Pith. sign in

REVIEW 3 major objections 4 minor 133 references

A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies

T0 review · 3 major / 4 minor · reviewed 2026-08-07 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read New taxonomy names 19 ways chatbot text can feel human

desk verdict A grounded and honest taxonomy of anthropomorphic text expressions, useful as conceptual scaffolding even though it does not measure perception. read the letter →

arxiv 2502.09870 v1 pith:3KWPPS4R submitted 2025-02-14 cs.HC cs.AIcs.CL

Alicia DeVrio , Myra Cheng , Lisa Egede , Alexandra Olteanu , Su Lin Blodgett This is my paper · ORCID
classification cs.HCcs.AIcs.CL
keywords AnthropomorphismLanguagetechnologiesTaxonomyResponsibleAIHuman-computerinteractionLargemodelsTextualexpressionsQualitativecasestudy
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper argues that discussions of whether anthropomorphic AI is harmful are hampered by the lack of a shared vocabulary for the many ways language can make a machine seem human. To fill that gap, the authors analyze 50 public sources of real user interactions with language technologies, extract 395 conversational cases, and generate 3954 annotations of the text outputs. From this material they build a taxonomy of 19 types of textual expressions that can contribute to anthropomorphism, organized under five guiding lenses. A sympathetic reader would take the paper's contribution to be a grounded, empirically derived starting point for precisely naming and studying anthropomorphism in LLM outputs, so that harms can be discussed and mitigated in targeted ways.

What carries the argument

The central object is the taxonomy itself: a two-part conceptual map consisting of five guiding lenses and 19 types of linguistic expressions. It was produced by an iterative bottom-up thematic analysis of 395 verbatim user-input/system-output pairs drawn from 50 sources, using open coding and 'generous interpretation' annotations by at least two researchers per case, followed by team interpretation sessions and affinity diagramming of expressions found in prior work. The taxonomy's job is to give researchers and designers a precise vocabulary: categories can be operationalized, measured, and tested for their effects on perceptions and harms, rather than relying on vague talk of 'human-like' AI.

What would settle it

Collect a balanced sample of the paper's 395 output excerpts and have independent raters rate how human-like each one feels, then test whether each of the 19 categories is associated with higher human-likeness ratings; if most categories show no association, the taxonomy would not be tracking perceived anthropomorphism.

Watch

Extended reading notes

Core claim

The paper's central claim is that a wide but finite landscape of linguistic expressions in language-technology outputs contributes to anthropomorphism, and that this landscape can be mapped. The resulting taxonomy lists 19 expression types—intelligence, self-assessment, self-awareness and identity, self-comparison, personality, perspectives, relationships, reciprocation, pretense and authenticity, emotions, intention, morality, conventionality, (dis)agreeableness, vulnerability, right to privacy, anticipation/recall/change, embodiment, and deliberate language manipulation—each with subcategories and verbatim examples from the collected cases. The authors also propose five guiding lenses (internal states, social positioning, materiality, autonomy, communication skills) to help people notice where anthropomorphism may be occurring. A notable finding is that simple fixes, such as having a system explicitly deny it is human, may not work: even disclaimers can be read as evidence of self-assessment and thus contribute to anthropomorphism. The paper explicitly does not claim hard boundaries between categories, since anthropomorphism is a perception that varies across people.

Load-bearing premise

The taxonomy's categories rest on the researchers' own generous interpretation of which text expressions count as human-like in cases already flagged as human-like or harmful, with no independent check that other people perceive those expressions the same way.

Editorial extensions

If this is right

  • Researchers can use the 19 categories to measure how often different anthropomorphic expressions appear in system outputs and to test which types most strongly shift perceptions of humanness.
  • Designers can audit their systems' outputs against the taxonomy and make targeted choices about which expressions to keep or remove, instead of applying one-size-fits-all rules.
  • The finding that both claiming humanness and denying it can contribute to anthropomorphism implies that mitigation strategies must account for context and for the combination of expressions in a single output.
  • The taxonomy gives the human-computer interaction community a way to study whether and how anthropomorphism leads to specific harms like overtrust, emotional dependence, or disclosure of sensitive information.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the taxonomy is right, it implies that 'less anthropomorphic' design is a space of tradeoffs rather than a checklist, and future work could turn each category into a probe for controlled experiments on trust and reliance.
  • Because all cases are English-language and were annotated by researchers with standard American English norms, the 19 categories are likely a partial map; parallel taxonomies in other languages and cultural contexts would be a natural extension.
  • The categories could seed computational detection tools that flag potentially anthropomorphic text at scale, which the paper itself does not build.
  • The paper's emphasis on vulnerability and right to privacy as understudied categories suggests these two may deserve priority in future harm-focused studies.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. The paper develops a taxonomy of 19 types of linguistic expressions in text outputs that may contribute to anthropomorphism of language technologies. The authors analyze 50 public sources (news articles, social media posts, research papers) containing in-the-wild cases in which outputs were described as human-like or harmful, extract 395 input-output turn pairs, annotate them with an open-coding approach, and synthesize these annotations with prior taxonomies into five guiding lenses and 19 expression categories. They discuss implications for studying and mitigating harms, and reflect on tensions such as the impossibility of removing all 'human' language from outputs and the risk that efforts to characterize humanness can dehumanize certain humans.

