DAISY ZHUO: At Interpretable AI, we deliver state-of-the-art analytic solutions that are not black boxes. My name is Daisy Zhuo. I'm a co-founding partner together with MIT Professor, Dimitris Bertsimas, and Dr. Jack Dunn.
Well, we all know about the great promise of self-driving cars. But the unfortunate fact is fatal accidents do happen. You just saw one from the Uber crash last year. So when that happens, how do we know who's at fault? Who should be held accountable? Can society really tolerate not understanding that?
Another example in admissions. Harvard, just down the road, is involved with a lawsuit related to their admissions process. Well, if a student is denied admissions to the school, is it sufficient to just tell them, mom and dad, that an algorithm made that decision, without any explanation or proof that the method is bias-free? Interpretability matters. And for that reason, many regulators, including GDPR, are not mandating all AI systems to be held accountable the same way that human decision makers are.
Interpretable AI addresses this issue head-on. We build interpretable solutions to your hard problems. Our solutions leverage proprietary software modules, each based on years of research from MIT AI.
With these modules as the building block, we now build solutions that achieve state-of-the-art performance but remain completely understandable and fully transparent to everyone at your organization. These modules also cover the entire spectrum of the data analytics process, from data cleaning to predictions to decision making.
The technology has very broad applications with current customers in many industries. Just to name a few, we have worked with major hospitals, including Massachusetts General, to build a very accurate surgical risk predictor that doctors there are using every day. We're working with a cybersecurity company that we delivered a highly-accurate, real-time malware detection algorithm that they can understand the nature of the latest attack.
With major car manufacturing companies, we help them to identify machine failure modes, make much better predictions, and make their predictive maintenance system much more effective. Many other applications in retail, banking, insurance, pharmaceutical, just to name a few. We're looking for additional partners to build and improve the trust in your data-driven decision making. Please come talk to us at lunch. Thank you.