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Annual Review of Linguistics

Volume 9, 2023

Ethics in Linguistics

Abstract

In linguistics, ethics has long encompassed matters typically covered under regulatory oversight, but it is increasingly understood as relational and reciprocal, conferring responsibilities and obligations that extend beyond the work produced for other researchers. Those who study language are also coming to interrogate their professional responsibilities not only in how research is done but also in how research is conceived, framed, reported, discussed, and taught, as part of larger discussions around decolonization, intersectionality, and social justice. In this article, we review existing literature on ethics in linguistics, both as it relates to research and as it relates to broader practices, which we then situate within ongoing conversations across subfields. The overarching frame for our discussion is that ethical practice and scientific validity are aligned, and that dismantling dominant discourses and normative practices will serve to advance the work linguists do in meaningful ways.

Keyword(s): ethical praxis, regulatory ethics, relational ethics, scientific validity
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/content/journals/10.1146/annurev-linguistics-031120-015324
2023-01-17
2024-04-27
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Literature Cited

  1. Ahmed S. 2013. Making feminist points. feministkilljoys Sept. 11. http://feministkilljoys.com/2013/09/11/making-feminist-points/
    [Google Scholar]
  2. Austin PK. 2017. Language documentation and legacy text materials. Asian Afr. Lang. Linguist. 11:23–44
     [Google Scholar]
  3. Barocas S, Crawford K, Shapiro A, Wallach H. 2017. The problem with bias: allocative versus representational harms in machine learning Paper presented at 9th Annual Conference of the Special Interest Group for Computing, Information and Society (SIGSIS) Philadelphia: Oct. 29
  4. Bender EM. 2019. The #BenderRule: on naming the languages we study and why it matters. The Gradient Sept. 14. https://thegradient.pub/the-benderrule-on-naming-the-languages-we-study-and-why-it-matters/
    [Google Scholar]
  5. Bender EM, Friedman B. 2018. Data statements for natural language processing: toward mitigating system bias and enabling better science. Trans. Assoc. Comput. Linguist. 6:587–604
     [Google Scholar]
  6. Bender EM, Friedman B, McMillan-Major A. 2021. A guide for writing data statements for natural language processing Guide, Tech Policy Lab, Univ. Wash., Seattle. https://techpolicylab.uw.edu/wp-content/uploads/2021/11/Data_Statements_Guide_V2.pdf
  7. Benjamin R. 2019. Race After Technology: Abolitionist Tools for the New Jim Code. Cambridge, UK: Polity
  8. Berez-Kroeker AL, Andreassen HN, Gawne L, Holton G, Kung SS et al. 2018. The Austin principles Guide, Res. Data Alliance/Linguist. Data Interest Group, Arctic Univ. Nor. Tromsø: https://site.uit.no/linguisticsdatacitation/austinprinciples/
  9. Beygelzimer A, Dauphin Y, Liang P, Wortman Vaughan J 2021. Introducing the NeurIPS 2021 paper checklist. Neural Information Processing Systems Conference Blog March 26. https://neuripsconf.medium.com/introducing-the-neurips-2021-paper-checklist-3220d6df500b
    [Google Scholar]
  10. Birhane A. 2021. Algorithmic injustice: a relational ethics approach. Patterns 2:1–9
     [Google Scholar]
  11. Bowern C 2003. Laves’ Bardi texts. Maintaining the Links. Language, Identity and the Land: Proceedings of the 7th Conference of the Foundation for Endangered Languages (FEL VII) J Blythe 137–43 Morrisville, NC: Lulu
     [Google Scholar]
  12. Bowern C. 2010. Fieldwork and the IRB: a snapshot. Language 86:4897–905
     [Google Scholar]
  13. Brown T, Mann B, Ryder N, Subbiah M, Kaplan JD et al. 2020. Language models are few-shot learners. Proceedings of the 33rd Conference on Neural Information Processing Systems (NeurIPS 2020)1877–901 Red Hook, NY: Curran
