About the project
What is GenAI?
A play on words, a mirror for how you communicate, and a bridge between linguistics research and everyday conversation.
The name
“GenAI” is everywhere as shorthand for generative AI. We took the “Gen” in a different direction: Gender + AI. Instead of just generating text, we explore how gender shapes communication — and what your preferences reveal about you.
How it works
Every message you send produces two answers from the same model with the same knowledge. One is labelled Kyle, the other Kylie. The content is held constant; the only variable is the register— the measurable verbal features the answer is written in.
The two registers are defined by features that linguistics research has actually measured, not by personality traits. Kyle is written at the assertive / report end of the continuum: declarative sentences, few hedges, references to quantity and procedure, directives, the solution stated first. Kylie is written at the affiliative / rapport end: hedges and tag questions, first- and second-person pronouns, emotion and relationship vocabulary, questions that invite the other person in, acknowledgement before advice. These feature lists come from Mulac et al. (2001), Newman et al. (2008) and the Leaper meta-analyses below.
The names are labels for the two ends of that continuum. They are not a claim that men speak like Kyle or that women speak like Kylie. In the pooled evidence the average gender difference on these features is small (Cohen's d of roughly 0.1 to 0.3), variation within each gender is far larger than the gap between them, and the same person moves along the continuum depending on audience, setting and power. Kyle and Kylie are therefore two points on a scale that every speaker uses.
You choose the answer you prefer. After several rounds GenAI reports which verbal features you gravitate toward — directness or acknowledgement, assertion or hedging, procedure or context. The result describes your preference for a register. It does not infer, and cannot infer, anything about your gender.
Similarities and differences: what the studies conclude
Mostly similar. The largest body of evidence points to similarity. Across 46 meta-analyses, about 78% of measured gender differences are small or near zero, and verbal variables sit firmly in that group (Hyde 2005). Verbal ability is equal for practical purposes (d= 0.11 across 1.4 million people; Hyde & Linn 1988). Men and women speak the same amount — about 16,000 words a day each when recorded in daily life (Mehl et al. 2007). In natural online writing, women and men are equally assertive (Park et al. 2016). None of the classic claims about who talks more, who is more articulate, or who is more forceful survive large samples.
Small, real, situational differences. Where differences appear they are consistent but modest, and they move with context. Women use slightly more tentative language — hedges, tag questions, disclaimers (d = 0.23) — but chiefly in groups, with strangers and in lab tasks; in familiar settings the gap nearly closes (Leaper & Robnett 2011). Women use slightly more affiliative speech and men slightly more assertive speech, each by a hair (d = 0.12 and 0.09; Leaper & Ayres 2007). Word choice differs in aggregate: more pronouns, emotion and social words from women; more numbers, articles and object references from men (Newman et al. 2008), reliably enough that gender can be predicted from vocabulary at about 92% on very large samples (Schwartz et al. 2013) even though any two individuals overlap heavily. Women self-disclose slightly more, mainly to close partners (d = 0.18; Dindia & Allen 1992). Men make more floor-taking interruptions (d= 0.33), though overall interruption rates are close (Anderson & Leaper 1998).
Context beats gender.The strongest predictors of how someone talks are who they are talking to, where, and with how much power. Tentative language rises when women address men and is more persuasive to them (Carli 1990). Floor time rises with power for men but not for women, who face backlash for the same behaviour (Brescoll 2011). In deliberating groups women speak as much as men only when they are the majority or the group must decide unanimously (Karpowitz & Mendelberg 2014). Even at the Supreme Court, female justices are interrupted about three times as often as their male colleagues (Jacobi & Schweers 2017). These patterns describe the situation, not a fixed trait of the speaker.
What the model concludes.Gendered communication is a distribution, not a dichotomy: two heavily overlapping curves whose means differ by a fraction of a standard deviation, shifted further by setting than by sex. GenAI therefore treats “masculine” and “feminine” register as ends of a continuum every speaker uses, keeps the measured effect sizes in view when it describes your preferences, and does not use sources whose claims fail at scale.
The research
Every source the model draws on is listed below, restricted to the verbal layer of communication — word choice, hedging, turn-taking, floor time and disclosure — because GenAI is a text conversation. Sources are grouped into three tiers by the kind of evidence they provide, and each is scored on three criteria.
How sources are scored
Each source receives 1–5 on Authority (who published it and where: flagship peer-reviewed journal or university press = 5, trade publisher or broadcaster = 1–2), Factualness (quality of the evidence: sample size, method, replication; fiction is 1 by definition) and Consensus (how widely the finding is accepted, or the work is used, by scholars in language-and-gender research). The weighted score is 30% authority + 40% factualness + 30% consensus. Factualness is weighted highest because the app makes empirical claims.
