Sexism, racism, and other forms of discrimination are being built into the machine-learning algorithms that underlie the technology behind many 'intelligent' systems… — Kate Crawford Copy Share Image
Error-prone or biased artificial-intelligence systems have the potential to taint our social ecosystem in ways that are initially hard to detect, harmful… — Kate Crawford Copy Share Image
We should always be suspicious when machine-learning systems are described as free from bias if it's been trained on human-generated data. Our… — Kate Crawford Copy Share Image
Like all technologies before it, artificial intelligence will reflect the values of its creators. So inclusivity matters - from who designs it… — Kate Crawford Copy Share Image
Only by developing a deeper understanding of AI systems as they act in the world can we ensure that this new infrastructure… — Kate Crawford Copy Share Image
As AI becomes the new infrastructure, flowing invisibly through our daily lives like the water in our faucets, we must understand its… — Kate Crawford Copy Share Image
The amount of money and industrial energy that has been put into accelerating AI code has meant that there hasn't been as… — Kate Crawford Copy Share Image
We need to be vigilant about how we design and train these machine-learning systems, or we will see ingrained forms of bias… — Kate Crawford Copy Share Image
Books about technology start-ups have a pattern. First, there's the grand vision of the founders, then the heroic journey of producing new… — Kate Crawford Copy Share Image
Histories of discrimination can live on in digital platforms, and if they go unquestioned, they become part of the logic of everyday… — Kate Crawford Copy Share Image
Algorithms learn by being fed certain images, often chosen by engineers, and the system builds a model of the world based on… — Kate Crawford Copy Share Image
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… — Kate Crawford Copy Share
While many big-data providers do their best to de-identify individuals from human-subject data sets, the risk of re-identification is very real. — Kate Crawford Copy Share
People think 'big data' avoids the problem of discrimination because you are dealing with big data sets, but, in fact, big data is being… — Kate Crawford Copy Share
There's been the emergence of a philosophy that big data is all you need. We would suggest that, actually, numbers don't speak for themselves. — Kate Crawford Copy Share
Data and data sets are not objective; they are creations of human design. We give numbers their voice, draw inferences from them, and define… — Kate Crawford Copy Share
We urgently need more due process with the algorithmic systems influencing our lives. If you are given a score that jeopardizes your ability to… — Kate Crawford Copy Share
Sexism, racism, and other forms of discrimination are being built into the machine-learning algorithms that underlie the technology behind many 'intelligent' systems that shape… — Kate Crawford Copy Share
Books about technology start-ups have a pattern. First, there's the grand vision of the founders, then the heroic journey of producing new worlds from… — Kate Crawford Copy Share
The amount of money and industrial energy that has been put into accelerating AI code has meant that there hasn't been as much energy… — Kate Crawford Copy Share
Like all technologies before it, artificial intelligence will reflect the values of its creators. So inclusivity matters - from who designs it to who… — Kate Crawford Copy Share
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… — Kate Crawford Copy Share
We should have equivalent due-process protections for algorithmic decisions as for human decisions. — Kate Crawford Copy Share
