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What are Chatbots (+A Brief History of How They Evolved)

If you’re noticing that much of your customer service interactions are more automated, you’re not alone. The days of packed call centers have long been a thing of the past (and it’s not because of COVID-19).

Most customer service offices have substantially diminished their physical footprint by replacing call centers with live agents, who can communicate with multiple customers simultaneously, in addition to chatbots.

Through the advent of chatbots, businesses have successfully helped more customers with fewer employees while customers get the answers they need without spending time on-hold.

Over the last few years, higher education has undergone a similar transformation, where innovative schools are easing their administrative workload through the implementation of chatbots and live agents. Some may have heard of chatbots, but are unsure of their value and how they work.

This post will delve into the details of what chatbots are, how they work and how they can help the higher ed industry.

What is a Chatbot?

A chatbot is a program that mimics human conversation through spoken and written communication. Bots can converse with humans 24/7, and are programmed to respond to certain keywords or prompts.

They are also called intelligent virtual assistants, virtual customer assistants, conversational agents, or similar terms. They have varying levels of intelligence, from answering frequently asked questions to providing advanced features like personal shopping recommendations.

In higher education, chatbots can help students complete financial aid processes, sign up for classes, gain admissions information, and more. In this post, we’ll focus on chatbots in the context of higher education.

Why are Chatbots Valuable to Higher Education?

Today’s students are considered digital natives, which means they grew up with the internet, social media, and mobile devices. As a result, students expect to receive information at their wish.

Since students can do almost anything, from ordering pizza to furnishing an apartment, all from their mobile device, they simply do not want to deal with antiquated processes when it comes to higher education.

Universities and colleges traditionally waded through dense websites to find relevant information. A bot allows them to ask a question at any time, from anywhere.

Students are no longer reliant on traditional communication channels such as email or calling an administrative office to get the information they need. Instead, they prefer to text or chat, just as they have grown accustomed to interacting with customer service departments in other areas.

How do Chatbots Work?

Humans initiate a chatbot interaction by speaking or inputting text. Some chatbots are text-only and use some type of messaging service to analyze the input, find the appropriate response, and deliver that to the user.

Bots may have difficulty understanding the human’s request if the input doesn’t match the pre-programmed answers. As a result, more simplistic, rules-based bots may use a decision tree to provide relevant information almost instantly.

The disadvantage of this type of bot is that it’s only helpful for basic requests, such as frequently asked questions or relevant status updates, and may frustrate the user to the point of preferring to speak with a human.

For advanced information requests, artificial intelligence algorithms help plug the weaknesses of basic bots through national language technologies.

Natural Language Processing: This principle enables a bot to understand the context behind a user’s sentences, including sentiment and when something is singular as opposed to plural. It also allows it to reply correctly, even when the sentence is grammatically incorrect or has a spelling mistake.

Natural Language Understanding: Given that academia has its own lexicon, bots use this ability to understand what users are saying. For example, some students may refer to their first payment at an institution as a down payment rather than a deposit. The bot can learn that they are the same and still provide relevant information.

Natural language generation: Since bots don’t really understand English, they use this process to translate data points into content that users understand. Simply put, it provides the bot with the tools it needs to converse in sentences and paragraphs.

The History of Chatbots

The creation of robots and artificial intelligence dates back to 1950 when Alan Turing asked a question that led to a paper, known as the Turing Test. It may seem like chatbots have only been around for a few years, but they actually have a relatively long history.

The paper proposed a test to determine whether humanity could tell the difference between a human and machine. This question is still performed regularly today as a critical benchmark in understanding the capacity for bot performance.

Here is a list of other landmark events that helped define where bots are today.

ELIZA, 1966: Named after Eliza Doolittle in George Bernard Shaw’s Pygmalion, the first bot developed at MIT by Joseph Weizenbaum aimed to fool humans into thinking a psychotherapist was interviewing a patient. The project was ultimately successful in being the first machine to use natural language processing.

PARRY, 1972: Psychiatrist Kenneth Colby took ELIZA a step further by creating a more conversational chatbot, that allowed it to converse with ELIZA. PARRY was intended to represent a paranoid schizophrenic and had greater language capabilities compared to ELIZA.

JABBERWACKY, 1981-1988: British programmer Rollo Carpenter created the first chatbot with a goal of creating artificial intelligence capable of passing the Turing Test. The bot could emulate natural human chat while being interesting and entertaining.

Dr. Sbaitso and ALICE, 1991-1995: Dr. Sbaitso was another psychologist chatbot with a digital voice, powered by AI to show off an impressive range of digitized voices. It could ask questions similar to a therapist, such as “Why do you feel that way?” ALICE was a chatterbot that took the natural language processing ability of ELIZA to a new level.

Elbot and Smarterchild, 2000-2005: Elbot was the first chatbot to successfully use sarcasm and wit to converse with humans through AI. In 2008, it came close to successfully passing the Turing Test. Smarterchild was a bot for AOL Instant Messenger that offered personalized conversation and could offer information on movies, weather or current events.

IBM Watson, 2006-2009: Watson was designed as an AI chatbot meant to compete against humans on Jeopardy using natural language processing and machine learning. It is now arguably one of the smartest systems in the world with use cases in healthcare, weather forecasting, advertising, tax preparation and much more. Watson is used to reveal a variety of insights with a large amount of data.

Google, Siri, Alexa and Cortana, 2010-2015: Amazon, Apple, Google and Microsoft launched their first voice assistants, which allowed the user’s device of their choice (mobile, PC, tablet) to provide information to answer questions and make recommendations. Alexa was the first smart home speaker that enabled these capabilities, in addition to powering a variety of devices through a voice command.

Messaging Bots, 2016-present: Facebook launched its first messaging platform growing to over 300,000 active chatbots in 2018. It has since captured the imagination of industries like e-commerce, retail and higher education, with launching an artificially intelligent self-service chatbot to help students across the country access the answers they need.

The future of chatbots holds great promise, both for higher education and society at large. Between advances in technology, a change in student preferences and the COVID-19 pandemic, bots have become a necessity.

It’s not a stretch to state that in the not-too-distant future most of our customer service interactions will be carried out by a bot.

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