copy edits

10 files changed, 36 insertions, 18 deletions

diff --git a/site/content/pages/about/attribution.md b/site/content/pages/about/attribution.md
index 148fe6d1..180d87f0 100644
--- a/site/content/pages/about/attribution.md
+++ b/site/content/pages/about/attribution.md
@@ -16,6 +16,7 @@ authors: Adam Harvey
 <section class="about-menu">
 <ul>
 <li><a href="/about/">About</a></li>
+<li><a href="/press/">Press</a></li>
 <li><a class="current" href="/about/attribution/">Attribution</a></li>
 <li><a href="/about/legal/">Legal / Privacy</a></li>
 </ul>
diff --git a/site/content/pages/about/index.md b/site/content/pages/about/index.md
index 3884290b..0d9246ca 100644
--- a/site/content/pages/about/index.md
+++ b/site/content/pages/about/index.md
@@ -16,6 +16,7 @@ authors: Adam Harvey
 <section class="about-menu">
 <ul>
 <li><a class="current" href="/about/">About</a></li>
+<li><a href="/press/">Press</a></li>
 <li><a href="/about/attribution/">Attribution</a></li>
 <li><a href="/about/legal/">Legal / Privacy</a></li>
 </ul>
@@ -46,7 +47,7 @@ MegaPixels is an art and research project first launched in 2017 for an [install
 
 MegaPixels aims to provide a critical perspective on machine learning image datasets, one that might otherwise escape academia and industry funded artificial intelligence think tanks that are often supported by the several of the same technology companies who have created datasets presented on this site.
 
-MegaPixels is an independent project, designed as a public resource for educators, students, journalists, and researchers. Each dataset presented on this site undergoes a thorough review of its images, intent, and funding sources. Though the goals are similar to publishing an academic paper, MegaPixels is a website-first research project, with a academic publications to follow.
+MegaPixels is an independent project, designed as a public resource for educators, students, journalists, and researchers. Each dataset presented on this site undergoes a thorough review of its images, intent, and funding sources. Though the goals are similar to publishing an academic paper, MegaPixels is a website-first research project, with an academic publication to follow.
 
 One of the main focuses of the dataset investigations presented on this site is to uncover where funding originated. Because of our emphasis on other researcher's funding sources, it is important that we are transparent about our own. This site and the past year of research have been primarily funded by a privacy art grant from Mozilla in 2018. The original MegaPixels installation in 2017 was built as a commission for and with support from Tactical Technology Collective and Mozilla. The research into pedestrian analysis datasets was funded by a commission from Elevate Arts, and continued development in 2019 is supported in part by a 1-year Researcher-in-Residence grant from Karlsruhe HfG, as well as lecture and workshop fees.
 
diff --git a/site/content/pages/about/legal.md b/site/content/pages/about/legal.md
index a58fde48..53cbca9e 100644
--- a/site/content/pages/about/legal.md
+++ b/site/content/pages/about/legal.md
@@ -16,6 +16,7 @@ authors: Adam Harvey
 <section class="about-menu">
 <ul>
 <li><a href="/about/">About</a></li>
+<li><a href="/press/">Press</a></li>
 <li><a href="/about/attribution/">Attribution</a></li>
 <li><a class="current" href="/about/legal/">Legal / Privacy</a></li>
 </ul>
diff --git a/site/content/pages/about/press.md b/site/content/pages/about/press.md
index 11194ce2..a66f231d 100644
--- a/site/content/pages/about/press.md
+++ b/site/content/pages/about/press.md
@@ -16,12 +16,24 @@ authors: Adam Harvey
 <section class="about-menu">
 <ul>
 <li><a href="/about/">About</a></li>
+<li><a class="current" href="/press/">Press</a></li>
 <li><a href="/about/attribution/">Attribution</a></li>
 <li><a href="/about/legal/">Legal / Privacy</a></li>
 </ul>
 </section>
 
