Serendipity35 - Language

How Verbal Thinking Elevates Learning

ronkowitz@gmail.com (Kenneth Ronkowitz) — Thu, 06 Nov 2025 10:10:00 +0000

The notion of talking to oneself, often dismissed as a mere quirky habit or a sign of preoccupation, is, in fact, a powerful, evidence-based cognitive tool essential for learning, problem-solving, and achieving self-regulation. For educators, understanding and deliberately integrating this "verbal thinking"—known in psychological literature as private speech, self-talk, or self-explanation—into pedagogical practice can unlock deeper comprehension and foster truly independent learners.

The psychological roots of verbal thinking's benefit trace back most prominently to the work of Soviet psychologist Lev Vygotsky. His socio-cultural theory identifies a critical stage in a child's cognitive development where social communication turns inward to become a robust tool for thinking. Vygotsky outlined a three-stage developmental framework for language: beginning with Social Speech in young children, where language is purely external and used for communicating with others; progressing to Private Speech during the preschool years (ages 3-7), where the child begins to speak aloud to themselves, often in a whisper or mumble, utilizing this overt language as a self-guiding tool for planning, regulating, and controlling their own behavior and problem-solving attempts.

For example, a child engaged in a puzzle might audibly walk themselves through the steps: "First, put the red block here, then the blue block goes on top." This transitional phase ultimately leads to Inner Speech (age 7+), which is the fully internalized, silent verbal thought that most adults use for abstract reasoning, reflection, and sophisticated problem-solving. For educators, the key takeaway from Vygotsky’s work is that overt verbal thinking, or private speech, represents the crucial bridge from externally guided learning—where an adult or peer provides the instruction—to true self-regulation and independent, complex thought. By encouraging students to verbalize their process, teachers are helping them build the necessary internal scaffolding for later, silent, and more sophisticated thinking.

Crucially, verbal thinking doesn't just manage behavior; it fundamentally alters how information is encoded and understood by the brain, supporting both memory and comprehension. Research in memory retrieval highlights a phenomenon known as the Production Effect, which demonstrates that reading or generating information aloud significantly improves its memory retention compared to reading it silently. This memory boost occurs because speaking information aloud engages a greater number of sensory channels simultaneously. The learner uses visual input (seeing the text), verbal/motor input (the physical articulation of the words), and auditory input (hearing the words being spoken). This richer, multi-modal encoding creates a more distinctive and robust memory trace in the brain, making the information much easier to recall later. This distinctiveness is vital: when a learner produces a word aloud, it stands out against the background of other silently read words, making the item unique in memory. Therefore, simply having students read key definitions, summaries, or steps aloud in a low-stakes environment is a simple, yet highly effective, way for educators to leverage this proven physiological mechanism to strengthen long-term memory.

Perhaps the most powerful cognitive benefit, particularly for complex material, is the deep processing that occurs through self-explanation. This process is not mere repetition; it is the active, conscious act of trying to explain new information by relating it to what one already knows, making necessary inferences, and proactively clarifying any ambiguities. The first benefit here is powerful metacognitive monitoring: when a learner verbalizes a concept, the very act of articulation immediately exposes areas of confusion or "knowledge gaps." If a student struggles to explain a step in a math proof or a scientific concept, the flaw in their understanding is instantly revealed, prompting them to go back and refine their knowledge. This is a critical act of metacognition—the vital process of thinking about one's own thinking. Secondly, self-explanation drives coherence building. Verbalizing forces the student to translate disparate, often fragmented, pieces of information into a coherent, logical structure. They are not just recalling isolated facts but actively constructing a unified mental model of how the concepts interact. This principle is famously embodied by the Feynman Technique—explaining a concept simply as if teaching it to a novice—which serves as a form of high-level, deliberate verbal thinking that ruthlessly exposes the limits of a learner's comprehension.

The idea that talking to yourself out loud is not only "okay" but also an excellent learning technique is satisfying, but as I dug into this research, I recognized things from my college and grad school education courses. Other than the idea that it's not abnormal behavior to talk to yourself, this research is not completely new. I used several of these pedagogies in my teaching.

