There are 4 types of published posts on the SD-AI website: common (the majority of posts), article, research paper, and application code. With the exception of common posts, you can see the type of a post by the color of the bar under the top thumbnail picture of the post and by a word inside that bar. Take a look at the following examples of posts to familiarize yourself with their types.
Notice the color of the bar above and the word "article" inside that bar. They mark this post as being a general interest article. An article is more formal than a common post. Please keep in mind that an article on SD-AI will not only inform people but also help people form opinions regarding our mission. For us, objectivity is paramount and the article must be clearly marked as "opinion" if it contains non-factual information. Editors in the community may suggest changes or may even remove the article if they deem it to not be appropriate, after consultations with the author.
Notice the color of the bar above and the word "research" inside that bar. They mark this post as being a research paper. Research papers should follow the general structure for writing an academic journal article: title, keywords, abstract, acknowledgements, introduction, main body, conclusion, references and citations. The keywords and the abstract are particularly important for us, allowing our readers to easily find the research they are interested in. The paper will be peer reviewed by a chosen body of experts in the field.
Notice the color of the bar above and the word "code" inside that bar. They mark this post as containing application code. If the code is not related to an ongoing project, then it does not have to be reviewed. Otherwise, it will be continuously reviewed until reviewers conclude that it definitely improves the overall quality of the application being worked on. The metrics by which we judge progress will be developed and changed with time. Formal methods of software development will be adopted, but slowly. Most code reviews are done in Zoom meetings.
For common posts though, that color-coded identification bar is absent;
since the vast majority of posts are common posts,
this choice allows for a less cluttered experience for readers. Examples:
AI can analyze voter data and identify groups of people who are less likely to vote, such as young people or those with low income. Campaigns and outreach efforts can then be targeted specifically to these groups in order to encourage them to participate.
It can analyze voter data to create personalized messages that are tailored to an individual's interests and concerns. This can make the messaging more compelling and increase the chances that the person will take action and vote.
AI can be used to develop educational materials that explain the voting process and the importance of participating in elections. These materials can be delivered through social media, email, or other digital channels to reach a wider audience.
AI can help to streamline the voter registration process, making it easier for people to register to vote and verifying that their information is accurate and up-to-date.
It can be used to analyze data on voter turnout and identify areas where more polling places are needed or where lines are particularly long. This can help to ensure that voters are able to cast their ballots in a more effective way.