Reflections below:

Google “What age groups use Facebook” vs “… TikTok”? What does the data say? Is there purposeful exclusion in these platforms? Is it harmful? Should it be corrected? Is it good business?

  • Older people use facebook; the issues and ads circulating there will be different

  • Info spreads differently on different social media platforms, because the groups of consumers are different

Why do virtual assistants have female voices? Amazon, Alexa Google, Apple Siri. Was this purposeful? Is it harmful? Should it be corrected? Is it good business?

  • These assistants act as a teacher role. We see teachers are stereotypically more female, because they are nurturing and caring

Talk about an algorithm that influences your decisions, think about these companies (ie FAANG - Facebook, Amazon, Apple,Netflix, Google)

  • These companies use advertising techniques where they take personal information that they collect and use it to cater to user interests

  • This drives up engagement, and therefore profit, which is the main motive for these companies

5.4 Crowdsourcing

Think of a use case for crowdsourcing in you project …

CompSci has 150 ish principles students. Describe a crowdsource idea and how you might initiate it in our environment? What about Del Norte crowdsourcing? Could your project be better with crowdsourcing?

  • Computer science students are a single group of people. Therefore, if we take data from only them regarding meal preferences, then there may be a bias present.

  • A better option would be to randomly sample people from different subgroups in school. This would include athletes, artists, academically focused individuals, and more. This would give us more diversity in our quest to see what people our age prefer, and we would get a better understanding on how to make our features useful

  • Questions that could be asked would be related to the amount that people our age cook themselves, if they do grocery shopping, if they watch their calories/ sugar intake/ nutritional value of the foods they eat, and if they plan future meals based on these goals.

What kind of data could you capture at N@tM to make evening interesting? Perhaps use this data to impress Teachers during finals week.

  • At night at the museum, our group could collect data based on what meal preferences people have. We could use a form/ user system to see how many meals and snacks people typically eat, as well as how often they cook and go grocery shopping. We could then incorporate this information into our website as a voting feature, also involving recipe ratings where the top/ favorite recipes that people like are shown.