Reflection 5.3: I find that computing bias exists at various points in the program production process. It starts from when the idea is born, and continues through production, testing, and even in use. A good example of this is the video we watched of the follow camera not picking up skin color other than white. This may show a problem in testing, because if the majority of subjects were white, it is likely they could have missed this disparity. While bias is not always intentional, it almost always exists implicitly in result of our society and it’s foundations.
Reflection 5.4:
- CompSci has 150 ish principles students. Describe a crowdsource idea and how you might initiate it in our environment?
One might make and create a survey that is sent out to the population of CSP students. This will ensure that as many students as possible are given the chance to give their input, so the program would be best functional for the intended audience. I am on the LIFE Advisory of Mending Matters, and we recently created and sent out a survey so that we may improve mental health opportunities and support at Del Norte. This worked well to make students (our intended audience) feel heard and valued.
- What about Del Norte crowdsourcing? Could your project be better with crowdsourcing?
Del Norte crowdsourcing can be done through school-wide surveys. It can also be done by randomly selecting a variety of student to complete a short question are. This will again ensure that the project will best benefit the people we are marketing to.
- What kind of data could you capture at N@tM to make evening interesting? Perhaps use this data to impress Teachers during finals week.
After we present our project to the individual, we can ask them to fill out a short feedback survey on user-friendliness, functionality, and visual appeal. We should then blog this feedback, and work to implement it into our project. This will show that in addition to our understanding of the coding aspect of CSP, we also understand real world application of prototyping, crowdsourcing, and bias.