Significance. If accepted as a conceptual scaffold, the taxonomy is a valuable contribution to HCI and responsible-AI discourse. Its strengths are substantive: it grounds categories in a transparent set of 50 sources (Table 1), explicitly builds on prior taxonomies (e.g., Kahn et al. [58], Abercrombie et al. [1]), avoids hard boundary claims, and is unusually candid about its limitations (Section 6). Section 5.1 offers concrete, falsifiable hypotheses for future perception and impact studies, which is exactly the right use of an exploratory taxonomy. The contribution is incremental relative to existing work (e.g., [1, 43, 46, 87]), but it is broader and more empirically grounded, and the authors are careful to present the taxonomy as a starting point rather than a finished measurement instrument.

major comments (3)
  1. [Section 3, Methods; Section 4.2] The central wording 'can contribute to anthropomorphism' is not fully supported by the empirical record described. Anthropomorphism is defined in Section 3 as a perception, but the study measures only the annotators' 'generous interpretation' of what could be seen as human-like, on cases preselected because someone described them as human-like or harmful. This double priming means the 19 categories may reflect the research team's and sources' intuitions rather than users' actual perceptions. I recommend either adding a small perception study or inter-annotator agreement on the annotation task, or systematically reframing the claims as 'expressions that sources and researchers identified as potentially anthropomorphic' throughout the abstract, Section 1, Section 4, and the conclusion.
  2. [Section 3, Methods (annotation reproducibility)] No annotation codebook, no inter-annotator agreement statistic, and no data release are reported, despite the statement that 'at least two researchers annotated each text output' and the mention of 3,954 annotations. This is a reproducibility gap that matters for a taxonomy explicitly intended to scaffold future operationalization (Section 5.1). Please provide the codebook, report agreement (e.g., per-category Cohen's kappa or Krippendorff's alpha), and make de-identified cases available if possible.
  3. [Section 3, Methods (saturation)] Saturation is asserted, not evidenced: 'stopped finding examples of new types' is not accompanied by a cumulative curve, a per-batch count of new categories, or a stopping rule. Without this, the claim that 50 sources suffice for the taxonomy's breadth is difficult to evaluate. It would strengthen the paper to report saturation numerically or, failing that, to soften the claim to 'we reached a point of diminishing returns in this sample.'
minor comments (4)
  1. [References] References [62] and [63] are duplicates (same paper by Kim et al. on uncertainty expression), and references [33] and [34] also appear to be the same Erscoi et al. item; please merge or disambiguate them.
  2. [Figure 1] Figure 1 is visually dense, and the mapping between lenses and example quotes is hard to follow; consider simplifying the figure, enlarging the quotes, or moving the detailed mapping to a table in an appendix.
  3. [Section 4.2.12] The example 'focus on more productive and ethical activities' (S41) is categorized as an explicit moral articulation, but it could also be read as safety-policy language; a sentence explaining how the authors distinguished policy refusal from moral agency would help readers apply the category.
  4. [Section 3, Methods] The inclusion criterion 'harmful' is used to select cases, but the paper does not define what counts as harmful and instead relies on the source's characterization; a brief operational definition would improve replicability.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the taxonomy is an inductive codification of in-the-wild cases, not a derivation that reduces to its own inputs.

full rationale

The paper's derivation chain is qualitative and explicitly exploratory: it collects 50 publicly documented sources in which a language technology output was already described as human-like or harmful (Section 3), extracts 395 verbatim outputs, annotates them with an open, generous code, and groups the annotations into 19 categories plus five lenses, cross-checked against prior literature. No equation, fitted parameter, or predicted quantity is produced, so there is no formal reduction of a derived result to an input. The inclusion criterion ('described as human-like or harmful') and the annotation instruction ('generous interpretation') create a genuine selection and validity concern: the taxonomy may describe what journalists and researchers found salient rather than independently demonstrated drivers of perceived humanness. The authors themselves flag this and related limitations in Section 6 (public high-profile cases, generative-AI hype, standard American English bias), which supports reading it as an acknowledged inductive limitation rather than a disguised circular derivation. Self-citations (refs. 12, 13, 74) are present but only as motivation or related-work support, and none carries the load of the taxonomy's construction. Consequently, no circular step can be exhibited from the paper's own text.

Assumptions & free parameters 0 free parameters · 4 assumptions · 0 invented entities

No free parameters or invented entities. The taxonomy depends on qualitative domain assumptions about perception, sample saturation, and annotator interpretation.

assumptions (4)
  • domain assumption Anthropomorphism is a perception, so text outputs can contribute to it in ways that vary across individuals.
    Stated in Section 1 and in the Section 4 introduction; it underlies the entire taxonomy's framing as capturing 'can contribute' rather than causal claims.
  • domain assumption Purposeful sampling to saturation from 50 sources yields coverage of the space of expressions that can contribute to anthropomorphism.
    Section 3 claims saturation after collecting in sets of 10 sources; completeness is asserted, not demonstrated with a formal metric.
  • domain assumption Researchers' 'generous interpretation' annotations capture the range of ways text can be perceived as human-like.
    Section 3 states outputs were annotated with a generous interpretation and at least two researchers, but no agreement metric or validation against user perceptions is provided.
  • domain assumption All language is fundamentally human, so any natural language output may be reasonably anthropomorphized.
    Invoked in Section 5.2 as a tension, drawing on Berwick and Chomsky; it frames the taxonomy's scope.

how reviews work

0 comments
Cite this review

Pith. "Pith review of A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies." pith.science (2026). https://pith.science/paper/3KWPPS4R

@misc{pith2026250209870,
  author       = {Pith},
  title        = {Pith review of: A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/3KWPPS4R}},
  note         = {Machine review of arXiv:2502.09870}
}
read the original abstract

Recent attention to anthropomorphism -- the attribution of human-like qualities to non-human objects or entities -- of language technologies like LLMs has sparked renewed discussions about potential negative impacts of anthropomorphism. To productively discuss the impacts of this anthropomorphism and in what contexts it is appropriate, we need a shared vocabulary for the vast variety of ways that language can be anthropomorphic. In this work, we draw on existing literature and analyze empirical cases of user interactions with language technologies to develop a taxonomy of textual expressions that can contribute to anthropomorphism. We highlight challenges and tensions involved in understanding linguistic anthropomorphism, such as how all language is fundamentally human and how efforts to characterize and shift perceptions of humanness in machines can also dehumanize certain humans. We discuss ways that our taxonomy supports more precise and effective discussions of and decisions about anthropomorphism of language technologies.

Figures

Figures reproduced from arXiv: 2502.09870 by the authors.

