And that's what man does with it
Posted: Wed Feb 12, 2025 9:33 am
To ensure equal opportunities, it is essential that both girls and boys are encouraged in these fields from early education, incorporating the stories of female scientists in the curriculum and using gender-ambiguous terms. This is also important in recruitment processes: how do we expect women to feel called upon when all job offers are written in exclusively masculine terms?
It’s such a male-dominated field that if you Google “data engineer,” it tells you that you’ve typed something wrong and that you actually meant “data engineering.” The thousands of results for courses, articles, and job postings all use the term “data engineer” exclusively. It may seem like a small thing, but it’s a lot of little things like this that contribute to a common sense that technology is not a field for women.
Have you ever wondered why most robotic cambodia mobile database assistants (like Alexa or Siri) have a woman's voice? It's no coincidence. Nor is it a coincidence that an algorithm learns to associate images of household appliances with women. Or that AI tools rate photos of women as more sexually suggestive than those of men . “Algorithms are nothing more than opinions encrypted in code,” says Cathy O'Neill. It is evident that the biases of those who program and design these tools are reflected in the technologies.
In other cases, the problem is not so much the biases of the programmers but our own history. Gemma Galdón, an algorithm auditor and founder of Eticas Research and Consulting, explains that, for example, to decide who to give a mortgage to, the algorithm will be fed by historical data: “Based on this data, men will have more chances than women, because we have historically been granted fewer mortgages and because the system assigns us a risk profile.”
It’s such a male-dominated field that if you Google “data engineer,” it tells you that you’ve typed something wrong and that you actually meant “data engineering.” The thousands of results for courses, articles, and job postings all use the term “data engineer” exclusively. It may seem like a small thing, but it’s a lot of little things like this that contribute to a common sense that technology is not a field for women.
Have you ever wondered why most robotic cambodia mobile database assistants (like Alexa or Siri) have a woman's voice? It's no coincidence. Nor is it a coincidence that an algorithm learns to associate images of household appliances with women. Or that AI tools rate photos of women as more sexually suggestive than those of men . “Algorithms are nothing more than opinions encrypted in code,” says Cathy O'Neill. It is evident that the biases of those who program and design these tools are reflected in the technologies.
In other cases, the problem is not so much the biases of the programmers but our own history. Gemma Galdón, an algorithm auditor and founder of Eticas Research and Consulting, explains that, for example, to decide who to give a mortgage to, the algorithm will be fed by historical data: “Based on this data, men will have more chances than women, because we have historically been granted fewer mortgages and because the system assigns us a risk profile.”