Hadas Kotek

office location: Cambridge, MA
email: hkotek at alum.mit.edu

I am a machine learning researcher and linguist working at Apple. I am currently a data science manager on the Responsible AI team, leading the data and evaluation efforts for Apple Intelligence’s text features. In this role, I focus on identifying and evaluating harms and biases in customer-facing products that use Apple’s Large Language Models. These products include Apple’s summarization models, writing tools, smart replies, Siri, as well as the foundation model itself.

I additionally maintain an affiliation with the MIT Department of Linguistics, and continue to engage in research and publication as part of my role at Apple and as my role at MIT. My publications have focused on NLP, human-in-the-loop annotation, efficient data collection, question answering, visual understanding, and Responsible AI. In Falls 2023 and 2024, I taught a seminar on LLMs at MIT, open to undergraduate and graduate students in the Boston area. Check out the syllabus and blurb on my teaching page.

I am currently a member of the Executive Committee of the Linguistic Society of America (LSA), Chair of the LSA Committee on Gender Equity in Linguistics, and a member of the LSA Committee on Linguistic Institutes and Fellowships. Most recently, I co-organized LEXING: Linguists in Industry, Non-profits, and Government, a symposium co-located with the LSA Annual Meeting in January 2025, bringing together linguists working outside academia in all sectors and careers.

I received my PhD in Linguistics from MIT in 2014, with a dissertation on the syntax, semantics, and processing of questions. Prior to joining Apple, I was a Lecturer in Semantics at Yale and a Visiting Assistant Professor in Syntax at NYU, and I have held a Mellon Postdoctoral Fellowship at McGill University. My academic research focused on different aspects of the syntax-semantics interface, using both traditional and experimental methods. I mainly worked on A-bar phenomena, including wh-questions, focus constructions, relative clauses and free relatives, ellipsis, wh-indefinites, (focus) intervention effects, and comparatives and superlatives.

Please visit my About page for more details concerning my research interests and my academic history. See my resume, my academic CV, my MIT linguistics user page, or my LinkedIn page for additional details.

✨ ️NEW✨ Blog

Responsible AI

Text-to-image models are shallow in more ways than one (part 2): a discussion of interesting aspects of the images generated in part 1 with respect to gender, race and ethnicity, age, attractiveness, lexical choices, and image style. In short: the models exhibit biases along all these dimensions, in fairly predictable and yet concerning ways.
Text-to-image models are shallow in more ways than one (part 1): a summary of some basic experiments I carried out for my seminar on LLMs, focusing on syntactic and semantic ambiguity. We find that text-to-image models engage in very shallow parsing, likely not much more than a bag-of-words approach. Many sometimes-surprising frequency effects follow.
Stereotypical Gender Effects in 2016: a summary of a co-authored study I conducted in 2016 exploring stereotypes associated with occupation-denoting nouns. Full dataset here (csv)
Doctors can’t get pregnant and other gender biases in ChatGPT: a writeup of my Twitter post that went viral, illustrating gender biases in ChatGPT.

Informational posts about non-academic jobs

A science vs Engineering mindset (aka Academia vs Industry): on two major differences between academia an industry: the Science vs Engineering mindset, and teamwork.
My non-academic job market journey: An FAQ-style post answering the most commonly asked questions about my process of leaving academia and finding my first non-academic job.
Job application materials: in this post I share two versions of my academic job application materials, one from my first post-PhD cycle and one from the last cycle. I also share the resume that got me my alt-ac job at the end of that last cycle.
A guided self-reflection for getting started with Alt-Ac jobs: a post with lots of questions you can ask yourself to start figuring out what jobs are right for you.
Job titles and job descriptions for linguists (and other social scientists): a compilation of (a) job titles, (b) informal job descriptions, (c) sample job ads, and (d) interviews with job holders for a diverse set of non-technical roles for linguists. This post is over 5k words long and divided into 10 categories, since there’s a lot to cover.
Transferable skills (and how to talk about them): a compilation of transferable skills for AltAc jobs, including sample resume bullet points using my own experience in academia to illustrate.
Learning about Alt-Ac opportunities (aka how to get started): on getting started on the journey by asking yourself some questions and gathering some information.
Prepping for Alt-Ac jobs (aka taking action): on getting started on the journey by taking some active steps to learn or expand relevant skills.
Alt-Ac informational interviews: on informational interviews for alt-ac careers, including a suggested list of questions.
Do you need a graduate degree to get an Alt-Ac job?: answering this FAQ. Short answer: probably not.
Let’s talk about terminology: an ongoing master list of industry terminology.

Posts about academia

Rejection sucks: a post that reflects on just how much rejection sucks, and how it’s more a part of the academic life than the life outside it.
Job application materials: in this post I share two versions of my academic job application materials, one from my first post-PhD cycle and one from the last cycle. I also share the resume that got me my alt-ac job at the end of that last cycle.
On the emotional toll of the academic job market: a reflection on how emotionally difficult it was to be on the academic job market.
My academic job market journey: a short post about my own experience on the academic job market, mainly focusing on the numbers and concrete facts.
On leaving academia: a three-part post (part 2, part 3) that gets a bit navel-gazy.
Academic job interview questions: a compilation of 25 sets of interview questions I was asked in interviews between 2014–2019.

