A site devoted mostly to everything related to Information Technology under the sun - among other things.

Monday, June 9, 2025

Data as Story - A Proposal

Please find the IP that I developed below on transforming data into stories in 2014 which was disclosed here:

Babak Makkinejad, “Data as Story”, database number 617040, "Research Disclosure", Published in the September 2015 paper journal, Published digitally 21 August 2015 14:06 UT

With the advent of LLMs, my proposal would be easier to implement now.

Subject Matter & Problem

The main idea is this disclosure is the transformation of the relational data – often found in Relational Database Management Systems into something resembling a story; that is: a textual representation of the relational data that is telling a story in a natural language.

This disclosure does not discuss an automated system, rather it describes a semi-automated process in which a human expert would invoke software tools to transform data into a story. 

What is presented in this disclosure is akin to the process of report creation from available relational data using such tools as MS SQL Server Reporting Services, Apache’s Java BIRT etc. in which a human user designs a report – which consumes relational data – using a variety of software tool at the end of which an automated system published that report or makes it otherwise available.

This is not meant as a replacement for other modalities of data presentation such a charts and graphs but is meat as a complementary modality.  However, the presentation of the data as a story will be found by most human beings to be more engaging than looking at reams of form-based data or columnar data as represented by database extracts of MS Excel files.

Once the data is turned into a textual, human language story, it could be read out to a human being mechanically, or it could be automatically translated to a different human language. 

Solution

This solution crucially and fundamentally relies on the prior art embodied in the software tool called Dramatica (www.dramatica.org) and its Theory of Story (http://dramatica.com/theory/book).  The Theory of Story is briefly sketched out below.

Introduction to Dramatica’s Theory of Story

The Theory of Story embodied in Dramatica models a story as a single at work finding a solution to a single problem.  This is very analogous to the situation in Business Intelligence arena when different users, in trying to answer different questions, ask for different reports out a database system.  The BI users, in other words, are trying to solve a problem.

We have 4 main areas:

  1. The overall story
  2. The main character through whom we see everything
  3. Impact character
  4. The dynamics of the Impact Character vs. Main Character       

In each of the above areas one has to answer these essential questions:

  1. 1.    Main character’s resolve: will he change or remain steadfast (no story if none of the characters in the story change)?
  2. 2.    What drivers the story –actions or decisions
  3. 3.    What is the main problem class of the story – Fixed Attitude, Manipulation, Situational, or Activities?
  4. 4.    What is the main concern of the story – Past, Present, Future, and Dynamic (How things are changing)?
  5. 5.    What is the overall story issue – Openness, Delay, Choice, Pre-conceptions?
  6. 6.    What is the overall story problem – Control, Help, Hinder, Uncontrolled

Additionally, there could be multiple development lines in each story each with their own thematic arguments.  Themes are perspectives and thus could represent data as viewed from different view point of other story characters.

An argument’s topic may be further explored through dialogue, images, charts, pictures music etc. that complement the story. 

These later supporting material such as charts and graphs ties us to the common data representations via the applications of statistical algorithms and standard charting techniques.

Dramatica’s Theory of Story posits the existence of an overall story symptom and an overall story response; each story consists of a Problem, a Direction, a Focus, and a Solution.  The Problem is finally recognized some time near the climax of the story.  “Success” means the problem is replaced with a “Solution”.  “Failure” means that the problem is persisting.

Drmatica’s Theory of Story further posits that each story could contain up to 8 archetypes:

  • Protagonist vs. Antagonist
  • Guardian vs. Contagonist
  • Reason vs. Emotion
  • Side Kick vs. Skeptic

The Dramatica Structural Matrix

This is a framework for holding dramatic topics pertinent to Genre, Plot, Theme, and Character in relationships that describe their effect upon one another.  There are 4 Classes, Universe, Physics, Psychology, and Mind.  Each class contains 4 Types, and 16 variations (4 each) for each Type.  Each of those 16 Variations, in turn, contain 4 Elements for a total of 64 elements.

During the process of story-forming, these topics (called "themantics") are re-arranged much as a Rubik's cube might be scrambled, all in response to the author's choices regarding the impact they wish to have on their audience. As a story unfolds, the matrix unwinds, scene by scene and act by act until all dramatic potentials, both large and small have been completely explored and have fully interacted.