     [Google Scholar]
  14. Browne S. 2015. Dark Matters: On the Surveillance of Blackness Durham, NC: Duke Univ. Press
  15. Calhoun K, Charity Hudley AH, Bucholtz M, Exford J, Johnson B 2021. Attracting Black students to linguistics through a Black-centered Introduction to Linguistics course. Language 97:1e12–38
     [Google Scholar]
  16. Cameron D, Frazer E, Harvey P, Rampton MBH, Richardson K. 1992. Researching Language: Issues of Power and Method Oxford, UK: Routledge
  17. Cépeda P, Kotek H, Pabst K, Syrett K. 2021. Gender bias in linguistics textbooks: Has anything changed since Macaulay & Brice 1997?. Language 97:4678–702
     [Google Scholar]
  18. Charity Hudley AH, Mallinson C 2019. LSA statement on race Public Statement, LSA Washington, DC: https://www.linguisticsociety.org/content/lsa-statement-race
  19. Charity Hudley AH, Mallinson C, Berry-Mccrea EL, Muwwakkil J 2020. Empowering African-American student voices in college. Reconceptualizing the Role of Critical Dialogue in American Classrooms: Promoting Equity Through Dialogic Education A Kibler, G Valdés, A Walqui 157–84 Oxford, UK: Routledge
     [Google Scholar]
  20. Charity Hudley AH, Mallinson C, Bucholtz M, Flores N, Holliday N et al. 2018. Linguistics and race: an interdisciplinary approach towards an LSA statement on race. Proc. Linguist. Soc. Am. 3:11–14
     [Google Scholar]
  21. Cheng LSP, Burgess D, Vernooij N, Solis-Barroso C, McDermott A et al. 2020. The problematic concept of native speaker in psycholinguistics: replacing vague and harmful terminology with inclusive and accurate measures. Front. Psychol. 12:3186–205
     [Google Scholar]
  22. Chilisa B. 2012. Indigenous Research Methodologies London: Sage
  23. CIHR (Can. Inst. Health Res.), NSERC (Nat. Sci. Eng. Res. Counc.), SSHRC (Soc. Sci. Humanit. Res. Counc.) 2018. Ethical conduct for research involving humans (TCPS 2) Policy Statement, Secr. Responsible Conduct Res. Ottawa:
     [Google Scholar]
  24. Conzett P, De Smedt K. 2022. Guidance for citing linguistic data. The Open Handbook of Linguistic Data Management AL Berez-Kroeker 143–55 Cambridge, MA: MIT Press
     [Google Scholar]
  25. Crowley T. 2007. Field Linguistics: A Beginner's Guide Oxford, UK: Oxford Univ. Press
  26. Czaykowska-Higgins E 2009. Research models, community engagement, and linguistic fieldwork: reflections on working within Canadian Indigenous communities. Lang. Doc. Conserv. 3:15–50
     [Google Scholar]
  27. Czaykowska-Higgins E 2018. Reflections on ethics: re-humanizing linguistics, building relations across difference. Reflections on Language Documentation 20 Years After Himmelmann 1998 M Bradley 110–21 Honolulu: Univ. Hawai'i Press. Lang. Doc. Conserv. Spec. Publ. 15
     [Google Scholar]
  28. Dalzell S. 2020. Government coronavirus messages left ‘nonsensical’ after being translated into other languages. ABC News Aug. 12. https://www.abc.net.au/news/2020-08-13/coronavirus-messages-translated-to-nonsense-in-other-languages/12550520?nw=0
    [Google Scholar]
  29. D'Arcy A 2022. IRBs, researchers, and social media as (socio)linguistic field sites. Dimensions of Linguistic Variation C Cieri Oxford, UK: Oxford Univ. Press In press
    [Google Scholar]
  30. D'Arcy A, Salmons J 2021. Peer review in linguistics journals: best practices and emerging standards. Language 97:4e383–407
     [Google Scholar]
  31. D'Arcy A, Young TM 2012. Ethics and social media: implications for sociolinguistics in the networked public. J. Socioling. 16:4532–46
     [Google Scholar]
  32. Dastin J. 2018. Amazon scraps secret AI recruiting tool that showed bias against women. Reuters Oct. 10. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G
    [Google Scholar]
  33. Davis JL. 2017. Resisting rhetorics of language endangerment: reclamation through Indigenous language survivance. Lang. Doc. Descr. 14:37–58
     [Google Scholar]
  34. De Costa PI 2015. Ethics in applied linguistics research. Research Methods in Applied Linguistics: A Practical Resource B Paltridge, A Phaekti 245–57 London: Bloomsbury
