Simulating Human Conversations through AI

Conversational AI simplifies the request into essentials

The advent of technology has resulted in the development of several products that have automated manual tasks, making them easier to use, helping build profitable businesses, and making services accessible to all. One such product is the use of Artificial Intelligence to simulate human conversations. Also called Conversational AI, it's a subfield of Artificial Intelligence that deploys Machine Learning to make a conversation, which feels like a talk between humans as it is natural and personalized. The product has garnered worldwide attention in its nascent stage because of its engagement capabilities and impressive pace of interaction. Conversational AI simplifies the request into its essentials to identify people, actions, and objects.

How it works

There is a two-way interaction between a computer and a human because of Natural Language Processing (NLP), which leads to an automated conversation through messaging apps, voice assistants, and chatbots. Nowadays, Conversational AI is being adopted by industries across verticals and integrated into their platforms to provide 24/7 support to users without human agents. The origin of Conversational AI goes back to menus of options for users like 'cancel my order'. But today, we have Conversational AI answering everything from messages to calls.

The wide-ranging tool enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision-making. AI systems can learn and adapt as they make decisions. For example, ConveGenius Edu, a social edtech enterprise adopted the chatbot-based model of learning by integrating WhatsApp APIs into their solution. This technology made the teaching & learning process so easy by eliminating the dependency on concrete infrastructure. The conversational AI built into the platform helps to push each student up personalized pathways of learning. The AI-led algorithm is designed to connect students with the most relevant content. Further, teachers have their own version of chatbots which gives them access to student data. This empowers them to map and shape the learning trajectories of their students while assessing their individual learning outcomes.

In the automobile sector, semi-autonomous vehicles have tools to inform drivers and vehicles about upcoming congestion, potholes, highway construction, or other possible traffic impediments. Cars can take advantage of the experience of other vehicles on the road without human involvement, and the entire corpus of their achieved "experience" is immediately and fully transferable to other similarly configured vehicles.

Another prominent example is in stock exchanges, where high-frequency trading by machines has replaced much of human decision-making. People submit buy and sell orders, and computers match them in the blink of an eye without human intervention. Machines can spot trading inefficiencies or market differentials on a microscopic scale and execute trades that make money according to investor instructions.

Advantages and Disadvantages

As every bright side has a darker version, simulation of human conversation through AI also has some disadvantages like high cost of creation, unemployment, interaction lacking emotion, and out-of-the-box thinking. However, AI interaction tools are trained with a data set. The bigger the data set, the better the services. Thus, if you can train your device to exhibit emotions, it can simulate the same. But it is also a challenge to provide the machines with quality data and well-labeled to identify them quickly. Another challenge is explaining ability. When we're given the rationale behind the decision, it's easier for us to assess to what extent we can trust the model. Similarly, AI-based interactions are biased as they make decisions based on the available data only. It is also challenging to identify where something went wrong after an AI system makes a mistake.

Future Outlook

AI systems will further improve the delivery of chatbots, virtual agents, digital assistants, etc., in the future with more advances. As per Valuates Reports, the global Conversational AI market will reach USD 32.62 Billion by 2030 at a Compound Annual Growth Rate (CAGR) of 20% between 2021 and 2030. The rise in demand for AI-based human interactions is driving the growth trend. Conversational AI is reducing the scope of human error. Many of its benefits include taking risks, 24X7 availability, helping with repetitive jobs, digital assistance, quicker decision making, etc.

Summing up

Nevertheless, at present, Artificial Intelligence is one of the most promising new technologies shaping the future. AI is disrupting business today, and it stands tall to make the most significant impact. It is improving customer communications, resulting in saving costs. It is also enabling strengthening brand loyalty along with personalization. AI is everywhere. AI is here to stay.

Author

Jairaj Bhattacharya, Co-founder and MD of ConveGenius