Computers are Dumb Beasts

It is important to understand how computers work in order to get computers to do what you want them to do.  The strengths of computers and the obstacles that get in the way of using computers were summarized well by Andrew D. Spear in his paper Ontology for the Twenty First Century: An Introduction with Recommendations; here is his list summarized into bullet points with some modifications made by me:

Fundamental strengths/capabilities of computers:

• store information reliably and efficiently (tremendous amounts)
• retrieve information reliably and efficiently
• process stored information reliably and efficiently, mechanically repeating the same process over and over
• instantly accessible information, made available to individuals and more importantly other machine-based processes anytime and anywhere on the planet in real time

Major obstacles to harnessing the power of computers:

• business professional idiosyncrasies; different business professionals use different terminologies to refer to exactly the same thing
• information technology idiosyncrasies; information technology professionals use different technology options, techniques, and formats to encode and store, retrieve, and process exactly the same information
• inconsistent domain understanding of and technology's limitations in expressing interconnections within an area of knowledge
• computers are dumb beasts; computers don't understand themselves, the programs they run, or the information that they store, retrieve, process, or provide access to

Keep in mind that the information business professionals are trying to store, retrieve, process, access, and make use of is becoming more complex than what they have been storing, retrieving, processing, and accessing in relational databases or spreadsheets for the past 50 years.  For example, a financial report is complex information that is very challenging to store in a relational database and then query across thousands of such reports efficiently.

Organizations have a data mess and artificial intelligence cannot understand that mess or fix the mess no matter how much you might want that to be true or how much you think otherwise.

As described by Robert S. Seiner in All in the Data: Negative Attitudes and the Four Horsemen of the Data Apocalypse, the four horsemen can be used to describe the negative attitudes organizations have toward data that have prevented these organizations from addressing the need to improve and gain value from their most valuable asset.  Here are those negative attitudes (the four horsemen of the data apocalypse) explained in a bit more detail:

• Ignorance: The ignorance attitude can be best described as thinking that seeking value from data is not that important.
• Arrogance: The arrogance attitude can be described as the thinking that management knows more than the people that own and are responsible for the data.
• Obsolescence: The obsolescence attitude can be described as thinking that the present data, in the present systems, will never die and that, if it carried the organization this far, and there is no reason to change.
• Power: The power attitude can best be described as the feeling that projects owned by the most influential members of management are more critical than other projects.

There are specific differences between data, information, knowledge, and wisdom:

• Data: The basic compound for intelligence is data; data is the raw unprocessed words and numbers.  Data are measures, observations, symbols, phenomenon, utterances, and other such representations of the world around us presented as external signals and picked up by various sensory instruments and organs.
• Information: Information is data in context.  Information is produced by assigning relevant meaning related to the context of the data to the data.
• Knowledge: Knowledge is the understanding or interpretation of information.
• Wisdom (or Intelligence or Understanding): Wisdom embodies awareness, insight, moral judgments, and principles to construct new knowledge and improve upon existing understanding.

So how do you harness the capabilities of these dumb beasts,  computers, to help us perform work? The first step is to fix the mess and, again, artificial intelligence cannot mix that mess for you. As pointed out in The AI Ladder (page 5), "No amount of AI algorithmic sophistication will overcome a lack of

data [architecture] … bad data is simply paralyzing." MIT Sloan.

The path to knowledge and wisdom is through data and information.  Organizations need to understand and fix that problem before they will ever be able to apply artificial intelligence effectively.

Additional Information:

• A cat is on a mat.
• Problem Solving Systems
• AI + HI = Transformation