing, for normalization, or for evaluation), did you report the implementation, model, and parameter settings used (e.g., NLTK, Spacy, ROUGE, etc.)? _Not applicable. Left blank._
* D **Did you use human annotators (e.g., crowdworkers) or research with human participants?** _Left blank._
* D1. Did you report the full text of instructions given to participants, including e.g., screenshots, disclaimers of any risks to participants or annotators, etc.? _4.1 and Appendix A_
* D2. Did you report information about how you recruited (e.g., crowdsourcing platform, students) and paid participants, and discuss if such payment is adequate given the participants' demographic (e.g., country of residence)? _4.1_
* D3. Did you discuss whether and how consent was obtained from people whose data you're using/curating? For example, if you collected data via crowdsourcing, did your instructions to crowdworkers explain how the data would be used? _4.1_
* D4. Was the data collection protocol approved (or determined exempt) by an ethics review board? _Ethic guidelines follow. Explained in Ethic Stantent._
* D5. Did you report the basic demographic and geographic characteristics of the annotator population that is the source of the data? _Discussed in 4.1. We aim for a complete anonymization._