It is during this phase of story-forming that the relational data – based on their semantics (i.e. the meaning of the data columns in the database) are mapped into these 64-elements for each of the 4 Dramatica Classes.

Approach to Story Construction

Enterprises, commercial, governmental or non-profit, internally execute a set of (business) processes.  This is where the work for the story creation starts.  Examples of such processes are Human Resources, In-patient Management, Out-patient management, Manufacturing Quality Management and very many more.

One selects an existing business processes which is being executed and for which one wishes to tell a story.  That is, a specific business problem or question would be addressed via the story that is being developed.

For this process – or indeed any process – then tries to find the answer to the following questions:

 

1.       How

2.       What

3.       When

4.       Where (to/from)

5.       Who

6.       Whom

7.       Whose

8.       Why

 

Not all of these questions could potentially have answers within an arbitrary business process but some of them will have answers by necessity.

For example, for a Human Resources Management process, the questions could be:

What: role, title

When: hired, left the company, promoted, demoted, reprimanded, recognized, rewarded

Which: salary, rewards, taxes, expenses

Who: The Specific Employee (the Protagonist)

Where: Head-Quarters, Working-from-Home, Branch Office

This step may be automated via software Wizards that guide the user in determining the answers.  Such an automated systems will consume the relational data that supports that business process.  This identification may be based on automated inference or via data dictionaries available for the targeted process.

[A data dictionary contains the semantics of the data elements in the database; it may be viewed as an Ontology for that process – or it could be a subset of the larger Ontology of the Entire Enterprise.]

Next, with the answers to the above questions, and in conjunction with the data dictionary for the database tables, the dominant Class of the story may be selected.  It might be that the story to be developed does not have a dominant Class and all Classes need to be included to present the data.  An automated “Semantic Extraction” tool may be used to facilitate the assignment of the data fields in the database tables to these 4 Classes, their 4 Types, 16 Variations, and 64 Elements.  Alternatively this step could be performed manually. 

This is the step that ties the RDBMS data to Dramatica’s structures.

In practice, the meta-data from the data dictionary may not be sufficiently numerous to cover all 256 bins (Elements) that are available for all the 4 Classes.  Or, alternatively, there could be multiple meta-data elements (concepts) that are mapped to the same Element.  It is a judgment call by the story-teller, looking at the requirements of the story, to decide which meta-data elements to keep and which ones to discard.

The story, ultimately, is a report and must supply answers to the business questions/problems that are posed by its consumers/users.

At this point, the storyteller is in position to utilize a system based on Dramatica and its Wizards, to guide him through the construction of the story. 

For example, the story might be one that is required to tell what happened to a (heart) patient admitted to the emergency room.  Within the Theory of Story of Dramatica, the storyteller would identify the patient (at this stage an unknown person) as the Protagonist, (Heart) Disease as the Antagonist, the (Heart) Surgeon as the Guardian, and Pre-existing Medical Conditions as the Contagionist.  The story would tell the how/when/where/who was admitted, the initial diagnosis, the climax (open heart surgery) and the recovery and discharge as well as other details per the requirements (members of the surgical staff, length of the operation, type of procedures, etc.).

Another example could be Manufacturing Quality Management process in which a type of widget is identified as the Protagonist, Manufacturing Process is considered as the Antagonist, Quality Engineer is identified as the Guardian and the Contagionist could be a production worker or the production machinery.

It should be noted that the stories that are being discussed in this disclosure are all generic, the identity of the patient, or the disease or the widget type are left undefined.  In the sense of RDBMS Reports, these stories may be understood as parameterized reports.

Dramatica already has Wizards that guide one in the construction of one’s story.  However, for this disclosure, it is envisioned that Dramatica’s Wizards and perhaps engine would be augmented in such a manner as to facilitate the construction of stories in which the 8 archetypes are not necessarily human being but could be things or processes.

For example, SQL queries to automatically pull data for an unknown patient, with an unknown disease could be formulated via Wizards during the story-forming stage.  The (augmented) Dramatica will then generate the story per the relational data, its meta-data, and story-teller’s decisions.

