Resource Center

Guide for the design of inclusive infrastructures

Ministry of Transport and Sustainable Mobility

The Ministry of Transport and Sustainable Mobility publishes a guide for the design of land transport infrastructures with a gender perspective, a document that seeks to achieve a more inclusive and safe use of spaces through the development of infrastructures that promote an equal use of all the functionalities they offer.

The guide proposes a new approach to infrastructure design based on the identification of other types of users, such as women, the elderly, people with functional disabilities, and children, who have needs beyond mobility, such as safety and comfort.

Transport Innovation for Sustainable Development: A Gender Perspective

The International Transport Forum (ITF)

New technologies and business models in transport are opening alternative pathways, and offering opportunities for women. For example, ride-hailing or -sharing improves women’s ability to travel freely and provides women with mobility and a greater sense of independence. Accessibility to and affordability of these new mobility solutions often depend on income, educational and digital competence of the users.

These aspects need to be taken into consideration while designing governance framework for deployment of innovative transport services, so that they are inclusive for all users.

Gender Equality Index 2023: Towards a Green Transition in Transport and Energy

European Institute for Gender Equality (EIGE)

The Gender Equality Index 2023 presents the EU in relation to gender equality amid crises and uncertainties. In recent years, the world has been hit by repeated shocks and multiple crises. What remains constant is the fact that when crisis strikes, women and girls suffer disproportionally. The crises and shocks continuously threaten to create new challenges and reverse years of progress on women’s rights and gender equality.

Experiences and Projections on the Inclusion of the Gender Perspective in Mobility

Latin American Observatory on Gender and Mobility (OBGEM)

This publication is the result of collaborative work by various entities committed to transforming mobility into an equitable and fair experience. To achieve this, it is necessary to rely on four fundamental pillars: care mobility, gender mainstreaming, safety, and demasculinization.

Gender Perspective in Transport and Mobility

Ministry of Transport and Sustainable Mobility

The monographic report by the Observatory of Transport and Logistics in Spain (OTLE) addresses the importance of incorporating the gender perspective into transport and mobility policies and actions across all areas (urban, rural, interurban). It also highlights the need to raise awareness and sensitize society to ensure equal opportunities between men and women in the sector. This involves promoting employability and improving working conditions to attract talent to this profession.

The Algorithm is Sexist and Racist

By María Ibáñez

The most popular AI image generators reflect racial and gender biases, a reality that can perpetuate discriminatory outcomes in real life. For example? Not being hired because you’re a woman.

Algorithmic Justice and Talent Diversity: Foundations for a More Human-Centric AI

By Irene Iglesia Álvarez

The unstoppable advancement of artificial intelligence (AI) has compelled technologists, regulators, and civil society to apply critical thinking to reflect on the limits of technology, as well as its associated benefits and risks. Among the numerous challenges posed by the widespread adoption of AI, the most significant is the need to promote ethical, responsible, and human-centered AI.

Artificial Intelligence, Algorithm Use, and Ethnic-Racial Bias: Impact on the Roma Community

By Cristina de la Serna and Javier Sáez (Fundación Secretariado Gitano)

This article from the Fundación Secretariado Gitano examines ethnic-racial bias in artificial intelligence (AI) systems and its impact on the Roma community. It highlights how algorithms can perpetuate existing prejudices, negatively affecting access to social services, security, and other areas. The authors advocate for ethical practices in AI development and the implementation of legal frameworks to prevent discrimination and protect the human rights of marginalized groups.

The Importance of Data Equity in Artificial Intelligence Systems

By Miren Gutiérrez - data.gob.es

This article emphasizes the importance of data equity in artificial intelligence (AI) systems, addressing how biases and imbalances can lead to discrimination and unfair outcomes. It explores four key types of data equity: representation, resources, access, and outcomes, which are essential for achieving inclusive and fair AI. To overcome these challenges, the article recommends collaboration between industries, governments, and civil society.

Artificial Intelligence, Equity, and Digital Inclusion

By José A. Medina Talavera

Artificial intelligence has become an increasingly larger part of our lives in recent years, revolutionizing the way we work and live—from virtual assistants like Siri and Alexa, to self-driving cars and medical diagnostic systems, to generally simplifying daily life. However, as AI becomes more mainstream, it also magnifies existing inequalities while creating new ones.

How Artificial Intelligence is Transforming Transportation

By Celering Reimagine Mobility

Artificial Intelligence (AI) in transportation has significantly revolutionized the way we move and manage transportation systems worldwide. With advances in machine learning algorithms and data processing, AI is helping to improve efficiency, safety, and sustainability in the sector. From urban traffic management to autonomous vehicles, AI is transforming every aspect of modern transportation.

Study Discovers Racial Discrimination in Uber and Lyft Algorithms After Analyzing 100 Million Rides in Chicago

By Alba Asenjo - Business Insider

A study from George Washington University suggests that Uber and other ride-hailing apps could be charging higher fares to users in predominantly Black neighborhoods in Chicago.

What is AI Bias?

By James Holdsworth - IBM

AI bias, also known as machine learning bias or algorithmic bias, refers to the appearance of biased outcomes due to human biases that distort the original training data or the AI algorithm, leading to distorted and potentially harmful results.

Discover How Artificial Intelligence Impacts Diversity

By BOSCH COMPANY

Through the development and application of algorithms, artificial intelligence (AI) has entered the world programmed to optimize and improve various decision-making processes. From selecting interns for a university project to analyzing individuals deemed suspicious through facial recognition, AI’s participation and interference in people’s lives is advancing rapidly.

AI and Gender Bias: A Problem to Solve

By Telefónica Tech

In March, during International Women’s Day, I participated in the WomenWithTech event organized by Telefónica Tech, where several of us shared our experiences. During the event, a recurring topic emerged in these types of forums: Does AI have gender bias?

Artificial Intelligence and Gender: Real Cases of AI That Had to Be Stopped

By Tenea Tecnologías

With the definitive rise of widely used and mass-market AI, the debate around artificial intelligence and gender has found a place in large corporations that recognize social justice as key to developing a sustainable and fair future.

10 Examples of Bias in Artificial Intelligence

By Luis Maram

What does the AI consider a successful person? A feminist? A migrant? Does AI have biases? The answer is a resounding yes, and the consequences can be devastating for your brand.

Seven Examples of Bias in AI-Generated Images

By IJNET - INTERNATIONAL JOURNALISTS NETWORK

Creating images using AI generators has never been easier. At the same time, these results can reproduce biases and deepen inequalities, as shown in our latest research.

Artificial Intelligence and Diversity: Is Intelligence Without a Gender Perspective?

By Forbes Chile - Soledad Matos

According to a report by UNESCO, Artificial Intelligence can reinforce discrimination and prejudice, and in some cases, amplify and propagate them. This happens because AI systems are often trained with historical data, which can reproduce and perpetuate biases.

Diversity and Non-Discrimination in New Frontiers: Biases and Stereotypes in the Age of AI and Robotization

By Blog Legal Today - Teresa Rodríguez de las Heras Ballell

The unstoppable expansion of Artificial Intelligence (AI), which penetrates with promising applications into all corners of contemporary society and economy, is the hallmark of our time. With its exponential growth, AI has generated as much fascination for its promises as alarm for its dangers and fear of its risks.