The challenge for educators, then, is to move verbal thinking from an accidental occurrence to a deliberate, scaffolded learning strategy within the classroom environment. One highly effective technique is the Think-Aloud Strategy, which focuses on teacher modeling. This strategy is used to make the invisible thought process of an expert visible and accessible to students, thereby explicitly teaching them how to engage in effective self-talk. To implement this, the teacher must first explicitly state the goal: "I’m going to show you how a skilled reader or problem-solver thinks by saying my thoughts out loud." Then, as the teacher reads a complex passage, works through a mathematical equation, or analyzes a primary source, they must stop frequently to verbalize their internal dialogue. This might involve using strategic planning language like, "I'm thinking I should use the quadratic formula here because the equation is set to zero," or demonstrating monitoring and correction by saying, "That word, 'ephemeral,' sounds like it means brief, so I’m going to pause and look that up to make sure I understand the context," or making connections: "The author just described the main character as restless. That connects to the idea I read earlier about his lack of a stable job. I wonder if this will lead to him leaving town." Once modeled, the teacher must transition students to practicing the strategy, perhaps through paired activities known as Reciprocal Think-Alouds, before expecting independent use.

A second practical technique is the Self-Explanation Prompt. This method strategically inserts verbalization breaks into a learning task to force metacognitive reflection and is particularly useful in technical subjects. Implementation begins by identifying key moments in a text, problem set, or lab procedure where a deeper understanding is absolutely necessary before the student can proceed. At these pause points, the teacher provides students with specific open-ended questions they must answer aloud to themselves or in a brief reflection journal. Prompts should be targeted to specific cognitive functions, such as focusing on rationale ("Why did I choose this variable to isolate?"), demanding synthesis ("What is the main idea of this section in my own words?"), or explicitly asking for a connection ("How does this new concept relate to what we learned last week?"). For maximum impact, teachers should then encourage a "Think-Pair-Share" approach where students must first explain their logic to a partner, which solidifies the idea and provides practice in articulation before the whole class moves on.

Finally, the "Teach It Back" Method is a form of high-stakes verbal thinking rooted in the pedagogical principle that to teach a concept is to truly master it. In this strategy, a student is assigned the role of briefly "teaching" a key concept, a section of the reading, or a part of the homework to a small group, to the class, or even to an imaginary audience. The critical instruction given to the student is to explain the topic as simply as possible, perhaps using an analogy, metaphor, or non-technical language if appropriate. The student must translate complex, academic language into straightforward, accessible terms, which serves as the ultimate test of their own comprehension. The teacher should provide specific feedback not only on the accuracy of the content but also on the clarity and logical structure of the explanation, reinforcing the importance of effective verbal articulation as a measure of understanding. By integrating these verbal thinking strategies—modeling, prompting, and teaching back—educators are not just improving a single study skill; they are building the core components of the resilient and self-regulated learner, equipping students with the tools for lifelong, independent cognitive growth.

SOURCES
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press. (This source is foundational for the concepts of Private Speech and its role in Self-Regulation.)

MacLeod, C. M. (2011). The production effect: Better memory as a consequence of saying aloud during study. Applied Cognitive Psychology, 25(2), 195–204. (This research provides the physiological basis for the Production Effect and memory benefits.)

Chi, M. T. H. (2013). Self-explanation: The effects of talking aloud or writing on learning. Topics in Cognitive Science, 5(1), 1–4. (This source details the mechanism and benefits of Self-Explanation for deep comprehension.)

Berk, L. E. (1992). The role of private speech in the development of mental processes. Psychological Review, 99(4), 779–795. (This provides contemporary developmental research supporting and elaborating on Vygotsky’s observations of private speech.)

Hello AI, I Am Julia

ronkowitz@gmail.com (Kenneth Ronkowitz) — Fri, 19 Feb 2021 14:00:00 +0000

Julia for data visualization

A few friends and former students who are working as programmers have told me recently that I should write about Julia. Julia is not a person but a language. One person called this "the new Python" while another said it was the "Python killer."

Python is the so-far-unchallenged leader of AI programming languages and is used by almost 90% of data scientists, but it is probably not the future of machine learning. Programming languages, like all languages, fall out of favor and sometimes die. There is not much demand for the COBOL, FORTRAN and BASIC that was being taught when I was an undergrad.

