Digital Financial Reporting

This blog post pulls together a set of information which helps someone understand the moving pieces of digital financial reporting:

• Expert systems: Expert systems are computer programs that are built to mimic human behavior and knowledge.  A computer application that performs a task that would otherwise be performed by a human expert.
• Digital Financial Report Creation Vision: A digital financial report creation tool is an expert systetm.  This provides an example of the types of benefits offered by such an application.
• Framework and Theory: A framework and theory is necessary.
• Artificial Intelligence: Artificial intelligence is used to make an expert system work.  The term "artificial intelligence" tends to be overloaded and means different things to different people.  This is a good definition of artificial intelligence as I mean the term: 
  • Artificial intelligence is an area of computer science that deals with giving machines the ability to seem like they have human intelligence; the power of a machine to copy intelligent human But  behavior.
• Two approaches to constructing artificial intelligence: There are two approaches to building artificial intelligence:
  • #1-Know how to 'write down the recipe' meaning that those with the knowledge of some business domain articulate the information in machine-readable terms. In order to effectively express information in machine-readable terms, knowledge engineering skills are necessary.  This document, Knowlege Engineering Basics for Accounting Professionals, summarizes important information related to knowledge engineering.
  • #2-Let the machine grow the knowledge itself.  Another term for this is deep learning.
• Artificial intelligence to be 'the norm' in law firms in 2020: This article predicts that law firms will be using artificial intelligence by 2020 (only 5 years away).  It does not provide a lot of specific details.
• Artificial intelligence meets the C-suite: (McKinsey) "Many of the jobs that had once seemed the sole province of humans—including those of pathologists, petroleum geologists, and law clerks—are now being performed by computers."
• Digital Financial Report Information Quality Improving: I have been tracking the quality of XBRL-based digital financial reports for three years, information quality has improved significantly.  XBRL-US has created the Data Quality Committee to improve quality.
• Digital Financial Reporting Part of Larger Trend - Digital Business Reporting:  A digital financial report is a type of digital business report.  Another name for a digital business report is 'semantic spreadsheet'.

It would be great to synthesize all of this information into one clear, concise document.

Jeff Hawkins, in a 16 minute Ted Talk, How brain science will change computing, explains why a framework is necessary and why a theory is necessary.  He provides this explanation by taking about brains.  I can distill the important message pointed out by this video as it relates to digital financial reporting in this concise statement:

What is conspicuously lacking is a broad framework let alone a theory on how to think about digital financial reports.

Here are some of the important things that Jeff Hawkins points out his video:

• "We don't need more data, we need a good theory."
• "Things look complicated until you understand them."
• "We have an intuitive, strongly held, but incorrect assumption that has prevented us from seeing the answer. There is something that we believe that is obvious, but it is wrong."
• "Intelligence is defined by prediction."
• "We experience the world in a sequence of patterns." 
• "Real intelligence is a sequence of patterns."
• "Successful prediction is understanding."
• "Intelligence is making predictions about novel events."
• "Memory of high-dimensional patterns"
• "Memories are stored and recalled as a sequence of patterns"
• "Must be testable"
• "Must be buildable, if you cannot build it then you don't understand it."

For some reason, I intuitively understood that a theory and framework were necessary.  Rene van Egmond and I created a theory, Financial Report Semantics and Dynamics Theory, back in 2012.  That theory documents a framework.

The fundamental accounting concept relations are predictions.  I have been fiddling around with patterns that I have noticed in financial reports since 2000 or so.  I have used those patterns for many, many things; refining and tuning them along the way.  I have studied systems as part of the work toward my MBA way back in the 1980's and 1990's.

Seems like what Jeff Hawkins is saying is that the artificial intelligence community got it wrong.  (See minute 11 to about 13 in the video.

It seems to me like "memorizing" and "metadata" are the same thing.  Humans can memorize things, but these memories need to be put into machine-readable form for the computer to use.  So, these disclosures and these report frames seem like memories.  Using these memories helps you make predictions, "Because I see assets, because I see liabilities and equity, I predict that this is a balance sheet and not an income statement."

The biggest hurdle that I can see is summarized in this statement made by Jeff Hawkins:

We have an intuitive, strongly held, but incorrect assumption that has prevented us from seeing the answer. There is something that we believe that is obvious, but it is wrong.

[Another useful video, How Intelligent is Artificial Intelligence?]