Managing the AI (Automated Intelligence): Spotting the “unknown unknowns”
In our increasingly digital world, more and more companies are undergoing digital transformation, opting for ever more autonomous AI-driven apps.
AI algorithms
Develop a way to know when AI algorithms work and when they don’t. While it may not be critical if a movie recommendation is not that accurate, the results can be devastating if an algorithm performs poorly in an autonomous car or a medical app.
AI output
Unlike classical software, AI-based solutions provide predictions. That means that the correct answer is a matter of statistics and accuracy–as opposed to being right or wrong. It might be acceptable in some cases to have an incorrect answer from time to time, but it’s vital that we are able to understand and control the extent of a mistake and the circumstances under which it could occur.
AI deep test
Create tests to simulate real-life scenarios and improve the AI output. We’re working on automating testing, debugging, and improving AI models across a wide range of scenarios. In the world of AI, tests give us a record of the data and the predictions they are expected to output.