Home

TPT Notes and Actions

Data Structures Plan

Create Task

Quiz Corrections

Proctored MCQ Weeks

Part 1 Study Plan

Others

---

5.3 Actions

• After watching the video, “HP Computers are Racist,” I feel like the owner of the computer didn’t mean for it to move with the white lady and not move with the black man. He probably did not intend for that to happen. Maybe the computer couldn’t pick up the black guy because it couldn’t recognize him. He was probably too difficult to recognize and it probably thought he wasn’t their. The bias was probably the lighting. It could pick up lighter things. This is harmful because it is excluding certain people from being able to use the camera mover. The bias is harming people. Because it is excluding certain people, it should be excluded. What I would do to produce a better outcome is to make a camera that has a better way of seeing things so everyone can use the camera.

5.4 Actions

• There are 150 computer science students. I could make a survey about how they feel about the class, which every student could take, and then get the results. By doing this, it is crowdsourcing because I can then use the results to then make a page that updates when information is added. Other people can then look at the page to see what people think and how people rate the class. I could also use a vegetable versus non vegetable diet. This could see how many people eat vegetables or not, and it can update yearly based on what people put.
• Del Norte crowdsourcing could be good, since I can get reliable feedback from kids in the school. I could use their information on relevant stuff in school, or anything that could help in a final project.

5.3 Computing Bias

• Ex: Netflix
• Explicit data: thumbs up/thumbs down, name, address, etc
• Implicit data: When you watch, what show you binge(d), style of show frequently selected
• Bias in this example: Netflix exclusives are featured ahead of most - they want more subscriptions
• Main idea: Computing innovations can reflect existing human biases because of biases written into the algorithms or biases in the data used by the innovation.
• Ex: Hypothetical loan company - creating software to assist loan officers. Software finds trends in successful loans
• Reject those who don’t fit their trends: age, gender, race/ethnicity
• Main idea; Programmers should take action to reduce bias in algorithms used for computing innovations as a way of combating existing human biases.
• Main idea: Biases can be embedded at all levels of software development
• All software can be biased (unintentional/intentional):
• Casual vs sweaty YouTube Kids Facebook vs Instagram vs Snapchat/TikTok WeChat/KakaoTalk Google Home/Amazon Echo
• Questions to ask about bias:
• Enhancing or intentionally excluding?
• Intentionally harmful/hateful?
• Receiving feedback from a wide variety of people?

5.4 Crowdsourcing

• Public data sets
• Kaggle
• Courses in visualizations, TensorFlow, AI, machine learning, and more
• Competitions - cash prizes, swag, props
• Notebooks - code, data, notes
• Google public datasets
• Free for the 1st terabyte
• All-in-one package that uses BigQuery - Library and toolset that for SQL
• Data.gov
• US government data
• Agriculture, energy, water, health
• Your local government
• Keeps them accountable
• Help find solutions and trends in your area
• Main idea: widespread access to information and public data facilitates the identification of problems, development of solutions, and dissemination of results.
• Distributed computing
• Donate spare computing power to help calculations
• Folding@Home - Stanford University
• Protein folding
• BOINC - University of California, Berkeley
• A variety of projects: mathematics, astrophysics, climate, Minecraft@Home
• Main Ideas:
• Science has been affected by using distributed and “citizen science” to solve scientific problems.
• Citizen science is scientific research conducted in whole or part by distributed individuals, many of whom may not be scientists, who contribute relevant data to research using their own computing devices.
• Human capabilities can be enhanced by collaboration via computing.
• Innovations made possible with crowdsourcing
• Spotify Collaborative playlists Algorithm Metadata write-in
• Crowdfunding Kickstarter IndieGoGo
• Blockchain Cryptocurrency Other tokens - concert tickets
• Main Ideas:
• Crowdsourcing is the practice of obtaining input or information from a large number of people via the Internet.
• Crowdsourcing offers new models for collaboration, such as connecting businesses or social causes with funding.