Sachin Dixit's Blog

So , 2016 was year of chatbots . See the graphic at the end (its big image )and we see so many of the mainstream companies having built their bots . A github repo search will reveal similar story.The buzz that chatbots are creating is huge .So much so that people are claiming that chatbots will kill websites and mobile apps soon .We even notice that similar buzz was created a decade ago when mobile apps and app stores became mainstream .The mobile app wave was also looked at but incredulity so it is natural to be more welcoming towards chatbots wave .But the similarity does not hold beyond the English sentence you just read.

The move from website to mobile was actually reshaping of the form factor of the computing device .It is but natural ,albeit in hindsight ,that the content and its delivery fits itself into the new form.In the mobile wave also , the mobile and the app , were used interchangeably .While the mobile represents the shift , the app merely represents engagement .This difference is vital to analyzing the chatbot buzz .

Matt Schlicht,of the Chatbot Magazine defines,“A chatbot is a service powered by rules that a user interacts with using a chat interface. The service can be any number of things, ranging from form to function and live in any major chat product” . One might agree with this definition as is or diff with it in parts .While chatting itself is not a new paradigm nor is the concept of a daemon processing accomplishing the task , it is the combination of a always running agent , the bot facilitating the chat.The daemon could assigning your chat requests to human beings ,in a typical support center scenario .It might be reading your sentences and applying some pattern rules to serve reconfigured response .And because the state of the commoditized art allows us to program interpret ,human sentences (either typed or spoken), the so called NLP engine can be plugged into the chat bot to enhance the precision to the intent inference .

Most of the NLP styled chatbot guides mention NLP and intent-action mapping in the same breath ,but this is false connection .Intent-action mapping is what it is ,whether the inference is made via NLP,regex or rulesets. One might also throw machine learning in the stack to further enhance the inference via correlation and other techniques .Well that’s the short summary of what we get to read in the chat bot buzz as the first thing. What goes missing many times is the true nature of the chatbot for the end user , i.e. the conversational quality .

It is this conversational quality of the interaction , that needs deeper scrutiny ,because it represents an alternative to the laid out quality of our interfaces .

Its fine to say that Language is the most natural interface humans understand, and that’s the interface that bots use.but to miss that human language has an intent-explain-infer-confirm cycle embedded into it .

This model is very powerful the “range” of the expression is huge , like asking for a qualified advice amidst multiple factors .But it is very lengthy when the expressions are straight forward .

A typical chatbot sample told to us will be either a flightbooking bot, a billpay bot or an e-commerce bot.All these interactions are well modeled to human mind and the laidout-selection model fits better there .Infact it is an liberal model (read open) for both the parties to explore more options alongside the intended interaction.
Where as a personal assistant that can suggest a song based on the whether condition,travel duration,earlier playlist usage and so on , is the right case for chat (voice or test of gesture) to digest the complexity of intent-explain-infer-confirm cycle .
Thus the argument that because the end user are moving and are more and more available on chat platform and hence the business process should also move to them will add to chat fatigue once the novelty fades out .
We need to trust the end use to be able to decide on more convenient and time efficient model of interaction and offer them.Hence the conversational quality , used at qualified places while retaining the laid-out quality of presented content is the right blend .A jump into chat via bot will be shortlived for most mainstream businesses .Infact the power of ML or AI ,as we like,implies that the business understand and serve (ready to serve) us better even before we start interacting .To transport this whole responsibility onto AI assisted chat interfaces via chatbots is laziness .
In the end , there is a Google search experience to rescue.It lays out a nice search box for us to express , then does huge work in the background to make best sense of what we intended yet subtly suggest us alternatives and corrections ,like human conversation,if the confidence in the inference it made wasn’t high .
It is good case of fitment driven software than buzz driven software ..and that’s the case against chatbot , AI or no AI.

Here are some samples of how subtly google lays out the conversations , courtesy: littlebigdetails .
1. If you search the word “recursion” in Google, it’ll suggest “recursion”. If you click on the suggestion, it’ll suggest “recursion” again… creating a recursive search.And don’t miss the spell correction prompt “did you mean”

2.Google Chrome – Displays some search results in the suggested input area

3.When searching for an upcoming movie, the Knowledge Graph box shows the release date and asks if you’d like to create a reminder.

