Arize AI Helps Us Understand How AI Works Posted on : Sep 01 - 2020

As key functions in our society become more digitized, we come to rely on artificial intelligence (AI) to run these processes. While AI and its specialized forms such as machine learning (ML) are powerful tools, its practitioners generally lack insight into how these tools generate outputs. The lack of explainability and observability prevents AI and ML from being trusted tools in critical areas of human activity, such as getting approved for a loan or undergoing procedures to diagnose a disease. Fortunately, Jason Lopatecki and Aparna Dhinakaran understand the importance of explainability and observability of AI and ML in their prior professional experiences, creating Arize AI as the tool they never had. Arize AI is production-grade infrastructure tool used by developers to monitor, assess, understand how their deployed AI works. The San Francisco-based startup recently was a part of Y Combinator Summer 2019 batch.

Frederick Daso: What decisions are AIs deciding that affect people's lives? What is the nature of the problems stemming from these decisions that make AI the right tool to solve them?

Jason Lopatecki & Aparana Dhinakaran: There are trillions of decisions a day — and growing — made using AI that affects peoples' lives. AI influences:

• Whether you get a credit card or a loan;
• What stories you see in your news feed;
• What job applications you see — and whether someone sees your application;
• What advertisements you are bombarded with daily;
• How customer service responds to your call;
• And even whether you live or die given the use of machine learning in medical research and diagnosis.

The stakes are high, and the possibilities seem endless since AI can improve decisions nearly anywhere a large dataset exists. Wherever a business can save money, provide a better experience at scale, or automate a cumbersome process, they will likely use AI.

It's worth noting that many AI applications are mission-critical to businesses but mainly invisible to customers, who see the end-result in a given experience or product. View More