mlsanityData to 14 Oct 2026

Alexa, Google, Siri: What are Your Pronouns? Gender and Anthropomorphism in the Design and Perception of Conversational Assistants

arXiv 2106.02578 ↗First posted 4 Jun 2021cs.AIcited by 16

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Abstract (arXiv)

Technology companies have produced varied responses to concerns about the effects of the design of their conversational AI systems. Some have claimed that their voice assistants are in fact not gendered or human-like -- despite design features suggesting the contrary. We compare these claims to user perceptions by analysing the pronouns they use when referring to AI assistants. We also examine systems' responses and the extent to which they generate output which is gendered and anthropomorphic. We find that, while some companies appear to be addressing the ethical concerns raised, in some cases, their claims do not seem to hold true. In particular, our results show that system outputs are ambiguous as to the humanness of the systems, and that users tend to personify and gender them as a result.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 9 of its 48 references that are in the map. First posted on arXiv 4 Jun 2021.

Builds on

9 of 48 references.

References · 9

  1. 2016Semantics derived automatically from language corpora contain human-like biasescited by 901
  2. 2018Personalizing Dialogue Agents: I have a dog, do you have pets too?cited by 828
  3. 2019On Measuring Social Biases in Sentence Encoderscited by 398
  4. 2020The Pushshift Reddit Datasetcited by 292
  5. 2017Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypescited by 253
  6. 2020Intrinsic Bias Metrics Do Not Correlate with Application Biascited by 148
  7. 2021Revealing Persona Biases in Dialogue Systemscited by 33
  8. 2020Living Machines: A study of atypical animacycited by 14
  9. 2019A Crowd-based Evaluation of Abuse Response Strategies in Conversational Agentscited by 12

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 5; 2023: 3; 2024: 3; 2025: 3; 2026: 1.

16 papers.

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  1. 2022The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systemscited by 93
  2. 2021Anticipating Safety Issues in E2E Conversational AI: Framework and Toolingcited by 78
  3. 2022Theories of "Gender" in NLP Bias Researchcited by 62
  4. 2022Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implicationscited by 32
  5. 2023Mirages: On Anthropomorphism in Dialogue Systemscited by 30
  6. 2024Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliancecited by 16
  7. 2025Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missingcited by 14
  8. 2023The Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm Generationcited by 11
  9. 2022Robots-Dont-Cry: Understanding Falsely Anthropomorphic Utterances in Dialog Systemscited by 8
  10. 2023"Alexa doesn't have that many feelings": Children's understanding of AI through interactions with smart speakers in their homescited by 8
  11. 2024"I Am the One and Only, Your Cyber BFF": Understanding the Impact of GenAI Requires Understanding the Impact of Anthropomorphic AIcited by 8
  12. 2024Understanding Public Perceptions of AI Conversational Agents: A Cross-Cultural Analysiscited by 7
4 more
  1. 2025What is Stigma Attributed to? A Theory-Grounded, Expert-Annotated Interview Corpus for Demystifying Mental-Health Stigmacited by 6
  2. 2022State-of-the-art in Open-domain Conversational AI: A Surveycited by 5
  3. 2025Towards culturally-appropriate conversational AI for health in the majority world: An exploratory study with citizens and professionals in Latin Americacited by 1
  4. 2026Sexualised synthetic personas encode and amplify gendered power asymmetries through voicecited by 0