Science and other outreach

The Intersection of AI and Gender: Safety issues in LLMs. Panel at Grace Hopper, October 2024.
LSA Summer Institute at UMass: Careers in Language Technologies, a 4-lecture series, summer 2023.
Superlinguo jobs series post.
The Vocal Fries podcast appearance (“John Mary Bill Sue”).
Because Language podcast appearance.
@Science_Is_US #PeopleofScience campaign on Twitter and Instagram by scienceisus.org.
Linguistic Society of America: January 2021 Member Spotlight.
Resources on Equity and Inclusivity in Linguistics (REIL) Guidelbook: a joint effort of LSA’s COGEL (Committee on Gender Equity in Linguistics, formerly COSWL) and SALT’s SALTED (Semantics and Linguistic Theory: Equity and Diversity): with Melissa Baese-Berk, Michael Yoshitaka Erlewine, Ivona Kucerova, Elin McCready, Mary Moroney, Jessica Rett, Carly Sommerlot, and Susi Wurmbrand.
Pop-Up Mentoring Program; originally with by Melissa Baese-Berk, Paola Cepeda, Kristen Syrett, Jessica Rett, Ivona Kucerova. Now a continued LSA COGEL effort. The recipient of the 2019 LSA Linguistic Service Award.

Newest work

Technical Report

Apple Authors (including Hadas Kotek). 2024. Apple Intelligence Foundation Language Models

Peer reviewed conference papers:

Hadas Orgad, Michael Toker, Zorik Gekhman, Roi Reichart, Idan Szpektor, Hadas Kotek, Yonatan Belinkov. 2025. LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations. The Thirteenth International Conference on Learning Representations (ICLR).
Hadas Kotek, David Q. Sun, Zidi Xiu, Margit Bowler, Christopher Klein. 2025. Protected group bias and stereotypes in Large Language Models. The 101st Annual Meeting of the Linguistic Society of America (LSA).
David Q. Sun, Artem Abzaliev, Hadas Kotek, Zidi Xiu, Christopher Klein, Jason D. Williams. 2023. DELPHI: Data for Evaluating LLMs’ Performance in Handling Controversial Issues. The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP).
Hadas Kotek, Rikker Dockum, and David Q. Sun. 2023. Gender bias and stereotypes in Large Language Models. ACM Collective Intelligence conference (CI).
Xiu, Zidi, Kai-Chen Cheng, David Q. Sun, Jiannan Lu, Hadas Kotek, Yuhan Zhang, Paul McCarthy, Christopher Klein, Stephen Pulman, Jason D. Williams. 2023. Feedback Effect in User Interaction with Intelligent Assistants: Delayed Engagement, Adaption and Drop-out. The 27th meeting of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD).
Patel, Alkesh, Joel Moniz, Roman Nguyen, Hadas Kotek, Nick Tzou, Vincent Renkens. 2021. MMIU: Dataset for Intent Understanding in Multimodal Assistant”. West Coast NLP (WeCNLP).
Sun, David Q., Hadas Kotek, Christopher Klein, Mayank Gupta, William Li and Jason D. Williams. 2020. Improving Human-Labeled Data through Dynamic Automatic Conflict Resolution. The 28th International Conference on Computational Linguistics (COLING).
Patel, Alkesh, Akanksha Bindal, Hadas Kotak, Christopher Klein, and Jason D. Williams. Generating Natural Questions from Images for Multimodal Assistant.
- West Coast NLP (WeCNLP), October 2020.
- IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2021.

Journal papers:

Paola Cepeda, Hadas Kotek, Katharina Pabst, and Kristen Syrett. 2021. Gender bias in linguistics textbooks: Has anything changed since Macaulay & Brice (1997)?. Language 97(4): 678–702.
Kotek, Hadas, Rikker Dockum, Sarah Babinski, and Christopher Geissler. 2021. Gender bias and stereotypes in linguistic example sentences. Language 97(4): 653–677.
Kotek, Hadas, Sarah Babinski, Rikker Dockum, and Christopher Geissler. 2021. Gender stereotypes and inclusion in language teaching. Babylonia 1: 66–70.
Kastner, Itamar, Hadas Kotek, Rikker Dockum, Michael Dow, Maria Esipova, Caitlin Green, Todd Snider. Who speaks for us? Lessons from the Pinker letter. Manuscript.

Books:

Kotek, Hadas. 2019. Composing Questions. Linguistics Inquiry Monograph series. Cambridge, MA: MIT Press.
Halpert, Claire, Hadas Kotek, and Coppe van Urk (eds.). 2017. A Pesky Set: Papers for David Pesetsky. MIT Working Paper in Linguistics 80. Cambridge, MA: MITWPL.

Recorded talks

Gender bias in constructed example sentences (with Rikker Dockum, Sarah Babinski, and Christopher Geissler); slides, YouTube recording.
- Webinar, SOAS, March 2021.
- Colloquium talk, University of Connecticut, March 2021.
- Colloquium talk, University of Oregon, October 2020.
Ellipsis licensing in sluicing: A QuD account (with Matthew Barros; handout, slides, video recording).
- Chicago Linguistic Society (CLS) 53, University of Chicago, May 2017.
- Multiple questions about sluicing, Yale University, April 2017.
- GLOW workshop on compositionality at the interfaces, Leiden University, March 2017.
Diagnosing covert movement. Panel on questions, workshop for David Pesetsky. MIT Department of Linguistics, February 2017. (handout, slides, video recording, starting at 1:15:30).

Additional details about these and other papers and presentations can be found on my publications page. To read more about my various projects, visit the research page.

For the most up to date list of my presentations and publications, please consult my CV.