Julia is faster than Python because it is designed to quickly implement the math concepts like linear algebra and matrix representations. It is an open source project with more than a thousand contributors and is available under the MIT license with the source code available on GitHub.

I have learned that you don’t need to know programming to do some AI. There are no-code AI tools like Obviously.AI, but programming is necessary for some devlopment.

The home site for Julia is julialang.org which has a lot of information.

An article I read at pub.towardsai.net led me to investiagte a free online course on computational thinking at MIT that is taught using Julia.

Introduction to Computational Thinking with Julia, with Applications to Modeling the COVID-19…

This half-semester course introduces computational thinking through applications of data science, artificial…

ocw.mit.edu

This is not a course on programming with Julia but almost all data and AI courses are taught in Python (perhaps a few using R and other languages) so this is unique as a course. The course itself uses as its topic the spread of COVID-19.and includes topics on analyzing COVID-19 data, modeling exponential growth, probability, random walk models, characterizing variability, optimization and fitting to data. Through this topic the course teaches how to understand and model exponential functions. That has much broader application into financial markets, compound interest, population growth, inflation, Moore’s Law, etc.

Julia used for scientific computing

As that article notes, right now searching jobs on LinkedIn for “Python Developer” will turn up about 23,000 results, so there is a market for that skill set now. Searching “Julia Developer” will return few results now. You can find a LinkedIn group for Julia developers, called “The Julia Language,” so interest is there and the jobs are beginning to appear. A Julia specialits now has a big advantage in that there are fewer people with that skillset for the jobs that are appearing. The predictions (always a dangerous thing) are that Julia has a big role to play in the data & AI industry.

The Reading Level of Your Readers

ronkowitz@gmail.com (Kenneth Ronkowitz) — Fri, 07 Aug 2020 11:00:00 +0000

Writing online, I am kind of guessing about who are my readers. I know where they come from geographically and I know how they find me in a search and what articles they read and other analytics. I don't know what their reading level might be and every writing course will tell you that you "need to know your audience."

I make some assumptions that readers of a blog about technology and learning are mostly educators and so I further assume that they have a high school and above reading level. But how do you determine the reading level of what you are writing?

If you write in Microsoft Word, it is simple to use two major readability tests that are built-in: the Flesch Reading Ease and Flesch-Kincaid Grade Level.

For the Flesch Reading Ease and Flesch-Kincaid Grade Level statistics to come be part of the “Spelling & Grammar” review of your content, you will need to enable those statistics. To do this select “File” then “Options” next go to the “Proofing” tab and check the box that says “Show readability statistics.”

Flesch-Kincaid scores are readability tests designed to show how easy or difficult a text is to read. This score is given in two different ways. First is the “Flesch Reading Ease” number which ranges from 0 to 100. With a score of 90-100, your writing could be understood by an average 11-year old and a score of 60-70 could be understood by average 13 to 15-year olds. A score of zero to 30 means your writing could be understood by a university graduate. A bit counterintuitively, the higher the score the easier the writing is to read and comprehend.

For comparison, Time magazine averages at a score of 52 and the Harvard Law Review falls somewhere in the low 30s.

The Flesch-Kincaid Grade Level applies a reading grade level to your writing. I learned many years ago that most general news articles in The New York Times have a tenth-grade reading level. Romance novels have about a fifth-grade reading level.

I ran a recent article here through the test and got the results shown below. The Reading Ease score is about 55 and a Grade Level a tenth-grader in the middle of sophomore year.

You might think that score seems to be low for a post I am aiming at educators, but many sources will recommend that ease of reading in order to boost your numbers and even in your emails and communications. I know that some researchers have said that your response rate varies by reading level. The article linked here claims that emails written at a 3rd-grade reading level were optimal with a 36% boost over emails written at a college reading level and a 17% higher response rate than emails written even at a high school reading level.

When Microsoft Outlook and Word finish checking the spelling and grammar, you can choose to display information about the reading level of the document using the Flesch Reading Ease test and the Flesch-Kincaid Grade Level test. You can also set your proofreading settings to flag things like jargon, which is often what pushes ease aside and pushes readers to leave.