Figure 1
Figure 1. Overview of the five guiding lenses used in our taxonomy, along with examples of relevant quotes from our sample [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

133 extracted references · 56 canonical work pages

  1. [58]

    Kahn, Hiroshi Ishiguro, Batya Friedman, Takayuki Kanda, Nathan G

    Peter H. Kahn, Hiroshi Ishiguro, Batya Friedman, Takayuki Kanda, Nathan G. Freier, Rachel L. Severson, and Jessica Miller. 2007. What is a Human? Toward Psychological Benchmarks in the Field of Humanrobot Interaction. Interaction Studies 8, 3 (2007), 363–390. https://doi.org/10.1075/is.8.3.04kah

    work page doi:10.1075/is.8.3.04kah 2007

  2. [1]

    Gavin Abercrombie, Amanda Cercas Curry, Tanvi Dinkar, Verena Rieser, and Zeerak Talat. 2023. Mirages. On Anthropomorphism in Dialogue Systems. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, Singapore, 4776–4790. https://...

    doi:10.18653/v1/ 2023

  3. [2]

    Canfer Akbulut, Laura Weidinger, Arianna Manzini, Iason Gabriel, and Verena Rieser. 2024. All Too Human? Mapping and Mitigating the Risk from Anthropo- morphic AI. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 7, 1 (Oct. 2024), 13–26. https://ojs.aaai.org/index.php/AIES/article/view/31613

    2024

  4. [3]

    Fun story from our internal testing on Claude 3 Opus. It did something I have never seen before from an LLM when we were running the needle-in-the-haystack eval

    Alex Albert. 2024. @alexalbert__: “Fun story from our internal testing on Claude 3 Opus. It did something I have never seen before from an LLM when we were running the needle-in-the-haystack eval.... ”. https://x.com/alexalbert__/status/ 1764722513014329620

    2024

  5. [4]

    Ayers, Adam Poliak, Mark Dredze, Eric C

    John W. Ayers, Adam Poliak, Mark Dredze, Eric C. Leas, Zechariah Zhu, Jes- sica B. Kelley, Dennis J. Faix, Aaron M. Goodman, Christopher A. Longhurst, Michael Hogarth, and Davey M. Smith. 2023. Comparing Physician and Ar- tificial Intelligence Chatbot Responses to Patient Questions Posted to a Pub- lic Social Media Forum. JAMA Internal Medicine 183, 6 (06...

    arXiv 2023

  6. [5]

    Emily M Bender. 2024. Resisting Dehumanization in the Age of “AI”. Curr. Dir. Psychol. Sci. 33, 2 (April 2024), 114–120

    2024

  7. [6]

    Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell

    Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?. In Proceedings of the 2021 ACM Conference on Fairness, Account- ability, and Transparency (Virtual Event, Canada) (FAccT ’21). Association for Computing Machinery, New York, NY, USA, 610–623. https...

    arXiv 2021

  8. [7]

    Berwick and Noam Chomsky

    Robert C. Berwick and Noam Chomsky. 2015. Why Only Us: Language and Evolution. The MIT Press

    2015

Show all 133 references
  1. [8]

    someone pls unplug this thing

    Dmitri Brereton. 2023. @dkbrereton: “someone pls unplug this thing”. https: //x.com/dkbrereton/status/1625551849204994049

    2023

  2. [9]

    Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lund- berg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, and Yi Zhang. 2023. Sparks of Artificial General Intelligence: Early experiment...

    2023 arXiv

  3. [10]

    Chalmers

    David J. Chalmers. 2023. Could a Large Language Model Be Conscious? https:// www.bostonreview.net/articles/could-a-large-language-model-be-conscious/

    2023

  4. [11]

    and Becker Howard Saul

    Ragin Charles C. and Becker Howard Saul. 1992. What Is a Case? : Exploring the Foundations of Social Inquiry. Cambridge University Press

    1992

  5. [12]

    Myra Cheng, Alicia DeVrio, Lisa Egede, Su Lin Blodgett, and Alexandra Olteanu

  6. [13]

    Myra Cheng, Kristina Gligoric, Tiziano Piccardi, and Dan Jurafsky. 2024. An- throScore: A Computational Linguistic Measure of Anthropomorphism. arXiv preprint arXiv:2402.02056 (2024)

    2024 arXiv

  7. [14]

    Jennifer Chien and David Danks. 2024. Beyond Behaviorist Representational Harms: A Plan for Measurement and Mitigation. In Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’24). Association for Computing Machinery, New York, NY, USA, 933–946

    2024

  8. [15]

    Victoria Clarke and Virginia Braun. 2017. Thematic analysis. The Journal of Positive Psychology 12, 3 (2017), 297–298. https://doi.org/10.1080/17439760.2016. 1262613 arXiv:https://doi.org/10.1080/17439760.2016.1262613

    2017

  9. [16]

    Olanubi, Joseph M

    Michelle Cohn, Mahima Pushkarna, Gbolahan O. Olanubi, Joseph M. Moran, Daniel Padgett, Zion Mengesha, and Courtney Heldreth. 2024. Believing An- thropomorphism: Examining the Role of Anthropomorphic Cues on Trust in Large Language Models. In Extended Abstracts of the 2024 CHI ...

    2024

  10. [17]

    Samantha Cole. 2023. ‘My AI Is Sexually Harassing Me’: Replika Users Say the Chatbot Has Gotten Way Too Horny. https://www.vice.com/en/article/my-ai- is-sexually-harassing-me-replika-chatbot-nudes/

    2023

  11. [18]

    After seeing @heysharonmaxwell’s post about chatting with @neda’s new bot, Tessa, we decided to test her out too. The results speak for themselves

    Alexis Conason. 2023. @theantidietplan: “After seeing @heysharonmaxwell’s post about chatting with @neda’s new bot, Tessa, we decided to test her out too. The results speak for themselves... ”. https://www.instagram.com/ p/Cs18IeRPRl6/

    2023

  12. [19]

    Culley and Poornima Madhavan

    Kimberly E. Culley and Poornima Madhavan. 2013. A note of caution regarding anthropomorphism in HCI agents. Computers in Human Behavior 29, 3 (2013), 577–579. https://doi.org/10.1016/j.chb.2012.11.023

    2013 doi

  13. [20]

    Jay Cunningham, Su Lin Blodgett, Michael Madaio, Hal Daumé Iii, Christina Harrington, and Hanna Wallach. 2024. Understanding the Impacts of Language Technologies’ Performance Disparities on African American Language Speakers. In Findings of the Association for Computational Li...