-https://megapixels.cc
+
+##### Features
 
 - April 19, 2019: [Who's Using Your Face](https://www.ft.com/content/cf19b956-60a2-11e9-b285-3acd5d43599e) by Madhumita Murgia for FT.com
-- Aug 22, 2018: [Transgender YouTubers had their videos grabbed to train facial recognition software](https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset) by James Vincent
\ No newline at end of file
+
+##### Cited by
+
+- April 19, 2019: [Western AI researchers partnered with Chinese surveillance firm](https://www.ft.com/content/41be9878-61d9-11e9-b285-3acd5d43599e) by Madhumita Murgia for FT.com
+
+
+##### Related
+
+- April 20: Washington Post Editorial Board [Opinion | Microsoft worked with a Chinese military university on AI. Does that make sense?](https://www.washingtonpost.com/opinions/microsoft-worked-with-a-chinese-military-university-on-ai-does-that-make-sense/2019/04/21/a0fb82c6-5d59-11e9-842d-7d3ed7eb3957_story.html)
+- April 10, 2019: [Microsoft worked with Chinese military university on artificial intelligence](https://www.ft.com/content/9378e7ee-5ae6-11e9-9dde-7aedca0a081a) see also [MS Celeb](/datasets/msceleb)
+- Aug 22, 2018: [Transgender YouTubers had their videos grabbed to train facial recognition software](https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset) by James Vincent
diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md
index 47c41fd7..2c51a7b2 100644
--- a/site/content/pages/datasets/brainwash/index.md
+++ b/site/content/pages/datasets/brainwash/index.md
@@ -1,7 +1,7 @@
 ------------
 
 status: published
-title: Brainwash
+title: Brainwash Dataset
 desc: Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco in 2014
 subdesc: The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection surveillance algorithms
 slug: brainwash
diff --git a/site/content/pages/datasets/duke_mtmc/index.md b/site/content/pages/datasets/duke_mtmc/index.md
index 69de167b..11414fd3 100644
--- a/site/content/pages/datasets/duke_mtmc/index.md
+++ b/site/content/pages/datasets/duke_mtmc/index.md
@@ -1,7 +1,7 @@
 ------------
 
 status: published
-title: Duke MTMC
+title: Duke MTMC Dataset
 desc: <span class="dataset-name">Duke MTMC</span> is a dataset of surveillance camera footage of students on Duke University campus
 subdesc: Duke MTMC contains over 2 million video frames and 2,700 unique identities collected from 8 HD cameras at Duke University campus in March 2014
 slug: duke_mtmc
diff --git a/site/content/pages/datasets/index.md b/site/content/pages/datasets/index.md
index 95c96e7f..2c7def38 100644
--- a/site/content/pages/datasets/index.md
+++ b/site/content/pages/datasets/index.md
@@ -1,11 +1,11 @@
 ------------
 
 status: published
-title: MegaPixels: Datasets
+title: MegaPixels: Face Recognition Datasets
 desc: Facial Recognition Datasets
 slug: home
 published: 2018-12-15
-updated: 2018-12-15
+updated: 2019-04-24
 authors: Adam Harvey
 sync: false
  
@@ -13,4 +13,4 @@ sync: false
 
 # Face Recognition Datasets
 
-Explore face recognition datasets contributing the growing crisis of authoritarian biometric surveillance technologies. This first group of datasets focuses usage connected to foreign surveillance companies and defense organizations.
+Explore face recognition datasets contributing to the growing crisis of authoritarian biometric surveillance technologies. This first group of 5 datasets focuses on image usage connected to foreign surveillance and defense organizations.
diff --git a/site/content/pages/datasets/msceleb/index.md b/site/content/pages/datasets/msceleb/index.md
index 3d5c6c59..f0b07557 100644
--- a/site/content/pages/datasets/msceleb/index.md
+++ b/site/content/pages/datasets/msceleb/index.md
@@ -1,7 +1,7 @@
 ------------
 
 status: published
-title: Microsoft Celeb
+title: Microsoft Celeb Dataset
 desc: Microsoft Celeb 1M is a target list and dataset of web images used for research and development of face recognition
 subdesc: The MS Celeb dataset includes over 10 million images of about 100K people and a target list of 1 million individuals
 slug: msceleb
@@ -19,13 +19,13 @@ authors: Adam Harvey
 ### sidebar
 ### end sidebar
 
-Microsoft Celeb (MS Celeb) is a dataset of 10 million face images scraped from the Internet and used for research and development of large-scale biometric recognition systems. According to Microsoft Research, who created and published the [dataset](https://www.microsoft.com/en-us/research/publication/ms-celeb-1m-dataset-benchmark-large-scale-face-recognition-2/) in 2016, MS Celeb is the largest publicly available face recognition dataset in the world, containing over 10 million images of nearly 100,000 individuals. Microsoft's goal in building this dataset was to distribute an initial training dataset of 100,000 individuals' images, and to use this dataset to accelerate research into recognizing a larger target list of one million people "using all the possibly collected face images of this individual on the web as training data".[^msceleb_orig]
+Microsoft Celeb (MS Celeb) is a dataset of 10 million face images scraped from the Internet and used for research and development of large-scale biometric recognition systems. According to Microsoft Research, who created and published the [dataset](https://www.microsoft.com/en-us/research/publication/ms-celeb-1m-dataset-benchmark-large-scale-face-recognition-2/) in 2016, MS Celeb is the largest publicly available face recognition dataset in the world, containing over 10 million images of nearly 100,000 individuals. Microsoft's goal in building this dataset was to distribute an initial training dataset of 100,000 individuals' images to accelerate research into recognizing a larger target list of one million people "using all the possibly collected face images of this individual on the web as training data".[^msceleb_orig]
 
