There was a conference in Massachusetts called Data for Black Lives, this was the first year. I was not able to attend, but I did watch the livestream. There were a lot of great speakers and dialogue regarding data for social good and the ways it can help the Black community. With all the data that is being collected it is important that we not only use it to improve businesses, but also to create change in communities that need it. Although there are a ton of ways to use data for good, we must keep in mind the issues that will arise and be sure we learn how to use it responsibly.
Computers only do what humans instruct them too, but humans are prone to errors and these issues get passed down to the programs and algorithms that are used; if we do not have black and brown people in the room when these programs and algorithms are created there are going to be even more issues.
When we see businesses create content that is problematic, we begin to wonder who was in the room when the decision was being made to post it, because if they had black and brown people in the room then someone could have easily told them that the content is problematic. (Obviously this is easier said than done, because you can still have black and brown people in the room, but if it is not a welcoming environment there is no guarantee that they will speak up -- but that's a topic for another day)
People that are not data literate don't know to question the data being presented or know that the data does not paint a complete picture.
Samuel Sinyangewe gave a great example of how data can be presented and used to further an agenda:
- In his studies he has found that 'Black folks are 3x more likely to be killed by police.'
- Washington post database says 'Black folks are 1/4 killed by police and White folks are 2/4 people killed by police' and this is true, but this does not account for population.
This is just one example, so you can imagine the issues that can and will arise as we continue to use data. The people working with data aren't always aware of the social implications that come with their work and it may become easier and easier for them to forget that the data is not just data, those numbers can represent human lives. We must hold society accountable when data is being used. There needs to be transparency with the process: from collection to how it is presented.