The true loss for a society of Pokie Players

UPDATE 26th of May: I have recently discovered that turnover is defined by cash plus wagering wins, which means if a person puts in $300 cash, wins and loses $2700 over the course of the day in small increments, and then loses their $300 too, they have “wagered” $3000 and “won” $2700 so the expenditure […]

Hollywood: a man’s world?

Context: In this blog, I am imagining I am guest lecturer at University of Southern California’s Cinematic Arts School.  I work at seejane.org which is the public site of Geena Davis Institute on Gender in the Media. My target audience are students enrolled in Film Studies. This blog shows the presentation I did (although it […]

A News Agent and a Publican walk into a bar

A News Agent and a Publican walk into a bar…. Context: My imaginary target audience is News Agent National Association members, and the medium is an online newsletter to members. The message is to lobby for gaming machine licenses, and the goal is a call to action to members to give their feedback on this […]

Using think cell for the corporate audience

Sometimes, you have an extremely corporate audience, all blue suits and ties. This audience has seen it all before, every tool, every business idea and every design fad. They do not want razzle dazzle, they want accountability and reproduce-ability. They want transparent and honest presentation of your research,  assumptions, workings, plans and conclusions, to ensure […]

Down the Conversion Funnel using rawgraphs.io

Feedback on my first Data Viz blog led me down the conversion funnel My first blog and in class presentation used Tableau to explore conversion rates My feedback suggested funnel charts and Sankey diagrams, and a free app rawgraph.io site. A Sankey Diagram, and the more recent Alluvial Charts are an attention grabbing flow diagram […]

Professional Ethics in contemporary Data Science practice

Executive Summary This paper will discuss accountability, ethics and professionalism in data science (DS) practice, considering the demands and challenges practitioners face. Dramatic increases in the volume of data captured from people and things, and the ability to process it places Data Scientists in high demand. Business executives hold high hopes for the new and […]

Anthropomorphising the algorithm

Leading on from my last blog post conclusion that holding algorithms accountable is a bit of a daft idea, I want to thank Richard Nota for this wonderful comment on The Conversation article posted by Andrew Waites in our slack channel Richard Nota The ethics is about the people that oversee the design and programming […]

About algorithms being black boxes

For 36111 Philosophies of Data Science Practices’ first assignment, I am exploring the emerging practice of holding algorithms accountable. Often, people refer to algorithms as black boxes. There are three different definitions of a black box, according to merriam webster: Definition of black box 1 :a usually complicated electronic device whose internal mechanism is usually […]

GANs, glorious GANs!

GANs, based on supervised learning and game theory, are just so darn elegant. The Grace Kelly of deep learning. Pitting the generator and the discriminator against each other (where the generator tries to fool the discriminator into classifying its output as a real sample) is genius in its simplicity. This report here gives a very good […]