Merge pull request #134 from XDgov/project-content-updates

Project Content Updates

collections/_pages/about.md

@@ -24,7 +24,7 @@ seo_excerpt:
     <div class="grid-row">
       <div class="grid-col-6">
         <div class="about-priority">
-          <h3>1. Bias Mitigation in Federal Data</h3>
+          <h3>1. AI in Federal Statistics</h3>
         </div>
         <div class="about-priority">
           <h3>2. Future of Data Collection and Sharing</h3>
@@ -51,7 +51,7 @@ seo_excerpt:
       intelligence solutions to the delivery of government services. Each team
       works with federal stakeholders across government and often with the
       support of outside partners, such as academic research groups, to apply
-      the latest innovations in artificial intelligence to each project.
+      the latest innovations in data science to each project.
     </p>
   </div>
 </section>

collections/_pages/interview-guide.md

@@ -65,7 +65,7 @@ title: Interview Guide
                 </p>
                 <h4>What's the story behind xD?</h4>
                 <p>
-                    The Census Bureau has long been technologically forward-thinking, from creating the first punch cards and electronic tabulators to being the first civilian agency to install and use the UNIVAC 1 mainframe computer. Founded in 2017 by Presidential Innovation Fellows, xD continues in this tradition by exploring partnership with industry leaders and continuing to drive innovation at the Census Bureau. Working with other federal agencies and academia to bring artificial intelligence, data science, and other cutting-edge approaches to the work of the U.S. Census Bureau, xD has been focused on two project portfolios – Combating Bias in AI and Deploying Privacy Enhancing Technologies (PETs) – and will continue to explore further innovation in the coming years.
+                    The Census Bureau has long been technologically forward-thinking, from creating the first punch cards and electronic tabulators to being the first civilian agency to install and use the UNIVAC 1 mainframe computer. Founded in 2017 by Presidential Innovation Fellows, xD continues in this tradition by exploring partnership with industry leaders and continuing to drive innovation at the Census Bureau. Working with other federal agencies and academia to bring artificial intelligence, data science, and other cutting-edge approaches to the work of the U.S. Census Bureau, xD has been focused on two project portfolios – Applying best practices in AI and Deploying Privacy Enhancing Technologies (PETs) – and will continue to explore further innovation in the coming years.
                 </p>
                 <h4>How are projects funded or selected at xD?</h4>
                 <p>

collections/_pages/projects.md

@@ -16,7 +16,7 @@ seo_excerpt: View projects built by and with xD.
     </div>
   </div>
 </section>
-
+<!--
 <section class="projects-page all-projects">
   <div class="grid-container">
     <div class="breadcrumb">Previous Projects</div>
@@ -27,4 +27,4 @@ seo_excerpt: View projects built by and with xD.
       {% endfor %}
     </div>
   </div>
-</section>
+</section> -->

collections/_projects/automated-change-detection-in-geospatial-imagery.md

@@ -1,25 +1,20 @@
 ---
 title: Automated Change Detection in Geospatial Imagery
-subtitle: Employing machine learning on satellite imagery to improve representation in surveys.
-excerpt: This project seeks to reduce algorithmic bias and bias caused by human error in current workflows, as well as to improve operational efficiencies and representation in surveys.
-seo_excerpt: This project seeks to reduce algorithmic bias and bias caused by human error in current workflows, as well as to improve operational efficiencies and representation in surveys.
+subtitle: Employing machine learning on satellite imagery to improve efficiency and accuracy in surveys.
+excerpt: This project seeks to reduce algorithmic bias and bias caused by human error in current workflows, as well as to improve operational efficiencies and accuracy in surveys.
+seo_excerpt: This project seeks to reduce algorithmic bias and bias caused by human error in current workflows, as well as to improve operational efficiencies and accuracy in surveys.
 permalink: /projects/automated-change-detection-in-geospatial-imagery/
 image: /assets/img/projects/automated-change-detection-in-geospatial-imagery/automated-change-detection-in-geospatial-imagery-og.png
 img_alt_text: An isometric grid of cubes is arranged to look like a city block. One of the cubes is taller and a different color than the rest.
 partners:
   entities:
     - { url: 'https://www.census.gov/programs-surveys/geography.html', name: 'U.S. Census Bureau - Geography Division' }
 status: Ongoing
-project_url: 
+project_url:
 featured: false
 active: true
 portfolio: bias
 ---
 <p>
-  Are there emerging technologies and methods that might serve us as we work to ensure we have timely
-  and complete collection of residential addresses from which we create critical data? We’re employing
-  machine learning models which correlate changes in housing unit data with satellite imagery to improve
-  automation around change detection and bias reduction. If successful, this project will reduce algorithmic
-  bias and bias caused by human error in current workflows, to improve operational efficiencies and
-  representation in surveys.
+  Are there emerging technologies and methods that might serve us as we work to ensure we have timely and complete collection of residential addresses from which we create critical data? We’re employing machine learning models which correlate changes in housing unit data with satellite imagery to improve automation around change detection. If successful, this project will reduce algorithmic bias and bias caused by human error in current workflows, to improve operational efficiencies and representation in surveys.
 </p>

