The founders of the Holberton School, a small 2-year program in San Francisco, believe the lack of diversity in tech is a result of exclusive recruitment at elite universities– schools that do not attract diverse computer science students. To counter that, the school seeks out diverse applicants and provides them with the skills and networking opportunities required to make it in the technology sector. They rely on an algorithm to determine who gets admitted. It doesn’t ask about gender or ethnicity and it doesn’t require a college degree or previous experience with coding. The algorithm tests for skills tied less to an elite background and more to success in tech: problem-solving, collaboration, and perseverance.
Did you learn about notable LGBTQ historical figures in school? Most likely not. History Unerased is a new non-profit that provides LGBTQ history curricula to schools across the country. The organization trains teachers on LGBTQ issues and educational material, aiming for an inclusive educational experience for all children. Kezia Gilyard, a coordinator there, elaborates: “We believe in teaching the whole child to make sure they have a deep sense of empathy as well as critical thinking skills.” History Unerased faces backlash from those who equate discussion of LGBTQ issues with discussion of sexual conduct, and do not see such topics as part of a quality history curriculum.
The Uber saga reaches a boiling point this week as both CEO Travis Kalanick and board member David Bonderman step down. The company is known for its unprofessional culture and widespread sexual harassment. To turn things around, they had a law firm provide a list of recommendations for improvement. It included enhancing board oversight and human resources, publishing diversity statistics and using blind resume reviews. Will sweeping out the leadership and bringing in new standards be enough?
We’ve read about how female justices on the Supreme Court learn to drop polite language when fighting for a word among their male counterparts. A recent analysis of police body cam recordings reveals a biased language pattern at the other end of the justice system: police of all races use less polite language with Black drivers. Researchers surveyed footage from 1000 stops and over 36,000 language snippets of officers in Oakland, CA. The study controlled for a number of variables, including age, gender, race, crime rate, and population density of the neighborhood. Scientists say the findings lay promising groundwork for new and improved police training programs.