Error-prone or biased artificial-intelligence systems have the potential to taint our social ecosystem in ways that are initially hard to detect, harmful in the long term, and expensive - or even impossible - to reverse.
Interpretation
Artificial intelligence can negatively affect society in subtle and lasting ways that may be difficult to correct.
Kate Crawford's quote emphasizes the dangers associated with biased or unreliable artificial intelligence systems, highlighting how their impacts can be insidious and hard to identify at first. Over time, these negative effects can become deeply entrenched within our social structures, leading to consequences that may be costly or even irreversible, thus underscoring the importance of vigilance and oversight in the development and deployment of AI technologies.
In practice
In a public debate about AI regulations, this quote can emphasize the need for cautious development.
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.
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?
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.
Our lives look a lot more interesting when they’re filtered through the sexy Facebook interface. We star in our own movies, we photograph ourselves incessantly, we click the mouse and a machine confirms our sense of mastery.
The PC is the LSD of the '90s.
We want to build technology that everybody loves using, and that affects everyone. We want to create beautiful, intuitive services and technologies that are so incredibly useful that people use them twice a day. Like they use a toothbrush. There aren't that many things people use twice a day.
You don't get to cut that chain of evidence and start over. You're always going to be pursued by your data shadow, which is forming from thousands and thousands of little leaks and tributaries of information.
Social media's greatest assets - anonymity, 'virality,' interconnectedness - are also its main weaknesses.
The process of preparing programs for a digital computer is especially attractive, not only because it can economically and scientifically rewarding, but also because it can be an aesthetic experience much like composing poetry or music.
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