     [Google Scholar]
  35. DeGraff M. 2020. Toward racial justice in linguistics: the case of Creole studies (response to Charity Hudley et al.). Language 96:4e292–306
     [Google Scholar]
  36. Denis D, D'Arcy A 2022. American Speech, settler colonialism, and a view from a place currently known as Canada. Am. Speech 97:144–50
     [Google Scholar]
  37. Dobrin LM, Berson J. 2011. Speakers and language documentation. The Cambridge Handbook of Endangered Languages PK Austin 187–211 Cambridge, UK: Cambridge Univ. Press
     [Google Scholar]
  38. Dobrin LM, Schwartz S. 2016. Collaboration or participant observation? Rethinking models of “linguistic social work. .” Lang. Doc. Conserv. 10:253–77
     [Google Scholar]
  39. Dobrin LM, Schwartz S. 2021. The social lives of linguistic legacy materials. Lang. Doc. Descr. 21:1–36
     [Google Scholar]
  40. Dorian NC. 1993. A response to Ladefoged's other view of endangered languages. Language 69:3575–79
     [Google Scholar]
  41. Duff PA, Abdi K. 2015. Negotiating ethical research engagements in multilingual ethnographic studies in education. Ethics in Applied Linguistics Research PI De Costa 121–41 New York: Routledge
     [Google Scholar]
  42. Dwyer A 2006. Ethics and practicalities of cooperative fieldwork and analysis. Essentials of Language Documentation J Gippert 31–66 Berlin/New York: Mouton de Gruyter
     [Google Scholar]
  43. Dym B, Fiesler C. 2020. Ethical and privacy considerations for research using online fandom data. Transform. Works Cult. 33: https://doi.org/10.3983/twc.2020.1733
    [Crossref] [Google Scholar]
  44. Eckert P, Rickford JR, eds. 2001. Style and Sociolinguistic Variation Cambridge, UK: Cambridge Univ. Press
  45. Errington J. 2001. Colonial linguistics. Annu. Rev. Anthropol. 30:19–39
     [Google Scholar]
  46. Errington J. 2008. Linguistics in a Colonial World: A Story of Language, Meaning, and Power Malden, MA: Blackwell
  47. Fiesler C, Proferes N 2018. ‘Participant’ perceptions of Twitter research ethics. Soc. Media Soc. 4:1–14
     [Google Scholar]
  48. Figueroa M. 2022. Podcasting past the paywall: how diverse media allows more equitable participation in linguistic science. Annu. Rev. Appl. Linguist. 42:40–46
     [Google Scholar]
  49. Flores N, Rosa J. 2015. Undoing appropriateness: raciolinguistic ideologies and language diversity in education. Harvard Educ. Rev. 85:2149–71
     [Google Scholar]
  50. Fort K, Adda G, Bretonnel KC. 2011. Amazon Mechanical Turk: gold mine or coal mine?. Comput. Linguist. 37:2413–20
     [Google Scholar]
  51. Fort K, Adda G, Bretonnel KC, eds. 2016. TAL et éthique. Traitement Autom. Lang. 57:2)
     [Google Scholar]
  52. Friedman B, Hendry DG. 2019. Value Sensitive Design: Shaping Technology with Moral Imagination Cambridge, MA: MIT Press
  53. Friedman B, Khan PH, Borning A, Zhang P 2006. Value sensitive design and information systems. Human-Computer Interaction in Management Information Systems: Foundations P Zhang 348–72 Armonk, NY: Sharpe
     [Google Scholar]
  54. Gal S, Irvine JT. 1995. The boundaries of languages and disciplines: how ideologies construct difference. Soc. Res. 62:967–1001
     [Google Scholar]
  55. Gebru T, Morgenstern J, Vecchione B, Wortman Vaughan J, Wallach H et al. 2018. Datasheets for datasets Paper presented at 5th Workshop on Fairness, Accountability, and Transparency in Machine Learning Stockholm: July 15
  56. Gebru T, Morgenstern J, Vecchione B, Wortman Vaughan J, Wallach H et al. 2021. Datasheets for datasets. Commun. ACM 64:1286–92
     [Google Scholar]
  57. Gray M, Suri S. 2019. Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass Boston: Houghton Mifflin Harcourt
  58. Guillemin M, Gillam L. 2004. Ethics, reflexivity, and ‘ethically important moments’ in research. Qual. Inq. 10:261–280
     [Google Scholar]
  59. Hale K. 1972. Some questions about anthropological linguistics. The Role of Native Knowledge: Reinventing Anthropology D Hymes 382–400 New York: Pantheon
