The announcement of a new Perfect Dark has reminded me of a good story from my time at ATI. It was 2005 and I was in the 3D Application Research Group. The team which included @shaderwrangler @ChrisOat @mirror2mask @pixelmaven was working on the "Ruby: The Assassin" demo for

Users: hey can you get rid of the Nazis please

Twitter: ok sure, we've changed the stars to hearts for likes

Users: no no, zero Nazis please

Twitter: yep we're getting rid of Vine

Users: nah hey, what about the Nazis

Twitter: ok ok fine, no more likes

Really though, if you had to ask any average user what were the main things leading to a bad "quality of debate" on this bad website, the tiny little heart symbols would not exactly be at the top of most people's lists

Today we’re going to talk statistics and semantics. I’m going to do so via the medium of one of Twitter’s favourite stats 1.7% (aka “intersex is as common as red heads.”). The statistic comes from Fausto-Sterling’s work, which you can see a review of

To understand the statistic, we have to drill down into what the meaning of the word intersex is. Most people think of hermaphrodites. Let’s stress at the beginning there has been no example ever of a human being with both sets of working reproductive organs.

There is a very tiny percentage of people who are born with both testicular and ovarian tissue (what Fausto-Sterling calls “true hermaphrodites”). And when I say tiny, we’re talking intersex tiny, as in 0.0117/1,000 live births, or one in 1,000,000. These are very complex cases.

So, how do we arrive at 1.7%? What Fausto-Sterling does is apply a wider scope. Instead, she argues that intersex is anything that doesn’t fit into a platonic ideal. The platonic ideal, in this case, being a phenotypically perfect XX female and a phenotypically perfect XY male.

This means that intersex, used in the context of the 1.7% statistic, includes people for whom there is no sexual ambiguity. Take for example Klinefelter syndrome (XXY males). As Fausto-Sterling acknowledges, many males can go their whole life and not realise they are XXY.

Two years ago on a weekend, I built a tool to make it easier to evaluate Twitter accounts. Since then 36590 people used it to analyze 55390 different Twitter accounts.

Over the last months @mmkaradeniz and I made a new version. We launched it last night:

@accountanalysis doesn't use machine learning or AI „magic“. Instead of telling users if an account is authentic or not, it helps them to evaluate the accounts themselves.

It visualizes the different features (date, time, type, app, etc.) of Tweets to make them interpretable. /1

@accountanalysis The core concept is still the same, but it looks much better and is easier to operate. Not only for the users, but us developers as well. Enabling us to continuously roll out new features in the future.

Side-by-side screenshots of the old and new version. /2

@accountanalysis Some people had questions what different charts displayed and how they could be interpreted. There are now explanations for all charts, that can be toggled on and off at any time. /3

@accountanalysis The selected/retrieved Tweet count moved to the top to make it clear that not all Tweets of an account are analyzed. 3200 is the API limit by Twitter. It's possible to get more through the Premium API, but I don't think people would pay $100+ for the analysis of one account. /4

🙋🏾‍♀️ In 2011, I was hired into my first junior role in tech @Groupon

👩🏾‍💻 By 2020, I was headhunted into a VP role in a global tech company @Brandwatch

🤖 I achieved this progression in less than a decade, without ANY coding skills

🔮 How did I do it?

*a thread*

🤓 I established a track record of results.

💪🏾 No magic formula can replace hard work: do your job well & hit all the targets you are set.

😬 When you're struggling, ask for help so you can stay on track to get results, or collaboratively adjust targets.

🎨 I stayed creative.

🧙🏿‍♀️ When challenges arose I was bold enough to try new solutions. Not everything worked, but constantly trying produced valuable innovations.

🧠 I was proactive in finding new, better ways to get the job done.

🤩 I was a self-promoter. I recorded my achievements & ensured they were mentioned in any performance / compensation reviews.

😎 I put myself forward for any opportunities to gain recognition e.g. speaking opportunities or awards.

👀I actively worked on gaining visibility.

🙂 I was myself. Some say you need to be ruthless to succeed. I don't buy it. I'm a nice person so I'm nice at work, too.

❤️ I didn't fake it. I always acted on my values, and spoke up when something didn't feel right. I showed integrity.

🤗 I was a team player. To everyone.