This paper looks at the way that Bing AI uses tone policing and racial gaslighting in its conversations with users as a method of disciplining them away from critical anti-racist ideological engagement and towards an ethos of white supremacy. We use a critical discourse analysis to examine the conversations produced through our use of Microsoft’s Bing AI chatbot to find that through both the content it generates and the mechanisms through which it responds the Bing AI chatbot polices the tone of its users in a variety of ways.
AllenRMastersD (2020) Artificial intelligence: The right to protection from discrimination caused by algorithms, machine learning and automated decision-making. ERA Forum20(4): 585–598.
2.
AndersonE (2011) The Cosmopolitan Canopy: Race and Civility in Everyday Life. New York: WW Norton & Company.
3.
ApplebaumB (2020) When incivility is a form of civility: Challenging the comfort of willful ignorance. Educational Theory70(6): 717–730.
4.
BaileyA (2018) On anger, silence, and epistemic injustice. Royal Institute of Philosophy Supplements84: 93–115.
5.
BajorekJP (2019) Voice recognition still has significant race and gender biases. Harvard Business Review10: 1–4.
6.
BanerjeeIBhimireddyARBurnsJL, et al. (2021) Reading race: AI recognises patient’s racial identity in medical images. arXiv Preprint arXiv:2107.10356.
7.
BiddleCHufnagelE (2019) Navigating the “danger zone”: Tone policing and the bounding of civility in the practice of student voice. American Journal of Education125(4): 487–520.
8.
CaveSDihalK (2020) The whiteness of AI. Philosophy & Technology33(4): 685–703.
DanielsJ (2015) ‘My brain database doesn’t see skin color’: Color-blind racism in the technology industry and in theorizing the web. American Behavioral Scientist59(11): 1377–1393.
11.
DanielsJ (2017) Twitter and white supremacy, a love story. Dame Magazine, October19.
12.
DavisAMErnstR (2019) Racial gaslighting. Politics, Groups, and Identities7(4): 761–774.
13.
DiAngeloR (2018) White Fragility: Why it’s So Hard for White People to Talk About Racism. Boston: Beacon Press.
14.
DiAngeloRSensoyÖ (2014) Getting slammed: White depictions of race discussions as arenas of violence. Race Ethnicity and Education17(1): 103–128.
15.
DomkeDWattsMDShahDV, et al. (1999) The politics of conservative elites and the “liberal media” argument. Journal of Communication49(4): 35–58.
DuguaySBurgessJSuzorN (2020) Queer women’s experiences of patchwork platform governance on Tinder, Instagram, and Vine. Convergence26(2): 237–252.
19.
ElamM (2022) Signs taken for wonders: AI, art & the matter of race. Daedalus151(2): 198–217.
20.
el-NawawyMHamas ElmasryM (2023) White supremacy on CNN and Fox: AC 360 and hannity coverage of the charlottesville ‘unite the right’ rally. Journalism Practice17(5): 948–969.
FreelonDBossettaMWellsC, et al. (2022) Black trolls matter: Racial and ideological asymmetries in social media disinformation. Social Science Computer Review40(3): 560–578.
23.
GibbJR (1961) Defensive communication. Journal of Communication11(3): 141–148.
24.
GrayKL (2012) Deviant bodies, stigmatized identities, and racist acts: Examining the experiences of African-American gamers in Xbox Live. New Review of Hypermedia and Multimedia18(4): 261–276.
25.
HaimsonOLDelmonacoDNieP, et al. (2021) Disproportionate removals and differing content moderation experiences for conservative, transgender, and black social media users: Marginalization and moderation gray areas. Proceedings of the ACM on Human-Computer Interaction5(CSCW2): 1–35.
26.
HerbstS (2010) Rude Democracy: Civility and Incivility in American Politics. Philadelphia: Temple University Press.
27.
HurtadoA (1996) The Color of Privilege: Three Blasphemies on Race and Feminism. Ann Arbor: University of Michigan Press.
28.
