14.09.2019 –, Schlossallee
Language: English
The Google Memo was not the first and will not be the last sexism discussion in tech. And the problems do not end there.
Tech has a diversity problem, and discussions about inclusion, welcoming culture, toxic behaviour, discrimination and the reasons why people are leaving the field can and should not be ignored.
This talk asks why people do not feel at home in tech, examines why it is so important that they do, discusses requirements for improvement, and suggests some first steps we can all take to change this.
Come by and hear why a summer coding camp for school girls might be a good thing, but not the answer to our problems.
The Pay Gap, the Pipeline Problem, and the Glass Ceiling have been discussed, in society as a whole, as well as in the tech industry for years. Every now and then, a scandal fires up the discussions ageing, adds new facettes, or gives focus to another group of people.
However, inbetween there is a constant flow of reports and anecdotes of those people that do not feel as at home in tech as they want to. Not everyone interested in the subject matter finds their place -- and it is not a matter of lack of tasks, or versatility of the field. And it is also not a matter of isolated incidents.
Across its spectrum and locations tech has a diversity problem: Those already underrepresented leave the field.
Why is it that so many do not feel welcome here? How come tolerance can lead to exclusion? Why does not everybody have the same chance of success?
And why do we definitely need to change that?
Inclusion and diversity are not a matter of "nice-to-have". They are a basis of success. It is time for excuses to stop and for everyone in the field to do their part.
This is not an instruction manual to make everything better. But maybe it is food for thought and an inspiration for what can be done.
Master student in Computer Science, Focus on Machine Learning and Natural Language Processing, currently interested in Gender Equality/Fairness/Equity and Implicit Bias