     [Google Scholar]
  60. Hallinan B, Brubaker JR, Fiesler C. 2019. Unexpected expectations: public reaction to the Facebook emotional contagion study. New Med. Soc. 22:61076–94
     [Google Scholar]
  61. Haven TL, Van Grootel L. 2019. Preregistering qualitative research. Account. Res. 26:3229–44
     [Google Scholar]
  62. Henrich J, Heine SJ, Norenzayan A. 2010. The weirdest people in the world?. Behav. Brain Sci. 33:2/361–83
     [Google Scholar]
  63. Hern A. 2017. Facebook translates ‘good morning’ into ‘attack them’, leading to arrest. The Guardian Oct. 24. https://www.theguardian.com/technology/2017/oct/24/facebook-palestine-israel-translates-good-morning-attack-them-arrest
    [Google Scholar]
  64. Holliday N (@mixedlinguist) 2020. Introducing the Holliday rule for ling papers, summarized as “It's alright to say they're white.” If you got participants, you should ask their race(s), tell us what they said, even if they're white! h/t @kirbyconrod for the idea, & @emilybender for pioneering this kinda rule!. Twitter Dec. 2, 11:04 am. https://twitter.com/mixedlinguist/status/1334211797377818624
    [Google Scholar]
  65. Holton G. 2009. Relatively ethical: a comparison of linguistic research paradigms in Alaska and Indonesia. Lang. Doc. Conserv. 3:2161–75
     [Google Scholar]
  66. Holton G, Leonard WY, Pulsifer PL. 2022. Indigenous peoples, ethics, and linguistic data. The Open Handbook of Linguistic Data Management AL Berez-Kroeker 49–60 Cambridge, MA: MIT Press
     [Google Scholar]
  67. Hovy D, Spruit SL. 2016. The social impact of natural language processing. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, Vol. 2591–98 Stroudsburg, PA: Assoc. Comput. Linguist.
     [Google Scholar]
  68. Innes P. 2010. Ethical problems in archival research: beyond accessibility. Lang. Commun. 30:198–203
     [Google Scholar]
  69. Irani LC, Silberman MS. 2013. Turkopticon: interrupting worker invisibility in Amazon Mechanical Turk. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’13)611–20 New York: ACM
     [Google Scholar]
  70. Jacobs AZ, Wallach H. 2021. Measurement and fairness. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’21)375–85 New York: ACM
     [Google Scholar]
  71. Jurgens D, Tsvetkov Y, Jurafsky D. 2017. Incorporating dialectal variability for socially equitable language identification. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Vol. 251–57 Stroudsburg, PA: Assoc. Comput. Linguist.
     [Google Scholar]
  72. Kahn J. 2021. HireVue drops facial monitoring amid A.I. algorithm audit. Fortune Jan. 19. https://fortune.com/2021/01/19/hirevue-drops-facial-monitoring-amid-a-i-algorithm-audit/
    [Google Scholar]
  73. Kay M, Matuszek C, Munson SA. 2015. Unequal representation and gender stereotypes in image search results for occupations. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems3819–28 New York: ACM
     [Google Scholar]
  74. Koenecke A, Nam A, Lake E, Goel S. 2020. Racial disparities in automated speech recognition. PNAS 117:147684–89
     [Google Scholar]
  75. Kornei K. 2021. Academic citations evolved to include Indigenous oral teachings. Eos Novemb. 9. https://eos.org/articles/academic-citations-evolve-to-include-indigenous-oral-teachings
    [Google Scholar]
  76. Kotek H, Dockum R, Babinski S, Geissler C. 2021. Gender bias and stereotypes in linguistic example sentences. Language 97:4653–77
     [Google Scholar]
  77. Kovach M. 2010. Indigenous Methodologies: Characteristics, Conversations, and Contexts Toronto: Univ. Toronto Press
  78. Krämer P, Vogl U, Kolehmainen L. 2022. What is “language making”?. Int. J. Sociol. Lang. 2022:2741–27
     [Google Scholar]
  79. Kubaniyova M. 2008. Rethinking research ethics in contemporary applied linguistics: the tension between macroethical and microethical perspectives in situated research. Mod. Lang. J. 92:4503–18
     [Google Scholar]
