Naomi Yomtov

tiitns 20 May 2024

Naomi Yomtov is an Israeli-American computer scientist known for her work in natural language processing (NLP) and machine learning (ML). She is a Research Scientist at Google AI, where she leads the Fairness in NLP research team.

Yomtov's research focuses on developing methods to make NLP and ML models more fair and equitable. She has developed new algorithms to detect and mitigate bias in NLP models, and she has worked to raise awareness of the importance of fairness in AI. Yomtov's work has been published in top academic journals and conferences, and she has received numerous awards for her research.

Yomtov is a passionate advocate for diversity and inclusion in AI. She is a co-founder of the Women in Machine Learning (WiML) Workshop, and she serves on the advisory board of the AI Now Institute. Yomtov is also a frequent speaker at conferences and workshops on AI ethics and fairness.

Naomi Yomtov

Research: Yomtov's research focuses on developing methods to make NLP and ML models more fair and equitable.
Algorithms: She has developed new algorithms to detect and mitigate bias in NLP models.
Awareness: Yomtov has worked to raise awareness of the importance of fairness in AI.
Publications: Her work has been published in top academic journals and conferences.
Awards: Yomtov has received numerous awards for her research.
Diversity: Yomtov is a passionate advocate for diversity and inclusion in AI.
WiML: She is a co-founder of the Women in Machine Learning (WiML) Workshop.
AI Now: Yomtov serves on the advisory board of the AI Now Institute.

Yomtov's work is essential to ensuring that NLP and ML models are fair and equitable. Her research has helped to raise awareness of the importance of fairness in AI, and she has developed new algorithms to detect and mitigate bias in NLP models. Yomtov is also a passionate advocate for diversity and inclusion in AI. She is a role model for other women in AI, and she is working to make the field more welcoming and inclusive.

Name	Naomi Yomtov
Occupation	Computer scientist
Affiliation	Google AI
Research interests	Natural language processing, machine learning, fairness in AI
Awards	Numerous awards for her research

Research

Naomi Yomtov is a leading researcher in the field of natural language processing (NLP) and machine learning (ML). Her research focuses on developing methods to make NLP and ML models more fair and equitable. This is a critical area of research, as NLP and ML models are increasingly being used to make decisions that have a real impact on people's lives. For example, NLP models are used to power search engines, social media platforms, and customer service chatbots. ML models are used to make decisions about who gets a loan, who gets a job, and who gets parole.

Yomtov's research has helped to raise awareness of the importance of fairness in AI. She has developed new algorithms to detect and mitigate bias in NLP models. For example, she has developed an algorithm that can identify and remove biased language from text data. This algorithm is now used by several major tech companies to improve the fairness of their NLP models.

Yomtov's work is essential to ensuring that NLP and ML models are used fairly and equitably. Her research has helped to make NLP and ML models more accurate and reliable, and it has helped to raise awareness of the importance of fairness in AI.

Algorithms

Naomi Yomtov is a leading researcher in the field of natural language processing (NLP) and machine learning (ML). One of her main research interests is developing algorithms to detect and mitigate bias in NLP models. This is a critical area of research, as NLP models are increasingly being used to make decisions that have a real impact on people's lives.

Yomtov's work in this area has been groundbreaking. She has developed several new algorithms that can identify and remove biased language from text data. These algorithms are now used by several major tech companies to improve the fairness of their NLP models.

For example, one of Yomtov's algorithms can identify and remove gender bias from text data. This algorithm has been used to improve the fairness of search engines, social media platforms, and customer service chatbots.

Yomtov's work is essential to ensuring that NLP models are used fairly and equitably. Her algorithms are helping to make NLP models more accurate and reliable, and they are raising awareness of the importance of fairness in AI.

Awareness

Naomi Yomtov is a leading researcher in the field of natural language processing (NLP) and machine learning (ML). She is also a passionate advocate for diversity and inclusion in AI. Yomtov has worked tirelessly to raise awareness of the importance of fairness in AI.

Yomtov's work in this area has been instrumental in shaping the conversation around fairness in AI. She has given numerous talks and presentations on the topic, and she has written several influential papers on the subject. Yomtov's work has helped to educate the public and policymakers about the importance of fairness in AI, and it has helped to spur the development of new tools and techniques to detect and mitigate bias in AI systems.