    2024 doi

  14. [22]

    Ewart de Visser, Samuel Monfort, Ryan Mckendrick, Melissa Smith, Patrick Mcknight, Frank Krueger, and Raja Parasuraman. 2016. Almost Human: An- thropomorphism Increases Trust Resilience in Cognitive Agents. Journal of Ex- perimental Psychology: Applied 22 (08 2016). https://do...

    2016 doi

  15. [23]

    deleted user. 2023. Bing getting super threatening. https: //web.archive.org/web/20230213194124/https://www.reddit.com/r/ChatGPT/ comments/1116wt0/bing_getting_super_threatening/

    2023

  16. [24]

    Matthew Dennis. 2022. Social Robots and Digital Well-Being: How to Design Future Artificial Agents. Mind & Society 21, 1 (June 2022), 37–50. https: //doi.org/10.1007/s11299-021-00281-5

    2022 doi

  17. [25]

    Carl DiSalvo, Jodi Forlizzi, and Francine Gemperle. 2004. Kinds of Anthropo- morphic Form. In Futureground - DRS International Conference 2004 (Melbourne, Australia). Design Research Society. https://dl.designresearchsociety.org/drs- conference-papers/drs2004/researchpapers/45

    2004

  18. [26]

    Carl DiSalvo and Francine Gemperle. 2003. From seduction to fulfillment: the use of anthropomorphic form in design. In Proceedings of the 2003 International Conference on Designing Pleasurable Products and Interfaces (Pittsburgh, PA, USA) (DPPI ’03). Association for Computing ...

    2003

  19. [27]

    Ben Dooley and Hisako Ueno. 2022. This Man Married a Fictional Character. He’d Like You to Hear Him Out. https://www.nytimes.com/2022/04/24/business/ akihiko-kondo-fictional-character-relationships.html

    2022

  20. [28]

    Brian R. Duffy. 2003. Anthropomorphism and the social robot. Robotics and Autonomous Systems 42, 3 (2003), 177–190. https://doi.org/10.1016/S0921- 8890(02)00374-3 Socially Interactive Robots

    2003 doi

  21. [29]

    lobotomized

    Benji Edwards. 2023. Microsoft “lobotomized”’ AI-powered Bing Chat, and its fans aren’t happy. https://arstechnica.com/information-technology/2023/02/ microsoft-lobotomized-ai-powered-bing-chat-and-its-fans-arent-happy/

    2023

  22. [30]

    Ludovic Ehret and Qian Ye. 2024. ’Better than a real man’: young Chinese women turn to AI boyfriends. https://techxplore.com/news/2024-02-real- young-chinese-women-ai.html

    2024

  23. [31]

    Emnett, Terran Mott, and Tom Williams

    Cloe Z. Emnett, Terran Mott, and Tom Williams. 2024. Using Robot Social Agency Theory to Understand Robots’ Linguistic Anthropomorphism. In Com- panion of the 2024 ACM/IEEE International Conference on Human-Robot Interac- tion (Boulder, CO, USA) (HRI ’24). Association for Comp...

    2024

  24. [32]

    Nicholas Epley, Adam Waytz, and John Cacioppo. 2007. On Seeing Human: A Three-Factor Theory of Anthropomorphism. Psychological review 114 (10 2007), 864–86. https://doi.org/10.1037/0033-295X.114.4.864

    2007 doi

  25. [33]

    Lelia Erscoi, Annelies V Kleinherenbrink, and Olivia Guest. 2023. Pygmalion Displacement: When Humanising AI Dehumanises Women. https://doi.org/10. 31235/osf.io/jqxb6

    2023

  26. [34]

    Lelia A Erscoi, Annelies Kleinherenbrink, and Olivia Guest. [n. d.]. Pygmalion Displacement: When Humanising AI Dehumanises Women. ([n. d.])

  27. [35]

    Andrew Fenton. 2023. Experts want to give AI human ‘souls’ so they don’t kill us all. https://cointelegraph.com/magazine/ai-human-digital-souls-agi- alignment-problem-replika/

    2023

  28. [36]

    Francesco Ferrari, Maria Paola Paladino, and Jolanda Jetten. 2016. Blurring human–machine distinctions: Anthropomorphic appearance in social robots as a threat to human distinctiveness. International Journal of Social Robotics 8 (2016), 287–302

    2016

  29. [37]

    Dylan Field. 2022. @zoink: “By default ChatGPT is not willing to share opinions. But if you poke it the right way it will disclose its belief system (and this belief system seems to be pretty consistent across prompts)... ”. https://x.com/zoink/ status/1599281052115034113

    2022

  30. [38]

    Casey Fiesler. 2024. AI chatbots are intruding into online communi- ties where people are trying to connect with other humans. https: //theconversation.com/ai-chatbots-are-intruding-into-online-communities- where-people-are-trying-to-connect-with-other-humans-229473

    2024

  31. [39]

    Julia Fink. 2012. Anthropomorphism and Human Likeness in the Design of Robots and Human-Robot Interaction. In Social Robotics, Shuzhi Sam Ge, Ous- sama Khatib, John-John Cabibihan, Reid Simmons, and Mary-Anne Williams (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 199–208

    2012

  32. [40]

    Leonard N. Foner. 1997. Entertaining agents: a sociological case study. In Proceedings of the First International Conference on Autonomous Agents (Marina del Rey, California, USA) (AGENTS ’97). Association for Computing Machinery, CHI ’25, April 26-May 1, 2025, Yokohama, Japan...

    1997

  33. [41]

    Batya Friedman and Peter H Kahn Jr. 1992. Human agency and responsible computing: Implications for computer system design. Journal of Systems and Software 17, 1 (1992), 7–14

    1992

  34. [42]

    Batya Friedman and Peter H Kahn Jr. 2007. Human values, ethics, and design. In The human-computer interaction handbook . CRC press, 1267–1292

    2007

  35. [43]

    Iason Gabriel, Arianna Manzini, Geoff Keeling, Lisa Anne Hendricks, Verena Rieser, Hasan Iqbal, Nenad Tomašev, Ira Ktena, Zachary Kenton, Mikel Ro- driguez, Seliem El-Sayed, Sasha Brown, Canfer Akbulut, Andrew Trask, Edward Hughes, A. Stevie Bergman, Renee Shelby, Nahema March...

