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:

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.

Why Keywords Do Not Cut It on Social Search

Most of the online search is keywords-based. Same in social domain, a vast number of analytical tools, networking platforms and mobile apps use keyword-based technologies as well.

There is a difference, of course, between traditional internet search and social search. The former finds websites. The latter finds conversations, messages, posts. Keyword-based internet search is doing a decent job for us for over 20 years. Keyword-based social search is not doing a decent job at all.

Consider a basic example: finding on Twitter who is interested in buying jeans. We can start by typing ‘jeans’ but that brings up too much noise. Maybe ‘need jeans’? Less noise but then we people who use expressions like ‘looking for jeans’ or ‘want jeans’ or shopping for jeans’. Not to mention those who use ‘denim’, or brand names. So we have to run multiple searches or create a complex search string using logical AND and OR and hope it works. Neither option is simple, or convenient, and certainly not efficient.

The above example highlights the major flaw with keyword search - it does not capture the meaning of social conversations, and therefore cannot be a reliable source of information about conversations.

It does not provide too much of correct information. And it does provide lots of incorrect information. But the biggest problem is that it has extremely limited potential for improvement.

So as long as we stick with keyword-based social search the results are destined to be limited.

Why, then, we stick with keyword-based search in social search? Simply because there is no good alternative. Until recently, that is.

The advanced semantic technologies capable of capturing the meaning, or intent, of conversations are now offering an exciting alternative.

I will discuss these technologies on my next blog.