This may sound like advice to "dumb down" your writing. I don't think it is that. The English major part of me is reminded of Ernest Hemingway's journalistic simplicity. You can still get across deep ideas in simple language. I like the Einstein quote “Everything should be made as simple as possible,
but not simpler.”

Serendipities

ronkowitz@gmail.com (Kenneth Ronkowitz) — Tue, 05 Feb 2019 14:15:00 +0000

“Serendipity is looking in a haystack for a needle and discovering a farmer’s daughter.” - Julius Comroe

Umberto Eco's book, Serendipities: Language and Lunacy, is not a book about education or technology. It is about some riddles of history and the "linguistics of the lunatic." I am an Umberto Eco reader and first noticed him, as many people did, with his novel The Name of the Rose.

That novel takes place in 1327 in an Italian Franciscan abbey that is suspected of heresy. Brother William of Baskerville arrives to investigate and the story is a medieval mystery with a series of seven murders. Eco is

and he mixes in Aristotle, Thomas Aquinas and Roger Bacon. There are secret symbols and coded manuscripts in a higher level version of the Dan Brown novel formula.

I was partially attracted to Serendipities because of the title, but it's not an easy to read novel, but rather a non-fiction study.

Eco looks at mistakes that have shaped human history. For example, Christopher Columbus assumed that the world was much smaller than it is, land so he assumed he could find a quick route to the East via the West. He was wrong, but he accidentally "discovered" America.

Cults such as the Rosicrucians and Knights Templar seem to have resulted from a mysterious starting place that was a hoax. That kind of start made both groups ripe for conspiracy theories based on religious, ethnic, and racial prejudices.

Eco posits that serendipities and mistaken ideas can have fortuitous results.

On The Writer's Almanac, there was a nice short history of serendipity, parts of which I have also written about here. The word “serendipity” was first coined in 1754, and is now defined by Merriam-Webster as “the faculty or phenomenon of finding valuable or agreeable things not sought for.”

“Serendipity” was first used by parliament member and writer Horace Walpole in a letter that he wrote to an English friend who was spending time in Italy. In the letter to his friend written on this day in 1754, Walpole wrote that he came up with the word after a fairy tale he once read, called “The Three Princes of Serendip,” explaining, “as their Highnesses travelled, they were always making discoveries, by accidents and sagacity, of things which they were not in quest of.” The three princes of Serendip hail from modern-day Sri Lanka. “Serendip” is the Persian word for the island nation off the southern tip of India, Sri Lanka.

The invention of many wonderful things have been attributed to “serendipity,” including Kellogg’s Corn Flakes, Charles Goodyear’s vulcanization of rubber, inkjet printers, Silly Putty, the Slinky, and chocolate chip cookies.

Alexander Fleming discovered penicillin after he left for vacation without disinfecting some of his petri dishes filled with bacteria cultures; when he got back to his lab, he found that the penicillium mold had killed the bacteria.

Viagra had been developed to treat hypertension and angina pectoris; it didn’t do such a good job at these things, researchers found during the first phase of clinical trials, but it was good for something else.

The principles of radioactivity, X-rays, and infrared radiation were all found when researchers were looking for something else.

A U.K. translation company put "serendipity" on a list of the English language’s ten most difficult words to translate along with plenipotentiary, gobbledegook, poppycock, whimsy, spam, and kitsch.

In Eco's intellectual history of serendipities, he includes dead ends and mistakes that were not fortuitous. Leibniz believed that the I Ching illustrated the principles of calculus. Marco Polo identified a rhinoceros as the mythical unicorn.

Eco then turns to how language tried to "heal the wound of Babel." But throughout the Middle Ages and the Renaissance, various languages were held up as the first language that God gave to Adam. Greek, Hebrew, Chinese, and Egyptian were alternately seen as the starting place for language.

These essays by Umberto Eco are prefaced with his conclusion that serendipity is the positive outcome of some ill-conceived idea.

Poetry and the Presidency

ronkowitz@gmail.com (Kenneth Ronkowitz) — Mon, 14 Jan 2019 17:22:00 +0000

I originally posted this at Poets Online and reposted it here in 2008, but it seems like something that might need to be read again in 2019.