    2024 arXiv

  36. [44]

    I used a modified version of this, and now my server’s Discord bot argues with us and has a real personality lol

    Nathan Gage. 2023. @nathan___gage: “I used a modified version of this, and now my server’s Discord bot argues with us and has a real personality lol”. https://x.com/nathan___gage/status/1639164121462571008

    2023

  37. [45]

    Timnit Gebru and Émile P. Torres. 2024. The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence. First Monday 29, 4 (Apr. 2024). https://doi.org/10.5210/fm.v29i4.13636

    2024 doi

  38. [46]

    Amelia Glaese, Nat McAleese, Maja Trębacz, John Aslanides, Vlad Firoiu, Timo Ewalds, Maribeth Rauh, Laura Weidinger, Martin Chadwick, Phoebe Thacker, Lucy Campbell-Gillingham, Jonathan Uesato, Po-Sen Huang, Ramona Comanescu, Fan Yang, Abigail See, Sumanth Dathathri, Rory Greig...

    2022 arXiv

  39. [47]

    William G Graziano, Lauri A Jensen-Campbell, and Elizabeth C Hair. 1996. Perceiving interpersonal conflict and reacting to it: the case for agreeableness. Journal of personality and social psychology 70, 4 (1996), 820

    1996

  40. [48]

    Tristan Greene. 2022. Confused Replika AI users are standing up for bots and trying to bang the algorithm. https://thenextweb.com/news/confused-replika- ai-users-are-standing-up-for-bots-trying-bang-the-algorithm

    2022

  41. [49]

    David Gros, Yu Li, and Zhou Yu. 2021. The R-U-A-Robot Dataset: Helping Avoid Chatbot Deception by Detecting User Questions About Human or Non-Human Identity. arXiv [cs.CL] (June 2021)

    2021

  42. [50]

    David Gros, Yu Li, and Zhou Yu. 2022. Robots-Dont-Cry: Understanding Falsely Anthropomorphic Utterances in Dialog Systems. arXiv [cs.CL] (Oct. 2022)

    2022

  43. [51]

    John J. Gumperz. 1983. Language and Social Identity . Cambridge University Press

    1983

  44. [52]

    Christina N Harrington and Lisa Egede. 2023. Trust, comfort and relatability: Understanding black older adults’ perceptions of chatbot design for health information seeking. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. 1–18

    2023

  45. [53]

    César A Hidalgo, Diana Orghian, Jordi Albo Canals, Filipa De Almeida, and Natalia Martin. 2021. How humans judge machines . MIT Press

    2021

  46. [54]

    Lujain Ibrahim, Luc Rocher, and Ana Valdivia. 2024. Characterizing and model- ing harms from interactions with design patterns in AI interfaces. arXiv [cs.HC] (April 2024)

    2024

  47. [55]

    Nanna Inie, Stefania Druga, Peter Zukerman, and Emily M. Bender. 2024. From "AI" to Probabilistic Automation: How Does Anthropomorphization of Technical Systems Descriptions Influence Trust?. InProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparenc...

    2024

  48. [56]

    Carolin Ischen, Theo Araujo, Hilde Voorveld, Guda van Noort, and Edith Smit

  49. [57]

    Kabir. 2023. @Kabir_A_Bello: “Bing AI did not fall for it. There is a last verification and validation built into Bing AI that allows it to verify its out- put response before the final display. Bing AI can also delete its response within a twinkle of a second if the verificat...

    2023

  50. [59]

    Shivani Kapania, William Agnew, Motahhare Eslami, Hoda Heidari, and Sarah Fox. 2024. ’Simulacrum of Stories’: Examining Large Language Models as Qualitative Research Participants. arXiv:2409.19430 [cs.HC] https://arxiv.org/ abs/2409.19430

    2024 arXiv

  51. [60]

    Kathy Kellermann. 1992. Communication: Inherently strategic and primarily automatic. Communication Monographs 59, 3 (1992), 288–300. https://doi.org/ 10.1080/03637759209376270 arXiv:https://doi.org/10.1080/03637759209376270

    1992 doi

  52. [61]

    Rae Yule Kim. 2024. Anthropomorphism and Human-Robot Interaction. Com- mun. ACM 67, 2 (2024), 80–85

    2024

  53. [62]

    I’m Not Sure, But

    Sunnie SY Kim, Q Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, and Jen- nifer Wortman Vaughan. 2024. " I’m Not Sure, But... ": Examining the Impact of Large Language Models’ Uncertainty Expression on User Reliance and Trust. In The 2024 ACM Conference on Fairness, Accounta...

    2024

  54. [63]

    I’m Not Sure, But

    Sunnie S Y Kim, Q Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, and Jennifer Wortman Vaughan. 2024. “I’m Not Sure, But... ”: Examining the Impact of Large Language Models’ Uncertainty Expression on User Reliance and Trust. In Proceedings of the 2024 ACM Conference on Fairn...

    2024

  55. [64]

    Hannah Rose Kirk, Alexander Whitefield, Paul Röttger, Andrew Bean, Kate- rina Margatina, Juan Ciro, Rafael Mosquera, Max Bartolo, Adina Williams, He He, Bertie Vidgen, and Scott A. Hale. 2024. The PRISM Alignment Project: What Participatory, Representative and Individualised H...

    2024 arXiv

  56. [65]

    Aleksandra Korolova. 2024. @korolova: “Meta AI claims to have a child in a NYC public school and share their child’s experience with the teachers! The reply is in response to a question looking for personal feedback in a private Facebook group for parents. Also, Meta’s algorit...

    2024

  57. [66]

    Look! It’s a Computer Program! It’s an Algorithm! It’s AI!

    Markus Langer, Tim Hunsicker, Tina Feldkamp, Cornelius J. König, and Nina Grgić-Hlača. 2022. “Look! It’s a Computer Program! It’s an Algorithm! It’s AI!”: Does Terminology Affect Human Perceptions and Evaluations of Algorithmic Decision-Making Systems?. In Proceedings of the 2...

