Teresa Sandoval-Martín

Teresa Sandoval-Martín
University Carlos III de Madrid | UC3M · Department of Communication and Media Studies

PhD. Journalism. Associate Professor UC3M
Visiting Full Professor University College Dublin

About

21
Publications
4,131
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
89
Citations
Introduction
Teresa Sandoval-Martín is senior Professor of Journalism at the Carlos III University Madrid since 2001. European Doctor and Extraordinary Prize for Doctoral Thesis at the University of La Laguna 2002-2003, for “The representation of the Canary Islands in the German Kulturfilm from the II to the III Reich (1896-1945)” (scholarship holder). She founded the public Film Commission of the Canary Islands. Currently analyzing gender bias in AI from gender, ethic and communication perspectives.
Additional affiliations
January 2001 - present
Universidad Carlos III de Madrid
Position
  • Professor (Associate)

Network

Cited By

Projects

Projects (3)
Project
In the times of big data and algorithms and right on the verge of the fourth industrial revolution, the debate on the impact of the applications of Artificial Intelligence (AI) and robotics is open at an international level on many fields: the way in which the progress of these areas is going to influence employment and work relationships, the safety of transactions and relations, national security, commercial traffic, institutional frameworks and others are being discussed and, on a lower scale, it is being pondered upon the biases that these technologies involve and their consequences. In this context, until only a few months, the absence of a gender perspective in AI had not been taken into account. Several experiments performed at the core of some of the most important digital platforms such as Amazon and research done by female scientists have discovered the consequences of the use of AI and the harm it causes in terms of gender equality, focusing on NLGs, machine learning and deep learning. Recently, several supranational institutions as the UNO have made respective appeals to alert about gender biases that these intelligent systems involve and promote research in this sense. This project intends to identify and analyze, from a gender perspective, the biases that accentuate o perpetuate the social inequalities between women and men in the artificial intelligence systems that are being developed in Spain -in companies or research centres- and those applications that, while not being Spanish, operate on Spanish soil. All of this, with a multidisciplinary approach derived from the field of study gender studies, the object of study biases in AI and, favoured by the various fields of specialization of the members of the research team. We will largely focus on the most used applications by citizens: platforms, websites and media that use systems of recommendation, prediction, translation, news customization, and so forth. Likewise, an emphasis on the implementation of these technologies in the news production and development processes is planned, that is, in automated journalism.
Project
Supervisor/host Institution of Marie Skłodowska-Curie Action. H2020-MSCA-IF-2020 https://cordis.europa.eu/project/id/101028792 Challenging gender bias in telecoms sector While the number of women employed in the telecommunications industry is rising, it remains a male-dominated sector. Men continue to outnumber women, and this trend will be hard to shake off. The rise of algorithm-powered technology has been criticised for reproducing gender bias, particularly in AI-driven products. The EU-funded TELAIGEN project will explore the gender bias within the Spanish telecommunications industry as a direct consequence of the lack of women in the sector. The central hypothesis is that the current gender gap in the sector leads to lack of integration of a gender perspective leading consequently to the reproduction of gender bias in AI technologies. The findings will help improve the gender balance.