Big Idea 5: Impact of Computing — Topic 5.4: Crowdsourcing

Welcome! We are exploring Big Idea 5, which focuses on how computing affects our lives, our culture, and our world. In this chapter, we look at Crowdsourcing. Have you ever wondered how a navigation app knows there is traffic ahead, or how scientists can track thousands of bird migrations at once? The answer is often "the crowd!"

Don't worry if this seems like a big topic. At its heart, crowdsourcing is just about people using the Internet to work together on a massive scale.

What is Crowdsourcing?

Crowdsourcing is the practice of obtaining input or contributions from a large number of people via the Internet. Instead of one person or a small team doing all the work, a task is shared with a huge "crowd" of users.

Think of it like a giant group project where the "group" is anyone with an Internet connection. By using computing innovations, we can collect data or solve problems much faster than we ever could before.

Key Takeaway: Crowdsourcing relies on the Internet to connect people and gather their individual contributions into one big result.

Did you know? Crowdsourcing allows for a diversity of perspectives. When people from different backgrounds contribute to a project, it can help identify and reduce bias (which we cover in Topic \(5.3\)).

The Two Main Types of Crowdsourcing

The AP CSP syllabus highlights two specific ways the "crowd" is used to solve problems:

1. Citizen Science

Citizen science is scientific research conducted, in whole or in part, by amateur or non-professional scientists. Computing innovations allow everyday people to help professional scientists by collecting or analyzing data using their own devices.

Example: A scientist might ask people all over the country to take photos of the stars in their backyard and upload them to a website. By combining thousands of photos, the scientist gets a much better map of the night sky than they could have created alone.

2. Distributed Problem Solving

Distributed problem solving occurs when a large, complex problem is broken down into smaller parts, and those parts are sent out to a crowd of people to solve. This can happen in two ways:
• Active: People manually solve small parts of the problem (like identifying objects in a photo).
• Passive: People's computers or devices work in the background to process data for a larger project.

Example: A mapping app uses "distributed" data by looking at the GPS location and speed of thousands of different drivers to determine where a traffic jam is happening in real-time.

Why Use Crowdsourcing?

Crowdsourcing is a powerful tool because it offers several benefits:

  • Speed: Problems that would take one person years to solve can be finished in weeks or days by a crowd.
  • Scale: You can collect data from thousands of geographic locations at the exact same time.
  • Cost: It is often much cheaper to ask for volunteers or small contributions than to hire a massive full-time staff.
  • New Knowledge: As mentioned in Practice \(5.B\), computing allows us to generate new knowledge from the data we gather through crowdsourcing.

Common Mistakes to Avoid

Mistake: Thinking Crowdsourcing only happens on social media.
Correction: While social media is a tool, crowdsourcing happens anywhere people contribute data—like review sites, open-source software projects, or scientific databases.

Mistake: Forgetting that Crowdsourcing can have "harmful" effects.
Correction: While Topic \(5.4\) focuses on the "what" and "how," remember from Topic \(5.1\) that every innovation has both beneficial and harmful effects. For example, crowdsourced data might accidentally include personally identifiable information (PII), which leads to privacy concerns (Topic \(5.6\)).

Quick Review: The Essentials

• Definition: Getting contributions from a "crowd" via the Internet.
• Citizen Science: Everyday people helping with scientific research.
• Distributed Problem Solving: Breaking big tasks into small ones for many people/devices.
• Requirement: It must be done via the Internet to reach a large enough scale for the AP definition.

Study Tip: If you see a question on the exam about a "large number of people" or "volunteers" providing data to a central system via the web, the answer is almost always Crowdsourcing!

Note: For more on the legalities of using crowdsourced work, see Topic 5.5: Legal and Ethical Concerns.