To Luz Marina Mateo, proud fighter, woman, and Afro-descendant
By Javier Surasky
Introduction
Gender
discrimination in the sciences, especially in STEM, is not a new topic, nor is it
“a matter of perceptions”: according to official UNESCO data, women researchers
represented 31.7% of researchers worldwide in 2022 (Straza et al., 2025) and,
in the specific field of AI, there are field-specific gaps: in almost all of
the 43 countries analyzed in Stanford’s AI Index 2025 report (Maslej et al.,
2025:23–26), women show a lower “skills penetration” and “talent concentration”
index than men.
In other
words: inequality does not only affect who enters science and technology, but
also who reaches the spaces where the AI agenda is decided and, consequently,
the “truths” it produces, through multiple mechanisms that have already been
well studied by authors such as Margaret Rossiter (1995), who has documented
the multiple barriers that historically limited women’s participation and
recognition in scientific disciplines; Londa Schiebinger (1999), who made it
clear that it is not a quantitative but a qualitative problem from the moment
that gender shapes the questions and influences what is “sayable” in the
answers; Janet Abbate (2012), who describes how the patriarchal culture of the
computational field defined what should be understood as “expert work”; and
Judy Wajcman and Erin Young, who denounce that digital technologies “are
socially shaped by gender power relations” (Wajcman & Young, 2023:49).
When examining
AI from a gender perspective, it becomes clear that women’s contributions have
historically been undervalued or rendered invisible, a pattern that is
increasingly relevant given its impact on model training and bias.
In this
blog, we present the first part of a list of 20 pioneering and outstanding
women in the field of AI. Our choice of names, like any other on this topic, is
debatable and could be expanded, and each person will be able to find absences
that seem inexplicable. To be clear, this is my list of women who have
contributed to and continue to contribute to progress in AI, but each person
may have their own. The order of the list is chronological and does not imply
any “ranking”.
For reasons
of length, we begin here with the first nine women on the list, establishing a
cutoff that coincides with the holding of the 1956 “Dartmouth Conference”, a
foundational milestone of the AI field. In the second part, we will continue
with the remaining 11.
Outstanding women in the field of AI (before the Dartmouth Conference)
1. Ada Lovelace.
She was
born on December 10, 1815 in London and developed her intellectual work in the
British scientific circle, linked to Charles Babbage and the Analytical Engine
project. Daughter of the poet Lord Byron and of Anna Isabella Milbanke (Lady
Byron), a reform-minded woman and a mathematician.
Long before
computers existed, Ada Lovelace imagined the possibility that a calculating
machine could follow instructions and manipulate symbols to carry out
mathematical operations, but also create music or images if it were given
rules. Her 1843 “Notes” on the Analytical Engine, and in particular “Note G”,
with an algorithm to calculate Bernoulli numbers, are usually recognized as the
first published algorithm for a computer.
2. Grace Hopper.
She was
born in December 1906 in the United States, a country in which she pursued her
career in both the military (U.S. Navy) and the development of early computing
systems, including UNIVAC, and in the development of languages such as COBOL.
She was a
driving force behind making programming something more “human”, implementing
initial ideas to help compilers, those programs that translate instructions
into machine language, contributing to the expansion of software among
governments and companies, thereby demonstrating that the field of programming
could be a strategic political-economic domain and the value of moving toward
symbolic programming.
3. Gladys Brown West.
She was
born in the U.S. in 1930 and recently passed away (January 2026). She worked in
applied mathematics and satellite geodesy, that is, the mathematical modeling
of Earth's shape, gravity coefficients, and vertical deflections, and the
processing of data from satellites such as GEOS-3, Seasat, and Geosat.
Her “global
mapping” work was one of the most relevant inputs for the development of the
Global Positioning System (GPS), making it possible for it to achieve the
precision required for its operation and which today is critical for countless
AI applications that involve mobility, logistics and autonomy, such as robotics
or autonomous vehicles, among others.
In an
interview she gave to The Guardian (Mohdin, 2020) she said: “I felt
proud of myself as a woman, knowing that I can do what I can do. But as a black
woman, that’s another level, where you have to prove to a society that hasn’t
accepted you for what you are”.
4. Frances E. Allen.
She was
born in 1932 in New York. The central part of her career took place at IBM and
made her a pioneer in the search to make programs run better, faster and more
efficiently through optimization and the improvement of compilers, driving the
fields of high-performance computing and parallel processing.
She was the
first woman to receive the Turing Award, in 2006 (the prize began to be awarded
in 1966), for her pioneering work in the theory and practice of compiler
optimization.
5. Ruzena Bajcsy.
Born in
1933 in then-Czechoslovakia (today Slovakia). She traveled to the U.S. to study
and decided not to return to her country due to the Soviet invasion of 1968,
which followed the “Prague Spring”. She taught at universities such as
Pennsylvania and Berkeley and held posts such as head of the Computer and
Information Science and Engineering Directorate at the National Science
Foundation.
