Women’s Day 2026 Special: Women Who Shaped AI; From Early Computing To Modern Artificial Intelligence

Last Updated:March 08, 2026, 07:00 IST

Women’s Day 2026 Special: Women’s Day is a moment to recognise women who have shaped different fields, including technology and artificial intelligence.

Women’s Day 2026 Special: Women’s Day is marked on March 8. The day highlights the long struggle for equality, recognition, and rights for women around the world. It also shines a light on issues such as gender equality, women’s safety, and fair opportunities in different areas of life.

This special day is also a good moment to recognise women who have changed the world through science and technology. In the field of artificial intelligence and computing, many women have played key roles over the years. Their ideas, research, and inventions

helped shape the technology we use today and continue to guide the future of AI.

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Below are some of the women whose work has influenced artificial intelligence, from the early days of computing to the modern AI systems we see today.

Early Pioneers Who Shaped The Foundations Of Computing

Ada Lovelace (1815–1852): The First Programmer and AI Visionary 

Augusta Ada Byron, widely known as Ada Lovelace, is often called the world’s first computer programmer. In the 1840s, she worked with inventor Charles Babbage on his proposed machine called the Analytical Engine. While studying the machine, she wrote what many

consider the first computer algorithm. The program was designed to calculate Bernoulli numbers.

But Lovelace’s ideas went far beyond mathematics. She believed that machines could one day handle more than numbers. She imagined that computers might work with symbols such as music notes and possibly create complex pieces of music.

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Her famous “Note G" explained how machines could process symbolic information, an idea that later became important in modern computing and artificial intelligence. Lovelace also wrote that “the Analytical Engine has no pretensions whatever to originate anything."

This idea still connects to today’s AI debate about how machines process information compared to human creativity.

Hedy Lamarr (1914–2000): Hollywood Star and Wireless Communication Pioneer 

Hedy Lamarr was famous as a Hollywood actress, but she also had a strong interest in technology. During World War II, she worked with composer George Antheil on an invention designed to protect radio-controlled torpedoes from enemy interference.

Together, they developed frequency-hopping spread spectrum technology. The system allowed signals to move between different radio frequencies, making them harder to block or track.

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Although the idea was not used immediately during the war, it later became the base for several modern technologies. Systems such as WiFi, Bluetooth, and GPS rely on similar ideas. These wireless technologies now play a major role in connecting AI systems across

networks.

Grace Hopper (1906–1992): The Woman Who Made Programming Easier 

Grace Hopper, a computer scientist and U.S. Navy Rear Admiral, made major contributions to early computing. In the early 1950s, she created the world’s first compiler. A compiler is a program that converts code written by humans into instructions that computers

can understand.

Before this invention, programming required detailed knowledge of machine hardware. Hopper’s work made programming easier and allowed more people to develop software.

She also helped develop COBOL, a programming language designed for business applications. It’s simple, English-like structure influenced several later programming systems, including some used in AI development.

Women Who Helped Build The Mid-Century Computing Era

Betty Holberton (1917–2001): Programmer Of The First Electronic Computer 

Betty Holberton was one of six women who programmed ENIAC, one of the first general-purpose electronic computers. At that time, there were no programming languages or tools. The team had to create programming methods from scratch.

Holberton later worked on the UNIVAC computer system. She designed the first sort-merge generator, which helped automate basic data processing tasks. These tasks later became important in many AI systems.

She also worked on instruction codes that balanced human readability with machine efficiency. This idea remains important today, especially in areas such as machine learning.

Barbara Liskov (b. 1939): Building Flexible Programming Systems 

Barbara Liskov made important contributions to software design and programming. She developed the CLU programming language, which introduced the idea of data abstraction. This concept allows programmers to design systems that are easier to maintain and update.

Her work led to what is known as the Liskov Substitution Principle. This principle explains how different data types can be replaced without breaking a program. It later became a key idea in object-oriented programming, which is widely used in AI systems.

This approach helps developers create flexible programs where different algorithms or data structures can be swapped easily.