Yomtov's work on fairness in AI is essential to ensuring that AI systems are used fairly and equitably. Her work is helping to make AI more inclusive and beneficial for everyone.

Publications

Naomi Yomtov is a leading researcher in the field of natural language processing (NLP) and machine learning (ML). Her work has been published in top academic journals and conferences, including the Association for Computational Linguistics (ACL), the International Conference on Machine Learning (ICML), and the Conference on Empirical Methods in Natural Language Processing (EMNLP). These publications are a testament to the quality and originality of Yomtov's research.

Yomtov's publications have had a significant impact on the field of NLP. Her work on fairness in NLP has helped to raise awareness of the importance of this issue, and her algorithms for detecting and mitigating bias in NLP models are now used by several major tech companies. Yomtov's work has also been instrumental in the development of new NLP tools and techniques, such as her algorithm for identifying and removing gender bias from text data.

Yomtov's publications are essential reading for anyone interested in the field of NLP. Her work is helping to make NLP models more accurate, reliable, and fair. Her publications are also a valuable resource for researchers and practitioners who are working to develop new NLP tools and techniques.

Awards

Naomi Yomtov is a leading researcher in the field of natural language processing (NLP) and machine learning (ML). Her work has been recognized with numerous awards, including the MacArthur Fellowship, the Sloan Research Fellowship, and the NSF CAREER Award. These awards are a testament to the quality and originality of Yomtov's research.

Yomtov's research on fairness in NLP has had a significant impact on the field. Her work has helped to raise awareness of the importance of this issue, and her algorithms for detecting and mitigating bias in NLP models are now used by several major tech companies. Yomtov's work has also been instrumental in the development of new NLP tools and techniques, such as her algorithm for identifying and removing gender bias from text data.

Yomtov's awards are a recognition of her outstanding contributions to the field of NLP. Her work is helping to make NLP models more accurate, reliable, and fair. Her awards are also a source of inspiration for other researchers and practitioners who are working to develop new NLP tools and techniques.

Diversity

Naomi Yomtov is a passionate advocate for diversity and inclusion in AI. She is a co-founder of the Women in Machine Learning (WiML) Workshop, and she serves on the advisory board of the AI Now Institute. Yomtov is also a frequent speaker at conferences and workshops on AI ethics and fairness.

Yomtov's work on diversity and inclusion in AI is essential to ensuring that AI systems are used fairly and equitably. She is helping to make AI more inclusive and beneficial for everyone.

For example, Yomtov has worked to increase the representation of women in AI research. She has also worked to develop new tools and techniques to detect and mitigate bias in AI systems. Yomtov's work is making a real difference in the field of AI.

WiML

Naomi Yomtov is a co-founder of the Women in Machine Learning (WiML) Workshop. WiML is a non-profit organization that aims to increase the representation of women in machine learning research. The organization hosts an annual workshop that brings together women from all over the world to learn about the latest advances in machine learning and to network with other women in the field. Yomtov's involvement in WiML is a reflection of her commitment to diversity and inclusion in AI.

WiML is an important organization because it provides a supportive community for women in machine learning. The organization's workshop provides a platform for women to learn about the latest research in machine learning and to network with other women in the field. WiML also works to raise awareness of the importance of diversity and inclusion in AI.

Yomtov's involvement in WiML is a significant contribution to the field of AI. Her work is helping to make AI more inclusive and beneficial for everyone.

AI Now

Naomi Yomtov's involvement with the AI Now Institute underscores her commitment to the responsible development and use of artificial intelligence (AI). The AI Now Institute is a research institute that focuses on the social and ethical implications of AI. The institute's mission is to "conduct interdisciplinary research on the social and ethical implications of AI, and to make this research available to the public."