-These one million people, defined by Microsoft Research as "celebrities", are often merely people who must maintain an online presence for their professional lives. Microsoft's list of 1 million people is an expansive exploitation of the current reality that for many people, including academics, policy makers, writers, artists, and especially journalists, maintaining an online presence is mandatory.  This fact should not allow Microsoft or anyone else to use their biometrics for research and development of surveillance technology. Many names in the target list even include people critical of the very technology Microsoft is using their name and biometric information to build. The list includes digital rights activists like Jillian York; artists critical of surveillance including Trevor Paglen, Jill Magid, and Aram Bartholl; Intercept founders Laura Poitras, Jeremy Scahill, and Glenn Greenwald; Data and Society founder danah boyd; and even Julie Brill, the former FTC commissioner responsible for protecting consumer privacy, to name a few.
+These one million people, defined by Microsoft Research as "celebrities", are often merely people who must maintain an online presence for their professional lives. Microsoft's list of 1 million people is an expansive exploitation of the current reality that for many people, including academics, policy makers, writers, artists, and especially journalists; maintaining an online presence is mandatory.  This fact should not allow Microsoft nor anyone else to use their biometrics for research and development of surveillance technology. Many names in the target list even include people critical of the very technology Microsoft is using their name and biometric information to build. The list includes digital rights activists like Jillian York; artists critical of surveillance including Trevor Paglen, Jill Magid, and Aram Bartholl; Intercept founders Laura Poitras, Jeremy Scahill, and Glenn Greenwald; Data and Society founder danah boyd; and even Julie Brill, the former FTC commissioner responsible for protecting consumer privacy, to name a few.
 
 ### Microsoft's 1 Million Target List
 
-Below is a selection of names from the full target list, curated to illustrate Microsoft's expansive and exploitative practice of scraping the Internet for biometric training data. The entire name file can be downloaded from [msceleb.org](https://www.msceleb.org). You can email <a href="mailto:msceleb@microsoft.com?subject=MS-Celeb-1M Removal Request&body=Dear%20Microsoft%2C%0A%0AI%20recently%20discovered%20that%20you%20use%20my%20identity%20for%20commercial%20use%20in%20your%20MS-Celeb-1M%20dataset%20used%20for%20research%20and%20development%20of%20face%20recognition.%20I%20do%20not%20wish%20to%20be%20included%20in%20your%20dataset%20in%20any%20format.%20%0A%0APlease%20remove%20my%20name%20and%2For%20any%20associated%20images%20immediately%20and%20send%20a%20confirmation%20once%20you've%20updated%20your%20%22Top1M_MidList.Name.tsv%22%20file.%0A%0AThanks%20for%20promptly%20handing%20this%2C%0A%5B%20your%20name%20%5D">msceleb@microsoft.com</a> to have your name removed. Names appearing with * indicate that Microsoft also distributed images.
+Below is a selection of 24 names from the full target list, curated to illustrate Microsoft's expansive and exploitative practice of scraping the Internet for biometric training data. The entire name file can be downloaded from [msceleb.org](https://www.msceleb.org). You can email <a href="mailto:msceleb@microsoft.com?subject=MS-Celeb-1M Removal Request&body=Dear%20Microsoft%2C%0A%0AI%20recently%20discovered%20that%20you%20use%20my%20identity%20for%20commercial%20use%20in%20your%20MS-Celeb-1M%20dataset%20used%20for%20research%20and%20development%20of%20face%20recognition.%20I%20do%20not%20wish%20to%20be%20included%20in%20your%20dataset%20in%20any%20format.%20%0A%0APlease%20remove%20my%20name%20and%2For%20any%20associated%20images%20immediately%20and%20send%20a%20confirmation%20once%20you've%20updated%20your%20%22Top1M_MidList.Name.tsv%22%20file.%0A%0AThanks%20for%20promptly%20handing%20this%2C%0A%5B%20your%20name%20%5D">msceleb@microsoft.com</a> to have your name removed. Names appearing with * indicate that Microsoft also distributed your images.
 
