A Beginner’s Guide to Natural Language Processing
Natural Language Processing better known as ‘NLP’, is hot property as far as technology goes in 2020 and you’re going to hear a great deal about it in the coming months in major tech hubs including Dublin. Powered by the wizardry of Artificial Intelligence (AI), Natural Language Processing simply put – focuses upon the use of computers in analyzing and processing human (natural) languages. Human language, as you might expect, is an important source of vast amounts of data. Texts, emails, trolls in the comment box of your favorite online paper – we’re content producing machines. And, if I think back to Psychology lectures in college – we’re simply masters in the art of ‘infinite generativity’ i.e. we can produce language almost infinitely. That capability, and this mass of data makes it increasingly necessary for computers and other smart devices to be enabled to process human language in order to keep up with us! NLP is a fast-evolving space and use cases are growing at a staggering rate. So what does NLP look like in a practical sense? Let’s go deeper!
Day to day & innovation
NLP is currently in use across many different industries and through a range of technologies that we interact with daily. NLP is the technology behind the development and deployment of virtual assistants, chatbots, voice input features in search engines, voice analysis, and security protocols etc. We are already familiar with NLP; spell-checkers, voice assistants, translators, etc. are just some of the ways through you’ve probably already used NLP today! But big & deep technology always have loftier ambitions….
For example, in the health sector, interactive virtual nurses are currently being used to interact with patients on first-line inquiries. This alone is projected to save the health sector around $20 billion yearly and enable their human contemporaries to attend to other matters.
In a related development, the availability of Electronic Health Records or EHRs, has created a situation where unstructured data is threatening to overwhelm digital health management systems. NLP steps in here to give the ESR a breather by capturing unstructured data and converting it into organized data. Thus, clinical documentation is made more effective.
NLP in your pocket
In the banking and finance industry, NLP is driving a revolutionary approach to how financial institutions calculate the credit rating of individuals. Once consent is given, NLP algorithms are able to track the financial and social habits of the user and from there give a fair credit rating or help customer to understand their spending habits. By doing this for thousands of customers at a time, the act of simply processing language is helping financial institutions stay ahead. Revolut, N26, Monzo, traditional banks and many other Fintech groups are building large data teams to leverage such application at scale. There are ethical and data privacy considerations with all of these developments – but that’s another article to come from yours truly!
NLP as a consumer or candidate
NLP is also deployed in chatbots and advertising. Recent NLP algorithms in chatbots make human-chatbot interaction seem so natural, that it can be hard to decipher that there is no human on the other side just try pausing your Amazon Prime, seriously! These applications help businesses manage the scale of human capital required particularly if they are in the consumer goods space or online retail (one to many). For consumers – these applications also decrease waiting times.
In the recruitment & HR function- NLP is a particularly useful technology particularly where there are volume hiring campaigns – graduates, internships, public service appointments etc. By creating specific job descriptions and analyzing answers, NLP helps staff to eliminate irrelevant applications and thin down the qualified candidates so that the next step in the process is reached faster and more seamlessly.
Of course, there are some exceptionally advanced applications of NLP out there and I’m fortunately involved in hiring for many of them. If you’re interested in learning more, you’re a candidate in NLP or you’re a business owner or tech leader looking to augment human behavior with this technology – drop a note & I’ll be delighted to speak further!
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