I read in a post on the Library of Congress blog that in 1982, when Barack Obama was a 19-year-old student at Occidental College, he had 2 poems published in the spring issue of the school's literary magazine of the time.

Here's one of those poems:

Underground

Under water grottos, caverns
Filled with apes
That eat figs.
Stepping on the figs
That the apes
Eat, they crunch.
The apes howl, bare
Their fangs, dance,
Tumble in the
Rushing water,
Musty, wet pelts
Glistening in the blue.

Obama is taking on a job that is incomprehensibly difficult to most of us. I'm delighted that he even wrote poetry as a student, and I hope that it may still have a place in his life as reader and writer. But I'm surprised by the "analysis" that these two poems have been given in the press and online lately. (I know some of you are saying that I'm naive for even being surprised.)

The second poem, "Pop," is reported to be about his maternal grandfather, Stanley Dunham.

Pop

Sitting in his seat, a seat broad and broken
In, sprinkled with ashes,
Pop switches channels, takes another
Shot of Seagrams, neat, and asks
What to do with me, a green young man
Who fails to consider the
Flim and flam of the world, since
Things have been easy for me;
I stare hard at his face, a stare
That deflects off his brow;
I’m sure he’s unaware of his
Dark, watery eyes, that
Glance in different directions,
And his slow, unwelcome twitches,
Fail to pass.
I listen, nod,
Listen, open, till I cling to his pale,
Beige T-shirt, yelling,
Yelling in his ears, that hang
With heavy lobes, but he’s still telling
His joke, so I ask why
He’s so unhappy, to which he replies...
But I don’t care anymore, cause
He took too damn long, and from
Under my seat, I pull out the
Mirror I’ve been saving; I’m laughing,
Laughing loud, the blood rushing from his face
To mine, as he grows small,
A spot in my brain, something
That may be squeezed out, like a
Watermelon seed between
Two fingers.
Pop takes another shot, neat,
Points out the same amber
Stain on his shorts that I’ve got on mine, and
Makes me smell his smell, coming
From me; he switches channels, recites an old poem
He wrote before his mother died,
Stands, shouts, and asks
For a hug, as I shink, my
Arms barely reaching around
His thick, oily neck, and his broad back; ‘cause
I see my face, framed within
Pop’s black-framed glasses
And know he’s laughing too.

Someone asked Harold Bloom at Yale University to review it and he said it was “not bad—a good enough folk poem with some pathos and humor and affection... It is not wholly unlike Langston Hughes, who tended to imitate Carl Sandburg" and further says it is much superior to the poetry of former President Jimmy Carter whom Bloom calls "literally the worst poet in the United States."

I never knew critics were so interested (or tough!) on poetry in college literary magazines.

I picked up a book of Jimmy Carter's poetry in the library a few years ago, and I recall liking a few poems about fishing that were there. Great poetry? No. The worst poetry? Definitely not.

Presidents taking their chances on writing poetry is not without precedent.

How about this acrostic poem by George Washington?

From your bright sparkling Eyes, I was undone;
Rays, you have, more transparent than the sun,
Amidst its glory in the rising Day,
None can you equal in your bright array;
Constant in your calm and unspotted Mind;
Equal to all, but will to none Prove kind,
So knowing, seldom one so Young, you'l Find
Ah! woe's me that I should Love and conceal,
Long have I wish'd, but never dare reveal,
Even though severely Loves Pains I feel;
Xerxes that great, was't free from Cupids Dart,
And all the greatest Heroes, felt the smart.

John Tyler wrote several poems that have survived. One was written when his three-month old daughter Anne died in July 1825. Here are the opening stanzas to that elegy:

Oh child of my love, thou wert born for a day;
And like morning's vision have vanished away
Thine eye scarce had ope'd on the world's beaming light
Ere 'twas sealed up in death and enveloped in night.