  80. Kubota R. 2020. Confronting epistemological racism, decolonizing scholarly knowledge: race and gender in Applied Linguistics. Appl. Linguist. 41:5712–32
     [Google Scholar]
  81. Kucukyilmaz T, Cambazoglu BB, Aykanat C, Can F 2006. Chat mining for gender prediction. Proceedings of the International Conference on Advances in Information Systems (ADVIS 2006) T Yakhno 274–83 Berlin/Heidelberg: Springer
     [Google Scholar]
  82. Kukutai T, Taylor J. 2016. Indigenous Data Sovereignty: Towards an Agenda Canberra: Aust. Natl. Univ. Press
  83. Labov W. 1982. Objectivity and commitment in linguistic science. Lang. Soc. 11:165–201
     [Google Scholar]
  84. Landert D, Jucker AH. 2011. Private and public in mass media communication: from letters to the editor to online commentaries. J. Pragmat. 43:1422–34
     [Google Scholar]
  85. Lefeuvre-Halftermeyer A, Govaere V, Antoine J, Allegre W, Pouplin S et al. 2016. Typologie des risques pour une analyse éthique de l'impact des technologies du TAL. Rev. TAL 57:247–71
     [Google Scholar]
  86. Leonard WY. 2011. Challenging extinction through modern Miami language practices. Am. Indian Cult. Res. J. 35:2135–60
     [Google Scholar]
  87. Leonard WY. 2017. Producing language reclamation by decolonising ‘language.. ’ Lang. Doc. Descr. 14:15–36
     [Google Scholar]
  88. Leonard WY 2018. Reflections on (de)colonialism in language documentation. Reflections on Language Documentation 20 Years After Himmelmann 1998 B McDonnell 55–65 Honolulu: Univ. Hawai‘i Press. Lang. Doc. Conserv. Spec. Publ. 15
     [Google Scholar]
  89. Leonard WY 2021. Centering Indigenous ways of knowing in collaborative language work. Sustaining Indigenous Languages: Connecting Communities, Teachers, and Scholars L Crowshow 21–33 Athabasca, Can: Athabasca Univ. Press
     [Google Scholar]
  90. Leonard WY, Haynes E. 2010. Making “collaboration” collaborative: an examination of perspectives that frame linguistic field research. Lang. Doc. Conserv. 4:268–293
     [Google Scholar]
  91. Louagie D, Reinöhl U, eds. 2022. Typologizing the noun phrase. Linguistics 60:3)
     [Google Scholar]
  92. Louis RP. 2007. Can you hear us now? Voices from the margin: using Indigenous methodologies in geographic research. Geogr. Res. 45:130–39
     [Google Scholar]
  93. LSA (Linguist. Soc. Am.). 2019. LSA revised ethics statement, final version (approved July 2019) Public Statement, LSA Washington, DC: https://www.linguisticsociety.org/content/lsa-revised-ethics-statement-approved-july-2019
    [Google Scholar]
  94. Macaulay M. 2011. Surviving Linguistics: A Guide for Graduate Students Somerville, MA: Cascadilla. , 2nd ed..
  95. Macaulay M, Brice C. 1997. Don't touch my projectile: gender bias and stereotyping in syntactic examples. Language 73:4798–825
     [Google Scholar]
  96. Mackenzie J. 2017. Identifying informational norms in Mumsnet talk: a reflexive-linguistic approach to internet research ethics. Appl. Linguist. Rev. 8:293–314
     [Google Scholar]
  97. Madden M. 2017. Privacy, security, and digital inequality Rep., Data Soc. Res. Inst. New York: https://datasociety.net/pubs/prv/DataAndSociety_PrivacySecurityandDigitalInequality.pdf
  98. Majid A, Levinson SC. 2010. WEIRD languages have misled us, too. Behav. Brain Sci. 33:2/3103
     [Google Scholar]
  99. Mallinson C 2018. Ethics in linguistics research. Research Methods in Linguistics L Litosseliti 57–84 London: Bloomsbury. , 2nd ed..
     [Google Scholar]
  100. Mandel J 2017. Google Home vs Alexa: two simple user experience design gestures that delighted a female user. Medium Jan. 4 https://medium.com/startup-grind/google-home-vs-alexa-56e26f69ac77
    [Google Scholar]
  101. McGuffie K, Newhouse A. 2020. The radicalization risks posed by GPT-3 and advanced neural language models Tech. Rep., Cent. Terror. Extremism Counterterrorism, Middlebury Inst. Int. Stud. Monterey, CA: https://www.middlebury.edu/institute/sites/www.middlebury.edu.institute/files/2020-09/gpt3-article.pdf .
