Digital Financial Reporting

There are a number of people using this US GAAP test data for the 2017 10-Ks.  Here is a summary of that information:

• Human readable list of the 5,734 filings
• Machine readable RSS feed with 5,734 filings
• ZIP archive containing Excel file with the list of 5,734 filings
• ZIP archive containing XML infosets of model structure of each of the 5,734 filings taxonomy
• Second ZIP archive with Excel spreadsheet with list of 5,743 filings with additional metadata: total assets, number of facts reported
• Reporting Styles Used by Companies US GAAP
• Overview of reporting styles, US GAAP
• Inconsistencies with reporting styles, US GAAP
• Reporting checklist rules, US GAAP
• Disclosure mechanics rules, US GAAP
• Disclosures
• Topics
• Fundamental Accounting Concept Relations Rules
• Conceptual model
• US GAAP Ontology Prototype
• US GAAP Concept Roll Ups

The Forbes article, Will Artificial Intelligence And Cloud Accounting Replace The Accountants Of Tomorrow?, explains that robots and artificial intelligence will replace 7% of all jobs in the U.S. by 2025.  So, that 7% is actually a net of a 16% loss of existing jobs and a 9% increase in new jobs, per Forrester.

The article says:

In this not-too-distant future, businesses will be able to afford powerful CFO advice without the cost of a full-time employee. All of those menial, time-consuming tasks that used to eat up hours of a day will be gone – a victim (or virtue, depending on your perspective) of the automation process. This doesn't eliminate the need for accountants, but rather empowers them. It frees up time in their day to work with clients in a more effective way.

The article goes on to explain that disruption is what you make of it:

When people hear the word "disruption," they tend to assume it has a negative connotation. However, this doesn't have to be the case --technological disruption is more about creating an opportunity than creating a threat. For accountants working with small business owners, disruption is less about, "What I do can now be automated, putting me out of a job," and more about, "Now that I can automate X, Y and Z, I can change my job for the better and for the future."

Artificial intelligence has an issue.  You need to be aware of this issue because it means that artificial intelligence should not be employed for solving certain classes of problems.  The issue is straight forward.

There are two types of reasoning: deduction and induction. These two videos help you understand the difference between deduction and induction: Video 1; Video 2.

The bottom line is that deduction is certain; you can be logically certain of the conclusions reached using deduction. That is the goal of deduction, certainty. Induction is not certain, induction is based on probability.

The Black Swan Problem of Induction clearly explains the problem of induction.

“No amount of observations of white swans,” he said, “can allow the inference that all swans are white, but the observation of a single black swan is sufficient to refute that conclusion.”

Many employing artificial intelligence use inductive reasoning systems.  They believe that these systems can work because the problems caused by induction can be managed effectively.  That may be true.  But it likewise may not be true for certain knowledge domains.  The call here should be made by domain experts, not computer scientists that do not have a deep understanding of the domain.

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One problem to explain why AI works