Oh child of my love as a beautiful flower;
Thy blossom expanded a short fleeting hour.
The winter of death hath blighted thy bloom
And thou lyest alone in the cold dread tomb. . . . [4]

And we also have the precedent for the inclusion of poetry at Presidential inaugurals. Robert Frost recited "The Gift Outright" (PBS transcript) at John F. Kennedy's 1961 inaugural. (Frost actually recited that poem from memory because he was unable to read the text of "Dedication" (PBS transcript) which he had written for the occasion because the sun was in his eyes. (video of Frost reading "The Gift Outright" at Kennedy's inauguration)

Maya Angelou read "On the Pulse of Morning" at Bill Clinton's 1993 inaugural. (video of the reading) James Dickey read ''The Strength of Fields'' at Jimmy Carter's 1977 inaugural gala at the Kennedy Center.

Are any of you with me on thinking that having a President that reads, writes or at least has written and read poetry at some point is a GOOD thing?

Teaching the Language and Grammar of Film

ronkowitz@gmail.com (Kenneth Ronkowitz) — Tue, 23 Oct 2018 19:00:00 +0000

The past few years, I have gotten back into teaching filmmaking. When I was doing graduate work in media with a focus on film and video, I came to believe that films can be treated as "texts" and that they can be "read" and analyzed, as I had done in my undergraduate studies in literature.

If films can be read like texts, then the language that films use must also have a kind of grammar that can explain its structures.

Roger Ebert used to do "shot at a time" workshop where he would examine a film closely. A film, like a novel, is very controlling. I think a film is even more controlling than a novel. When I read The World According to Garp, I had an idea about how Garp looked. My original sense was he looked like the author, John Irving. But after I saw the film version, Garp became - and still is - Robin Williams. Atticus Finch is Gregory Peck. When you watch a film, you only see what the camera’s eye shows us. The director, editor, cinematographer, actors, set designers, costumers and many others control (and at times manipulate) viewers.

Knowing about the grammar of film allows you understand how that is done and can give you back some control over the way the film works. Part of the grammar is knowing the reasons why a long shot, medium shot, close up, or an extreme close up was chosen. Studying the language and grammar of the shot, the grammar of the edit will make you consider whether a high angle, a low angle, or eye level is used. Is the camera being objective or subjective? When the camera is subjective, we become one of the characters, and that can be like reading a first-person narrated novel. How does the pace of the edit affect an audience?

Citizen Kane offers many opportunities to illustrate film grammar

Every language teacher talks about composition. Every film teacher talks about the composition of shots and scenes. Look at how the director has arranged actors, objects and lighting.

Besides showing and discussing films, to teach the grammar of film you should really have students make films. Otherwise, you are teaching grammar in isolation. I learned through decades of teaching writing that grammar should be taught along with writing. Teaching grammar in isolation is not only boring, it is not effective.

You can start to teach students to make films on paper. Not every teacher has access to filmmaking gear - although today, many students are carrying a video camera in their pocket that is many times more powerful than the Super8 film cameras and video camcorders I first used in classes when I started teaching. Then and now, I have students use storyboarding as a way to really think about shots and angles and building a scene.

A wonderful "side effect" of teaching how to read a film and make a film is that it fosters critical thinking.

I recently discovered Pixar in a Box which is a behind-the-scenes look at how Pixar artists do their jobs. It allows you to animate bouncing balls, build a swarm of robots, and make virtual fireworks explode. The program connects to math, science, computer science, and humanities in very natural ways. The project is a collaboration between Pixar Animation Studios and Khan Academy and is sponsored by Disney.

One part of the Art of Storytelling section is on the grammar of film.

Basic Shot Types

Get Deeper Into This

How To Read a Film

Film Studies

Film Analysis

ELIZA and Chatbots

ronkowitz@gmail.com (Kenneth Ronkowitz) — Mon, 22 Jan 2018 13:33:00 +0000

I first encountered a chatterbot, it was ELIZA in the first computer lab in the junior high school where I taught in the 1970s.

ELIZA is an early natural language processing program that came into being in the mid-1960s at the MIT Artificial Intelligence Laboratory. The original was by Joseph Weizenbaum, but there are many variations on it.

This was very early artificial intelligence. ELIZA is still out there, but I have seen a little spike in interest because she was featured in an episode of the TV show Young Sheldon. The episode, "A Computer, a Plastic Pony, and a Case of Beer," may still be available at www.cbs.com. Sheldon and his family become quite enamored by ELIZA, though the precocious Sheldon quickly realizes it is a very limited program.

