Clara Higuera

Lead Data Scientist

BBVA AI Factory

Home2023 SpeakersClara Higuera

Speaker Bio

Clara is currently lead data scientist at BBVA AI Factory. She has worked in applied machine learning and the data science field for the last twelve years both in academia and industry. She has also worked in multiple sectors such as biomedicine, media, finance and in the last two years in the field of AI ethics and algorithmic fairness.

She has worked helping bridge the gap from theory to practice translating abstract ethical principles like fairness into practical decisions in the machine learning development cycle. She currently collaborates with Alexa Hagerty, anthropologist researcher, to build a collaborative approach to AI ethics that combines the humanistic and the technical perspective.

Prior to her industry experience she carried out her PhD in artificial intelligence and bioinformatics and holds a degree in computer science, she enjoys presenting her work in public events and is actively involved in activities which encourage women and girls pursuit a career in technology and science.

Fun Fact: As much as she like the digital world, Clara enjoys part of her free time making artistic collages with her own hands 🙂

Speaker Sessions

1:45pm
Workshop

What Does A Robust AI Ethics Framework Look Like?

60 mins
  • Track - Workshop
  • Data
  • Premium Only
  • Clara Higuera

    Lead Data Scientist

    BBVA AI Factory

AI is currently being applied in almost every sector of our lives such as healthcare, education, entertainment, transport and finance to name a few. However as use has risen, so has awareness of potential for bias, discrimination and other types of harms. AI systems also mediate social perceptions and interactions and have environmental and climate consequences. Given the pervasive impacts of AI systems, it is no surprise that the field of AI ethics has gained force in recent years.

The ethical aspects of AI are studied and debated in diverse fields including philosophy, social science, computer science, and engineering with each field contributing distinct viewpoints and practices. Integrating humanistic and technical perspectives has proved challenging. But AI systems are sociotechnical, meaning there are complex interdependencies between their ‘social’ and ‘technical’ aspects throughout their lifecycle. Interdisciplinary approaches are the only way forward.

In this session, a data scientist and an anthropologist specialising in AI ethics reflect on the challenges of putting AI ethics into action, the tools currently available for organisations to align their principles and practices, and examples of cutting-edge approaches to ethical and responsible AI being used in industry.

We draw on our different experiences and backgrounds to shed light on the complex and crucial challenge of developing ethical AI for more inclusive and equitable futures.

In the session we will discuss with the audience the different challenges of bringing AI ethics into practice and open a debate about why we need AI ethics integrated in the development cycle of AI now more than ever after the recently released large language models like ChatGPT.

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