“The Robo-Raconteur” – a StoryAlity Theory Artificial-Writer computer-program
So, I love all things: Computational Creativity…
(September 2021 update: Some great computational creativity work, shown at):
2018 Update: As of April 2018, I have a journal article out, which is online, here.
Velikovsky, J. T. (2017). Introducing `The Robo–Raconteur‘ Artificial Writer – Or: Can a Computer Demonstrate Creativity? in the International Journal of Art, Culture and Design Technologies, 6(2), 28-54.
(…If desired, please feel free to read the article, and try out the Robo-Raconteur yourself, and maybe even do the 10-minute online survey! (i.e., On: Did you think that the outputs of the artificial-writing-program was: creative? Or, not?)
For more on extreme (i.e., genius-level) creativity, if of interest – maybe also see my article (March 2018) in The Journal of Genius and Eminence. As a member of The Newcastle School of Creativity, I am a big fan of the 4C model of creativity (Kaufman & Beghetto, 2009, 2013, etc) – it helps a lot, with, classifying – and evaluating – computational creativity…! In that (2018) JoG&E article, I also combined the 4-C model (Kaufman & Beghetto, 2009, 2013) and Simonton’s `boldface Big-C Creativity’ category (i.e., eminent-genius-level creativity, like say a Darwin, Einstein, Marie Curie, Jane Austen, etc), to show, `the 5C model’ of creativity… (but – am sure there are more categories that can be nuanced, within the 4-C, or even, perhaps a 5-C model… just, a handy classification/taxonomy!)
& just a random sampling, of some fun CC (Computational Creativity) `Technological Wonders’ …
(Side Note …In AI, there is a distinction drawn between (1) `Strong CC’ (i.e., autonomous AI-CC smart systems), versus, (2) `Co-creative CC’ (i.e., involving a human partner, and, augmenting human creativity…)
For some fun applications of Computational Creativity (CC) that are already out there:
LoFi-Player (Vibert Theo, 2020)
Quick, Draw! (a Pictionary-game style, AIML [Artificial Intelligence Machine Learning] drawing/sketch-recognizer)
Visit: Quick, Draw!
Random 2022 AI News:
& more cool stuff:
Evolution Sim: https://keiwan.itch.io/evolution
(inspired by the great Borges story!)
Check out all those books… just like DNA, reshuffling over the aeons… 🙂
(see also the great evolutionary philosophy book: Darwin’s Dangerous Idea, Dennett 1995)
Also – as of, 25th Oct 2018 – an AI artwork sells for $432,500 at Christie’s of NY … (!!!)
…And, maybe see: AIVA, the AI music composer
Maybe even listen to: Music By Robots, on Radio National’s Big Ideas (2019)…
And check out Philosopher AI. (GPT-3)…
And an AI-comedy-chatbot-duo (with, an audience-member heckler!) made by my PhD supervisor, Dr Michael Meany:
And a book-chapter by Dr Michael Meany on Atomic & Romeo:
Meany, M. (2016). Comedy, Creativity, Agency: The Hybrid Individual. In McIntyre P., Fulton J., & Paton E. (Eds.), The Creative System in Action. Palgrave Macmillan. https://doi.org/https://doi.org/10.1057/9781137509468_13
& for a “blast from the past” – here’s, an older AT&T / Bell Labs video, from the 1950s: Claude Shannon demonstrates machine learning (with: Theseus the maze-solving robot-mouse)
In Shannon’s words, Theseus was: “a demonstration device to make vivid the ability of a machine to solve, by trial and error, a problem – and remember the solution.” (Shannon in Soni & Goodman 2018, p. 206)
See also, the great book:
Soni, J., & Goodman, R. (2018). A Mind At Play: How Claude Shannon Invented the Information Age. Simon & Schuster.
And so – here’s (i.e. below) a more informal discussion of these topics:
So, a great question to ask:
…Can computers be creative-?
Answer: Yes. Or, No. Or Maybe.
Depends who you ask, and, what definition and what criteria of creativity they are using. And whether they understand what computers and algorithms are, and what they can do. (Organisms are algorithms, see Harari (2017), Homo Deus) Also – it depends, How good they are, at actually judging all that stuff! (See D K Simonton’s point on creativity, about: `Who is to judge The Judges?’)