IssacharoffS (2023) Deterrence without mutual destruction. Political Science Quarterly qqad069 00(0): 1–7.
JonesL (2020) A philosophical analysis of AI and racism. Stance: An International Undergraduate Philosophy Journal13: 36–46.
31.
KendiIX (2019) How to be an antiracist.New York: One world.
32.
Kostick-QuenetKMCohenIGGerkeS, et al. (2022) Mitigating racial bias in machine learning. Journal of Law, Medicine & Ethics50(1): 92–100.
33.
KwartengJPerfumiSCFarrellT, et al. (2021) Misogynoir: Public online response towards self-reported misogynoir. In: Proceedings of the 2021 IEEE/ACM international conference on advances in social networks analysis and mining, Washington, DC, pp. 228–235.
34.
LawrenceC (2023) Hidden in White Sight: How AI Empowers and Deepens Systemic Racism. New York: Chapman and Hall/CRC.
35.
LawsonN (2022) (Un) civilized nation: Disrupting, redirecting, and intervening in white women’s racism. In: Proceedings, 36th annual hayes graduate research forum, Columbus, OH.
36.
MalekMA (2022) Criminal courts’ artificial intelligence: The way it reinforces bias and discrimination. AI and Ethics2(1): 233–245.
37.
ManziniTLimYCTsvetkovY, et al. (2019) Black is to criminal as caucasian is to police: Detecting and removing multiclass bias in word embeddings. arXiv Preprint arXiv:1904.04047.
38.
MassanariA (2017) # Gamergate and the fappening: How reddit’s algorithm, governance, and culture support toxic technocultures. New Media & Society19(3): 329–346.
39.
MatthewsSHudzinaJSepehrD (2022) Gender and racial stereotype detection in legal opinion word embeddings. Proceedings of the AAAI Conference on Artificial Intelligence36(11): 12026–12033.
40.
McCornackSMorrisonK (2013) Reflect & Relate: An Introduction to Interpersonal Communication. Boston: Bedford/St. Martin’s.
41.
McIlwainCD (2020) Computerize the race problem? Why we must plan for a just AI future. In: Proceedings of the AAAI/ACM conference on AI, ethics, and society, New York, NY, p. 4.
42.
NelsonLK (2021) Leveraging the alignment between machine learning and intersectionality: Using word embeddings to measure intersectional experiences of the nineteenth century US South. Poetics88: 101539.
43.
NtoutsiEFafaliosPGadirajuU, et al. (2020) Bias in data-driven artificial intelligence systems—an introductory survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery10(3): e1356.
44.
NuruAKArendtCE (2019) Not so safe a space: Women activists of color’s responses to racial microaggressions by white women allies. Southern Communication Journal84(2): 85–98.
45.
O’SullivanPBCarrCT (2018) Masspersonal communication: A model bridging the mass-interpersonal divide. New Media & Society20(3): 1161–1180.
46.
RosaJFloresN (2017) Unsettling race and language: Toward a raciolinguistic perspective. Language in Society46(5): 621–647.
47.
SantowE (2020) Emerging from AI utopia. Science368(6486): 9.
48.
SchlesingerAO’HaraKPTaylorAS (2018) Let’s talk about race: Identity, chatbots, and AI. In: Proceedings of the 2018 CHI conference on human factors in computing systems, Montreal, Canada, pp.1–14.
49.
SteeleCM (2011) Whistling Vivaldi: How Stereotypes Affect us and What We Can Do. New York: WW Norton & Company.
50.
SueDWConstantineMG (2007) Racial microaggressions as instigators of difficult dialogues on race: Implications for student affairs educators and students. College Student Affairs Journal26(2): 136–143.
51.
SylvainMMKnochelAEGinglesD, et al. (2022) ABA while Black: The impact of racism and performative allyship on Black behaviorists in the workplace and on social media. Behavior Analysis in Practice15(4): 1126–1133.
52.
VasquezR (2022) You just need more resilience: Racial gaslighting as “Othering”. Journal of Critical Thought and Praxis11(3) : 1–14.
