July 26, 2019
Trends in Insurance | How Can We Prevent Fraud?
Across the board, insurers found they were experiencing a huge…
The promise of artificial intelligence is too attractive to ignore. Ideas range from discerning trends we are currently unable to see and optimizing decision making to hundreds of other ways AI could make our lives easier is too tempting to not entertain. Artificial intelligence is capable of solving complex problems from housing to disease – its potential is truly limitless. Fears from skeptics and naysayers that are worried about job displacement to a robotic apocalypse are not unfounded.
While fears persist about AI growing out of control of humans, that reality is not yet upon us. We are still viewing AI’s infancy, with machine learning advancements happening every day. Just like every other infant – training is required.
Children are also an example of independent intelligence capable of more than we understand. However, they also need to be trained to learn language, relationships, and a long list of how not to do things. We must teach children cause and effect, which one is the dog, and which is the cat. Then which one is our dog and our cat. And that those are different than the neighbors cat on so on.
So while AI promises us a better tomorrow, we are in charge of teaching it today. Artificial intelligence can also be described as a blank slate – it needs context in order to learn how to interact with almost anything. Based on our years of learning and experience, for example, listening to audio and deciphering what is relevant, or determining someone’s intent is still a very human endeavor. Here at Pindrop, our solutions analyze audio, but still need constant teaching. Our AI deems certain conversations as risky, but before it is confirmed with fraudulent intent, the customer are able to listen in and verify. Once this intervention has occurred, the data is sent back to be incorporated in machine learning. This human intervention and machine learning data is at the core of teaching our machines to be suspicious of callers.