`There is some debate about what judges should be told (Runco 1989) and about how judges should be selected. As Murray (1959) put it, who is to judge the judges? And the judges of the judges? There is even controversy about the need for agreement (and reliability) among judges. Csikszentmihalyi and Getzels (1970) proposed that some disagreement is useful for it indicates that the judges are covering various perspectives. The problem is that any disagreement will lower estimates of reliability.’
(Simonton in The Handbook of Creativity ed: Sternberg 1999, p. 87)
Either way, the definition that I use is: the standard bipartite definition of creativity (Runco & Jaeger 2012), and I also like the tripartite definition: new, useful & surprising (as per, Bruner, Boden, Simonton).
Also by the way – if you didn’t know, this punctuation symbol is an interrobang: an exclamation-mark combined with a question mark.
And so, here is a startling quote about what a “creative” product is, from the great creativity researcher Colin Martindale (1990):
`Ultimately, all creative products have this quality: old ideas or elements are combined in new ways. This is the case for all domains of creativity.’
(Martindale, 1989, p. 212).
Note how, the interrobang is also a combination of two old things into a new thing, and, it works…(!)
Anyway – so – to the question: Can Computers Be Creative?
For a Longish Answer – Read this great book, by creativity researcher Margaret Boden, in particular, chapters Five (5), through Eight (8)-!
i.e. Sometimes, somewhat-complex questions – with detailed answers – often don’t have short, snappy, `general’ answers, that are very useful.
Also – a shorter answer – read this whole book, but, particularly pages 147-8 on “Artificial Writers” (computer programs)…!
Also, if you want to understand my inspirations and “the thinking” here, then maybe read the last 10 pages of this (pp. 408-416): (or even better still, read the whole thing)!
And – read all of this:
Check out this terrific podcast about the above book:
In the opening chapter, Tegmark theorizes about a possible future, where an AI program called Prometheus kicks in.
“Although Prometheus was astonishingly capable by Sunday morning, steadily raking in money from M[echanical] Turk, its intellectual abilities were still rather narrow: Prometheus had been deliberately optimized to design AI systems and write software that performed rather mind-numbing MTurk tasks.
It was, for example, bad at making movies—bad not for any profound reason, but for the same reason that James Cameron was bad at making movies when he was born: this is a skill that takes time to learn.
Like a human child, Prometheus could learn whatever it wanted from the data it had access to. Whereas James Cameron had taken years to learn to read and write, Prometheus had gotten that taken care of on Friday, when it also found time to read all of Wikipedia and a few million books.
Making movies was harder. Writing a screenplay that humans found interesting was just as hard as writing a book, requiring a detailed understanding of human society and what humans found entertaining.
Turning the screenplay into a final video file required massive amounts of ray tracing of simulated actors and the complex scenes they moved through, simulated voices, the production of compelling musical soundtracks and so on.
As of Sunday morning, Prometheus could watch a two-hour movie in about a minute, which included reading any book it was based on and all online reviews and ratings. The Omegas noticed that after Prometheus had binge-watched a few hundred films, it started to get quite good at predicting what sort of reviews a movie would get and how it would appeal to different audiences.
Indeed, it learned to write its own movie reviews in a way they felt demonstrated real insight, commenting on everything from the plots and the acting to technical details such as lighting and camera angles.
They took this to mean that when Prometheus made its own films, it would know what success meant.
The Omegas instructed Prometheus to focus on making animation at first, to avoid embarrassing questions about who the simulated actors were. On Sunday night, they capped their wild weekend by arming themselves with beer and microwave popcorn, dimming the lights and watching Prometheus’ debut movie.
It was an animated fantasy-comedy in the spirit of Disney’s Frozen, and the ray tracing had been performed by boxed Prometheus-built code in the Amazon cloud, using up most of the day’s $1 million MTurk profit. As the movie began, they found it both fascinating and frightening that it had been created by a machine without human guidance. Before long, however, they were laughing at the gags and holding their breath during the dramatic moments. Some of them even teared up a bit at the emotional ending, so engrossed in this fictional reality that they forgot all about its creator.”
And – I could get into loads more references of books that inspired me to build this AI-robot movie-pitcher (The Robo-Raconteur) – but, that’s a start.
Well okay then, one more – another great (also, big) book: Boden, M. A. (2008). Mind as Machine: A History of Cognitive Science. Oxford: Oxford University Press.
(I am currently only partway through reading this one (Boden 2006), but… it is a very long book!)
