AI is already perpetuating social bias and prejudice because it lacks representation of LatinX professionals in the AI industry. Machine learning algorithms can encode a discriminative bias during training with real-world data in which underrepresented groups are not properly characterized or represented. A question quickly emerges: how can we make sure Machine Learning does not discriminate against people from minority groups because of the color of their skin, gender, ethnicity, or historically unbalanced power structures in society?
Even more, as the tech industry does not represent the entire population, underrepresented populations in computing such as Hispanics, women, African-Americans, and Native Americans have limited control over the direction of machine learning breakthroughs. As an ethnicity, the Latinx population is an interesting case study for this research as members are comprised of all skin tones with a wide regional distribution across the world.
In this session, we claim that it is our responsibility to advance the progress of machine learning by increasing the presence of members of our minority group that are able to build solutions and algorithms to advance the progress of this field towards a direction in which AI is being used to solve problems in our communities while bias and unfairness are accordingly addressed. As the number of Hispanic and Latinx identifying AI practitioners increases, it is also imperative for us to have access to share our work at international AI and Machine Learning conferences which yield new opportunities for collaboration, funding, and job prospects we would not have access to otherwise. The benefits will not only be for the LatinX community and minority groups, but also to the AI community in general. The reason for this is that the multiplicity of cultures and backgrounds is connected to higher creativity in the solution of problems in general. This applied to AI will bring positive results in the long term.
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