AI has been the hottest and most buzzworthy topic of the past few years, capturing the imagination and curiosity of people worldwide. By now, many mobile applications and software have AI embedded within their systems, yet the secret process to getting a top-tier AI product to the market is still not widely known. Whether you are developing an AI app for healthcare, autonomous vehicles, or any other domain, understanding how to effectively test and validate its capabilities is essential.
What exactly does “testing AI” mean? Pooja, the operation head of Valere’s Indian team at Valere Labs, was gracious enough to share the secrets of testing AI. With 17 years of experience in the tech and banking sectors working for the most premier financial powerhouses around the world, Pooja has overseen the testing of many AI products. Here in this guide, Pooja will lay out the ins and outs of AI testing. Making all those uncertainties and questions about AI keeping you up at night a thing of the past.
What does it mean to test an AI?
By conducting comprehensive testing, you can ensure the reliability and performance of your AI app. Testing AI involves systematically assessing its capabilities, performance, and behavior under various conditions. This includes evaluating its ability to complete tasks accurately, efficiently, and reliably. Testing also plays a crucial role in uncovering potential issues such as biases, bugs, or security vulnerabilities. Pooja explains that this is the ONLY way to ensure that your AI app isn’t a failure and can reach its maximum potential.
Why is it important to test AI?
Testing AI is essential for several reasons. First, it ensures accuracy by verifying that AI models provide precise and reliable results, particularly in critical applications like healthcare or autonomous vehicles. Second, testing helps identify and mitigate biases in AI systems, promoting fairness and reducing discriminatory outcomes. Pooja mentions keeping biases under control in AI models also ensures that the technology remains trustworthy and its decisions are more universally acceptable. Third, rigorous testing enhances the robustness of AI systems, enabling them to perform well under diverse and real-world conditions. Finally, testing is crucial for AI safety, as it helps prevent unintended behaviors that may pose safety concerns.
In a world where competition is fierce, everyone strives to be the best. However, achieving excellence in AI is no easy feat. Conducting rigorous testing before launching is not just a best practice; it is crucial for survival in an artificially intelligent world.
How to test AI?
When testing AI, there are several phases and methods involved. Here Pooja will share 6 different testing phases that are the mere beginnings of a long laundry list of things to do, to ensure the AI product receives the best testing possible:
- Unit Testing: This phase assesses individual components or algorithms within the AI system to ensure they function correctly. For example, testing the accuracy of a sentiment analysis algorithm by providing various text inputs and verifying the expected outputs.
- Integration Testing: Here, the focus is on evaluating how different AI components work together within the system. For instance, testing the integration of a speech recognition module with a natural language processing module to ensure seamless communication between the two.
- User Testing: This phase involves collecting feedback from end-users in real-world scenarios to understand how the AI performs and make necessary improvements. For example, conducting usability tests with a group of users to evaluate the effectiveness of a voice-controlled virtual assistant.
- Stress Testing: Stress testing pushes AI products to their limits to identify vulnerabilities or performance bottlenecks. For instance, subjecting an image recognition system to a large dataset containing various challenging images to assess its robustness and accuracy under demanding conditions.
- Data Validation: Data validation involves creating extensive datasets to verify the quality and integrity of inputted data, preventing data-related issues. For example, validating the integrity of a dataset used for training a machine learning model by checking for missing or inconsistent data.
- Security Testing: This phase assesses AI systems for vulnerabilities and ensures they are protected against virus attacks. For instance, conducting penetration testing to identify potential security flaws in an AI-powered cybersecurity system.
Continuous monitoring is also necessary to detect and address issues as they arise in AI systems deployed in production. By continuously testing and refining AI systems throughout their development and deployment lifecycle, we can ensure their effectiveness, safety, and ethical compliance.
Remember, these testing phases are not exhaustive, and the specific methods employed may vary depending on the nature of the AI application and its intended use. The goal is to optimize the performance, reliability, and usability of AI systems to deliver exceptional user experiences.
AthesAI
One of the projects that saw a rigorous phase of AI testing is Valere’s latest app, Athes. AthesAI is a cutting-edge mobile application that offers a safe and secure space for athletes to connect and learn. It is specifically designed for the young, competitive Gen Z athletes across the globe, providing curated sports content to elevate athletic performance at every stage of their journey. Athes is the most intelligent AI trainer for sports that knows how to engage with athletes in their youth. AthesAI provides engaging and personalized content content to enhance performance. Using machine learning, Valere created AthesAI which is able to optimize the feed so users get the best sports training without the fluff.
Pooja recalled that testing the AthesAI product was a thoughtful and rigorous process. During the testing phase of the AthesAI product, testers focused on three key areas to ensure the app’s perfection. First, they meticulously checked the algorithm logic for fetching videos, ensuring that the process was efficient and accurate. Second, they implemented various scenarios to comprehensively evaluate the performance of the video fetching feature, considering different user interactions and potential challenges. Lastly, the team paid close attention to AI-based cropping, making sure that large videos could be easily digested by users.
One of the main focuses of the Valere testing team was to ensure the accuracy and reliability of the AI cropping feature in AthesAI. This involved fine-tuning the algorithm to target specific skills in various sports, such as soccer, basketball, and lacrosse. By prioritizing this aspect of the app, Valere aimed to provide users with the most relevant and helpful training videos for their chosen sport.
Work With Valere
If you have an idea, even if it’s just on the drawing board, come share your thoughts. Valere can be your trusted partner in creating meaningful, cutting-edge AI solutions.
To experience the power of AI in your own application and achieve top-tier results, collaborate with Valere. With Valere’s expertise in testing and validating AI products, it ensures the reliability, performance, and safety of your app. Contact us today to unlock the full potential of AI and deliver exceptional user experiences.
Valere is an award-winning digital transformation, innovation, and software development company. As an expert-vetted, top 1% agency on Upwork, Valere has re-invented the way software design and development agencies operate — mitigating issues related to communication and process inefficiencies while partnering with clients to architect the right solution for the right problem.
Valere utilizes emerging technology in machine learning (ML) and artificial intelligence (AI) to enable startups and enterprise businesses alike to execute, launch, and scale their vision, transform organizations, and build something meaningful.
Valere has built over 300 successfully launched applications –ranging from startups to Fortune 500 companies! Valere has experience developing for both consumer and B2B audiences across a myriad of verticals such as healthcare, finance, sports, fitness, education, and more!
Valere has a successful track record of building applications that have yielded millions in revenue, downloads, and Venture Capital — while also getting apps featured by the New York Times, Apple App Store top featured apps, TechRadar and Google Play Store top featured apps!
The Valere team consists of expert engineers, project managers, designers, and quality assurance specialists, with offices in the United States, India, Croatia, Peru, and Uruguay.
Schedule a call with us today to learn how we can help your team create the perfect software or application that can Accelerate Your Business Goals!