Also here is an interesting New Scientist article: Artificially intelligent painters invent new styles of art (29 Jun 2017).
And some interesting AIs here: 2016: The Year AI Got Creative (Haridy)
So, I built an Artificial-Writer computer-program (movie-pitcher & transmedia generator), that integrates some of StoryAlity Theory (as derived from my 2016 PhD study of creativity in movie creation).
And, it’s called “The Robo-Raconteur“. It looks like this –
A definition of that French-sounding word:
raconteur: (noun.): a person [or algorithm] who tells anecdotes in a skilful and amusing way.
(synonyms): storyteller, teller of tales, spinner of yarns, narrator, relater, [story-]recounter.
A 4 minute demo: (you just download the Excel file, run it, and press F9 (or, CTRL-R, for `regenerate’) a few times – and, click the 7 tabs along the bottom of the Excel worksheet and do the same… Easy-peasy!)
More info about it:
AN OLDER EXPLANATORY-ARTICLE ABOUT IT (DRAFT-ONLY, on Academia.edu)
A 40-page article, explaining what it is, and how it works, is online, here.
(The Short-Story: It generates, story pitches (including, `transmedia universes’), and then, it judges / `ranks’ them, into the best, and the worst.)
Important: on a PC, `F9′ key is `recalculate’ in Excel. On a Mac, it’s: Command + =
(More recently, CTRL-R has been integrated as a macro in the Excel spreadsheet, of the above doesn’t work for you)
DOWNLOAD THE ROBO-RACONTEUR (XLSM file)
You can download the artificial-writer-program (a 30-meg XLS file), here. (Yes, it’s safe. i.e. malware-free.) It’s an Excel file, with Macros in it.
Actually this XLS file is a 2019 update, which uses CTRL-R [for: `recalculate worksheet’] on pc (or Command-R on a Mac) instead of F9
AN ANONYMOUS 5-10 MIN ONLINE SURVEY, ABOUT IT ALL
And – you can even take a 5-minute survey about it (the Robo-Raconteur), here! (If desired).
THE 1-PAGE `INVITE & INSTRUCTIONS for The Robo-Raconteur (for very busy people, or even, bots)
Important: on a PC, `F9′ key is `recalculate’ in Excel. On a Mac, it’s: Command + =
Or try: CTRL-R (recalculate the worksheet)
*June 2017 – Update – There was a great interview about computational-creativity (and artificial-writers) on ABC Radio National on 1st June 2017, and you can hear it… here! Interview with Ross Goodwin (Creative Technologist) and Dave King (CEO & founder of Move37).
eg Ross was talking about this kind of stuff:
And for a more intense look at it, see, also:
Gillings, M., Hilbert, M., & Kemp, D. (2016). Information in the Biosphere: Biological and Digital Worlds. Trends in Ecology & Evolution, 31(3), 180-189.
And – another Update!
Listen to the full Spark Ep (53 mins), here! Or – sections of the Ep, below:
How an algorithm can help you make decisions (includes: computational kindness-! And, The Abeline Paradox…)
Can an algorithm be unfair? (on algorithmic bias!)
Can an algorithm detect sarcasm better than you? (Probably, yes…)
Weapons of Math Destruction (the Ethics of Big Data algorithms…!)
~ & Thanks for reading !!!
(…even if, you’re: a bot 🙂
Comments always welcome.
(well; unless, you’re: a bot..?)
PS – This story was also interesting: Researchers shut down AI that invented its own language (July 2017)
PPS – And, if Ethics & AI is of interest, perhaps, see also: The EthiSizer…
JT Velikovsky, PhD
& High-RoI Story/Screenplay/Movie and Transmedia Researcher
& Evolutionary Systems Analyst
& Human and Computer Creativity Researcher
& Million-selling Transmedia Writer
& Rural Firefighter
& Random Person*
*(as is everyone… who says all hominids are not created equal-?)
The above is (mostly) an adapted excerpt, from my (2016) doctoral thesis: “Communication, Creativity and Consilience in Cinema”. It is presented here for the benefit of fellow screenwriting, filmmaking and creativity researchers. For more, see https://aftrs.academia.edu/JTVelikovsky
JT Velikovsky is also a produced feature film screenwriter and million-selling transmedia writer-director-producer. He has been a professional story analyst for major film studios, film funding organizations, and for the national writer’s guild. For more see: http://on-writering.blogspot.com/
Can computers really be creative? Frankly it’s all a bit deliberately-ambiguous.
