Sexism in Tech conferences


Writing about sexism in tech conferences is hard. Especially as a young white male. I can only speak anecdotally – but most women in the Tech industry I speak to, talk a bit about moments of subtle sexism or sometimes out-and-out harassment. As a member of the tech community I’m completely behind any promotion of minorities in the industry, and feel that more can be done. It is interesting that most men I speak to in the industry don’t notice any problem.

Two articles spring to mind:

This was written about STEM but I feel the same rules apply to the Tech community (especially since I personally straddle both communities).

It’s “not a big deal” when someone tells you he came to your talk because you’re attractive.
It’s “not a big deal” when a coworker comments on your appearance.
It’s “not a big deal” when someone makes a “joke” at work demeaning women.
It’s “not a big deal” when you are asked in a job interview if you have or are planning to have kids.
It’s “not a big deal” that you were warned about what professor to avoid basically as soon as you got to school.
It’s “not a big deal” that that same professor was untouchable by the administration because he was too famous.
It’s “not a big deal” when someone assumes you are your own secretary on the phone.
It’s “not a big deal” when someone calls you “Miss” and your male colleague “Doctor.”
It’s “not a big deal” when going to parties at a conference comes with warnings of which of your fellow scientists are dangerous.
It’s “not a big deal” when your boss, adviser, or senior colleague asks you out.
All of this stuff IS a big deal. One of the things I hear about the tech industry – partly because of the passive agression that Hackers sometimes adopt is that as a community we need to grow up and become more professional AND inclusive. I agree wholeheartedly with this and applaud the conferences that encourage more female participation and more female speakers. Diversity is a good thing and I think it makes us smarter :).
The other link I saw was about Defcon a famous security conference. I found the following paragraph to be very powerful.
When you say, “Women shouldn’t go to DEFCON if they don’t like it,” you are saying that women shouldn’t have all of the opportunities that come with attending DEFCON: jobs, education, networking, book contracts, speaking opportunities – or else should be willing to undergo sexual harassment and assault to get access to them. Is that really what you believe?
I am glad things are getting better but there are still a number of actions that we can all take. I think this is a subproblem of the larger problem that Pete Warden commented about. I consider his article to be self-recommending
Comments are welcome. The articles I linked to, contain some excellent resources on how to enforce or come up with policies in regards harassment – which is a legal issue. Lots of us like to avoid legal issues like this – but an advantage of policies and ‘processes’ is that they are transparent and fair. Some of us consider these things to be too formal – but as I get older I see that some of these ‘formalities’ that we have in corporations and other organizations are useful and save a lot of hassle.

Book Review: Analytics in a Big Data World


So this is a quick review of a book that ended up in my mailbox a few months ago.

Firstly the good: this is a good academic introduction to a variety of techniques all in one reference book. I particularly liked the discussion of Process mining and survival analysis as I feel these are techniques often neglected in the discussion of data science. I know that the author of the Lifelines library. Cameron-Davidson Pilon has done some screencasts on Data Origami of this technique and the applications it has to say Customer Churn modelling but this is the first time I saw it in a book aimed at Data Scientists.

I believe that Bart is an expert in risk modelling so there is a lot of discussion of financial services applications – this is fine and a good addition to the literature on data science, since a lot of the literature is focused on Machine learning applications for social networking websites or the e-commerce sector.This last point may be due to the fact that Bart is based in Europe as opposed to the Bay Area.

An interesting addition to the data science literature is in his applications chapter – and he includes Business Process Analytics, as someone who has worked on some Business Process Mining I’ve not seen too many remarks to this field in the literature and certainly none in book form so this is a worthy addition.

The bad: The print of the book is terrible and the paper a colour that makes reading it extremely difficult. I also felt that the type face for the mathematics equations was hard to read. This may not be Dr Baesens fault. I felt that some of the material was not new to me – but this is fine I’ve probably got more experience in this sector than the target audience who seems to be soon to finish Masters students or PhD students in STEM subjects who are considering a career in Data Science.

I would also like more discussion on how to present your ideas to clients but I guess this is for a separate book or a book on ‘Creating Data Products’.

Nevertheless I would give recommend the book to any MSc or PhD students interested in a career in data science and any analysts like myself who want a good reference for Survival Analysis and Process Mining. I think those chapters and subchapters make this a worthy addition to my own library. I think also that the discussion of risk modelling and customer churn modelling is excellent as this is a bottom up approach from the Mathematical models and data processing to how a model could be produced and evaluated. Together with say a good Coursera course this could be an excellent preparation for interviews for Data Science roles.

Disclaimer: Dr Bart Baesens sent me a copy of this book for review but I have no stake in it’s success.