To highlight remarkable women contributing to the AI revolution, TechCrunch is launching a series of interviews focusing on AI-focused women academics and professionals. The goal is to shine a well-deserved spotlight on their significant contributions, which often go unrecognized. The series will feature profiles throughout the year to coincide with the ongoing AI boom.
Emilia Gómez, a principal investigator at the European Commission’s Joint Research Centre and the scientific coordinator of AI Watch, is one such notable figure. Her team plays a crucial role in providing scientific and technical expertise for EC AI policies, including the recently proposed AI Act.
Gómez’s background lies in computational music, where she explores how humans describe music and its digital modeling. She has delved into the impact of AI on human behavior, including its effects on jobs, decisions, and child cognitive and socioemotional development.
In a Q&A session, Gómez shares insights into her AI journey, from developing algorithms for music audio signal description to her current focus on evaluating AI’s impact on human behavior. She reflects on her proud contributions to music-specific machine learning architectures, such as extracting tonality from audio signals and designing methods for music signal description and emotion modeling.
As a female leader in AI, Gómez navigates the challenges of a male-dominated tech industry by emphasizing the importance of diversity and seeking support from women, nonbinary colleagues, and male allies in the field.
Her advice to women entering the AI field is twofold: recognize the urgent need for diversity and seek mentorship and support from existing groups and initiatives promoting diversity in AI.
Regarding pressing issues in AI evolution, Gómez stresses the need for balanced efforts in AI development and evaluation, highlighting the importance of proper evaluations and impact assessments to mitigate biases and ensure responsible AI use.
For AI users, Gómez advises understanding AI working principles and limitations to use AI tools responsibly and be informed about AI product quality and certification processes.
She emphasizes responsible AI development by prioritizing evaluation, social impact assessment, and risk mitigation, aligning with principles reflected in the AI Act to build trustworthy and socially beneficial AI systems while protecting citizens’ rights and fostering trust in AI technology.
