---
title: "Meaning & Key Takeaway of: As we move into an era in which personal…"
description: "\"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..."
image: "https://sms4smile.com/quotes/i/0fa/kate-crawford-15804_data_as-we-move-into-an-era-in-which-personal_3017649.jpg"
---

#  As we move into an era in which personal devices are seen…

![“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…” quote by Kate Crawford](https://sms4smile.com/quotes/i/0fa/kate-crawford-15804_data_as-we-move-into-an-era-in-which-personal_3017649.jpg)   [Download](https://sms4smile.com/quotes/i/0fa/kate-crawford-15804_data_as-we-move-into-an-era-in-which-personal_3017649.jpg) [Open image](https://sms4smile.com/quotes/i/0fa/kate-crawford-15804_data_as-we-move-into-an-era-in-which-personal_3017649.jpg)

> “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 Crawford](https://sms4smile.com/quotes/author/kate-crawford/)

## About This Quote

This interpretation was drafted with AI assistance. It is one reading of the quote, not the author's own explanation.

Big data can deepen existing inequities; we must identify who is excluded.

**In simple terms:** Data can widen gaps.

Key Takeaway

Audit data for bias.

Themes

equity technology bias

Mood

critical concerned

Type

analytical inspirational

When to use this quote

- policy making
- tech design
- research

Key Concepts

inclusion justice

Questions to Reflect On

- Who is left out of data sets?
- How can we make data more inclusive?

A Different Perspective

Data collection may be incomplete.

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[Big Data](https://sms4smile.com/quotes/about/big-data/) [Data](https://sms4smile.com/quotes/about/data/) [Excluded](https://sms4smile.com/quotes/about/excluded/) [Excluded Places](https://sms4smile.com/quotes/about/excluded-places-4868147/) [Inequities](https://sms4smile.com/quotes/about/inequities/) [Live](https://sms4smile.com/quotes/about/live/) [People](https://sms4smile.com/quotes/about/people/) [People Excluded](https://sms4smile.com/quotes/about/people-excluded-2086651/) [Shadow](https://sms4smile.com/quotes/about/shadow/) [Will](https://sms4smile.com/quotes/about/will/)

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