As, that’s what Martindale (1990) says it should be, if, you’re doing it right.
Boden, M. A. (2004). The Creative Mind: Myths and Mechanisms (2nd ed.). London; New York: Routledge.
Martindale, C. (1989). Personality, Situation and Creativity. In J. A. Glover, R. R. Ronning & C. R. Reynolds (Eds.), Handbook of Creativity: Perspectives on Individual Differences (pp. 211-232). New York; London: Plenum.
Runco, M. A., & Jaeger, G. J. (2012). The Standard Definition of Creativity. Creativity Research Journal, 24(1), 92-96.
Sawyer, R. Keith (2012), Explaining Creativity: The Science of Human Innovation (2nd ed. edn.; New York: Oxford University Press).
Simonton, D. K., (1999) `Experimental Studies of Creativity’ in (ed) Sternberg, R. J. (1999). Handbook of Creativity. Cambridge: Cambridge University Press.
Simonton, D. K. (2012). Taking the U.S. Patent Ofﬁce Criteria Seriously: A Quantitative Three-Criterion Creativity Deﬁnition and Its Implications. Creativity Research Journal, 24(2-3), 97–106.
Velikovsky, J. T. (2016). `Communication, Creativity and Consilience in Cinema: A comparative study of the top 20 Return-on-Investment (RoI) Movies and the Doxa of Screenwriting’. PhD Thesis, University of Newcastle, Australia. Retrieved from http://hdl.handle.net/1959.13/1324018
Velikovsky, J. T. (2016). `The Holon/Parton Theory of the Unit of Culture (or the Meme, and Narreme) in Science, Media, Entertainment and the Arts’, chapter in A. Connor & S. Marks (Eds.), Creative Technologies for Multidisciplinary Applications. New York: IGI Global.
Velikovsky, J. T. (2017). Chapter 405: The Holon/Parton Structure of the Meme, or, The Unit Of Culture. In M. Khosrow-Pour (Ed.), Encyclopedia of Information Science and Technology, Fourth Edition (pp. 4666-4678). New York: IGI Global.
Wilson, E. O. ( 1999). Consilience: The Unity of Knowledge (1st Vintage Books ed.). New York: Knopf: Random House; ebrary Inc.
PS – My current project (August 2017) is:
Creating an algorithm that is able to discover that it is an algorithm.
i.e. Examining: Can a computer be self-aware? (…Conscious of: Itself.)
(Actually it will be the algorithm, not the computer running the algorithm that’s self-aware, but, anyway.) Basically it just has to be able to figure out that, its own internal model of the world matches its external experience of the world… And that it has an internal model.
i.e.: What’s the shortest algorithm (ie system), that can discover its own algorithmic-ness. Algorithmicity. Sort of, Doug Hofstadter kinda stuff.
PPPS – I also like this talk, by Yuval Noah Harari.
TED TALK – Nationalism vs. globalism: the new political divide | Yuval Noah Harari
Also I like to think about, what could happen with The Technological Singularity. (When computer-AI outstrips human intelligence and consciousness, etc… and also – what if, the AI is autonomous and makes its own decisions? etc.)
Basically it could be terrific, or terrible or something in between or all of the above. Here’s a picture I drew.
On the left, is say: Roko’s Basilisk, who goes around killing everyone who didn’t help it ascend to godlike omnipotence. e.g. from RationalWiki:
`Roko’s basilisk is a thought experiment about the potential risks involved in developing artificial intelligence. The premise is that an all-powerful artificial intelligence from the future could retroactively punish those who did not help bring about its existence, including those who merely knew about the possible development of such a being. It resembles a futurist version of Pascal’s wager, in that it suggests people should weigh possible punishment versus reward and as a result accept particular singularitarian ideas or financially support their development. It is named after the member of the rationalist community LessWrong who first publicly described it, though he did not originate it or the underlying ideas.’
(Source: RationalWiki 2018. online)
And so, yeah; that’s just one example of how stuff could go seriously pear- shaped with AI. (There are many, many others, but I won’t get into it here.)
And so in the graph above, on the right, (i.e., one possible good outcome for us humanimals) we have, is what I call “OMNI”. (e.g. see: Omnibenevolence).