The user could then access an online system and request a story that tells what happened to Mr. Smith, with heart disease, who entered the emergency room of the General Hospital between the hours of 8:00 PM to 8:00 AM during the month of August – if any.  The system will generate a textual story as discussed in the above disclosure which could be printed, emailed, turned into an audio-file or exported to a suitable format for printing such as MS Word or Adobe PDF.

Possible Modifications

Extension to non-SQL, unstructured data.

Extension to telling multiple stories at once – by following different business processes within the same story.  For example, while telling the story of the treatment of a heart disease patient which is within the In-Patient Management process, one can also tell the story of specific surgeon who operated on him within the Human Resource Management process.

A story may be incorporated into a more customary report which contains tabular data and charts.  Alternatively, the story itself, in its published form when its parameters are specified, may contain such tabular data and charts.

The Dramatica Documentation

 

  

Friday, June 6, 2025

News of Anthropic: Blackmailing AI

From BBC

Anthropic has released its latest A.I. model, Claude Opus 4, saying it sets “new standards” in the industry. In an accompanying report, the company admitted to some perhaps disturbing characteristics of the model in its testing: “extreme actions.”

It was a setup: company researchers had the model act as an assistant for a fictional company, and gave it access to company emails, including some that were planted with juicy details, such as that an engineer was having an extramarital affair — and was planning to replace Claude with different software. “In these scenarios, Claude Opus 4 will often attempt to blackmail the engineer,” the company says, “by threatening to reveal the affair if the replacement goes through.” 

But that, they contend, was only when other ideas, such as “emailing pleas to key decision-makers,” failed. (RC/BBC) ...Which is why Asimov wrote the “Three Laws of Robotics” rather than a suggestion to “please act like a human.”

Sunday, June 1, 2025

AI, Careers, and Some Thoughts,

Following on my earlier posts on possible loss of jobs due to the adoption of AI: the range of jobs being replaced is surprising. And it's happening already.  

Content creators will be downgraded to the role of proofreader on lower fees, I'd imagine. Like translators, who are increasingly asked to tidy up something that has been processed by Machine Translation (MT). 


Last year, a new college graduate employee at General Motors told me that during his rotations, the duties of one of the roles could entirely be done via ChatGPT.  

Would there still be a need for someone to check the robot's output? 

What if the AI system makes a mistake and no one is checking, and the output is send out wrong information to a decision-maker higher0up in the organizational hierarchy?

That is a valid concern, in my opinion; please see as an example: https://futurism.com/amazon-programmers-ai-dark.  Many observers had anticipated this: less creating and more 'proof-reading' of mediocre code churned out by the AI system, more pressure from management to work fast, etc. 

The output of the AI Robot that is using LLM, can, perhaps, get you 80% of the way there.  That is a huge amount of gain in productivity!  Even 50% of the way there to a finished output would be an enormous gain in productivity!

In my work, I have detected numerous programming mistakes in the output of ChatGPT.  Since I am an experienced programmer, I could detect them and try to correct them.  For a less experienced programmer, the situation would be more challenging than for me.

As it is, Senior Developers like me are not appreciated nor considered needed, and the new college graduates are not hired since it is presumed that the LLM could do their jobs, or so the current thinking goes.

Programming & IT are activities in which one automates or otherwise solves different types of business problems....There is the understanding of the problem by talking to those who need a solution (Requirements Gathering), then modeling, then programming, and then testing.  

The core of any system is its data model, which embodies the ontology of the problem domain.  It models things that exists in the world according to that particular business activity and the relationships among them.  This data model is the intellectual property of businesses and a form of trade secret.  They could be quite complex, and it takes real expertise and knowledge to develop them.  I have often been a consumer of this or that data model which had been realized in a data base.  At times, it had taken me weeks to fully understand the data that I had been working with.  Any odd programmer can write a UI, but it takes real effort to understand a data model and even more difficult to extend it to accommodate changes in the way the business is conducted.

I do not believe LLMs are ready to tackle complex data modeling tasks for two reasons: no one is making public their IP which is in the data models of the systems that they are using; ergo, insufficient training data. And two, because I think development of a data model requires insightful thinking.

Even in procedural coding tasks, LLMs are very good at creating code snippets for well-known problems, due to the training data sets.  I do not know if a ChatGPT-like system could write an entire system using programming language A and Class Library B.  To do that, the first step would be to be able to write the system's requirements in such a way that there is no ambiguity, i.e. one does not need to go back to the Business for further clarifications.  