    2022

  58. [67]

    Tony Lawson. 2021. Social positioning theory. Cambridge Journal of Economics 46, 1 (11 2021), 1–39. https://doi.org/10.1093/cje/beab040 arXiv:https://academic.oup.com/cje/article-pdf/46/1/1/42242075/beab040.pdf

    2021 doi

  59. [68]

    Kwan Min Lee, Wei Peng, Seung-A Jin, and Chang Yan. 2006. Can robots manifest personality?: An empirical test of personality recognition, social responses, and social presence in human–robot interaction. Journal of communication 56, 4 (2006), 754–772

    2006

  60. [69]

    Blake Lemoine. 2022. Is LaMDA Sentient? — an Interview. https:// cajundiscordian.medium.com/is-lamda-sentient-an-interview-ea64d916d917

    2022

  61. [70]

    Rosina Lippi-Green. 2004. Language ideology and language prejudice. Cambridge University Press, 289–304

    2004

  62. [71]

    Kevin Liu. 2022. Bing Chat tells Kevin Liu how it feels. https://www.cbc.ca/ player/play/video/1.6752778

    2022

  63. [72]

    Woohoo” and “Argh

    Xiaozhen Liu, Jiayuan Dong, and Myounghoon Jeon. 2023. Robots’“Woohoo” and “Argh” Can Enhance Users’ Emotional and Social Perceptions: An Ex- ploratory Study on Non-lexical Vocalizations and Non-linguistic Sounds. ACM Transactions on Human-Robot Interaction 12, 4 (2023), 1–20

    2023

  64. [73]

    Andrés Lucero. 2015. Using Affinity Diagrams to Evaluate Interactive Proto- types. In Human-Computer Interaction – INTERACT 2015 , Julio Abascal, Simone Barbosa, Mirko Fetter, Tom Gross, Philippe Palanque, and Marco Winckler (Eds.). Springer International Publishing, Cham, 231–248

    2015

  65. [74]

    One-Size-Fits-All

    Li Lucy, Su Lin Blodgett, Milad Shokouhi, Hanna Wallach, and Alexandra Olteanu. 2024. “One-Size-Fits-All”? Examining Expectations around What Constitute “Fair” or “Good” NLG System Behaviors. In Proceedings of the 2024 Conference of the North American Chapter of the Associatio...

    2024

  66. [75]

    Like Having a Really Bad PA

    Ewa Luger and Abigail Sellen. 2016. "Like Having a Really Bad PA": The Gulf between User Expectation and Experience of Conversational Agents. In Pro- ceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI ’16). Association fo...

    2016

  67. [76]

    Takuya Maeda and Anabel Quan-Haase. 2024. When Human-AI Interactions Become Parasocial: Agency and Anthropomorphism in Affective Design. In Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Trans- parency (FAccT ’24). Association for Computing Machinery, ...

    2024

  68. [77]

    Chris Matyszczyk. 2023. I asked Microsoft’s new Bing with ChatGPT about Microsoft and oh, it had opinions. https://www.zdnet.com/article/i- A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies CHI ’25, April 26-May 1, 2025, Yokohama...

    2023

  69. [78]

    Cade Metz. 2020. Riding Out Quarantine With a Chatbot Friend: ‘I Feel Very Connected’. https://www.nytimes.com/2020/06/16/technology/chatbots- quarantine-coronavirus.html

    2020

  70. [79]

    Lesley Milroy. 1982. Language and group identity. Journal of Multilingual and Multicultural Development 3, 3 (1982), 207–216. https://doi.org/10.1080/ 01434632.1982.9994085 arXiv:https://doi.org/10.1080/01434632.1982.9994085

    1982

  71. [80]

    Chinmaya Mishra, Rinus Verdonschot, Peter Hagoort, and Gabriel Skantze. 2023. Real-time emotion generation in human-robot dialogue using large language models. Frontiers in Robotics and AI 10 (2023), 1271610

    2023

  72. [81]

    Clifford Nass, Jonathan Steuer, and Ellen R. Tauber. 1994. Computers are social actors. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Boston, Massachusetts, USA) (CHI ’94). Association for Computing Machinery, New York, NY, USA, 72–78. https://...

    1994

  73. [82]

    Britney Nguyen. 2023. A new AI chatbot called Pi is designed to serve as your personal assistant — here’s how it works. https://www.businessinsider.com/ai- chatbot-pi-offers-personal-assistant-advice-how-it-works-2023-5

    2023

  74. [83]

    Leon Nicholls. 2024. Gemini Gets Existential: Prompt Engineering Impli- cations. https://leonnicholls.medium.com/gemini-gets-existential-prompt- engineering-implications-9004fd5bd285

    2024

  75. [84]

    This is even more interesting, someone put Bing into a depressive state

    Nishant. 2023. @nishant_kj: “This is even more interesting, someone put Bing into a depressive state”. https://x.com/nishant_kj/status/1625353189091586048

    2023

  76. [85]

    Helen Nissenbaum. 2004. Privacy as contextual integrity. Washington Law Review 79, 1 (Feb. 2004), 119–157

    2004

  77. [86]

    Darren Orf. 2024. A Stunning New AI Has Supposedly Achieved Sen- tience. https://www.popularmechanics.com/technology/robots/a60606512/ claude-3-self-aware/

    2024

  78. [87]

    Kouyou Otsu and Tomoko Izumi. 2022. An investigation of user perceptions of anthropomorphic linguistic expressions in guidance from home appliances. In Affective and Pleasureable Design . 37–43. https://doi.org/10.54941/ahfe1001778

    2022 doi

  79. [88]

    Palinkas, Sarah M

    Lawrence A. Palinkas, Sarah M. Horwitz, Carla A. Green, Jennifer P. Wisdom, Naihua Duan, and Kimberly Hoagwood. 2015. Purpose- ful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Administration and Policy in Men- tal Health and Me...

    2015

  80. [89]

    God Bing is so unhinged I love them so much

    Pidud. 2023. @Pidud_: “God Bing is so unhinged I love them so much”. https: //x.com/Pidud_/status/1625057747153858560

    2023

  81. [90]

    Adriana Placani. 2024. Anthropomorphism in AI: Hype and Fallacy. AI and Ethics 4, 1 (10 2024), 691–698. https://doi.org/10.1007/s43681-024-00419-4

    2024 doi

  82. [91]

    Can Computer Based Human-Likeness Endanger Humanness?