The axis of
her work was in robotics and perception, with a special focus on active sensory
perception, analyzing how to model and control the perceptual processes that
robots achieve through sensors and processing to decide their actions. One of
her works in the area, titled Active Perception (Bajcsy, 1988), is
considered a milestone.
6. Karen Spärck Jones.
Born in
August 1935 in England. She advanced computerized information retrieval in
texts, through identifying words that matter more and less in a document, the
basis of many current search and language analysis techniques: she formulated
the idea of “inverse document frequency (IDF)” in 1972, which is the basis of
TF-IDF (Term Frequency–Inverse Document Frequency), which is a statistical
technique currently used in natural language processing and supports a good
part of modern search.
7. Margaret Hamilton.
Born in
August 1936 in the U.S. and made her most influential contribution at the MIT
Instrumentation Laboratory, within NASA, where she led the development of
navigation and control software for the Apollo missions, driving the design of
programs that could withstand failures, recover from errors, and function under
extreme pressure. She is considered a key figure in the professionalization of
software engineering.
8. Barbara Grosz.
Born in
July 1948 in the U.S., and her main contribution took place in the field of
conversation and the coordination of actions between people and systems: she
researched how systems can follow the thread of a dialogue, interpret
intentions and collaborate with people in complex tasks. Her findings were
taken up in the development of conversational assistants and models of
human-machine cooperation.
Her work Attention,
Intentions, and the Structure of Discourse, written together with Candace
Sidner, is considered a classic on discourse structure and the purpose of
dialogue, where the authors themselves state that “Although admittedly still
incomplete, the theory (presented in the article) does provide a solid basis
for investigating both the structure and meaning of discourse, as well as for
constructing discourse-processing systems” (Grosz & Sidner, 1986:202).
9. Katharina Morik.
Born in
Germany in 1954, she pursued her career there, initially focusing on the
development of computer science and later on machine learning, with special
emphasis on the challenges of operation under constraints/data insufficiency,
as well as on efficient resource handling (resource-constrained/green machine
learning).
She earned
her doctorate in 1981 from the University of Hamburg, with work on AI and
language. Ten years later, she inaugurated the Chair of Artificial Intelligence
at the University of Dortmund, where she kept the center of her professional
activity until her retirement, in 2023. In the final part of her career, she
contributed to the consolidation of the German machine learning ecosystem and
served as the founding director of the Lamarr Institute for Machine Learning
and Artificial Intelligence.
She stated
that “there are obstacles and discomforts in the reality of studies and work
[in computer science] for women” since “women are seen less as colleagues than
as visual decoration” (Morik, n.d. Translated from German with AI).
What comes next
In our next blog post, we will continue expanding this list with 11 women born after the Dartmouth conference in 1956, when AI became a specific field of study.
References
Abbate, J.
(2012). Recoding Gender: Women’s Changing Participation in Computing.
The MIT Press. https://direct.mit.edu/books/monograph/2962/Recoding-GenderWomen-s-Changing-Participation-in
Bajcsy, R.
(1988). “Active Perception”. Proceedings of the IEEE, 76(8), 996–1005. https://www.researchgate.net/profile/Yiannis-Aloimonos/publication/228083826_Active_Perception/links/00b49528e6f94c813e000000/Active-Perception.pdf
Grosz, B. y
Sidner, C. (1986) Attention, Intentions, and the Structure of Discourse.
Computational Linguistics, 12(3), 175–204.
Maslej, N.;
Fattorini, L.; Perrault, R.; Gil, Y.; Parli, V.; Kariuki, N.; Capstick, E.;
Reuel, A.; Brynjolfsson, E.; Etchemendy, J.; Ligett, K.; Lyons, T.; Manyika,
J.; Niebles, J.C.; Shoham, Y.; Wald, R.; Walsh, T.; Hamrah, A.; Santarlasci,
L.; Betts Lotufo, J.; Rome, A.; Shi, A. y Oak, S. (2025). The AI Index 2025
Annual Report. AI Index Steering Committee, Institute for Human-Centered
AI, Stanford University. https://doi.org/10.48550/arXiv.2504.07139
Mohdin, A,
(2020, November 19). Gladys West: the hidden figure who helped invent GPS. The
Guardian. https://www.theguardian.com/society/2020/nov/19/gladys-west-the-hidden-figure-who-helped-invent-gps
Morik, K.
(n.d.). Gedanken zur Attraktivität der Informatik bei begabten
Schulabgängerinnen. Dortmund University. https://www-ai.cs.tu-dortmund.de/PERSONAL/MORIK/INFORMFrau.pdf
Rossiter,
M. W. (1995). Women Scientists in America: Before Affirmative Action,
1940–1972. Johns Hopkins University Press.
Schiebinger,
L. (1999). Has Feminism Changed Science? Harvard University Press.
Straza, T.,
Peršić, A; Clark, E.; Kasry, A.; Pathirage, R. y Zandaryaa, S. (2025). Status
and Trends of Women in Science. New Insights and Sectoral Perspectives. UNESCO.
https://zenodo.org/records/15667540
This is the original version of the blog entry
A Spanish version (ES) will be available next
Friday