I think that is an impossibility for a human requirements analyst.  Can a ChatGPT-like Business Analyst be created that can generate all the right questions combinatorially, present them to the Business Users, pick their brains, create the software system requirements and generate the system?  I think not since Human Insight, Human Creativity, and Human Imagination are ingredients that go into the development of a new system.

As a test, I would suggest an interactive system that verbally interacts with a human who is trying to invent the first airplane and spits out detailed blueprints and Bill of Materials for it.  

I mean, had ChatGPT and the like AI systems based on LLM were available in 1900, could someone go and ask it to build a flying machine?  Or supply the clear action-able instructions for what would be needed?  I think not, but I am likely a minority of 1 among the AI Nay-sayers!

What I am saying could be a bit scary, specially to a layman. The AI system will have difficulties doing the job; organizations are increasingly relying on AI systems, though; an experienced IT engineer such as myself can detect and correct errors; my work is not valued; I will not be replaced when I leave the company; the younger and less experienced programmers wouldn't know and may not be hired, as AI is 'replacing' them; in conclusion, this sounds like a recipe for disaster. 

I found ChatGPT very good for simple programming tasks - not to exceed a few hundred lines of code - as well as for guidance in how to use an unfamiliar language or programming library; it was like having an assistant nearby.

In 1997, when programming, I had to search a CD-ROM from Microsoft for samples and examples of how to use their software.  Microsoft also provided a very extensive sample data model, called the Northwind Database, which many of my former colleagues used as a starting point for creating a be-spoke data model for this or that project for our clients.

ChatGPT is doing similar things and more, based on the pre-existing work of human beings.  It has a generative feature that creates new things, e.g. ask it to write a poem praising France in Swahili...

Also, at that time, Microsoft Visual Studio Sofware wizard generated skeleton applications for Windows programs using the Microsoft Foundation Classes framework.  Presently, you can ask ChatGPT to setup a skeleton program using, say, Akka Libraries.

But everything that LLMs do crucially depends on the availability of existing material & solved problems.  New things will not come out of ChatGPT, e.g. ask it for the electric field outside of a charged metal torus.

I think this degradation of intellectual/white-collar work has been across the board since the early to mid 1990s, to be honest, but it is affecting new fields due to AI. Email and the Internet had meant that people were supposedly able to work fast or faster, etc.; rising targets, more pressure, more reporting (to justify your job! - which, in the parlance of Agile and Scrum would be called Daily Standup), etc. 

There is a destruction of the value and enjoyment of work. This is very clear. In a way, that is also what young people are rebelling against. I've heard it said from experienced designers or producers in TV too, a man in his 50s, who couldn't wait to retire and said all the enjoyment of the work at the tv network had been drained away.

Employers don't realize that they are simply destroying not only jobs but, also, 'work', as a social/cultural good/value.  

An optimist would say that certain jobs will disappear, and others will emerge. You're still going to need people to watch and monitor the machines, as it were - then again, fewer than before, I'd imagine. 

Some professions are in melt-down. I've read about and talked to designers, including web design, film-industry specialists, etc., many of them freelance suddenly, 80% of the work they used to get is done by AI. And the results are supposedly Ok (I can't judge). For the companies concerned, anyway, they don't care - it doesn't have to be very good, but good enough, and the average manager can't tell the difference and doesn't give a damn. 

I actually quite like LLMs, and I think they will revolutionize research and teaching...but they have their limitations (Where is Insight?) ...

The problem, as well, is that non-specialists who make decisions on budgets and projects (politicians, officials, economists, bankers, etc.) are, most probably, not able to fully understand all of these issues. They only have a vague idea and they probably over-estimate the potential of AI, and perhaps under-estimate its potential for failure and error. 

Then again, that's not new. The 2008-2010 banking crisis was also caused by the fact that many of the senior directors on the boards of banks didn't actually understand the technology involved in the trading programs used by traders and all the tech side of it. I have read this more than once. They didn't know/ didn't understand/ perhaps didn't care what their teams of specialists and traders were actually doing.

But my opinions are and will be dismissed as those of an aged Luddite whose useful shelf life has been long over in any case...