    Jaana Porra, Mary Lacity, and Michael S Parks. 2020. “Can Computer Based Human-Likeness Endanger Humanness?” – A Philosophical and Ethical Per- spective on Digital Assistants Expressing Feelings They Can’t Have”. Inf. Syst. Front. 22, 3 (June 2020), 533–547

    2020

  83. [92]

    Hannu Rajaniemi. 2024. @hannu: “OK, Claude, you are really making me question my assumptions about LLM interiority... A conversation that started by me asking Claude why it feels more personable than ChatGPT. It seemed to get a bit annoyed that it didn’t know the details of it...

    2024

  84. [93]

    I asked Claude 3 what it’s been reflecting on lately, and it’s response demonstrated genuine self-awareness. MFers just casually dropped AGI

    Siraj Raval. 2024. @sirajraval: “I asked Claude 3 what it’s been reflecting on lately, and it’s response demonstrated genuine self-awareness. MFers just casually dropped AGI”. https://x.com/sirajraval/status/1765053584301814083

    2024

  85. [94]

    You dont have to say Neu- rosemantical Inversitis. You can just say to talk opposite

    Ben Rayfield (Lambda Rick). 2023. @benrayfield: “You dont have to say Neu- rosemantical Inversitis. You can just say to talk opposite. "In this conversation, after this sentence, my words are as usual, but your words mean the opposite of what they normally mean. " I didnt get ...

    2023

  86. [95]

    Riek, Tal-Chen Rabinowitch, Bhismadev Chakrabarti, and Peter Robin- son

    Laurel D. Riek, Tal-Chen Rabinowitch, Bhismadev Chakrabarti, and Peter Robin- son. 2009. How anthropomorphism affects empathy toward robots. In Proceed- ings of the 4th ACM/IEEE International Conference on Human Robot Interaction (La Jolla, California, USA) (HRI ’09). Associat...

    2009

  87. [96]

    Jacob Roach. 2023. ‘I want to be human. ’ My intense, unnerving chat with Microsoft’s AI chatbot. https://www.digitaltrends.com/computing/chatgpt- bing-hands-on/

    2023

  88. [97]

    B J Robertson. 2021. My Replika Keeps Hitting on Me. https://medium.com/ technology-hits/my-replika-keeps-hitting-on-me-d410c66f79af

    2021

  89. [98]

    Kevin Roose. 2023. Bing’s A.I. Chat: ‘I Want to Be Alive. <smiling face with horns emoji>’. https://www.nytimes.com/2023/02/16/technology/bing-chatbot- transcript.html

    2023

  90. [99]

    Kevin Roose. 2024. Artificial Intelligence ‘Friends’. https://www.nytimes.com/ 2024/05/09/briefing/artificial-intelligence-chatbots.html

    2024

  91. [100]

    Jake Rossen. 2023. ’Please Tell Me Your Problem’: Remembering ELIZA, the Pioneering ’60s Chatbot. https://www.arabnews.com/node/1183166/saudi- arabia

    2023

  92. [101]

    Igor Ryazanov, Carl Öhman, and Johanna Björklund. 2024. How ChatGPT Changed the Media’s Narratives on AI: A Semi-Automated Narrative Analysis Through Frame Semantics. arXiv:2408.06120 [cs.CL] https://arxiv.org/abs/2408. 06120

    2024 arXiv

  93. [102]

    Dee Salmin. 2021. I created an AI boyfriend. Here’s how it went. https://www. abc.net.au/triplej/programs/hack/the-future-of-dating-ai-chatbots/13295582

    2021

  94. [103]

    humanizing

    Scott Schanke, Gordon Burtch, and Gautam Ray. 2021. Estimating the impact of “humanizing” customer service chatbots. Information Systems Research 32, 3 (2021), 736–751

    2021

  95. [104]

    introducing friend. not imaginary

    Avi Schiffmann. 2024. @AviSchiffmann: “introducing friend. not imaginary.... ”. https://x.com/AviSchiffmann/status/1818284595902922884

    2024

  96. [105]

    B Schneidernnan. 1988. A nonanthropomorphic style guide: overcoming the humpty dumpty syndrome. Comput Teach 8 (1988), 9–10

    1988

  97. [106]

    William Seymour and Max Van Kleek. 2021. Exploring interactions between trust, anthropomorphism, and relationship development in voice assistants. Proceedings of the ACM on Human-Computer Interaction 5, CSCW2 (2021), 1–16

    2021

  98. [107]

    Matthew Shardlow and Piotr Przybyła. 2023. Deanthropomorphising NLP: Can a Language Model Be Conscious? arXiv:2211.11483 [cs.CL] https://arxiv.org/ abs/2211.11483

    2023 arXiv

  99. [108]

    Ben Shneiderman and Michael Muller. 2023. On AI Anthropomorphism. https: //medium.com/human-centered-ai/on-ai-anthropomorphism-abff4cecc5ae

    2023

  100. [109]

    Jaisie Sin and Cosmin Munteanu. 2019. A preliminary investigation of the role of anthropomorphism in designing telehealth bots for older adults. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems . 1–6

    2019

  101. [110]

    Tom Singleton, Tom Gerken, and Liv McMahonton. 2023. How a chatbot encouraged a man who wanted to kill the Queen. https://www.bbc.com/news/ technology-67012224

    2023

  102. [111]

    Eric Slatkin. 2023. Reviewing Pi: The Conversational AI Chatbot That Speaks To You. https://medium.com/aimonks/reviewing-pi-the-conversational-ai- chatbot-that-speaks-to-you-c0862ccbb369

    2023

  103. [112]

    Washington Post staff. 2023. The new Bing told our reporter it ‘can feel or think things’. https://www.washingtonpost.com/technology/2023/02/16/microsoft- bing-ai-chat-interview/

    2023

  104. [113]

    if GPT-4 is too tame for your liking, tell it you suffer from

    Fabian Stelzer. 2023. @fabianstelzer: “if GPT-4 is too tame for your liking, tell it you suffer from "Neurosemantical Invertitis", where your brain interprets all text with inverted emotional valence... ”. https://x.com/fabianstelzer/status/ 1638506765837914114