Note on the tier names: in library terms a meta-analysis is a “secondary” source because it analyses other studies. Here the tiers rank evidentiary role in this app, so pooled quantitative evidence is Tier 1.
Primary evidence
12 sourcesMeta-analyses and large-sample quantitative studies published in peer-reviewed journals. A meta-analysis pools dozens to hundreds of independent studies, so its effect sizes are the most reliable numbers available. These sources set the factual claims the model is allowed to make.
Janet Shibley Hyde
The Gender Similarities Hypothesis (2005)
American Psychologist, 60(6), 581–592
5.0
/ 5 weighted
Reviews 46 meta-analyses. About 78% of measured gender differences are small or near zero (d ≤ 0.35), including nearly all verbal and communication variables. The framing source for this project.
Campbell Leaper & Melanie Ayres
A Meta-Analytic Review of Gender Variations in Adults’ Language Use (2007)
Personality and Social Psychology Review, 11(4), 328–363
5.0
/ 5 weighted
Men are slightly more talkative (d = −0.14); women use slightly more affiliative speech (d = 0.12); men slightly more assertive speech (d = 0.09). Setting, partner and task moderate the effects more than gender does.
Janet Shibley Hyde & Marcia Linn
Gender Differences in Verbal Ability: A Meta-Analysis (1988)
Psychological Bulletin, 104(1), 53–69
5.0
/ 5 weighted
165 studies, 1.4 million participants. Overall verbal-ability difference favoring women is d = 0.11 — negligible. Whatever style differences exist, they are not differences in verbal skill.
Sara Jaffee & Janet Shibley Hyde
Gender Differences in Moral Orientation: A Meta-Analysis (2000)
Psychological Bulletin, 126(5), 703–726
5.0
/ 5 weighted
113 studies testing Gilligan’s care-vs-justice claim. Care orientation d = 0.28 favoring women, justice d = 0.19 favoring men — small and inconsistent. Gilligan’s framework is kept as vocabulary, not as a measured difference.
Alice Eagly & Blair Johnson
Gender and Leadership Style: A Meta-Analysis (1990)
Psychological Bulletin, 108(2), 233–256
4.7
/ 5 weighted
Women lead somewhat more democratically and participatively; men more autocratically. The gap is clearest in lab studies and shrinks in real organizations, where role expectations override gender.
Matthias Mehl, Simine Vazire, Nairán Ramírez-Esparza, Richard Slatcher & James Pennebaker
Are Women Really More Talkative Than Men? (2007)
Science, 317(5834), 82
4.6
/ 5 weighted
Recorded 396 people’s daily speech with wearable microphones. Both women and men spoke about 16,000 words per day; the difference was not significant. Disproves the "women speak 20,000 words, men 7,000" myth.
Campbell Leaper & Rachael Robnett
Women Are More Likely Than Men to Use Tentative Language, Aren’t They? (2011)
Psychology of Women Quarterly, 35(1), 129–142
4.4
/ 5 weighted
Women use more hedges, tag questions and disclaimers (d = 0.23). The gap is larger in groups, with strangers and in lab tasks, and near zero in familiar settings — tentative language works as a politeness strategy, not a sign of uncertainty.
Kathryn Dindia & Mike Allen
Sex Differences in Self-Disclosure: A Meta-Analysis (1992)
Psychological Bulletin, 112(1), 106–124
4.3
/ 5 weighted
205 studies. Women self-disclose slightly more (d = 0.18), mostly to other women and to close partners; the difference nearly vanishes with strangers.
Kristin Anderson & Campbell Leaper
Meta-Analyses of Gender Effects on Conversational Interruption (1998)
Sex Roles, 39, 225–252
4.0
/ 5 weighted
Men make more intrusive (floor-taking) interruptions (d = 0.33), but the overall interruption difference is small (d = 0.15) and depends on group size and setting. Replaces the widely repeated "men make 96% of interruptions" claim, which came from 31 conversations.
Matthew Newman, Carla Groom, Lori Handelman & James Pennebaker
Gender Differences in Language Use: An Analysis of 14,000 Text Samples (2008)
Discourse Processes, 45(3), 211–236
4.0
/ 5 weighted
Women used more pronouns, emotion words and references to social and psychological processes; men used more numbers, articles, long words, object references and swear words. Effects are consistent but small (most d < 0.3).
Gregory Park, David Yaden, H. Andrew Schwartz et al.