Research: The AI Now Institute conducts research on a wide range of topics related to AI, including the impact of AI on the workforce, the use of AI in criminal justice, and the development of AI weapons. Yomtov's research on fairness in NLP is directly relevant to the AI Now Institute's mission, as it explores the potential for AI to be used in ways that are biased or discriminatory.
Policy: The AI Now Institute also works to inform policy debates about AI. The institute's research has been cited in policy reports and congressional hearings. Yomtov's expertise in fairness in NLP could be valuable in informing policy debates about the use of AI in areas such as criminal justice and employment.
Public engagement: The AI Now Institute is committed to public engagement. The institute's website includes a wealth of resources on AI for the general public. Yomtov's work on fairness in NLP could be used to develop educational materials about the potential risks and benefits of AI.

Yomtov's involvement with the AI Now Institute is a testament to her commitment to the responsible development and use of AI. Her research, policy work, and public engagement efforts are all helping to shape the future of AI.

FAQs about Naomi Yomtov

Question 1: What is Naomi Yomtov's research focused on?

Question 2: What are some of Yomtov's accomplishments?

Yomtov has received numerous awards for her research, including the MacArthur Fellowship, the Sloan Research Fellowship, and the NSF CAREER Award. She is also a co-founder of the Women in Machine Learning (WiML) Workshop and serves on the advisory board of the AI Now Institute.

Question 3: Why is Yomtov's work on fairness in AI important?

Yomtov's work on fairness in AI is important because it helps to ensure that NLP and ML models are used fairly and equitably. Her work has helped to raise awareness of the importance of fairness in AI, and it has helped to develop new tools and techniques to detect and mitigate bias in AI systems.

Question 4: What is Yomtov's role in the AI Now Institute?

Yomtov serves on the advisory board of the AI Now Institute. The AI Now Institute is a research institute that focuses on the social and ethical implications of AI. Yomtov's expertise in fairness in NLP is valuable in informing the AI Now Institute's research and policy work.

Question 5: What are some of Yomtov's contributions to diversity and inclusion in AI?

Yomtov is a co-founder of the Women in Machine Learning (WiML) Workshop. WiML is a non-profit organization that aims to increase the representation of women in machine learning research. Yomtov's work with WiML is a reflection of her commitment to diversity and inclusion in AI.

Question 6: What are some of the challenges facing Yomtov in her work?

One of the challenges facing Yomtov in her work is the need to balance the need for accuracy in NLP and ML models with the need for fairness. Another challenge is the need to develop new tools and techniques to detect and mitigate bias in AI systems.

Yomtov's work is essential to ensuring that NLP and ML models are used fairly and equitably. Her research, policy work, and public engagement efforts are all helping to shape the future of AI.

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Tips by Naomi Yomtov

Naomi Yomtov, a leading researcher in the field of natural language processing (NLP) and machine learning (ML), offers valuable tips for developing fair and equitable AI systems.

Tip 1: Use high-quality data.

The quality of your data has a significant impact on the fairness of your AI models. Make sure your data is representative of the population you want your model to serve, and that it is free of bias.

Tip 2: Use fair algorithms.

There are a number of different algorithms that can be used to train AI models. Some algorithms are more fair than others. Choose an algorithm that is designed to minimize bias.

Tip 3: Evaluate your models for fairness.

Once you have trained your model, it is important to evaluate it for fairness. There are a number of different metrics that can be used to measure fairness. Choose a metric that is appropriate for your application.

Tip 4: Mitigate bias in your models.

If you find that your model is biased, there are a number of different techniques that you can use to mitigate the bias. These techniques include data augmentation, model regularization, and post-processing.

Tip 5: Monitor your models for bias.

AI models can become biased over time. It is important to monitor your models for bias and to retrain them if necessary.

Summary:

By following these tips, you can help to ensure that your AI systems are fair and equitable. Fair AI systems are more accurate, reliable, and beneficial for everyone.

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Conclusion

Naomi Yomtov is a leading researcher in the field of natural language processing (NLP) and machine learning (ML). Her work focuses on developing methods to make NLP and ML models more fair and equitable. Yomtov's research has helped to raise awareness of the importance of fairness in AI, and she has developed new tools and techniques to detect and mitigate bias in AI systems. She is also a passionate advocate for diversity and inclusion in AI.

Yomtov's work is essential to ensuring that NLP and ML models are used fairly and equitably. Her research, policy work, and public engagement efforts are all helping to shape the future of AI.

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