How Algorithms Can Predict Our Intentions Faster Than We CanEvery trace we leave online allows NLP to track and predict our future decisions.
Opinions expressed by Entrepreneur contributors are their own.
The speed at which technology is advancing means that it's impacting more and more people from across the world. Better yet, it's doing it without people even knowing it. Artificial Intelligence (AI) and Natural Language Processing (NLP) can gather data from anywhere online where we leave a mark. This includes our social media posts, our email, and even any small comments we leave on blog posts. Every trace we leave online allows NLP to track and predict our future decisions.
This article highlight how NLP can impact our day-to-day lives with the use of case studies.
Target sends a 16-year old girl pregnancy ads.
In 2012 Target, a company that owns and operates general merchandise stores,realized a 16-year old customer was pregnantbefore her father did. Based on the girl's shopping history, Target started sending her coupons for baby clothes and cribs. Her father complained to Target that his 16-year-old daughter had no need for those products. Later, he found out Target was right and he was going to be a grandfather.
The reality is, every time we shop, whether online or in a store, we leave a pattern that brands can then use to send targeted advertising and coupons. NLP can tell us about more than just our shopping behaviors. These algorithms are also able to predict our intentions and thoughts. Moreover, they can affect the decisions we make.
Related:This Technology Can Help Leaders Better Understand Their Employees
Social media to predict the future.
Today, there are dozens of reports that say that social media is able to predict the future. And, thanks to NLP, this could be more than hearsay. Take the Hillary Clinton vs. Donald Trump presidential election, for example.
Paul Nemirovsky, CEO and cofounder ofdMetrics, an MIT startup that analyses unstructured text, describes how his firm's technology was used to forecast the outcome of Brett Kavanaugh's confirmation hearings. "A member of our marketing team spent two hours teaching our AI how to look at an online comment and decide if the posted expresses pro- or anti-Kavanaugh views. Once our AI learned the concept of supporting/opposing a political candidate, it read millions of comments from over 50,000 social networks, forums and blogs. Surprisingly, we saw that a significant majority of the online commentators were strongly in favor of Kavanaugh's confirmation. This insight was later confirmed by the events on the ground."
The implications of this are wider than any political battle. In the future each of us, armed with the right AI, will be able to forecast the right outcome. This means better investment decisions, improved marketing messaging, higher customer satisfaction, and deeper insights on any topic of your choosing.
Related:机L如何earning Can Create a More Meritocratic, Less Biased Job Market
So, what is NLP and how does it actually work?
There are millions of ways for us to share our intentions, opinions, and beliefs with words. The problem is that one person could express themselves in a completely different way to another. With this in mind, it's impossible for a rule-based machine to understand what we say. This is where technology has always failed to understand the human language -- until now.
Natural Language Processing, or NLP, is a neuro-network that essentially teaches itself the way we say things. By being exposed to different conversational experiences, the machine learns. Simply put, once you tell the machine what each sentence means, it records each meaning in order to process it in the future. By processing this information, it learns the skills to better understand our intentions than we do.
David, CEO ofZensoft说,“我们的NLP已经可以预测未来elections as well as more personal details about our day-to-day lives. With this in mind, we have had strong demand for integrations of NLP technology into a wide variety of industrial applications. Today, NLP is changing industries from oil and gas, legal, to FinTech."
