UnBias Facilitator Booklet
July 3, 2019 by Giles Lane · Comments Off on UnBias Facilitator Booklet
Our colleagues, Helen Creswick and Liz Dowthwaite, at Horizon Digital Economy Institute (University of Nottingham) have recently produced a new booklet for facilitators to accompany the UnBias Fairness Toolkit.
The booklet is the result of an Impact Study grant to run a series of workshops with people of different ages and to co-devise games and activities using the Awareness Cards. It also contains further advice and feedback for facilitators and other running workshops using the Toolkit, to guide them to what works best with different groups.
Download PDF versions to print out and make up
Illustrating for algorithmic bias
September 27, 2018 by aliceangus · Comments Off on Illustrating for algorithmic bias
As part of the UnBias project I was asked to create illustrations for the Fairness Toolkit’s Trustscape and Awareness Cards. The toolkit is designed to raise awareness and create dialogue about algorithms, trust, bias and fairness. My involvement in the project started with a series of quick sketches for stickers to be used with the Trustscape. The sketches were made in response to the results of workshops with young people who identified issues, themes and difficulties in the network world, and described a wide range of bias in algorithmic decisions and how they impact on peoples lives.
For the UnBias Awareness Cards the brief was to create a design for each of the eight suits: Rights, Data, Factors, Values, Process, Exercise and Glossary. The fronts of the cards contain examples, activities, scenarios and information about algorithmic bias and the ways prejudiced behaviours can emerge in systems. The focus of my illustrations was on how algorithmic decisions could affect people and communities; how do we know decisions are being made fairly and not threatening rights; how do we know decisions are not being based on gender and race? How do we know we are in social media bubble, what is real or fake and what to trust?
At the same time I also wanted the illustrations to celebrate some of the pioneering developments in computing, often made by people who wanted to enable others, and to reference the history of communication technologies, computation devices, predicting machines and mass communication technologies.
It was important for each card to be unique but for the common themes to flow through all of them. Across the cards you will find patterns and references to computation devices and processes: QR codes, punch cards, network diagrams, server arrays, excerpts of code for sorting algorithms, circuit board diagrams, flowcharts, early devices like the Difference Engine and Tide Predicting Machine no 2, the Mac Classic and the handheld devices and social media apps we use today. Since algorithms work behind the scenes of the web to filter and sort data, several cards feature machines used for measuring, weighing, sorting, ranking, dividing and filtering.
The main text styles are inspired by typefaces that have a relationship to the history of computing. ‘Factors’ is based on the early Selectric font for IBM’s Selectric electric typewriter which went on to become one of the first to provide word processing capability. ‘Exercise’ and ‘Example’ were inspired by the typefaces in early forms of electronic communication; telegrams, teletext and ticker tape. The lettering of ‘Data’, ‘Values’, ‘Rights’, ‘Process’ and ‘Glossary’ were inspired by fonts I had seen on early computation devices, like Pascal’s Typewriter, Babbage’s Difference Engine, Kelvin’s and Ferrel’s Tide Predicting Machines, and by typefaces used on mass-produced adverts and posters in the industrial revolution.
The edge of the main title scrolls are decorated with mathematical motifs like > <, ( ), X, etc. And the outer borders are decorated with binary. One of the simplest ways of visualising an algorithm is using a flowchart, and the centre shape of each card is inspired by the frames used in flowcharts to represent different stages of the process:- ‘stop/start’, ‘database’, ‘processing’, ‘decision’, ‘repetition’ ‘connector’.
UnBias Awareness Cards – Glossary Suit Illustration
Glossary is a bit different to the other cards, there is only one Glossary card and it holds a definition of the meaning of ‘ALGORITHM’. The images on the back reference various storage and processing devices, reel to reel, server array, a mac classic, an early word processor, tablet, ticker tape, punch cards, fortran cards, blackboard and an abacus.
The card also celebrates some pioneers in mathematics. The algorithm on the computer screen and on the blackboard is Euclid’s Greatest Common Divisor (GCD), dating back to Ancient Greece it is one of the oldest algorithms still in usage.
The writing around the scroll border are excerpts from Ada Lovelace‘s pioneering algorithm to calculate Bernoulli numbers, written in the early 1840s, it is considered by some to be the first computer programme. Ada was an english mathematician, thought to be the first computer programmer and the work this is from is one of the most important documents in the history of computing.
Standing at the chalkboard is Dorothy Vaughn, a leading mathematician and early programmer who worked at NASA and its predecessor in the 1930s, 40s, 50s and 60s. Working in a time of racial segregation she led the West Area Computing team. She was the first African American supervisor at NASA and one of very few women at that level, but was not officially acknowledged, or paid, as such for several years. She was visionary in her realisation that computers would take over much of the human calculators work and taught herself FORTRAN and other languages, which she then taught to the other women, to be ready for the change. Her work fed into many areas of research at the Langley Laboratory and she paved the way for a more diverse workforce and leadership at NASA today.
Grace Hopper was a groundbreaking programmer who, in the 1950s and 60s, pioneered machine-independent programming languages and invented one of the first compiler tools that translated English words into the machine code that computers understood. Grace was an American computer scientist who realised that people would more easily be able to use computers if they could programme in English words and then have those translated into machine code. She created the FLOW-MATIC the first English like programming language and was instrumental in the Development of COBOL, which is still widely used today. She did much to increase understanding of computer communications and went on to push more women to enter the field and for people to experiment and take chances in computing.
A Raven sits on the Blackboard watching because all Corvids (Ravens, Crows, Rooks etc) are renowned for their problem solving skills (the Crow Search Algorithm (CSA) is based on the intelligent behaviour of crows).
UnBias Awareness Cards – Data Suit Illustration
UnBias Fairness Toolkit
September 7, 2018 by Giles Lane · Comments Off on UnBias Fairness Toolkit
The UnBias Fairness Toolkit is now available to download and use. It aims to promote awareness and to stimulate a public civic dialogue about algorithms, trust, bias and fairness. In particular, on how algorithms shape online experiences, influencing our everyday lives, and to reflect on how we want our future internet to be fair and free for all.
The tools not only encourage critical thinking, but civic thinking – supporting a more collective approach to imagining the future as a contrast to the individual atomising effect that such technologies often cause. The toolkit has been developed by Giles Lane, with illustrations by Alice Angus and Exercises devised by Alex Murdoch; alongside contributions from the UnBias team members and the input of young people and stakeholders.
The toolkit contains the following elements:
- Handbook
- Awareness Cards
- TrustScape
- MetaMap
- Value Perception Worksheets
All components of Toolkit are freely available to download and print under Creative Commons license (CC BY-NC-SA 4.0).
Download the complete UnBias Fairness Toolkit (zip archive 18Mb)
