AI unmasked: Have chatbots failed?

sasha uritsky

Oct 28, 2019

It is becoming increasingly popular to say that chatbots have failed and are overhyped.

While it is true that in many cases expectations from chatbots significantly exceed the results on the ground, the anticipation of chatbots’ demise are somewhat premature.

One of the main problems for chatbots is that the market is inundated with low quality solution providers who deliver low quality results. This happened because conversational AI seems to have low entry barriers. Unlike other recent technological darlings such as space technology or renewable energy, conversational AI is purely software and therefore does not require vast sums of initial investment.

What this approach is missing however, is that conversational AI, in addition to being a software, also requires an accurate understanding of how language works. And there is a limited number of people in the world that do have such understanding.

When conversational AI is delivered by AI experts who understand the way human language works, the results are good and convincing, just as how you would expect them to be.

Suffering from unsatisfactory product quality is a common problem for many new and emerging industries. The rules of the market dictate that most of the low quality players will eventually disappear. Poorly created chatbots will therefore not be around for too long.

See how a chatbot will help your businessnmodes.com

Interested in reading more? Check out our other blogs:

When Big Data is not so big anymore

We are inundated with information. There is so much information around us they coined a special term - Big Data. To emphasize the sheer size of it.

It is, of course, a problem - to deal with a large amount of data. Various solutions have been created to address it efficiently.

At nmodes we developed a semantic technology that accurately filters relevant conversations. We applied it to social networks, particularly Twitter. Twitter is a poster child of Big Data. They have 500 million conversations every day. A staggering number. And yet, we found that for many topics, when they are narrowed down and accurately filtered, there are not that many relevant conversations after all.

No more than 5 people are looking for CRM solutions on an average day on Twitter. Even less - two per day on average - are asking for new web hosting providers explicitly, although many more are complaining about their existing providers (which might or might not suggest they are ready to switch or looking for a new option).

We often have businesses coming to us asking to find relevant conversations and expecting a large number of results. This is what Big Data is supposed to deliver, they assume. Such expectation is likely a product of our ‘keyword search dependency’. Indeed, when we run a keyword search on Twitter, or search engines, or anywhere we get a long list of results. The fact that most of them (up to 98% in many cases) are irrelevant is often lost in the visual illusion of having this long, seemingly endless, list in front of our eyes.

With the quality solutions that accurately deliver only relevant results we experience, for the first time, a situation when there are no longer big lists of random results. Only several relevant ones.

This is so much more efficient. It saves time, increases productivity, clarifies the picture, and makes Big Data manageable.

Time for businesses to embrace the new approach.

Abundance of Information Often is a Liability

A massive change has occurred in the world during the last ten to twenty years. Until recently and throughout the history of mankind information was hard to access. Obtaining and sharing information was either a laborious process or impossible, and the underlying assumption was that information can never be enough.

Today, of course, we have the opposite picture. Not only information is easily available, it keeps pouring in from a growing number of sources, and we continuously find ourselves in situations when there is more information than we want or able to process.

A major task we, as species, are facing is therefore how to reduce or filter out relevant information. It is, to repeat, in direct opposition to the task we’ve been accustomed to during all previous centuries, which was how to obtain information.

Since this change took place only recently, within a lifetime of one generation, we didn’t have time to develop efficient set of procedures to address the new problem. But the work has started and will only accelerate with time.