  102. Mitchell M, Wu S, Zaldivar A, Barnes P, Vasserman L et al. 2019. Model cards for model reporting. Proceedings of the Conference on Fairness, Accountability, and Transparency (FAT* ’19)220–29 New York: ACM
     [Google Scholar]
  103. NAACL (N. Am. Chapter Assoc. Comput. Linguist.). 2021. Ethics FAQ Guidel., NAACL. https://2021.naacl.org/ethics/faq/
  104. Newman P. 2007. Copyright essentials for linguists. Lang. Doc. Conserv. 1:128–43
     [Google Scholar]
  105. Noble SU. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism New York: NYU Press
  106. Nosek BA, Ebersole CR, DeHaven AC, Mellor DT. 2018. The preregistration revolution. PNAS 115:112600–6
     [Google Scholar]
  107. O'Meara C, Good J. 2010. Ethical issues in legacy language resources. Lang. Commun. 30:162–70
     [Google Scholar]
  108. Price R. 2016. Microsoft is deleting its AI chatbot's incredibly racist tweets. Business Insider March 24. https://www.businessinsider.com/microsoft-deletes-racist-genocidal-tweets-from-ai-chatbot-tay-2016-3
    [Google Scholar]
  109. Radford A, Wu J, Child R, Luan D, Amodei D, Sutskever I. 2019. Language models are unsupervised multitask learners. OpenAI 1:89 https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf
    [Google Scholar]
  110. Raji DI, Bender EM, Paullada A, Denton E, Hanna A. 2021. AI and the Everything in the Whole Wide World benchmark. Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS 2021) https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/file/084b6fbb10729ed4da8c3d3f5a3ae7c9-Paper-round2.pdf
    [Google Scholar]
  111. Rankin YA, Henderson KK. 2021. Resisting racism in tech design: centering the experiences of Black youth. Proceedings of the ACM on Human-Computer Interaction, Vol. 5 art. 192 New York: ACM
     [Google Scholar]
  112. Rice K. 2006. Ethical issues in linguistic fieldwork: an overview. J. Acad. Ethics 4:123–55
     [Google Scholar]
  113. Rice K 2018. Collaborative research: visions and realities. Insights from Practices in Community-Based Research: From Theory to Practice Around the Globe S Bischoff 13–37 Berlin/Boston: de Gruyter Mouton
     [Google Scholar]
  114. Rickford JR. 1997. Unequal partnership: sociolinguistics and the African American speech community. Lang. Soc. 26:2161–97
     [Google Scholar]
  115. Rickford JR. 1999. African American English: Features, Evolution, and Educational Implications Malden, MA: Blackwell
  116. Rickford JR, King S. 2016. Language and linguistics on trial: hearing Rachel Jeantel (and other vernacular speakers) in the courtroom and beyond. Language 94:948–88
     [Google Scholar]
  117. Rosborough T, Rorick CL, Urbanczyk S. 2017. Beautiful words: enriching and indigenizing Kwak'wala revitalization through understandings of linguistic structure. Can. Mod. Lang. Rev./Rev. Can. Lang. Vivantes 73:425–37
     [Google Scholar]
  118. Rousseau AL, Baudelaire C, Riera K. 2020. Doctor GPT-3: hype or reality?. Nabla Oct. 27. https://www.nabla.com/blog/gpt-3/
    [Google Scholar]
  119. Samarin W. 1967. Field Linguistics New York: Holt, Rinehart & Winston
  120. Sap M, Card D, Gabriel S, Choi Y, Smith NA. 2019. The risk of racial bias in hate speech detection. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics1668–78 Stroudsburg, PA: Assoc. Comput. Linguist.
     [Google Scholar]
  121. Schwartz-Shea P. 2014. Interpretive social science. The Encyclopedia of Political Thought MT Gibbons New York: Wiley-Blackwell
     [Google Scholar]
  122. Seaman Cook J 2016. From Siri to sexbots: Female AI reinforces a toxic desire for passive, agreeable and easily dominated women. Salon April 8. https://www.salon.com/2016/04/08/from_siri_to_sexbots_female_ai_reinforces_a_toxic_desire_for_passive_agreeable_and_easily_dominated_women/
    [Google Scholar]
