## Big Idea 5.3 Computing Bias

We discussed about how most default assistant voices are female instead of male. Some people wondered if it was anything to do with stereotypes, and how females are generally seen as “assistants” for males. However, people agreed with a possible process which included a survey about which voice would be more suitable. People might have preferred the female voice over the male voice, and hence it caught on.

Sometimes, bias can bleed to racism, as we saw in the HP computer. The entire class agreed that the computer camera was modified to scan the white person instead of the black person. We wanted to believe that the original computer camera AI was not edited, but we would never know.

Our code for this project includes electric cars, and information about them. This proves a little advantageous to us, as this information is not only gender-neutral, but does not include race. As our facts and information is as pristine and to the point as possible, bias will most likely be minimal, if not gone completely.

## Big Idea 5.4: Crowdsourcing

We talked about Wikipedia, blockchains, and certain data which represents a lot of people. We mentioned how crowdsourcing is useful for helping people make informed decisions, and can also give a general idea of certain trends and other things happening in society. However, people would want the least amount of private information (SSN, street address, etc) out on the internet, as it could lead to theft and other negative things Crowdsourcing is generally a good thing, as it shows what is liked and what is disliked among many things.

Our project depends on crowdsourcing, in a sense. Since we want to help people make informed decisions on what electric cars they would want to buy. We need some kind of public opinion about which car is the most / least popular. This is seen in our “likes / dislikes” system in our website.