by arinze.onyebuchi -

15 – Defining What Gets Scanned

After sketching out how users would scan their data and review the results, I knew it was time to focus on something deeper. If someone’s trusting this tool to find their personal data online, they should be able to control exactly what it’s looking for and how it behaves. That’s where the Settings tab comes in, specifically, the part that lets people manage the data points the app scans for.

This is more than just a list of preferences. It’s the part of the app that decides how useful the tool really is. If it can’t scan for the right things or look in the right places, then it doesn’t matter how nice the interface looks. So I started thinking through the user journey here. What does it feel like to set this up for the first time? How easy is it to update your info later? What happens when someone wants to remove or change something?

I broke it down into a few simple flows. When someone taps into this section, they see a list of data types like full names, email addresses, phone numbers, home addresses, usernames, and social media handles. Each one has a toggle, so they can decide which categories they want the app to track. Tapping into a category opens a list of actual data points. For example, under “email addresses,” you might see:

Users can add new entries, remove old ones, or give them a label like “Work” or “Personal” to keep things organized. It should feel simple, like updating a contacts list.

User flow of the entire settings tab
Zooming into the Scan Preferences

Another part of this section is where the app should scan. Some people might want full control, while others may prefer a more hands-off setup. So I imagined a second area where users can select the types of platforms the app should search, like:

  • Public data brokers
  • Social media sites
  • Search engines
  • Forums or blogs
  • Data breach records

By default, the app could suggest a recommended setup, but users who want to go deeper can switch things on or off based on what they care about.

I also wanted to give users a quick summary before they leave this section. Something that says, “You’re scanning for 6 data points across 4 categories.” Just a simple, reassuring message that confirms everything’s set up the way they want. From there, they can either save changes or jump straight into a new scan.

This part of the tool gives people full control over what they’re sharing with the app and what the app is doing for them. It also needs to feel like something they can come back to anytime. Maybe they changed their email or want to track a new phone number. It should be easy to update without starting from scratch.

by arinze.onyebuchi -

06 Transparency in Data Use: Building Trust Through Clear Communication

Introduction

Trust is the foundation of any user-platform relationship, and transparency is the key to earning it. Users need to know what data is being collected, why, and how it’s being used. In this post, I’ll explore how clear communication about data use can strengthen user trust and discuss practical design strategies for achieving transparency. These insights will inform my thesis objectives: creating a Privacy Framework for companies and prototyping a tool for managing personal data online.

Why Transparency Matters

Transparency transforms uncertainty into trust. When users understand how their data is used, they’re more likely to engage with a platform. Without it, users feel manipulated, leading to distrust and disengagement. Example: Many users became wary of Facebook after the Cambridge Analytica scandal because the platform failed to communicate how user data was being shared and exploited.

Key Elements of Transparent Data Use

  1. Clarity: Use plain language to explain data practices. Example: Replace “We may collect certain information to enhance services” with “We use your email to send weekly updates.”
  2. Visibility: Make privacy policies and settings easy to find. Example: A single-click link labeled “Your Data Settings” at the top of a webpage.
  3. Real-Time Feedback: Show users how their data is being used in real time. Example: A privacy dashboard that displays which apps or services are currently accessing your location.
Possible transparency settings that can be introduced by companies

Case Studies of Transparency in Action

  1. Apple’s Privacy Nutrition Labels: These labels show, at a glance, what data an app collects and how it is used, simplifying complex privacy policies into digestible bits of information.
  2. Google’s My Activity Dashboard: Google allows users to view and manage their activity data, offering options to delete or limit collection.
  3. noyb.eu’s Advocacy Work: By challenging platforms that obscure their data use, noyb has pushed for greater clarity and compliance with GDPR.

These examples demonstrate how transparency fosters trust and aligns with ethical design principles.

Apple lets you know what data is being used.
image source: Adjust
Google has a “My Activity” section tyhat shows relevant info.

How can design effectively communicate data use to build trust and ensure transparency?

  • What visual and interactive elements improve users’ understanding of data use?
  • How can transparency features integrate seamlessly into existing platforms?

Designing for Transparency

To achieve transparency, platforms can:

  1. Integrate Visual Feedback: Use graphics, charts, or icons to explain data use. Example: A pie chart showing how much of your data is used for ads vs. analytics.
  2. Streamline Privacy Policies: Provide short, bulleted summaries of key data practices. Example: “We collect: your email for updates, your location for recommendations, and your browsing history for ads.”
  3. Offer Customization: Allow users to adjust permissions directly. Example: Toggles for enabling/disabling specific data categories like tracking or personalization.

These approaches will also inform the Privacy Framework I’m developing, ensuring it includes actionable guidelines for platforms to improve data transparency.

Challenges and Personal Motivation

Transparency isn’t always easy to achieve. Challenges include balancing clarity with detail, overcoming user distrust, and addressing corporate reluctance to reveal data practices. However, I’m motivated by the potential to create tools and frameworks that make transparency accessible and actionable for users and companies alike.