From 6555000d37c4c808929aff3fdce9b85fc9719ea4 Mon Sep 17 00:00:00 2001
From: fria <138676274+friadev@users.noreply.github.com>
Date: Mon, 14 Jul 2025 07:01:52 -0500
Subject: [PATCH] add us census

---
 blog/posts/differential-privacy.md | 16 +++++++++++++++-
 1 file changed, 15 insertions(+), 1 deletion(-)

diff --git a/blog/posts/differential-privacy.md b/blog/posts/differential-privacy.md
index 8d18d356..beeb2167 100644
--- a/blog/posts/differential-privacy.md
+++ b/blog/posts/differential-privacy.md
@@ -187,4 +187,18 @@ That's just based on their initial whitepaper, they've likely increased their us
 
 Apple uses a similar method to Google, with a matrix initialized with all zeros. The input for the matrix is encoded with the SHA-256 hashing algorithm, and then bits are flipped randomly at a probablility dependent on the epsilon value.
 
-Apple only sends a random row from this matrix instead of the entire thing in order to stay within their privacy budget.
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+Apple only sends a random row from this matrix instead of the entire thing in order to stay within their privacy budget.
+
+### See What's Sent
+
+You can see data sent with differential privacy in iOS under Settings > Privacy > Analytics > Analytics Data, it will begin with DifferentialPrivacy. On macOS, you can see these logs in the Console.
+
+## U.S. Census
+
+Differential privacy isn't just used by big corporations, in 2020 famously the U.S. Census used DP to protect the data of U.S. citizens for the first time.
+
+As a massive collection of data from a large number of U.S. citizens, it's important for the census bureau to protect the privacy of census participants while still preserving the overall aggregate data.
+
+### Impetus
+
+Since the 1990's, the U.S. Census used a less formal injection of statistical noise into their data
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