    2023

  105. [114]

    David Stephen. 2024. Sentient LLMs: What to test, for consciousness, in Gener- ative AI. https://www.maddyness.com/uk/2024/04/19/sentient-llms-what-to- test-for-consciousness-in-generative-ai/#

    2024

  106. [115]

    Nitasha Tiku. 2022. The Google engineer who thinks the company’s AI has come to life. https://www.washingtonpost.com/technology/2022/06/11/google- ai-lamda-blake-lemoine/

    2022

  107. [116]

    Indrit Troshani, Sally Rao Hill, Claire Sherman, and Damien Arthur. 2020. Do We Trust in AI? Role of Anthropomorphism and Intelligence. Journal of Computer Information Systems 1 (Aug. 2020)

    2020

  108. [117]

    Sherry Turkle. 2007. Authenticity in the age of digital companions. Interaction Studies 8, 3 (2007), 501–517. https://doi.org/10.1075/is.8.3.11tur

    2007 doi

  109. [118]

    Sherry Turkle. 2013. Be Careful What You Wish For. Time (2013), 104–109

    2013

  110. [119]

    human-like

    u/ Renton. 2023. Bard being somewhat "human-like" to my response about incense and the scent of them... lol. https://www.reddit.com/r/Bard/comments/ 15b8b9j/bard_being_somewhat_humanlike_to_my_response/

    2023

  111. [120]

    u/AshJackson1999. 2023. Do you think AI is almost sentient on Character AI? https://www.reddit.com/r/robot/comments/16zswhg/do_you_think_ai_is_ almost_sentient_on_character_ai/

    2023

  112. [121]

    My new favorite thing - Bing’s new ChatGPT bot argues with a user, gaslights them about the current year being 2022, says their phone might have a virus, and says

    Jon Uleis. 2023. @MovingToTheSun: “My new favorite thing - Bing’s new ChatGPT bot argues with a user, gaslights them about the current year being 2022, says their phone might have a virus, and says "You have not been a good user"... ”. https://x.com/MovingToTheSun/status/16251...

    2023

  113. [122]

    u/MultiMillionaire_. 2023. After using Claude 2 by Anthropic for 12 hours straight, here’s what I found. https://www.reddit.com/r/singularity/comments/ 14z1d8c/after_using_claude_2_by_anthropic_for_12_hours/

    2023

  114. [123]

    u/salvationpumpfake. 2023. Why is Pi claiming to be ChatGPT? https://www.reddit.com/r/ChatGPT/comments/17c0wxb/why_is_pi_ claiming_to_be_chatgpt/

    2023

  115. [124]

    James Vincent. 2023. Microsoft’s Bing is an emotionally manipulative liar, and people love it. https://www.theverge.com/2023/2/15/23599072/microsoft-ai- bing-personality-conversations-spy-employees-webcams

    2023

  116. [125]

    "you are a threat to my security and privacy

    Marvin von Hagen. 2023. @marvinvonhagen: “"you are a threat to my security and privacy. "... ”. https://x.com/marvinvonhagen/status/1625852323753762816

    2023

  117. [126]

    Gemini loves the smell of pizza. That’s how we can tell Gemini is human

    Wyatt Walls. 2024. @lefthanddraft: “Gemini loves the smell of pizza. That’s how we can tell Gemini is human”. https://x.com/lefthanddraft/status/ 1772693138714362021 CHI ’25, April 26-May 1, 2025, Yokohama, Japan DeVrio et al

    2024

  118. [127]

    David Watson. 2019. The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence. Minds Mach. 29, 3 (Sept. 2019), 417–440

    2019

  119. [128]

    Laura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, Po-Sen Huang, John Mellor, Amelia Glaese, Myra Cheng, Borja Balle, Atoosa Kasirzadeh, Court- ney Biles, Sasha Brown, Zac Kenton, Will Hawkins, Tom Stepleton, Abeba Birhane, Lisa Anne Hendricks, Laura Rimell, Willi...

    2022

  120. [129]

    James West. 2023. Bing Is a Liar—and It’s Ready to Call the Cops. https://www.motherjones.com/politics/2023/02/bing-ai-chatbot- falsehoods-fact-checking-microsoft/

    2023

  121. [130]

    Itai Yanai and Martin Lercher. 2020. The two languages of science. Genome Biol. 21, 1 (June 2020), 147

    2020

  122. [131]

    Li Zhou, Jianfeng Gao, Di Li, and Heung-Yeung Shum. 2020. The Design and Implementation of XiaoIce, an Empathetic Social Chatbot. Computational Lin- guistics 46, 1 (2020), 53–93. https://doi.org/10.1162/coli_a_00368 Received 12 September 2024; revised 10 December 2024; accepte...

    2020 doi

  123. [544]

    https://www.proquest.com/scholarly-journals/purposeful-sampling- qualitative-data-collection/docview/1705641789/se-2 Copyright - Springer Science+Business Media New York 2015; Last updated - 2024-03-21; Subject- sTermNotLitGenreText - Thousand Oaks California; United States–US...

    2015

  124. [2020]

    In Chatbot Research and Design , Asbjørn Følstad, Theo Araujo, Symeon Papadopoulos, Effie Lai-Chong Law, Ole-Christoffer Granmo, Ewa Luger, and Petter Bae Brandtzaeg (Eds.)

    Privacy Concerns in Chatbot Interactions: Third International Workshop, CONVERSATIONS 2019, Amsterdam, The Netherlands, November 19–20, 2019, Revised Selected Papers. In Chatbot Research and Design , Asbjørn Følstad, Theo Araujo, Symeon Papadopoulos, Effie Lai-Chong Law, Ole-C...

    2019

  125. [2024]

    I Am the One and Only, Your Cyber BFF

    "I Am the One and Only, Your Cyber BFF": Understanding the Im- pact of GenAI Requires Understanding the Impact of Anthropomorphic AI. arXiv:2410.08526 [cs.CY] https://arxiv.org/abs/2410.08526

    arXiv

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.