- Title: McKenna Minister
- Creator: Christi and Barry Minister
- Subject: Animal Science Major
- Description: Quiet, Nice, Funny,
- Publisher: Friends, Family
- Contributor: Washington State University, Kentridge Highschool
- Date: January 3rd 2000
- Type: Female
- Format: Short, Green eyes, Brown hair
- Identifier: Kenna
- Source: Iola and Bob Callahan
- Language: English, Some French
- Relation: Brendon Minister
- Coverage: Pullman Washington, Kent Washington
- Rights: United States Constitution, Bill of Rights
DTC Homework #9
In Maria Popova’s article, “In a new world of informational abundance, content curation is a new kind of authorship”, she brought to light an interesting point about twitter, “The point is that new tools in general, and Twitter in particular, greatly challenge the binary dichotomy of attention as something that is either given or taken away, distracted. Instead, these tools allow us to direct attention to destinations where it can be sustained with more concentration and immersion”. I found this quote particularly interesting because it challenges the negative reputation social media has for distracting people and making them obsessed with their phones. Popova rather explains that social media, specifically twitter in this example, are used to feed people information and further connect them to more information. I recently wrote an argumentative essay that distraction doesn’t exist because it is difficult to determine what is a distraction and what is a valuable use of time, and anything can be categorized as a distraction. This quote by Popova furthers my claim because she argues that social media isn’t a distraction but rather a different facet which one concentrates upon. What makes social media great is the diverse ways in which it can be used as Popova implies, social media links people to new sources and feeds curiosity. There are accounts made for educational, promotional, personal, and commercial purposes which creates many possibility for what can be gained from concentrating on social media. Maria Popova states in this quote that attention is neither given or taken away meaning that any use of time is of value so no-matter how your time is used you gain something from the experience. Popova’s view is truly insightful because it opens up the possibilities and understandings that can be gained from social media.
DTC Homework 6: Data Visualizations
http://www.visualcomplexity.com/vc/project_details.cfm?id=980&index=980&domain=
This diagram displays the areas most walked in downtown Boston, it uses lines to demonstrate a path of travel, the darker and denser the line, the more popular that street is walked. The map is much darker in the center and diffuses out, streets near the water are also more populated. We can learn from this that the city center and water ways must have something attracting people likely food, jobs, and activities that cause more people to want to be there. We can also tell from this that the city was likely designed to have these things closer together so people could easily go from place to place. The areas by water are likely attracting people because it’s more scenic for walking and running, for those living in the city it’s better to walk or run away from the center of the city where there is a lot of traffic. This is useful for people in Boston to see where most activity is so they can find places, or avoid highly trafficked areas. This is interesting because it differs from a normal map which only shows the streets, instead it actually shows the areas on the streets that are populated. The data here is interesting because this also demonstrates a pattern, if we were to look at other city maps showing places of travel we would likely find similar results, a dense city center and coast.
https://www.reddit.com/r/dataisbeautiful/comments/9ddzey/oc_amount_of_music_listened_to_vs_time_of_day/?utm_content=title&utm_medium=hot&utm_source=reddit&utm_name=dataisbeautiful
The bar graph demonstrates the number of songs listened to per given time of day. There are large peaks at 3pm and 9pm, we can use these trends to see why people are listening to more music at these points in the day. We can assume the 3pm peak is from students getting out of school and listening to music and the 9pm peak is from people listening before bed or partying. There is also a smaller peak at noon, we can assume this is because most people are at their lunch break around this time. The graph is in no way symmetrical, the left side is empty from 3am-8am while the rest of the day is packed with music, this is likely because most people are asleep from 3-8am and aren’t listening to music. This data can be used by companies to know when they should put in ads to make sure they reach a larger audience. The trends in this data is interesting to understand not only when people like to listen to music, but also to understand society. People often listen to music independently today on their phones with headphones, this data shows us when people are more independent during the day. It also demonstrates when people usually wake up and go to bed. Data can represent more than just what the variables show nbecause data trends demonstrate other trends in society.
Weapons of Math Destruction Through The DIKW Framework
Cathy O’neil explores the ethics behind using algorithms to determine if specific people are adequate matches for certain jobs. Specifically she analyzes tests such as the Kronos test which determines if someone would be a good fit for a job, and the impact tool to weed out underperforming teachers. Both are computerized tests that lack human input, which leaves out many important factors in determining someone’s ability to do a job. Comparing the Kronos test to a human creates two very different processes, I’ll demonstrate through the DIKW framework. One data point the Kronos test may receive is “yes”. The information test has it that this is a response to the test question “Get mad easily?” which the Kronos test knowledge would understand this as a red flag. The wisdom in this situation would be that this person may not be good to hire since they may act irrationally due to their anger. The test doesn’t leave room for explanation or justification as a human might. An interviewer in the same situation may go through a different process. In this situation the interviewer would receive the same data point and information, but the knowledge and wisdom would be different since an interviewer can see things in shades of gray unlike the Kronos test. The knowledge an interviewer may have is “this person may have a mental illness” and then would be followed by the wisdom “I should ask them to elaborate further on why they may get angry easily to better understand the candidate”. There are many contributing factors to why someone responds the way they do on a test, using tests like these are good ways to gather information about a job candidate, but one cannot rely solely upon a test otherwise they won’t get the full picture. The same situation applies in the example including the Impact tool, this only uses mathematical scores, it doesn’t include human responses. In the case with Sarah Wysocki she was known to be a great educator, but her impact score said otherwise and she lost her job. The DIKW framework in this situation would result similarly to that of the Kronos test. The data the algorithm receives is just a number, it reduces a person down to one single score, which isn’t a fair way to estimate someone’s value. The computer would receive this number with the information including many similar scores from other teachers. The knowledge the impact score has is to compare these scores to find the lowest scores. The wisdom that the algorithm shows is that the lower scoring teachers are less fit for their job and therefore should be laid off. This method is unethical and eliminates possibilities for having strong educators like the Kronos test eliminates the possibility of some good workers.