As we move into an era in which personal devices are seen as proxies for public needs, we run the risk that already-existing inequities will be further entrenched. Thus, with every big data set, we need to ask which people are excluded. Which places are less visible? What happens if you live in the shadow of big data sets?
Interpretation
This quote highlights the risk of bias in big data and the potential exclusion of marginalized populations.
Kate Crawford emphasizes the importance of recognizing the limitations of big data and the potential harm caused by overlooking certain groups or locations. As technology advances, it is crucial to critically assess who is represented in the data we collect and analyze, as ignoring these aspects can reinforce existing social inequalities.
In practice
This quote could be used in a discussion about the impact of technology on societal inequities at a tech conference.
If you're not thinking about the way systemic bias can be propagated through the criminal justice system or predictive policing, then it's very likely that, if you're designing a system based on historical data, you're going to be perpetuating those biases.
We need to be vigilant about how we design and train these machine-learning systems, or we will see ingrained forms of bias built into the artificial intelligence of the future.
Only by developing a deeper understanding of AI systems as they act in the world can we ensure that this new infrastructure never turns toxic.
It is a failure of imagination and methodology to claim that it is necessary to experiment on millions of people without their consent in order to produce good data science.
The fear isn't that big data discriminates. We already know that it does. It's that you don't know if you've been discriminated against.
If you have rooms that are very homogeneous, that have all had the same life experiences and educational backgrounds, and they're all relatively wealthy, their perspective on the world is going to mirror what they already know. That can be dangerous when we're making systems that will affect so many diverse populations.
No amount of source-level verification or scrutiny will protect you from using untrusted code.
... the Kindle is a "roach motel" device: its license terms and DRM ensure that books can check in, but they can't check out.
Television isn't inherently good or bad. You go to a bookstore, there are how many thousands of books, but how many of those do you want? Five? Television's the same way. If you're going to show people stuff, television is the way to go. Words and pictures show things.
Ultimately, it's not going to be about man versus machine. It is going to be about man with machines.
You can be good at technology and like fashion and art. You can be good at technology and be a jock. You can be good at technology and be a mom. You can do it your way, on your terms.
I have got a scheme to make a thing in the form of a horse with a steam engine in the inside so contrived as to move an immense pair of wings, fixed on the outside of the horse, in such a manner as to carry it up into the air while a person sits on its back.
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