In this era of unprecedented technological advances, artificial intelligence (AI) is a tool that offers great possibilities in areas such as medicine, energy efficiency, sustainable development , the environment, climate change and humanitarian emergencies, among others. However, AI also poses challenges, especially in the fight against digital discrimination, including gender discrimination.

A clear example is that of the recommender systems or search engines of our mobile devices because they can discriminate when offering us certain products or services based on gender. Similarly, due to the existence of historical or cultural biases, AI algorithms that process data of people in staff selection tools may favor one class over another. By class we mean a particular gender, group age, community or collective.

On International Women's Day, women and men alike can take up this ethical challenge in relation to AI. On the one hand, as consumers (IoT devices, robots, digital platforms, etc.) we must take responsibility for making informed decisions that allow us to make fair, respectful of others and sustainable choices: our choices have the power to transform those algorithms that learn from the data (machine learning algorithms or machine learning) to promote equality.

On the other hand, teams of women and men working with real data to develop and implement AI tools must be committed to building fair and egalitarian projects with social impact. These projects would not only aim to prevent digital discrimination, but also to discover patterns of discrimination or stigmatization in society that allow the design of strategies to ensure equality.

Although AI automates processes that intellectually belong to human beings, this definition becomes today more than ever a commitment of professionals and teachers working in this field to ensure the quality of life of all people without discrimination of any kind subject. Is not service to others an intellectual process inherent to human beings that transcends borders? In this regard, on International Women's Day it is essential that we share this "space for equality" with all vulnerable groups: children, young people, adolescents, the elderly, people with disabilities, people at status , etc.

In this context, it is important to address the following questions: Can AI combat discrimination? What steps can be taken towards equality? To answer we must take a multifactorial approach .

• From diversity and Education

  Creating multidisciplinary teams of AI developers that are equally represented by women and men. Such teams should be supported by a management team that is equally represented and committed to fairness, ethics and quality. In order to achieve this diversity, it is essential to empower the skills and critical spirit of young people from Education in all areas.

  We still have a lot work ahead of us. Here again, this day that we have designated as a space for equality becomes the perfect platform to support the efforts of all girls, teenagers and women with profile science-technology or STEM(Science, Technology, Engineering and Mathematics) so that they can pursue their goals and conquer their goals without "glass ceilings".

• From discussion social and political action

  Promoting awareness campaigns and policies that promote equal opportunities in the academic world, in the business world and in industrial or cultural production. For example, in the E.U. there is the high school European Institute for Gender Equality (EIGE), which aims to be a channel of advice that allows countries to carry out equality policies in various areas. Outside the E.U., there are initiatives such as the project Gender Shades which aims to identify gender discrimination in AI. goal .

• From regulation rules and regulations

  Creating a suitable ethical and political framework for the management of AI. Proposals from the European Commission(The AI Act, 2022), the USA(Blueprint for an AI Bill of Rights, 2022) or international bodies such as UNESCO(Recommendation on the Ethics of Artificial Intelligence, 2022) are directing their efforts towards the formulation of guidelines that promote equality in algorithms.

• From a technical point of view

  The representativeness of the data from entrance (inputs) is fundamental, since "supervised" AI models learn and train from these data, which means that all classes must be equally represented.

  Likewise, the transparency and accessibility of algorithms is necessary to be able to verify that they are not linked to gender, race, age, religion or nationality stereotypes and can be validated through audits. Companies such as IBM (AI Fairness 360) and Google (What-if) are developing open source libraries with the goal to detect possible biases through fairness metrics in the algorithms before their implementation.

To conclude, I will tell you that as a professor of courses at the University of Navarra, where we use artificial intelligence tools on real use cases, year after year the groups formed by students demonstrate their concern and commitment to ensure that algorithms do not harm the most vulnerable by resolving these ethical issues with determination. Future AI professionals seek support and solutions to build a more just and egalitarian world.