  123. Smith LT. 2012. Decolonizing Methodologies: Research and Indigenous Peoples New York: Zed. , 2nd ed..
  124. Speer R. 2017. ConceptNet Numberbatch 17.04: better, less-stereotyped word vectors. ConceptNet Blog April 24. https://blog.conceptnet.io/2017/04/24/conceptnet-numberbatch-17-04-better-less-stereotyped-word-vectors
    [Google Scholar]
  125. Stark L, Hutson J. 2022. Physiognomic artificial intelligence. Fordham Intellect. Prop. Media Entertain. Law J. 32:4922–78
     [Google Scholar]
  126. Steiger M, Bharucha TJ, Venkatagiri S, Reidl MJ, Lease M. 2021. The psychological well-being of content moderators: the emotional labor of commercial moderation and avenues for improving support. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (CHI ’21) art. 341 New York: ACM
     [Google Scholar]
  127. Stengers I. 2018. Another Science Is Possible: A Manifesto for Slow Science transl. S Mueke Cambridge, UK: Polity (from French)
  128. Sweeney L. 2013. Discrimination in online ad delivery. Commun. ACM 56:544–54
     [Google Scholar]
  129. Tatman R. 2017. Gender and dialect bias in YouTube's automatic captions. Proceedings of the 1st ACL Workshop on Ethics in Natural Language Processing53–59 Stroudsburg, PA: Assoc. Comput. Linguist.
     [Google Scholar]
  130. Tatman R. 2018. Should you keep the tweet? Balancing reproducibility, open data and participant privacy Workshop session presented at 47th Annual Meeting of New Ways of Analyzing Variation (NWAV47), Univ. Wis. Madison: Oct. 18–21 http://www.rctatman.com/files/Tatman_2018_NWAV_ShouldYouKeepTheTweet.pdf
  131. Tatman R, Kasten C. 2017. Effects of talker dialect, gender and race on accuracy of Bing Speech and YouTube automatic captions. Proceedings of the 18th Annual Conference of the International Speech Communication Association (INTERSPEECH 2017)934–38 Paris: Int. Speech Commun. Assoc.
     [Google Scholar]
  132. Trechter S, Bucholtz M. 2001. White noise: bringing language into whiteness studies. J. Linguist. Anthropol. 11:13–21
     [Google Scholar]
  133. Tsikewa A. 2021. Reimagining the current praxis of field linguistics training: decolonial considerations. Language 97:4e293–319
     [Google Scholar]
  134. UBC (Univ. B. C.). 2021. APA citation style guide Style Guide, UBC Libr., Vancouver, Can https://guides.library.ubc.ca/apacitationstyle/indigenousknowledge
  135. Warner N, Luna Q, Butler L 2007. Ethics and revitalization of dormant languages: the Mutsun language. Lang. Doc. Conserv. 1:158–76
     [Google Scholar]
  136. Wassink AB, Gansen C, Bartholomew I. 2022. Uneven success: automatic speech recognition and ethnicity-related dialects. Speech Commun. 140:50–70
     [Google Scholar]
  137. Way A 2020. Machine translation: Where are we at today?. The Bloomsbury Companion to Language Industry Studies E Angelone 311–32 London: Bloomsbury
     [Google Scholar]
  138. Williams I. 2022. Can A.I.-driven voice analysis help identify mental disorders?. New York Times April 5. https://www.nytimes.com/2022/04/05/technology/ai-voice-analysis-mental-health.html
    [Google Scholar]
  139. Wilson S. 2008. Research Is Ceremony: Indigenous Research Methods . Halifax/Winnipeg, Can: Fernwood
  140. Wolfram W. 1993. Ethical consideration in language awareness programs. Issues Appl. Linguist. 4:225–55
     [Google Scholar]
  141. Wolfram W. 1998. Scrutinizing linguistic gratuity: a view from the field. J. Socioling. 2:271–78
     [Google Scholar]
  142. Zaugg IA. 2020. Digital surveillance and digitally-disadvantaged language communities Paper presented at International Conference on Language Technologies for All (LT4All), UNESCO Paris: Dec. 4–6
  143. Zook M, Barocas S, Boyd D, Crawford K, Keller E et al. 2017. Ten simple rules for responsible big data research. PLOS Comput. Biol. 13:3e1005399
     [Google Scholar]
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Ethics in Linguistics
Annual Review of Linguistics 9, 49 (2023); https://doi.org/10.1146/annurev-linguistics-031120-015324
/content/journals/10.1146/annurev-linguistics-031120-015324
/content/journals/10.1146/annurev-linguistics-031120-015324
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