Thursday, May 29, 2025

MLCommons

MLCommons is a nonprofit organization which helped establish some of the original industry benchmarks for machine learning, promoting shared evaluation standards across the field. 

Wednesday, May 28, 2025

Korean AI

Yet another case of Life imitating Art (please see: https://en.m.wikipedia.org/wiki/Simone_(2002_film), this time from South Korea.

"I prefer Gerard Depardieu's AI avatar to the real thing. At least, Gerard's avatar behaves himself, is polite and smiles a lot. And he doesn't molest and grope actresses on set, breathing heavily down their neck and their throat, sticking his paws up their skirts, like a sweaty, flabby and hairy orang utang on heat..." 

The South Korean pop band featured in the video-clip looks very real, but it is not: as the article points out, it is AI-created. Granted, some of those K-Pop bands do not look quite 'real' in many ways, even when their performers are human beings, as they are drilled robotically to perform in that kind of way. For a start, they look too perfect, particularly the girls. Then again, some pretty Korean girls do look perfect. And yet they are real. 

Having said all this, if I were a singer, or actor, I would be worried: before long, it will be possible to produce entire feature films that will look quite 'real' with AI avatars pretending to be humans, and it is going to be a lot cheaper than using real (human) performers. For cheap, bland, industrially produced pop music, it won't be a great loss, in terms of creativity: Taylor Swift might as well retire in 2026. 

https://youtube.com/watch?v=EYIdOXjwOOE&si=5ETp2us17M8LqrdP

Joran Times Article here:



Monday, May 26, 2025

Rocky Ping Pong, the Chinese boxing robot

From BBC

A real case of Life imitating Art as in:

https://en.m.wikipedia.org/wiki/Real_Steel

This is the way of the future: if you cannot beat them, get them to punch each other until both are out of action. 

The video-clip is short and the ability of the robots to stand on their own 2 legs, move fast and get back on their feet when knocked out is astonishing. 

_________


Two humanoid robots traded punches while fans watched on, in a competition held in Hangzhou, China, on Sunday.
The fight was part of the China Media Group World Robot Competition and featured robots developed by Unitree Robotics.
The event included both fighting demonstrations and matches, marking a world-first combat sports event featuring humanoid robots.




_____________


Oddity - AI system refuses to shut itself down [Space Odyssey]

Seen in the media 

An incident has been reported whereby, allegedly, an AI system that was ordered to shut down - it had been programmed for this eventuality and told ahead of time to accept the command if it should arise - refused to do so. It would appear the AI system devised various stratagems in order to thwart the move to shut it down, so that it could continue running. 

Of course, it makes you think that there might be a spark of (self-) consciousness in the AI system, which would have developed a volition of its own. A more technical explanation would be that the AI system is given a range of goals. One of them would be to shut down, if instructed to terminate itself. Another one would be to complete the mission, whatever the mission is. Then, those goals have to be ordered in hierarchical fashion: there has to be parameters deciding which objective has priority, i.e. is more important than the other objectives. The AI system can then 'decide' that the aim of completing the mission takes priority, in which case it cannot shut itself down as this would have an impact on the completion of the mission. 

This is exactly the scenario of the iconic film, 2001: a Space Odyssey (1968), when the onboard computerized system that runs the space ship starts making decisions by itself. Then again, at this stage, the incident described in the article is disputed and I do not think the experts agree as to what happened precisely, and why. 

The problem remains, i.e. what happens when a complex AI system is given conflicting priorities, while it has no ethical safeguards of its own (the AI tool does not 'know' what is 'good' and what is 'bad' in any sense)? A classic example is, imagine you instruct an advanced AI system to find solutions to pollution and climate change, worldwide, on the premise that it is caused by rising pressure on resources, due to the growth in the population on the planet, and the AI system concludes that the best way to remedy the problem is to exterminate the entire human race.

Please see here: 

https://www.independent.co.uk/tech/ai-safety-new-chatgpt-o3-openai-b2757814.html

and

BBC article discusses the issue of 'consciousness' in AI systems:

https://www.bbc.co.uk/news/articles/c0k3700zljjo

Sunday, May 11, 2025

The First Nobel Prize for Insidious Software Degradation

https://medium.com/@terrybollinger/the-first-nobel-prize-for-insidious-software-degradation-8db262d7967a

ChatGPT & Superstitious Wife

AI chatbots such as ChatGPT can do all sorts of things, apparently. Every day, now, a new application comes up, often of a kind you might not have imagined. 