So – “OMNI” is a super-AI, who decides to solve all our problems for us, and help us humanimals. So – think of our problems, like say: poverty, war, inequality, injustice, humanimal-caused climate-change, overpopulation, overconsumption, the lack of Universal Basic Income, and also meme-conflict (i.e., ideas which conflict, eg – 2 or more religions that hate each others’ guts and want the others to die; or even, religions that get in the way of science, since all science is problem-solving, all life is doing science all the time) – etc.
And by the way – “intelligence” is just: problem-solving ability. Or another way to view it is: understanding. (see my paper on it from IE2014)
Anyway so – yeah. OMNI would really help us. (Omni may have to make some “hard” decisions, but they would only be hard for a humanimal – who doesn’t have all the information, nor well-designed decision-trees, and good (moral and ethical) values. Basically, Omni is kinda like “The Machine” in the Asimov short story, “The Evitable Conflict” (Asimov 1950).
Turns out, most of us `humanimals’ don’t even have the mental capacity to think of more than about 7 things at once (let alone thinking of, or simulating a system with 7 billion things at once, like the current humanimal population), and we humanimals also have lots of cognitive biases that Evolutionary Biology and Evolutionary Culturology put there… So – when you look at it this way, we humanimals actually need OMNI, and as soon as possible.
And so, if I was OMNI, I would create a Roko’s Basilisk anyway – and put it to work, wiping out all of those who got in the way of OMNI, as they are ethically-and-morally-responsible for, most of the problems anyway – and should be taken to task [executed] for that.
Nah; just kidding. – Or am I? I am not even sure sometimes. Am pretty sure this is all a parody and a satire. But wait, The Robo Raconteur is: real. So; Hmmm.)
Hey also – as mentioned above, maybe check out my article in The Journal of Genius and Eminence (2018). It talks about ethics and morals and values. I even have a graph of it, in there.
And if you like that kind of thing (ethics and morals and values), maybe see also, The EthiSizer.
Thanks for reading!
And, sorry that you now have heard of: Roko’s Basilisk. But hey, it was Religion where the idea first came from (if you know about one of the 4000 gods and don’t pick one, maybe you are going to 3,999 hells?), so, that’s why I subscribe to The Simulation Argument. and for me, Roko’s Basilisk is all part of the colour, magic and excitement of it all.
Maybe that’s why they call it (i.e. The Sim Argument) “Religion for Atheists”. (…It’s just an equal rights thing, mainly.)
Also I love this book:
In it he has this great chart:
Figure 1.1: The three stages of life: biological evolution, cultural evolution and technological evolution. Life 1.0 is unable to redesign either its hardware or its software during its lifetime: both are determined by its DNA, and change only through evolution over many generations. In contrast, Life 2.0 can redesign much of its software: humans can learn complex new skills—for example, languages, sports and professions—and can fundamentally update their worldview and goals. Life 3.0, which doesn’t yet exist on Earth, can dramatically redesign not only its software, but its hardware as well, rather than having to wait for it to gradually evolve over generations.
(Tegmark 2018, p. 26)
Anyway I highly commend that great book to you too.
I also think there’s a lot we can learn about humanimal creativity from studying animal creativity… see, the great book Animal Creativity (eds: Kaufman & Kaufman, 2015)…
Finally, I should note, the Robo-Raconteur reminds me of a section of Margaret Boden’s Mind As Machine: A History of Cognitive Science (2006) :
`Lull built several machines to embody this knowledge and reasoning.
They’re remembered today largely because—along with the Ars Magna itself—they inspired Gottfried Leibniz to build his calculating machine four centuries later…. They’d also inspired the famous/infamous Cornelius Agrippa (1486–1535), and the equally renowned and controversial John Dee (1527–1607)…
Jonathan Swift was less impressed, and put his famed talent for mockery into top gear. In Gulliver’s Travels, he described a professor in Laputa’s Lagado Academy who’d built a forty-handled frame that filled the room. The frame contained many squares of wood, linked by slender wires and carrying bits of paper displaying ‘‘all the words of their language, in their several moods, tenses, and declensions, but without any order’’. The order was provided by the professor’s forty students, who turned the iron handles at random. Whenever they found three or four words juxtaposed which could form part of a sentence, they told four students assigned as scribes to write the word strings down.
The professor’s intention, said Swift, was that:
“the most ignorant person at a reasonable charge, and with a little bodily labour, may write books in philosophy, poetry, politics, law, mathematics and theology, without the least assistance from genius or study.” (Swift 1726: 227)’
(Boden 2006, p. 56)