Team Name:
Council Voting🗳️
Team Members:
Council Voting🗳️
We’re developing an AI to help voters engage with and access information in local elections, similar to ABC’s “Election Compass” for federal elections. This AI will scrape the web for up-to-date candidate research and summarize council minutes to present incumbents’ voting history. As part of the “UNSW Election Help Desk” initiative, we’ve set up a stall next Tuesday and Thursday to assist UNSW students with voter enrolment, provide critical election information, and offer a chance to meet local candidates. Our goal is to make local elections more accessible and empower voters with AI-driven political journalism.
Description of Use To introduce the candidates, what area they are running for and party affiliation.
Description of Use In our project, we use this dataset to integrate historical election results into our AI tool, allowing voters to see past voting patterns and trends. This helps contextualize current candidates and election issues by providing a historical perspective on electoral outcomes, which can inform voters about shifts in political landscapes and candidate performance over time.
Description of Use In our project, we use this dataset to incorporate local school data into our AI tool, offering voters insights into educational impacts and school conditions in their area. This helps contextualize candidates’ education policies and provides voters with relevant information about how potential policies might affect local schools and student outcomes.
Description of Use We use the disaster-affected LGAs dataset to integrate real-time information on how local areas have been impacted by disasters into our AI. This will allow our AI to provide context about the current conditions and challenges in different council areas, enriching candidate profiles with relevant details about their responses and involvement in disaster management. It can help voters understand how candidates have handled or are prepared to handle local emergencies, adding another layer of information to support informed voting decisions.
Description of Use In our project, we use this dataset to integrate educational data into our AI tool, helping voters understand how local candidates’ policies might impact local schools and education systems. This can offer additional context on candidates’ education-related initiatives and provide voters with a more comprehensive view of their potential impact on community education.
Description of Use In our project, we utilize AES data to analyze voter sentiments and political trends in our local elections, enhancing our AI’s ability to provide context on current electoral issues and candidate profiles. This will help in creating a more informed and engaging AI tool for voters, by integrating historical and contemporary political data into our candidate summaries and responses.
Description of Use We use the ACNC dataset to enhance our AI by integrating charity data into candidate profiles, highlighting their community involvement and past contributions. This will provide voters with a deeper understanding of each candidate’s impact and align it with their local initiatives, enriching the AI’s responses and making it a more comprehensive tool for informed voting decisions.
Description of Use Use of data to generate information about council areas such as largest employer area, socio-economic index
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