ELIZA was created to demonstrate how superficial human-to-computer communications were at that time, but that didn't mean that when it was put on personal computers, humans didn't find it engaging. Sure, kids had fun trying to trick it or cursing at it, but after a while you gave up when it started repeating responses.

The program in all the various forms I have seen it still uses pattern matching and substitution methodology. She (as people often personified ELIZA), gives canned responses based on a keyword you input. If you say "Hello," she has a ready response. If you say "friend," she has several ways to respond depending on what other words you use. Some early users felt they were talking to "someone" who understood their input.

ELIZA was one of the first chatterbots (later clipped to chatbot) and a sample for the Turing Test. That test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human, is not one ELIZA can pass by today's standards. ELIZA fails very quickly if you ask her a few complex questions.

The program is limited by the scripts that are in the code. The more responses you gave her, the more variety there will be in her answers and responses. ELIZA was originally written in MAD-Slip, but later versions were often in JavaScript or other languages. Many variations on the original scripts were made as amateur coders played around with the fairly simple code.

One variation was called DOCTOR and it was meant to be a crude Rogerian psychotherapist who likes to "reflect" on your questions by turning the questions back at the patient. This was the version that I worked with my students when I taught middle school. They found it fascinating and my little programming club decided to hack the code and make their version.

Are chatbots useful to educators? They have their uses, though I don't find most of those applications to be things that will change education in ways I want to see it change. I would like to see them used for things like e-learning support and language learning,

If you want to look back at an early effort, you can try a somewhat updated version of ELIZA that I used in classes (if it still lives online on my old NJIT website) and get some "advice" from my "doctor."

It's Not the Singularity Just Yet

ronkowitz@gmail.com (Kenneth Ronkowitz) — Tue, 10 Oct 2017 13:00:00 +0000

There were some alerts this past summer that made it sound like an artificial intelligence (AI) system being developed at Facebook was taking over the world. At least that is what some anti-AI folks seemed to be saying.

The story seemed to be that the AI had started its own conversation between two AI agents developed inside Facebook. They were speaking to each other in plain English. The revelation to the researchers was that because of a mistake in programming the AI had created its own language. It developed a system of code words to make communication more efficient. The researchers shut the system down when they realized it was no longer using English - and they didn't understand what the two agents were saying.

The "singularity" (at least the tech one, not the mathematical or gravitational versions) is the point hypothesized when an upgradeable artificial intelligence will enter a "runaway reaction" of self-improvement cycles. It improves itself to the point of being a superintelligence that surpasses human intelligence. It's when the machines are smarter than us. John von Neumann first used the term "singularity" back in the 1950s i talking about technological progress causing accelerating change.

Why is Facebook messing around with this? For one thing, they want to build chatbots that can have conversations and negotiate with humans in a way that mimics human responses so that they can then make decisions on their own.

Does that scare you?

Facebook was trying to get the chatbots working with a "partner" to divide up several objects that had different numerical points value. That requires negotiation to work out the best way to divide the objects and accumulate the highest possible number of points.

The event is not the first example of AI diverging from its training in English to develop its own language. The new language is nonsense to humans but has semantic meaning when interpreted by AI agents.

A chatbot (like the ones shown conversing above) repeating "to me" five times might mean to run a routine five times. It's shorthand. A + B = C is the kind of unsophisticated math we can easily understand, but to the computer the “A” could mean thousands of line of code and that is when we are lost.

It's not that the Facebook chatbots gave up on using English in order to hide from the human observers, it was just more efficient to use another language.

The scary factor is that when Bob the chatbot says "I can can I I everything else” and chatbot Alice replies “Balls have zero to me to me to me to me to me to me to me to me to” we really don't know what they are saying.

At the OpenAI artificial intelligence lab founded by Elon Musk, they experimented with letting AI bots learn their own languages and it worked. This strikes fear in the hearts of many people, but there's not enough evidence to determine whether AI presents a real threat that could enable machines to overrule their operators.

The team that works on Google Translate believes that the AI created the most efficient solution to some problems.

The singularity is not here yet, but it is coming.