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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.
Kate Crawford
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Interpretation

What this quote means

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.

Themes

Artificial IntelligenceBiasSocietyTechnologyImpact

In practice

Example use cases

In a public debate about AI regulations, this quote can emphasize the need for cautious development.

More from Kate Crawford

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.
Kate CrawfordRead
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.
Kate CrawfordRead
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?
Kate CrawfordRead
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.
Kate CrawfordRead
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.
Kate CrawfordRead
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.
Kate CrawfordRead

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