collections/_projects/bias-toolkit.md

@@ -1,27 +1,24 @@
 ---
-title: Bias Toolkit
-subtitle: Equipping experts with tools that help mitigate and correct sources of bias in federal data.
+title: AI Toolkit
+subtitle: Tools that help deploy AI in government contexts.
 excerpt: Bias in federal data is not a new issue, but the importance of addressing it is compounded by the increasing application of machine learning (ML) models. This toolkit is designed to meet the unique needs of the public sector, highlighting the range of government processes that can benefit from a consideration of machine learning ethics.
 seo_excerpt: This project seeks to build tools designed to meet the unique needs of the public sector, highlighting the range of government processes that can benefit from a consideration of machine learning ethics.
-permalink: /projects/bias-toolkit/
-image: /assets/img/projects/bias-toolkit/bias-toolkit-og.png
+permalink: /projects/ai-toolkit/
+image: /assets/img/projects/ai-toolkit/ai-toolkit-og.png
 img_alt_text: An isometric computer monitor displays the xD logo with a keyboard in front of it.
 partners:
   entities:
     - { url: 'https://10x.gsa.gov', name: 'General Services Administration - 10x' }
     - { url: 'https://www.dol.gov/agencies/odep', name: 'Department of Labor - Office of Disability Employment Policy' }
 status: Ongoing
-project_url: 
+project_url:
 featured: false
 active: true
 portfolio: bias
 ---
 <p>
-  AI/machine learning-based tools and techniques are quickly being adopted and deployed across
-  governments at all levels and are continuously evolving. We’re building a toolkit designed to meet the
-  unique needs of the public sector, highlighting the range of government processes that can benefit from
-  a consideration of machine learning ethics.
+  AI/machine learning-based tools and techniques are quickly being adopted and deployed across governments at all levels and are continuously evolving. We’re building a toolkit designed to meet the unique needs of the public sector, highlighting the range of government processes that can benefit from a consideration of the impact of applied machine learning.
 </p>
 <p>
   <a href="https://bias.xd.gov" class="usa-button usa-button-black" target="_blank">Get the Toolkit</a>
-</p>
+</p>

collections/_projects/data-modernization-project.md

@@ -0,0 +1,18 @@
+---
+title: Data Modernization Project
+subtitle: Operationalize cloud-based data management and storage
+seo_excerpt: Operationalize cloud-based data management and storage
+permalink: /projects/data-modernization-project/
+image: /assets/img/projects/data-modernization-project/data-modernization-project-og.png
+partners:
+  entities:
+featured: false
+status: Ongoing
+active: false
+---
+<p>
+  This project is a collaboration with the Associate Director for Research and Methodology (ADRM) and aims to help stakeholders understand the extent of data utilization and storage, the applicability and cost/benefit of developing bespoke solutions internally and lead the execution of operationalizing cloud-based data management and data storage.
+</p>
+<p>
+  Related resources: <a href=" https://www.census.gov/about/what/transformation/maximizing-operational-efficiency/data-centric-business-ecosystem.Overview.html.html"> https://www.census.gov/about/what/transformation/maximizing-operational-efficiency/data-centric-business-ecosystem.Overview.html.html</a>
+</p>