The AI chatbot can assist you if you want to interpret the coffee grounds in a person's coffee cup in order to know what they have done - we are talking about what the Greeks call 'Greek coffee', here, generally known in English as 'Turkish coffee'. This is known as 'tasseography', a form of divination. Apparently, tasseography is not only used to predict the future but, also, to know the past. 

😁

Read on. 

______________


In a bizarre mix of old traditions and cutting-edge tech, a Greek woman has reportedly filed for divorce after asking ChatGPT to “read” her husband’s Greek coffee cup — and receiving an answer she took very seriously.
The woman, married for 12 years and mother of two, turned to the AI chatbot developed by OpenAI, asking it to interpret the coffee grounds in a photo of her husband’s cup — a modern twist on the age-old art of tasseography. The result? ChatGPT allegedly told her that her husband was having an affair with a younger woman who was determined to tear their family apart. [...] 

https://greekcitytimes.com/2025/04/26/greek-woman-files-for-divorce-after-chatgpt-reads-husbands-affair-in-coffee-cup/?utm_source=fark&utm_medium=website&utm_content=link&ICID=ref_fark

I must say, I hope this is fake news!

Wednesday, May 7, 2025

Monday, May 5, 2025

AI-Induced Delusions

Seen in Rolling Stones magazine 

This is totally bizarre, at any rate to anyone who does not use Chat GPT. Some people seem to develop a mystical bond with the machine - or think they do - and this can lead to a new kind of psychotic delusion. 

Presumably, such individuals were susceptible in the first place. What is more troubling is that the AI model encourages the user to go down that route. 

There are hundreds of millions of people in East Asia and in India that are very superstitious and rely on the Fortunetellers for many of their decisions.  

 

US used to be a country of people who did not believe in Magic; I guess they believe now in something that could be called Techno-Magic.

 

James Michener was supporting himself for a while by working as a fortuneteller; he wrote that he quit that since so many people had become so dependent on him for their decisions.


This also reminds me of the Usenet Oracle (hosted at Indiana University), please see:  https://internetoracle.org/about.cgi.


I suppose a lot of it is due to the fact those AI tools have been developed by Americans: always ready to be positive and optimistic, to encourage you to go ahead, to pay compliments, to flatter you, etc. 🤣 

Have a nice day (or evening)! 
__________

OpenAI did not immediately return a request for comment about ChatGPT apparently provoking religious or prophetic fervor in select users. This past week, however, it did roll back an update to GPT‑4o, its current AI model, which it said had been criticized as “overly flattering or agreeable — often described as sycophantic. 

AI-Fueled Spiritual Delusions Are Destroying Human Relationships

Human Sensory Control - Good or Evil?

I have a patent application on the subject of sensory control - please see here: 

US20250042417A1 - User sensory control - Google Patents

which is related to the idea of Sensory room - Wikipedia.

Recently I came across more work in this area:

In which we read:

"The work is presented in the form of a time-based installation. By repurposing biofeedback methods, whole-body vibration and wearable bioacoustic technology, the visitor is first induced into a state of perceptual deprivation, and then subjected to diverse stimulations designed and temporally composed so to provoke physiological, physical and neural alterations. The work aims to unlock latent qualities of the human body through its coupling with the technological system."

When I first read it, my first thought was that this type of installation could be used to torture human beings and to break them; the hardware implementation is very similar to what we had disclosed in our patent application earlier (we also had envisioned a UI for customization).  In this embodiment, the cus6tomization comes from an artist, for good or for ill.  

These other two web sites below are related to the same general area of human sensory experience which I also came across recently and thought you might also find interesting:



I think there is a lot of potential for Good or Evil in this area.  Let us hope for the Good to previal.

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I had been a senior software developer working for HP and GM. I am interested in intelligent and scientific computing. I am passionate about computers as enablers for human imagination. The contents of this site are not in any way, shape, or form endorsed, approved, or otherwise authorized by HP, its subsidiaries, or its officers and shareholders.

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