Merge branch 'master' of github.com:adamhrv/megapixels_dev

3 files changed, 13 insertions, 11 deletions

diff --git a/site/public/about/index.html b/site/public/about/index.html
index 9f3c1a02..36a094d4 100644
--- a/site/public/about/index.html
+++ b/site/public/about/index.html
@@ -42,11 +42,11 @@
 <li><a href="/about/legal/">Legal / Privacy</a></li>
 </ul>
 </section><p>MegaPixels is an independent art and research project by Adam Harvey and Jules LaPlace that investigates the ethics, origins, and individual privacy implications of face recognition image datasets and their role in the expansion of biometric surveillance technologies.</p>
-<p>This project is made possible with support from <a href="http://mozilla.org">Mozilla</a>.</p>
+<p>MegaPixels is made possible with support from <a href="http://mozilla.org">Mozilla</a></p>
 <div class="flex-container team-photos-container">
    <div class="team-member">
        <h3>Adam Harvey</h3>
-       <p>is Berlin-based American artist and researcher. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for counter-surveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups) and is a currently researcher in residence at Karlsruhe HfG.</p>
+       <p>is Berlin-based American artist and researcher. His previous projects (<a href="https://cvdazzle.com">CV Dazzle</a>, <a href="https://ahprojects.com/stealth-wear">Stealth Wear</a>, and <a href="https://github.com/adamhrv/skylift">SkyLift</a>) explore the potential for counter-surveillance as artwork. He is the founder of <a href="https://vframe.io">VFRAME</a> (visual forensics software for human rights groups) and is a currently researcher in residence at Karlsruhe HfG.</p>
        <p><a href="https://ahprojects.com">ahprojects.com</a></p>
        </p>
    </div>
@@ -56,10 +56,10 @@
        </p>
        <p><a href="https://asdf.us/">asdf.us</a></p>
    </div>
-</div><p>MegaPixels is an art and research project first launched in 2017 for an <a href="https://ahprojects.com/megapixels-glassroom/">installation</a> at Tactical Technology Collective's GlassRoom about facial recognition datasets. In 2018 it was extended to cover pedestrian analysis datasets for a <a href="https://esc.mur.at/de/node/2370">commission by Elevate Arts festival</a> in Austria. Since then MegaPixels has evolved into a large-scale interrogation of hundreds of publicly-available face and person analysis datasets.</p>
-<p>MegaPixels aims to provide a critical perspective on machine learning image datsets, 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.</p>
-<p>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 paper to follow.</p>
-<p>One of the main focuses of the dataset investigations presented on this site is to uncover where funding originated. Because of our empahasis on other researchers' funding sources, it is important that we are transparent about our own. This site and the past year of reserach 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 Reseacher-in-Residence grant from Karlsruhe HfG and lecture and workshop fees.</p>
+</div><p>MegaPixels is an art and research project first launched in 2017 for an <a href="https://ahprojects.com/megapixels-glassroom/">installation</a> at Tactical Technology Collective's <a href="https://tacticaltech.org/pages/glass-room-london-press/">GlassRoom</a> about face recognition datasets. In 2018 MegaPixels was extended to cover pedestrian analysis datasets for a <a href="https://esc.mur.at/de/node/2370">commission by Elevate Arts festival</a> in Austria. Since then MegaPixels has evolved into a large-scale interrogation of hundreds of publicly-available face and person analysis datasets, the first of which launched on this site in April 2019.</p>
+<p>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.</p>
+<p>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.</p>
+<p>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.</p>
 </section><section><div class='columns columns-3'><div class='column'><h5>Team</h5>
 <ul>
 <li>Adam Harvey: Concept, research and analysis, design, computer vision</li>
@@ -77,7 +77,7 @@
 <li>Leaflet.js for maps</li>
 <li>C3.js for charts</li>
 <li>ThreeJS for 3D visualizations</li>
-<li>PDFMiner.Six and Pandas for research paper data analysis</li>
+<li>PDFMiner.Six and Pandas for research paper analysis</li>
 </ul>
 </div></div></section><section><h5>Attribution</h5>
 <p>If you use MegaPixels or any data derived from it for your work, please cite our original work as follows:</p>
@@ -90,7 +90,7 @@
  urldate = {2019-04-18}
 }
 </pre><h5>Contact</h5>
-<p>Please direct questions, comments, or feedback to <a href="https://mastodon.social/@adamhrv">mastodon.social/@adamhrv</a></p>
+<p>Please direct questions, comments, or feedback to <a href="https://mastodon.social/@adamhrv">mastodon.social/@adamhrv</a> or contact via <a href="https://ahprojects.com/about">https://ahprojects.com/about</a></p>
 </section>
 
   </div>
diff --git a/site/public/about/press/index.html b/site/public/about/press/index.html
index 4870eec3..233201bf 100644
--- a/site/public/about/press/index.html
+++ b/site/public/about/press/index.html
@@ -41,8 +41,10 @@
 <li><a href="/about/attribution/">Attribution</a></li>
 <li><a href="/about/legal/">Legal / Privacy</a></li>
 </ul>
-</section><ul>
-<li>Aug 22, 2018: "Transgender YouTubers had their videos grabbed to train facial recognition software" by James Vincent <a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset</a></li>
+</section><p><a href="https://megapixels.cc">https://megapixels.cc</a></p>
+<ul>
+<li>April 19, 2019: <a href="https://www.ft.com/content/cf19b956-60a2-11e9-b285-3acd5d43599e">Who's Using Your Face</a> by Madhumita Murgia for FT.com</li>
+<li>Aug 22, 2018: <a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">Transgender YouTubers had their videos grabbed to train facial recognition software</a> by James Vincent</li>
 </ul>
 </section>
 
diff --git a/site/public/datasets/index.html b/site/public/datasets/index.html
index 731bd3e0..3bf8ec18 100644
--- a/site/public/datasets/index.html
+++ b/site/public/datasets/index.html
@@ -37,7 +37,7 @@
 
   <div class='dataset-heading'>
     <section><h1>Face Recognition Datasets</h1>
-<p>Explore publicly available facial recognition datasets contributing the growing crisis of authoritarian biometric surveillance technologies. This first group of datasets presented in April 2019 focus on connections to surveillance companies connected to defense organizations.</p>
+<p>Explore face recognition datasets contributing the growing crisis of authoritarian biometric surveillance technologies. This first group of datasets focuses usage connected to foriegn surveillance companies and defense organizations.</p>
 </section>
   </div>