# human-based computation game

> video game genre

**Wikidata**: [Q1493064](https://www.wikidata.org/wiki/Q1493064)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Human-based_computation_game)  
**Source**: https://4ort.xyz/entity/human-based-computation-game

## Summary
A **human-based computation game** is a video game genre designed to harness human intelligence for computational tasks, such as data labeling or problem-solving, by engaging players in enjoyable gameplay. It is a subset of **human-based computation**, a computer science technique that leverages human cognitive abilities to solve complex problems that machines struggle with.

## Key Facts
- **Genre of video games** that use gameplay to perform computational tasks.
- **Subclass of human-based computation**, a broader computer science technique.
- Also known as **game with a purpose (GWAP)** or **purposeful game**.
- **Wikipedia articles** exist in English, German, Italian, and Portuguese.
- **Wikidata description**: "video game genre."
- **Freebase ID**: /m/04gvjx9.
- **Main category on Wikipedia**: Category:Human-based computation games.

## FAQs
### Q: What is the difference between human-based computation games and regular video games?
A: Unlike traditional video games, human-based computation games are designed to solve computational problems by engaging players in tasks that contribute to larger datasets or research efforts. The gameplay is often secondary to the data collection or problem-solving purpose.

### Q: Who created the concept of human-based computation games?
A: The concept was developed as part of the broader field of human-based computation, with notable examples like the ESP Game (2004), which used players to label images for machine learning.

### Q: Are human-based computation games still used today?
A: Yes, they remain relevant in fields like artificial intelligence, data annotation, and crowdsourcing, where human input is essential for tasks machines cannot perform efficiently.

### Q: What are some examples of human-based computation games?
A: Examples include the ESP Game (for image labeling), FoldIt (for protein folding), and Peekaboom (for object recognition). These games turn human contributions into valuable computational outputs.

### Q: How do human-based computation games differ from traditional crowdsourcing?
A: While both leverage human labor, human-based computation games incorporate gameplay mechanics to make tasks more engaging and enjoyable, increasing participation and data quality compared to traditional crowdsourcing methods.

## Why It Matters
Human-based computation games bridge the gap between entertainment and computational problem-solving. By embedding tasks within engaging gameplay, they incentivize human participation in ways that traditional crowdsourcing cannot. This approach has been particularly valuable in fields like artificial intelligence, where large datasets are needed for training models. Games like ESP Game demonstrated that humans could efficiently label images, contributing to advancements in machine learning. Additionally, these games foster a sense of community and purpose, motivating players to contribute meaningfully. Their impact lies in their ability to scale human intelligence for complex problems that require creativity, pattern recognition, or subjective judgment—areas where machines still fall short.

## Notable For
- **Innovative problem-solving**: Pioneered the use of gameplay to solve computational challenges.
- **AI training data**: Contributed to early datasets for machine learning, such as image labeling.
- **Engagement-driven crowdsourcing**: Set a precedent for making human labor more enjoyable and effective.
- **Interdisciplinary approach**: Combines psychology, computer science, and game design.
- **Wikipedia recognition**: Documented in multiple languages, indicating its academic and cultural relevance.

## Body
### Origins and Foundations
Human-based computation games emerged from the need to solve problems that required human cognition, such as image recognition or data labeling. The first notable example was the **ESP Game (2004)**, which asked players to guess the same word for an image to earn points. This simple mechanic generated valuable labeled image data for Google’s image search.

### Key Characteristics
These games typically:
- **Embed computational tasks** within gameplay (e.g., labeling images, solving puzzles).
- **Reward players** with points, leaderboards, or social recognition.
- **Scale human effort** by distributing tasks across a large player base.

### Applications
Beyond entertainment, human-based computation games have been used in:
- **Protein folding** (e.g., FoldIt).
- **Object recognition** (e.g., Peekaboom).
- **Data annotation** for AI training.

### Legacy
The genre proved that human engagement could be leveraged for computational tasks, influencing modern crowdsourcing platforms and AI research. Its success lies in its ability to make tedious tasks enjoyable, ensuring high-quality contributions from a motivated workforce.

### Wikipedia and Documentation
The concept is documented in **Wikipedia articles** across four languages, reflecting its academic and public interest. The **Wikidata entry** classifies it as a **video game genre** and links it to broader categories like human-based computation.