Kate Crawford Quotes

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Vivametrica isn't the only company vying for control of the fitness data space. There is considerable power in becoming the default standard-setter for health metrics. Any company that becomes the go-to data analysis group for brands like Fitbit and Jawbone...

Self-tracking using a wearable device can be fascinating.

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Rather than assuming Terms of Service are equivalent to informed consent, platforms should offer opt-in settings where users can choose to join experimental panels. If they don't opt in, they aren't forced to participate.

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.

Surveillant anxiety is always a conjoined twin: The anxiety of those surveilled is deeply connected to the anxiety of the surveillers. But the anxiety of the surveillers is generally hard to see; it's hidden in classified documents and delivered in...

We urgently need more due process with the algorithmic systems influencing our lives. If you are given a score that jeopardizes your ability to get a job, housing, or education, you should have the right to see that data, know...

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 all-night coding and caffeine abuse, and finally, the grand finale: immense wealth and secular sainthood. Let's...

Big Data is neither color-blind nor gender-blind. We can see how it is used in marketing to segment people.

Data is something we create, but it's also something we imagine.

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 how we are categorized and advertised to.

Like all technologies before it, artificial intelligence will reflect the values of its creators. So inclusivity matters - from who designs it to who sits on the company boards and which ethical perspectives are included.

Histories of discrimination can live on in digital platforms, and if they go unquestioned, they become part of the logic of everyday algorithmic systems.

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.

Many of us now expect our online activities to be recorded and analyzed, but we assume the physical spaces we inhabit are different. The data broker industry doesn't see it that way. To them, even the act of walking down...

We need a sweeping debate about ethics, boundaries, and regulation for location data technologies.

The promoters of big data would like us to believe that behind the lines of code and vast databases lie objective and universal insights into patterns of human behavior, be it consumer spending, criminal or terrorist acts, healthy habits, or...

Numbers can't speak for themselves, and data sets - no matter their scale - are still objects of human design.

Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.

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.

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...

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