Textual edits

Author: jfparie

content/english/about/teams.md

@@ -3,7 +3,7 @@ title: Teams
 subtitle: "Algorithm Audit consists of an executive board, advisory board, supervisory board, various teams and works with case-based advice commissions that consist of independent experts and stakeholder. Learn more about\_our the [governance](/about/boards/).\n"
 image: /images/svg-illustrations/about.svg
 about_AA:
-  title: Activities
+  title: Core activities
   content: >-
     In 2021, NGO Algorithm Audit was founded on the idea that ethics in
     algorithmic methods urgently needs a case-based and bottom-up approach.
@@ -118,7 +118,7 @@ team3:
 quick_navigation:
   title: Overview
   links:
-    - title: Activities
+    - title: Core activities
       url: '#about'
     - title: Executive team
       url: '#executive-team'

content/english/technical-tools/SDG.md

@@ -126,7 +126,7 @@ Synthetic data generation (SDG) offers a solution. By creating artificial data t
 {{< container_open title="Has SDG been used in the past?" icon="fas fa-history" id="use-cases" >}}
 
 For two reasons, the use of synthetic data has long been hindered:
-1. - <span style="color:#005AA7">Privacy risks</span> – Concerns, particularly among legal professionals, existed about the risks of personal data being exposed when sharing synthetic data. Research and practical examples have demonstrated that these risks can be mitigated. See the attached [memo](/technical-tools/sdg/#privacy-legal) below for more background information on the legal aspects of synthetic data generation.
+1. <span style="color:#005AA7">Privacy risks</span> – Concerns, particularly among legal professionals, existed about the risks of personal data being exposed when sharing synthetic data. Research and practical examples have demonstrated that these risks can be mitigated. See the attached [memo](/technical-tools/sdg/#privacy-legal) below for more background information on the legal aspects of synthetic data generation.
 2. <span style="color:#005AA7">Cloud dependencies risks</span> – Many existing (commercial) APIs rely on cloud-based software, making them unsuitable for public organizations, as citizen data cannot simply be uploaded to cloud platforms. [Local-first](/technical-tools/sdg/#local-first) data processing offers a solution to this problem. With this tool, synthetic data can be generated directly in the browser. The data does not leave the user's computer or the organization's environment.
 
 In sum, recent use cases have shown that synthetic data can be safely shared and generated without the involvement of a cloud provider. It is time to scale up so that stakeholders can gain more and better insights into the data managed by government organizations.

content/nederlands/about/teams.md

@@ -7,7 +7,7 @@ subtitle: >
   meer](/nl/about/boards/) over de governance van de stichting.
 image: /images/svg-illustrations/about.svg
 about_AA:
-  title: Activiteiten
+  title: Kernactiviteiten
   content: >-
     Stichting Algorithm Audit is in 2021 opgericht vanuit het idee dat de
     verantwoorde inzet van algoritmes alleen slaagt als normatieve aspecten van
@@ -123,7 +123,7 @@ team3:
 quick_navigation:
   title: Overzicht
   links:
-    - title: Activiteiten
+    - title: Kernactiviteiten
       url: '#about'
     - title: Uitvoerend team
       url: '#executive-team'