4.The Oreily report :

So every organization and their sales guy is pitching you about the wave of digital transformation that is essential to your organization and to be ready for the future. It is a must a do for cxo and their architects, if their business has to stay agile and thus, relevant.

Quite true, isn’t it? There is indeed a great sense is taking all your process online, enhancing your digital presence, offer deeper engagement to your end users and grow your business, except that under the noise of these right sentences, lies a misuse, overuse and confusion of the underlying terms which, if true, can lead to different path than intended.

Earlier attempts

The fact that businesses need to go online, i.e. be present on the same electronic plane that their customers exist and then offer interactions on the electronic plane is something that we all came to realize with the dot com era. A business should rightfully move in sync with their customers likings. This used to be called, for a long time , e-everything. E as in electronic. We had e-commerce-payments, e-medicine and so on, overlapping with its twin buzz words, web as in website and online as in online store. What this wave started was indeed a digital view of the world except that for the most part, it was a conversion of existing paper based on a human-facilitated way of doing business. Of course it had resulted in gains by sheer virtue of the expansion of reach it produced.

Digital transformation wave on the contrast is about expansion of the depth . The depth to which end-user can interact with a business and everything around it. Along with this, businesses must also look into essential services like the top Internal audit services if they truly want their brands to be efficient.

Genesis of digital transformation

Human mind is a double edged sword. At one end it can offer rich contextual insights about everything that ,computers are still struggling to match. At other end it can create huge roadblocks due to the linearity with which it sees the world. Imagine a loan application, while you are filling up the forms, can one parallelly start estimating your loan worth?, can it eliminate your need to sign at multiple places or your need to photo copy and attach supporting documents. We need to also consider that the process of application is designed with average human being in mind, on both sides of the interaction, mind you; so we introduced, a sequentially to the process.

It is this human intervention both apparent as well as embedded that the digital transformation wave intends to eliminate. Eliminate so that ,the depth to which the end-user can interact with business is enhanced by order of magnitude. It is apt to call this process as digitization. Digitization of all human intervention, obvious as well as implicit so that the interaction process is as below

Charetiristics of useful digital transformation

1.Instant :Instant as in immediate .Because we eliminate the human aspect of service ,we also eliminate queue nature of our business interaction.This is not same as number of simultaneous users but the ability of the system to react immediately and lead the user to the next logical step or even fulfilment of the process itself.

2.Always on:Always on is not the traditional availability,which is a service indicator that is essential to digital business .But if say ,your payment is waiting for payment network to be on or your application is waiting for an approver and appraiser to process it is not Always on.

3.Resumable : Tought we enable to business process to always on and instant , the same constraint does not apply to the end user .This calls for a resumability of the business process at a later point . Resumability is not a mere memory of users unfinished actions but also updating those actions for the business context that might have changed in the (larger) time lapse that might have occurred .

4. Simplified :As we digitize the actors and process in our system ,it also allows us to eliminate many constrains thus allowing us to simplify the whole user experience in our process . However simplification is not a call for giving up prudence ,but to shift it to a later phase or in background so that the regular flow in the system is far more short, easy and clear. This might even call for coordination between diff systems for this . A case in point is use of precomputed credit score to allow on demand consumer loan. Stay competitive by offering affordable processing credit card fees to your customers.

5.Parallelized : Removal of human view of the business opens up many opportunities to parallelize the tasks in the process so as to shorten as well as smoothen the overall journey .

6.Inferential: As we digitize diff aspects of our business , we also enable addresability of all these entities .This allows us to infer lots of data points,decision making,exception in our system to everyones benifit .An easy example is use of QR code or face recognition or even user segment to accelerate overall process .

Whereas,simplified is often misquoted as frictionless and Inferential is often mis-understood as big data analytics.

It is also important to stress that the earlier attempt of e-fication has sometime resulted in partial achievement of above goals.But due to generational nature of transformation waves,it often merely converted existing process in electronic forms.Case in point,tough e-payments was established early on,it took long time to allow e-cheques inside the system. Where as the main aim of digitization should have been ti eliminate the need of cheques as means of payment as well as legal record.

What then becomes obvious is that digital transformation will need lots of effort to question the business practices , to re imagine the world in digitized manner, and then do it ie digitally transform.For which,most often, that CMS platform,MbaaS suite,service gateway and so on,is not a pre condition.It might ,at max be, an eventual fitment.

Good luck