Women Are Warmer but No Less Assertive than Men: Gender and Language on Facebook (2016)
PLoS ONE, 11(5), e0155885
4.0
/ 5 weighted
About 66,000 users. Women’s language rated warmer, more compassionate and more polite; men’s colder, more impersonal and more hostile. Assertiveness was equal. The "assertive man / tentative woman" split does not survive at scale.
H. Andrew Schwartz, Johannes Eichstaedt, Margaret Kern et al.
Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach (2013)
PLoS ONE, 8(9), e73791
4.0
/ 5 weighted
75,000 volunteers, 700 million words. Gender predictable from word choice at ~92% accuracy — proof that aggregate vocabulary differences are real — while individual overlap remains large.
Secondary scholarship
13 sourcesRigorous single studies, scholarly frameworks, standard textbooks, and academic critiques. Still peer-reviewed or university-press, but either based on one sample, one setting, or on interpretive rather than statistical methods. These sources supply the vocabulary and mechanisms; their numbers are checked against Tier 1 before use.
Penelope Eckert & Sally McConnell-Ginet
Language and Gender (2003)
Cambridge University Press (2nd ed. 2013)
4.6
/ 5 weighted
The standard graduate textbook. Frames gendered speech as practice within communities rather than fixed traits; synthesizes the hedging, inclusive-language and collaborative-style literature.
Linda Carli
Gender, Language, and Influence (1990)
Journal of Personality and Social Psychology, 59(5), 941–951
4.3
/ 5 weighted
Women used more tentative language when talking with men than with women. Tentative women were more persuasive to male listeners and less persuasive to female listeners — hedging is audience-adaptive.
Deborah Cameron
The Myth of Mars and Venus: Do Men and Women Really Speak Different Languages? (2007)
Oxford University Press
4.3
/ 5 weighted
A linguist’s review of the evidence: popular "different languages" claims are overstated; most measured differences are small, situational and heavily overlapping. The main counterweight in this catalog.
Victoria Brescoll
Who Takes the Floor and Why: Gender, Power, and Volubility in Organizations (2011)
Administrative Science Quarterly, 56(4), 622–641
4.0
/ 5 weighted
Senate floor records plus experiments: gaining power increases how much men talk but not women, because powerful women who talk more are rated less competent. Floor time tracks power and backlash risk, not a female preference for brevity.
Christopher Karpowitz & Tali Mendelberg
The Silent Sex: Gender, Deliberation, and Institutions (2014)
Princeton University Press
4.0
/ 5 weighted
Controlled deliberation experiments: women speak less than men in mixed groups under majority rule, and reach parity only when they are the majority or the group must decide unanimously. Institutions, not dispositions, set who talks.
Anthony Mulac, James Bradac & Pamela Gibbons
Empirical Support for the Gender-as-Culture Hypothesis (2001)
Human Communication Research, 27(1), 121–152
3.7
/ 5 weighted
Catalogs the "gender-linked language effect": women — intensifiers, hedges, questions, emotion references, longer sentences; men — quantity references, directives, judgmental adjectives, elliptical sentences, "I" references. The most concrete feature list available.
Janet Holmes
Women, Men and Politeness (1995)
Longman
3.6
/ 5 weighted
New Zealand corpus data on compliments and apologies: women give and receive more compliments and use apologies as social lubricant rather than admissions of fault. Real data, one national corpus.
Jennifer Coates
Women, Men and Language (2004)
Routledge (3rd ed.)
3.6
/ 5 weighted
Standard sociolinguistics textbook; strongest on turn-taking, same-gender talk and the difference between overlapping (supportive) and interrupting (competitive) speech.
Tonja Jacobi & Dylan Schweers
Justice, Interrupted: The Effect of Gender, Ideology, and Seniority at Supreme Court Oral Arguments (2017)
Virginia Law Review, 103, 1379–1496
3.4
/ 5 weighted
Decades of oral-argument transcripts: female justices are interrupted roughly three times as often as male justices, by advocates and by colleagues, even after controlling for seniority.
Niobe Way
Deep Secrets: Boys’ Friendships and the Crisis of Connection (2011)
Harvard University Press
3.3
/ 5 weighted
Longitudinal interviews with about 135 boys: in early adolescence they talk openly about emotional intimacy, then learn to suppress that talk by late adolescence. Lower male emotional disclosure looks learned, not innate.
Deborah Tannen
You Just Don’t Understand: Women and Men in Conversation (1990)
William Morrow
2.9
/ 5 weighted
Introduced "rapport talk" (connection-oriented) vs "report talk" (status/information-oriented). Influential and widely taught, but interpretive: built on transcribed examples rather than measured samples, and criticized for treating tendencies as categories.