 === columns 2
 
@@ -42,12 +42,12 @@ Below is a selection of names from the full target list, curated to illustrate M
 | Evgeny Morozov* | Tech writer, researcher |
 | Glenn Greenwald* | Journalist, author |
 | Hito Steyerl | Artist, writer |
+| James Risen | Journalist |
 
-===
+====
 
 | Name |  Profession |
 | --- | --- | --- |
-| James Risen | Journalist |
 | Jeremy Scahill* | Journalist |
 | Jill Magid | Artist |
 | Jillian York | Digital rights activist |
@@ -56,14 +56,17 @@ Below is a selection of names from the full target list, curated to illustrate M
 | Kim Zetter | Journalist, author |
 | Laura Poitras* | Filmmaker |
 | Luke DuBois | Artist  |
+| Michael Anti | Political blogger |
+| Manal al-Sharif* | Womens's rights activist |
 | Shoshana Zuboff | Author, academic |
 | Trevor Paglen | Artist, researcher |
 
 === end columns
 
-After publishing this list, researchers from Microsoft Asia then worked with researchers affiliated with China's National University of Defense Technology (controlled by China's Central Military Commission) and used the the MS Celeb dataset for their [research paper](https://www.semanticscholar.org/paper/Faces-as-Lighting-Probes-via-Unsupervised-Deep-Yi-Zhu/b301fd2fc33f24d6f75224e7c0991f4f04b64a65) on using "Faces as Lighting Probes via Unsupervised Deep Highlight Extraction" with potential applications in 3D face recognition.
 
-In an [article](https://www.ft.com/content/9378e7ee-5ae6-11e9-9dde-7aedca0a081a) published by Financial Times based on data surfaced during this investigation, Samm Sacks (a senior fellow at the New America think tank) commented that this research raised "red flags because of the nature of the technology, the author's affiliations, combined with what we know about how this technology is being deployed in China right now". Adding, that "the [Chinese] government is using these technologies to build surveillance systems and to detain minorities [in Xinjiang]".[^madhu_ft]
+After publishing this list, researchers affiliated with Microsoft Asia then worked with researchers affiliated with China's National University of Defense Technology (controlled by China's Central Military Commission) and used the the MS Celeb dataset for their [research paper](https://www.semanticscholar.org/paper/Faces-as-Lighting-Probes-via-Unsupervised-Deep-Yi-Zhu/b301fd2fc33f24d6f75224e7c0991f4f04b64a65) on using "Faces as Lighting Probes via Unsupervised Deep Highlight Extraction" with potential applications in 3D face recognition.
+
+In an April 10, 2019 [article](https://www.ft.com/content/9378e7ee-5ae6-11e9-9dde-7aedca0a081a) published by Financial Times based on data surfaced during this investigation, Samm Sacks (a senior fellow at the New America think tank) commented that this research raised "red flags because of the nature of the technology, the author's affiliations, combined with what we know about how this technology is being deployed in China right now". Adding, that "the [Chinese] government is using these technologies to build surveillance systems and to detain minorities [in Xinjiang]".[^madhu_ft]
 
 Four more papers published by SenseTime, which also use the MS Celeb dataset, raise similar flags. SenseTime is a computer vision surveillance company that until [April 2019](https://uhrp.org/news-commentary/china%E2%80%99s-sensetime-sells-out-xinjiang-security-joint-venture) provided surveillance to Chinese authorities to monitor and track Uighur Muslims in Xinjiang province, and had been [flagged](https://www.nytimes.com/2019/04/14/technology/china-surveillance-artificial-intelligence-racial-profiling.html) numerous times as having potential links to human rights violations.
 
diff --git a/site/content/pages/datasets/oxford_town_centre/index.md b/site/content/pages/datasets/oxford_town_centre/index.md
index fbabcce5..bd340113 100644
--- a/site/content/pages/datasets/oxford_town_centre/index.md
+++ b/site/content/pages/datasets/oxford_town_centre/index.md
@@ -1,7 +1,7 @@
 ------------
 
 status: published
-title: Oxford Town Centre
+title: Oxford Town Centre Dataset
 desc: Oxford Town Centre is a dataset of surveillance camera footage from Cornmarket St Oxford, England
 subdesc: The Oxford Town Centre dataset includes approximately 2,200 identities and is used for research and development of face recognition systems
 slug: oxford_town_centre
diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md
index 0850bd99..55b48a07 100644
--- a/site/content/pages/datasets/uccs/index.md
+++ b/site/content/pages/datasets/uccs/index.md
@@ -1,7 +1,7 @@
 ------------
 
 status: published
-title: UnConstrained College Students
+title: UnConstrained College Students Dataset
 slug: uccs
 desc: <span class="dataset-name">UnConstrained College Students</span> is a dataset of long-range surveillance photos of students on University of Colorado in Colorado Springs campus
 subdesc: The UnConstrained College Students dataset includes 16,149 images of 1,732 students, faculty, and pedestrians and is used for developing face recognition and face detection algorithms