According to many experts, artificial intelligence (AI) is the most crucial technology of our time. However, the notion of artificial intelligence (AI) is not new. In reality, it has been in existence for about 75 years. We’ve seen repeated periods of AI winters during this time when interest and investment declined, followed by periods of AI springs when enthusiasm returned. The current AI spring is possibly the most fruitful development phase thus far, with maturity and advancement quickly growing.
While artificial intelligence is a topic of many discussions throughout the globe, you might wonder whether the machines have evolved far enough to grasp such conversations. Yes, in certain aspects, but in general, it’s more complex than anyone imagined. Let’s see it in the detail:
The extraordinary progress of narrow AI
Over the last decade, AI has affected our daily lives, whether recommending songs, translating languages, answering questions, carrying out activities by voice command, or dispatching the nearest Uber driver. Many of these activities are usually ignorant. The most significant developments and achievements have been made in narrow AI, that is, fields that focus on particular tasks, like:
- It can Outperform human radiologists in detecting cancer via a mammogram and decreasing false positives and false negatives.
- Narrow AI can Capture and analyze photos of car damage to automatically forecast repair costs for insurers.
- It can autonomously pick, pack, sort, and transport goods for fulfillment.
- Inspect the finished goods for quality utilizing smart cameras and AI-enabled quality control software at rates faster than humans are capable.
Things that are simple for humans are complex for computers
The benefits of narrow AI are reshaping the world in various ways. Meanwhile, more generalized AI (intelligence that encompasses human-like creative and associative thinking) has yet to produce comparable outcomes. Melanie Mitchell, a computer scientist and author- has explained this topic in her paper- why AI is harder than we think. She has mentioned that- looking out into the world and making sense of what we see, carrying on a conversation, walking along a crowded sidewalk without bumping into anyone—are the most challenging tasks for machines. In contrast, it is sometimes easier to have machines doing things that humans find incredibly complex- for example, solving complicated mathematical problems, mastering games like chess and Go, and translating words between hundreds of languages. These tasks have proven to be relatively convenient for machines.
Carrying on a conversation, according to Mitchell, is an example of what is easy for humans but challenging for AI. It turns out that understanding human language is perhaps a challenge to tackle in the artificial intelligence area. Even the brightest linguists are baffled as to why language operates the way it does. We cannot design machines that operationalize authentic human discourse unless we have a fully developed theory of language (which we do not) that allows computerized machines to understand our discussions. That is why we can’t communicate with computers the same way we would with another human. When you ask a question or send a command to a voice assistant, it is often necessary to dumb down and slow down the discussion, making it more like speaking to a toddler rather than an adult.
Conversational AI
It is a collection of advanced AI technology that detects and comprehends human language in different languages and utilizes this understanding to optimize and analyze conversations across various channels.
Understandable conversations for AI
While recent advancements in the field are still far from a generic AI capable of mimicking human intellect, domain-specific conversational AI is making enormous strides in sophistication and is generating transformative benefits for contact center use cases. Specialized or domain-specific conversational AI, as a focused AI application, integrates a combination of advanced AI technologies to interpret, optimize, and automate human discussions and actions inside a given environment.
The contact center is one area where techniques like reinforcement learning and machine learning have advanced AI skills to understand and optimize human-to-human communication within contact centers by utilizing millions of chats. Moreover, narrowing the domain expertise to a specific industry increases AI accuracy and understanding. AI technology, for example, might be programmed to grasp a distinct language to a particular industry, such as wealth management. Automation of compliance with restrictive laws is one of the many use cases for conversational AI in this field. A conversational AI platform can detect when an order is being taken and whether the agent taking the order is following disclosure regulations.
Conversational AI in the contact center has a bright future
When domain-specific conversational AI abilities become more robust and intelligent, they have the potential to change the consumer and agent experience. Contact centers may achieve desired objectives like improved customer satisfaction and Net Promoter Score, increased sales effectiveness and revenue, decreased costs and improved agent efficiency, and much more by supplementing people with AI and automation.
Author Bio:
Deepali Daiya is a communication expert who excels in understanding customer needs. She writes powerful sales scripts and articles with very high conversion rates. Currently, she is associated with Sage Software Solutions, a leading distributor of high-quality ERP and CRM systems to small and mid-sized businesses in India.
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