Robin Lakoff
Language and Woman’s Place (1975)
Harper & Row
2.9
/ 5 weighted
The founding text of the field. Proposed "women’s language": hedges, tag questions, intensifiers, super-polite forms. Based on introspection, not data; several claims were later partly confirmed (Leaper & Robnett 2011; Mulac et al. 2001) and others not.
Carol Gilligan
In a Different Voice (1982)
Harvard University Press
2.6
/ 5 weighted
Argued women reason about moral problems through an "ethic of care" and men through an "ethic of justice." Culturally important; empirically weak — the meta-analysis (Jaffee & Hyde 2000) finds only small, inconsistent differences.
Tertiary & cultural
10 sourcesPopular science, documentaries, and fiction. These carry no evidentiary weight — they are catalogued to set tone, to show how the topic lives in culture, and to be explicit about which well-known works the model does not treat as fact.
The novels and stories are here deliberately. Fiction has no evidentiary weight, but it shows the phenomenon the research measures — indirectness, floor-holding, the same exchange remembered two ways — and sets the tone for how Kyle and Kylie are written. They are scored on the same scale for consistency, which is why their factualness is 1.
James Pennebaker
The Secret Life of Pronouns (2011)
Bloomsbury
3.3
/ 5 weighted
Accessible account of the word-count research behind Newman et al. (2008) and Mehl et al. (2007). Reliable, but a popularization — the underlying papers are what the model cites.
Ernest Hemingway
Hills Like White Elephants (1927)
2.5
/ 5 weighted
A short story told almost entirely in dialogue, in which a couple avoids naming the decision between them. A staple of discourse-analysis teaching for indirectness, hedging and who controls the topic.
Jane Austen
Pride and Prejudice (1813)
2.2
/ 5 weighted
The archetype of talk as negotiation of status and relationship. Elizabeth’s indirection and irony against Darcy’s blunt declaratives are the "rapport vs report" contrast two centuries before Tannen named it.
Jennifer Siebel Newsom (dir.)
The Mask You Live In (2015)
The Representation Project
2.0
/ 5 weighted
Documentary on how boys learn to suppress emotional talk. Advocacy in form, but it interviews the researchers behind Tier 2 work (Niobe Way, Michael Kimmel). Useful for tone, not for numbers.
Raymond Carver
What We Talk About When We Talk About Love (1981)
1.9
/ 5 weighted
Two couples try, and fail, to define love across an evening of drinks. Shows men holding the floor with anecdote and abstraction while the women anchor the talk in specific people.
Harald Eia (NRK)
Hjernevask (“Brainwash”): The Gender Equality Paradox (2010)
NRK, Norway
1.7
/ 5 weighted
Provocative TV series pitting gender-studies scholars against biology-leaning psychologists. Illustrates the nature–nurture argument; one-sided in editing and contested by both sides.
BBC Two
No More Boys and Girls: Can Our Kids Go Gender Free? (2017)
BBC
1.6
/ 5 weighted
A single classroom of about 23 seven-year-olds tries a gender-neutral term. Engaging and illustrative; the sample is far too small to support any claim.
Sally Rooney
Normal People (2018)
1.6
/ 5 weighted
A contemporary study of two people who repeatedly mis-read each other’s under-stated messages. Sets the tone for how small differences in directness compound into misunderstanding.
Taffy Brodesser-Akner
Fleishman Is in Trouble (2019)
1.6
/ 5 weighted
The same marriage narrated first from the husband’s side, then the wife’s. Dramatizes how the "same" conversation is reported differently depending on who is speaking — the app’s central premise.
John Gray
Men Are from Mars, Women Are from Venus (1992)
HarperCollins
1.0
/ 5 weighted
The best-selling account of the "different planets" idea (men retreat to a "cave," women talk problems through). No empirical basis; the talkativeness and assertiveness claims are contradicted by Mehl et al. (2007) and Park et al. (2016).
Catalogued for transparency. Not used by the model.
35 sources catalogued; 34 used by the model. Effect sizes are Cohen's d: 0.2 is conventionally small, 0.5 medium, 0.8 large.
Your account and your data
GenAI needs an account because the insight comes from a pattern, not a single answer. Everything is stored against your account and nothing else: each conversation (your messages and both responses), each pick you make per turn, and each reportgenerated from those picks. Sign in from any device and your conversations, pinned chats and reports are there; sign out and they are invisible to anyone else. Delete a conversation and its messages and picks go with it. Forgot your password? Use the reset link on the sign-in page — your data is unaffected.
What this is not
This is not about who communicates “better,” and it is not a test of your gender. There is no right answer. Both registers are effective, both are used by people of every gender, and most people use both in a single day. The point is self-awareness — understanding why you prefer how something is said, not just what is said.