Bias Catcher

Project Info

Language Learners thumbnail

Team Members


Angus , Beau , Jesse Bugden and 4 other members with unpublished profiles.

Project Description


The language that is used, verbally or in text, strongly influences our thoughts and actions. Certain words or phrases can create and perpetuate biases, unwittingly or deliberately.
Biases that constrains or diminishes the worth, value, inclusiveness or potential of other human beings only serves to perpetuate disharmony, violence and a weakened society.
Leaders, whether they be politicians, CEO’s, educators, sports coaches, local community group, workplace or family leaders, have a responsibility to be aware of the language that they use when communicating to those that they lead or influence.
If we agree with the premise that the language used influences biases aligned to gender, race, sexual orientation or social class, and that such biases have a detrimental and sometimes dire impact on people’s lives and society as a whole, it would be irresponsible of us not to address the issue.
We propose that a tool or application which is able to highlight words or phrases that may perpetuate abovementioned biases and proffer bias-free, inclusive alternatives would be very beneficial in raising awareness and changing people’s linguistic habits to be less divisive.
If leaders, educators and those within the media were to realise the value and employ such a tool, then the shift to a more bias-free and inclusive language would occur in a more timely manner, leading to enormous social and economic benefits.
Benefits would include reduced racial tensions, such as the current Black Lives Matter movement, less stereotypical thinking and biases that only restrict our growth as a Nation and a Global community both economically and personally.
Black Lives Matter - We are confident that Bias Catcher could be adapted and utilised to access the Government’s Open Data to highlight information, provide understanding and recommend language that would enable the user to communicate far more effectively and engender a confidence that helps to bridge the current divide.
Bias Catcher can be adapted to a range of communication scenarios, and can help facilitate communication in a range of contexts. This can include a reduction in divisive language against different groups of people, improved harmony between different religious groups, better international communication and better cultural sensitivity.


#nlp #ai #word2vec #python #flask

Data Story


We examined public data sources such as Trove, which includes classic tales like Peter Pan; as well as Hansard records, which contain sometimes robust debate from our federal leaders. These were full of examples of divisive word choices.


Evidence of Work

Video

Homepage

Team DataSets

Trove

Description of Use Trove was a fantastic resource for finding free text content critical to our project. In particular it allowed us to access high quality media articles and books made available through project Gutenberg. The ability to get some of these datasets in bulk allowed us to attempt to train our own model on content specific text - a task we were unable to complete this weekend but one which could improve the contextual relevance of our model.

Data Set

Research Data Australia

Description of Use This research tool allowed us to locate software snippets and datasets that we used in the experimental phase of our project. For example there was python software which related to gathering and processing text.

Data Set

The National Archives of Australia

Description of Use We used the National Archives to explore trends in changing attitudes to racial bias. We would like to have analysed the data directly but many of the examples we found were only available physically in the archives.

Data Set

Federal Election speeches

Description of Use We accessed the dataset which contained transcripts of Federal Election Speeches from 1901 when Edmund Barton formed the first Australian Government. It was evident that the language used by our political leaders of the time contained words or phrases that reinforced gender bias. See examples below. Edmund Barton Election Speech Excerpt (1901) – First responsibility. Formation of Ministry. Describe colleagues. Will not attempt to exalt them. Not a _one-man_ ministry nor _men_ with shibboleths. Ministry does not include all the _men_ one would have desired but there were only 7 portfolios. Not a fact any pressure was exercised by any one of them for _his_ inclusion. John Curtain Election Speech Excerpts (1937) - We should take the home as the base of this problem and ensure for the _father_ good work and good wages... In prosperity, and more so during years of depression, the lot of those families in which there is no _male_ breadwinner has been a sad one. While the _male_ breadwinner lives ... Malcolm Fraser Election Speech Excerpts (1980) - Five years ago, it was an unhappy business travelling around the Australian countryside. Many farmers were bankrupt; prices had collapsed. Farmers did not know whether to encourage their _sons_ to stay on the land, or to desert their farms. But the defence of Australia is more than _men_ and destroyers; patrol boats and tactical fighters.

Data Set

Australian parliament - Record of Proceedings -Hansard API

Description of Use We used the open record of proceedings to gather words that can be exclusionary. We also used passages of speech to evaluate our model.

Data Set

Challenges

Awareness, understanding and respect – How can Open Data help the #BLM movement?

The Black Lives Matter (#BLM) movement is not new, neither are racial injustices. However, in 2020 a series of racially motivated deaths, brutality and profiling in the US sent shockwaves around the world. Over 15 Million people took to the streets around the world to protest, and demand change. What can Open Government Data do to help the movement?

Go to Challenge | 5 teams have entered this challenge.

The language of leadership

In times of crisis words can inspire and unite us, but they can also provoke division and conflict. How has the language of Australia’s leaders changed over time? How can we represent these changes in public discourse within a historical timeline?

Go to Challenge | 7 teams have entered this challenge.

Identifying government investment for enhancing community safety

How can governments apply resources so as to proactively address social issues before they escalate and require reactive interventions (e.g. social work, law enforcement etc.)?

Go to Challenge | 16 teams have entered this challenge.