When software is developed or enhanced, distinct kinds of testing are performed to ensure the desired results are achieved.

Diverse kinds of testing include Functional, Performance, Security, Automation, System Integration, System Testing, and so on. There is also an especially important test known as Crowd Testing. 

What is Crowd testing?

Crowdsource testing is conducted by a substantial number of professional Quality Assurance analysts or beta testers who perform testing using different devices, environments, and scenarios, which could be real or wild, with the goal of uncovering critical issues and launching stable software.

There have been many discussions on the need for crowd-testing when different forms of testing exist. Crowd testing uncovers defects that have not been identified in normal testing processes because it is tested under various real-world scenarios.

There exist multiple testing approaches like simulators, emulators, real devices, cloud-based testing, and Crowdsource testing, but all the aforementioned cannot be implemented in all conditions. Crowd Source Testing Team is a consistent team with greater skill sets and capabilities that overpowers the in-house skilled testing talents.

Crowdsourcing making AI smarter:

Individuals and large companies collect data and annotations from various sources, such as people, and the medium used is the Internet. This collected data is used to train the Learning Models fed into various AI tools. This enormous, diversified data is less likely to be false positive and has more data coverage for all scenarios since it comes from the real world.

E.g.: Systems like Speech Datasets where there could be a need for a special language spoken in a traditional accent.  

One of the leaders in speech datasets is Defined.AI, which uses tools, models, and datasets driven by AI. Defined.AI, located in Seattle, USA, is built on the Neevo platform and recently launched the Neevo app for Android and iOS. It was able to crowdsource a workforce from more than 70 countries, speaking over 50+ languages and plus 500,000 global contributors.

Advantages of Crowd Testing

Main advantage is to uncover hidden bugs and second in line it saves time and cost. Example there is a QA team or skilled talents whose billing rate is more which costs heavy on the project. But cost significantly lowers when similar skill sets and talents join on digital platforms. In addition, if the talents are guided and directed correctly, it reduces time and organization effort.

The next important advantage is procuring data quickly and inexpensively.

As quoted earlier, crowdsource testing has low data privacy. For example, multiple testers are using multiple accounts to finish the allocated work or deliver a low-quality product. AI can contribute to analyzing the patterns of a person performing tasks and identifying fraudulent activities. In addition, Machine language algorithms also aid in discovering anomalous activities.

Risks with Crowdsource Testing:

Crowdsourced testing, while offering benefits in terms of cost and speed, comes with its own set of risks. These include reduced data privacy and security, as sensitive information may be exposed to a wide array of contributors. Scaling challenges also emerge, as managing a large crowd of testers can be complex and unwieldy. Additionally, there’s the issue of inconsistent annotation; relying on a global pool of contributors can result in inaccuracies and disparities in annotations due to varying levels of skill and expertise in the required domain or task.

Conclusion:

With the large volume of data, Crowdsourcing plays a pivotal role in making AI smarter. It will continue to evolve and enhance with AI and ML tools.

Author Profile:

Arpita Soni has been influential in Web Automation and evolved as a Subject Matter Expert in emerging technologies like Artificial Intelligence [AI], Machine Learning [ML], and Deep Learning [DL] in Information Technology. At the core, she is dedicated and focused on continuous discoveries, improvisations and innovations.

An admired mentor and pacemaker, Arpita has contributed to a variety of publications that serve as important resources for professionals.

Arpita’s membership in prestigious bodies like IEEE depicts her professional expertise and active engagement in fostering a collaborative ecosystem for technological advancement. She has strategic leadership and a passion for mentorship,

Arpita Soni is an outstanding figure in driving the evolution of efficient, innovative digital solutions.

Published By: Aize Perez