Data will always bear the marks of its history. That is human history held in those data sets. — Kate Crawford Copy Share Image
We need a sweeping debate about ethics, boundaries, and regulation for location data technologies. — Kate Crawford Copy Share Image
Numbers can't speak for themselves, and data sets - no matter their scale - are still objects of human design. — Kate Crawford Copy Share Image
Big Data is neither color-blind nor gender-blind. We can see how it is used in marketing to segment people. — 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
Hidden biases in both the collection and analysis stages present considerable risks and are as important to the big-data equation as the… — Kate Crawford Copy Share Image
Data and data sets are not objective; they are creations of human design. We give numbers their voice, draw inferences from them,… — Kate Crawford Copy Share Image
While massive datasets may feel very abstract, they are intricately linked to physical place and human culture. And places, like people, have… — Kate Crawford Copy Share Image
If you're not thinking about the way systemic bias can be propagated through the criminal justice system or predictive policing, then it's… — Kate Crawford Copy Share Image
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… — Kate Crawford Copy Share Image
There's been the emergence of a philosophy that big data is all you need. We would suggest that, actually, numbers don't speak… — Kate Crawford Copy Share Image
Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a… — Kate Crawford Copy Share Image
Many of us now expect our online activities to be recorded and analyzed, but we assume the physical spaces we inhabit are… — Kate Crawford Copy Share Image
When dealing with data, scientists have often struggled to account for the risks and harms using it might inflict. One primary concern… — Kate Crawford Copy Share Image
The promoters of big data would like us to believe that behind the lines of code and vast databases lie objective and… — Kate Crawford Copy Share Image
As we move into an era in which personal devices are seen as proxies for public needs, we run the risk that… — Kate Crawford Copy Share Image
We urgently need more due process with the algorithmic systems influencing our lives. If you are given a score that jeopardizes your… — Kate Crawford Copy Share Image
People think 'big data' avoids the problem of discrimination because you are dealing with big data sets, but, in fact, big data… — Kate Crawford Copy Share Image
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 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
