The article, What is cognitive computing? IBM Watson as an example, says that cognitive computing is the third era of computing:
If we consider that the first era of computing that the one of tabulating systems (1900), the 2nd the one of programmable systems (1950), cognitive computing is the 3rd era of computing.
It is a mistake to overstate the capabilities of something. It is likewise a mistake to understate the capabilities of something. Philosophers, theologians, and academics like to debate things simply for the sake of the debate. Business professionals, me included, tend to take a different approach. We like to use practical tools that actually work. Me personally, I don't see a computer having a conscience any time soon.
People love buzz words. Early in my career one buzz word was "client server". Few people seemed to know what client server was, but everyone felt they needed one. Artificial intelligence has been a buzz word for quite some time. Some of today's buzz words are: Big data. Smart data. Smart machines. There are even people who track buzz words. I tend to take this persons view on buzz words:
Not all buzzwords are bad. Some actually convey an idea, a concept, or a valid technology. However, some exist to confuse, distort, and empower those who don't want you to know what they're talking about.
Many people tend to miss a really important point when it comes to XBRL. They look at XBRL as "tagging" and they equate XBRL to the "barcode". But, turn the equation around. What would it mean if all financial information were properly bar coded? What could you do? What would that enable?
Think about this: What would happen if you took financial reports and rather than reporting information in an unstructured format that only machines could understand (because the information is unstructured or more accurately structured for presentation); but rather reported information was in a structured format both humans and machines could read and understand? What exactly would that mean?
Well guess what. We will get a chance to see exactly what that means. Financial information is being reported to the SEC by public companies in the structured format XBRL. The quality of that information is being dialed in. Professional accountants are understanding more and more about how digital works. Professional accountants are building prototype financial report ontologies and suggesting how ontologies can be used to improve financial reporting. Professional accountants are coming up with ways to work with technical artifacts so that they can employ these useful technologies on their terms.
Cognitive computing is the simulation of human thought processes in a computerized model.
Notice the word simulation. Computers cannot think, they are dumb beasts. But these dumb beasts can be made to mimic the human thought process, if you understand how to harness the power of a computer. (If you don't understand what it takes to harness the power of a computer, read Zeroing in on the Holy Grail of Global Standard Financial Reporting.)
Computers do not create the magic. Skilled craftsmen who wield their tools effectively are what create the magic. Computers simply follow instructions.
This article, Cognitive Computing And Semantic Technology: When Worlds Connect, points out something that is really important in two key statements in that article:
For cognitive computing to achieve its promise we need a thick metadata layer that incorporate semantic tagging formats.
A lot of the focus is on machine learning, especially as things move to really analyzing and building explicit knowledge models, but other areas that should be included in the cognitive computing mix include constructive ontologies and constructive knowledge modeling, whether it's done by groups or individuals or crowd-sourced in the case of the semantic web.
So, what is not in dispute is the need for a "thick metadata layer" in order for the computer to be able to perform useful work. But what is sometimes disputed, it seems, is HOW to get that thick metadata layer. There are two basic approaches:
- Have the computer figure out what the metadata is: This approach uses artificial intelligence, machine learning, and other high-tech approaches to detecting patterns and figuring out the metadata.
- Tell the computer what the metadata is: This approach leverages business domain experts and knowledge engineers to piece together the metadata so that the metadata becomes available.
Now, I understand many things about how computers work. Not remotely everything, but a lot. If there is an error in my understanding of what computers can achieve, it would tend to under estimate what they can achieve rather than over estimate.
As a professional accountant, I understand that the probability of a computer starting from scratch and using the most sophisticated technologies and approaches available today and creating any useful metadata is very close to zero. However, the more manually created metadata that a computer has to work with, the higher the probability that the computer would be helpful in correctly figuring out financial reporting metadata.
So what I am saying is that humans are going to have to prime the pump and get quite a lot of metadata pieced together. Then at some point and for some things, computers can effectively be used to contribute more metadata. And so, this is not an either-or question. Both approaches can be used effectively and contribute to what is needed to realize the potential offered by cognitive computing. I am also saying that there are no short cuts.
Can cognitive computing work and have an impact on financial reporting? No doubt. Work practices of professional accountants will be changing over the coming years in very big ways. 1 year? 5 years? 10 years? 15 years? Hard to say. So keep Gartner's Hype Cycle in the back of your mind.
Computers assisting professional accountants in correctly representing financial reports digitally will cause high-quality financial information to be available for analysis by investors and regulators. Everyone in the financial reporting supply chain will benefit from the meaningful exchange of financial information in machine-readable formats.
XBRL was never about "tagging" or "barcodes". XBRL is about all the possibilities that are enabled if information can be successfully exchanged between business systems. While financial reporting is leading the way, in particular XBRL-based financial reporting by public companies to the U.S. Securities and Exchange Commission, other reporting schemes will likely benefit from the SEC's bold experiment. Business professionals will build their own Watson-type systems for way less than what IBM paid to build Watson.
Concept computing will contribute to changing how financial reports are created similar to how CAD/CAM contributed to how blueprints are created and how the design supply chain interacts.