(upbeat music) - [Interviewer] What can we do to advocate for people to fight for their data? - Well, the first thing is we all have a voice, and we should be speaking up about it. So, wherever you have representation around the world you should be speaking out about saying this is what we expect and what we demand. The second part is if you're a developer or a designer, you have a responsibility.
You have a responsibility just like someone who's an architect of a building to make sure that you're building it in a responsible way. You have the responsibility to say here's how we should do it. Here's a simple way of thinking about that. One version is that we say, hey you know what, everyone should take an oath of saying like when I ask for your data, if I'm building a system and I ask for your data, I'm going to treat your data as if it was my own data or my own family's data. And I take that as a first level principle.
Second is what would it look like as we're building a product to have a checklist around all the things that we say. Check the box, have we done an assessment of what happens if somebody gets hold of or breaks into the system. Would it still be hard to put the data sets together? Two, what happens if the person wants their data back or wants it removed? Three, is there a way that this data could be abused or maybe harmful from an algorithmic perspective, could it have bias? Number four, and number five, and number six and number seven.
We could create a checklist, it wouldn't be that hard. We have those checklists around data, we have those checklists around design principles. We need to have that around broad aspects of data as well. Some of those checklists maybe need a model like we have around regulatory, just like you know, your credit cards do. They can't deny you, or they have to show that they can't use race as an indicator in your credit. We need to ask that in bigger things, and part of that is going to be training auditors, training policy makers, training the public.
Not having crappy passwords. (laughing) Basically it's a, how do we lift everybody up together and start asking that. The reason it sounds like a broad answer is because we're at the front end of this. And the speed at which this technology is moving means that we are not, we're still chasing the problem rather than ahead of the problem. (upbeat music)
Skill Level Appropriate for all
Bracketology Club: Using March Madness to Learn Data Sciencewith Brian Tonsoni12m 7s Appropriate for all
The Data Science of Government and Political Science, with Barton Poulsonwith Barton Poulson1h 2m Appropriate for all
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.