Perhaps I shall first recall the essentials of Watson. Watson is the new computer brain from IBM which can answer questions on different topics, varying from science, culture, history up to economics or even the last pop music events and their related “chit chats”. The questions to Watson are formulated in natural language. Just like human beings do. And Watson formulates the answer to each question also in natural language. Sometimes Watson may say, it does not know any answer.
Furthermore, Watson has been trained to play in competition against human beings on the US television quiz show Jeopardy. Jeopardy is the number one quiz show in North America. The best Jeopardy players are respected for their encyclopedic knowledge. Watson being able to understand a question and to give the correct answer to the formulated question, makes it somewhat human.
And IBM wanted to set a mile stone. Just like it did in 1997 with DeepBlue, the chess computer who won against the world champion chess player, Garri Kasparow. IBM brought Watson between the 14th and the 16th of February 2011 in competition against the best human Jeopardy players ever, Brat Rutter and Ken Jennings . And Watson did win. Winning twice as much money as the best of the two human beings. A new milestone, for IBM. For the computer science. For the definition of human intelligence.
So what technology is behind Watson? It is called DeepQA for Deep Question and Answer. At a very high level, DeepQA analyses natural language sentence and extracts information it contains. For example from the sentence “Albert Einstein, born on the 14th of March 1879” it can fill its database of birthdates with the entry Albert Einstein and the corresponding date. It can also go further and extract interesting knowledge across sentence boundaries that are obviously in the same context. In the following example Watson makes use of temporal calculation, geographical relationships and paraphrasing statistics to relate Vasco da Gama stated in the sentence “on the 27th of May 1498, Vasco da Gama landed in Kappad Beach” together with the explorer mentioned in the question “In may 1898 Portugal celebrated the 400th anniversary of this explorer’s arrival in India”.
Without going into the details of the technology behind, this allows for 2 interesting activities.
- The first one is data mining: Watson analyses text offered to it, categorises this knowledge and collects it into tables, knowledge bases and lists of semantically annotated sentences.
- The second one is answering a question: Watson extracts the context from a question and evaluates the best possible fit between the question and Watson’s accumulated knowledge.
But Watson is good enough to help human beings in decision making: Watson can extract from a huge database the relevant piece of information to support the decision process of human beings, for example on illness diagnosis.
And why is the showing of Watson good for the customer care market?
The essence of customer care is to answer questions. And if Watson can answer open questions on a very wide variety of themes, it certainly can be very efficient in answering customer care questions. More, Watson does it automatically.
And automation brings in quality: answer quality, process quality.
- Automation brings control: you know exactly what your automated service delivers.
- Automation brings repeatability. Same question same answer. As long as it is not changed or improved.
- Automation allows to work on increase of quality: one can teach, fine tune an automated system.
Just as DeepBlue validated the market for automated chess players, DeepQA will validate the market for virtual assistants. Good news for a market (that of automating customer care) which until now took its time to mature.