Eleanor Rosch (b. 1938): Changing How AI Understands Categories 

Psychologist Eleanor Rosch studied how people organise knowledge. Her research showed that humans usually group things based on examples or “prototypes" rather than strict rules.

For example, people may think of a robin as a typical bird even though penguins and ostriches are also birds. Rosch’s work showed that categories often have flexible boundaries.

Her ideas helped shape how AI systems recognise objects and patterns. Today, machine learning systems use similar ideas when working with real-world data that is often unclear or complex.

Modern Leaders Pushing AI Forward Today

Fei-Fei Li: Expanding The Possibilities Of Machine Vision 

Fei-Fei Li is widely known for her work in computer vision. In 2007, she helped create ImageNet, a large dataset containing around 15 million labelled images. This dataset allowed computers to learn how to recognise objects more accurately.

ImageNet played a major role in the growth of deep learning and modern AI research. Beyond her technical work, Li also focuses on making AI more inclusive. She co-founded AI4ALL, an organisation that encourages students from different backgrounds to enter AI

research.

She also helped establish the Stanford Human-Centred AI Institute, which studies how AI affects society.

Mira Murati: Helping Develop Powerful AI Tools 

Mira Murati served as the former Chief Technology Officer at OpenAI. She played a key role in developing widely used AI systems such as ChatGPT and DALL·E.

Murati supported an approach called “iterative deployment," where AI systems are released step by step so researchers can study their effects and improve safety.

After leaving OpenAI, she started Thinking Machines Lab, which focuses on artificial general intelligence research while keeping safety and social benefits in mind.

Daniela Amodei: Working Toward Safer AI Systems 

Daniela Amodei co-founded the company Anthropic, which focuses on building AI systems that behave responsibly. Her work combines interests in literature, politics, and technology policy.

Before starting Anthropic, she worked on safety and policy projects at OpenAI. Her organisation studies ways to ensure AI systems follow clear principles.

One example is “Constitutional AI," a method that guides AI behaviour using a defined set of rules and values.

Timnit Gebru: Raising Questions About Fairness In AI 

Dr. Timnit Gebru is known for her work on AI ethics. She studied how facial recognition systems can show bias against certain groups.

Her research also raised concerns about large language models and their possible risks. One of her well-known papers is titled On the Dangers of Stochastic Parrots.

After leaving Google, Gebru founded the Distributed AI Research Institute (DAIR). The organisation focuses on fair and independent AI research that considers social impact.

Joy Buolamwini: Fighting Bias In technology 

Joy Buolamwini began studying AI bias after noticing that facial recognition software struggled to recognise her face. Her research later showed that many systems performed poorly when identifying people with darker skin tones.

She founded the Algorithmic Justice League, which studies fairness and accountability in AI systems.

Buolamwini is also the author of the book Unmasking AI, which explains how algorithms can reflect social bias and how technology can be improved.

Many Other Women Continue Shaping The AI World

The list of women influencing artificial intelligence continues to grow. Many researchers, engineers, and leaders are pushing the field forward in different areas.

Some of these contributors include Daniela Rus, who leads MIT’s Computer Science and AI Laboratory and works on robotics and human-machine collaboration. Joelle Pineau heads AI research at Meta and focuses on reinforcement learning.

Lisa Su, CEO of AMD, has helped turn the company into a major force in high-performance computing hardware used for AI. Cynthia Breazeal has worked on social robots designed to interact with humans.

Researchers such as Anima Anandkumar and Chelsea Finn are advancing machine learning and meta-learning. Claire Delaunay has helped bring AI into real-world robotics.

Daphne Koller has applied AI to medical research and drug discovery. Francesca Rossi works on ethical AI development at IBM.

Other notable voices include Irene Solaiman in AI policy research, Kate Crawford in studying AI’s social impact, and Latanya Sweeney in data privacy and fairness.

Manuela Veloso has contributed to robotics and multi-agent systems, while Regina Barzilay has used machine learning to improve cancer detection and drug discovery.

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