SHAPE is a new collective name for those subjects that help us understand ourselves, others and the human world around us. They provide us with the methods and forms of expression we need to build better, deeper, more colourful and more valuable lives for all.
From an Australian speaker at the INKE conference I learned about SHAPE or Social Sciences, Humanities & The Arts For People & The Economy. This is an initiative of the London School of Economics, the British Academy and the Arts Council of England. It is trying to complement the attention given to STEM fields. I like how they use the word shape in various assets as in:
Un manuale ampio ed esauriente che illustra tra teoria e prassi il tema dell’informatica umanistica per l’insegnamento e l’apprendimento universitario.
The publisher (Vita e Pensiero) kindly sent me a copy of Guido Milanese’s Filologia, letteratura, computer (Philology, Literature, Computer), an introduction to thinking about and thinking through the computer and texts. The book is designed to work as a text book that introduces students to the ideas and to key technologies, and then provides short guides to further ideas and readings.
The book focuses, as the title suggests, almost exclusively on digital filology or the computational study of texts. At the end Milanese has a short section on other media, but he is has chosen, rightly I think, to focus on set of technologies in depth rather than try a broad overview. In this he draws on an Italian tradition that goes back to Father Busa, but more importantly includes Tito Orlandi (who wrote the preface) and Numerico, Fiormonte, and Tomasi’s L’umanista digitale (this has been translated into English- see The digital humanist).
Milanese starts with the principle from Giambattista Vico that knowledge is made (verum ipsum factum.) Milanese believes that “reflection on the foundations identifies instruments and operations, and working with instruments and methods leads redefining the reflection on foundations.” (p. 9 – my rather free translation) This is virtuous circle in the digital humanities of theorizing and praxis where either one alone would be barren. Thus the book is not simply a list of tools and techniques one should know, but a series of reflections on humanistic knowledge and how that can be implemented in tools/techniques which in turn may challenge our ideas. This is what Stéfan Sinclair and I have been calling “thinking-through” where thinking through technology is both a way of learning about the thinking and about the technology.
An interesting example of this move from theory to praxis is in chapter 7 on “The Markup of Text.” (“La codifica del testo”) He moves from a discussion of adding metadata to the datafied raw text to Minsky’s idea of frames of knowledge as a way of understanding XML. I had never thought of Minsky’s ideas about articial intelligence contributing to the thinking behind XML, and perhaps Milanese is the first to do so, but it sort of works. The idea, as I understand it, goes something like this – human knowing, which Minsky wants to model for AI, brings frames of knowledge to any situation. If you enter a room that looks like a kitchen you have a frame of knowledge about how kitchens work that lets you infer things like “there must be a fridge somewhere which will have a snack for me.” Frames are Minsky’s way of trying to overcome the poverty of AI models based on collections of logical statements. It is a way of thinking about and actually representing the contextual or common sense knowledge that we bring to any situation such that we know a lot more than what is strictly in sight.
Frame systems are made up of frames and connections to other frames. The room frame connects hierarchically to the kitchen-as-a-type-of-room frame which connects to the fridge frame which then connects to the snack frame. The idea then is to find a way to represent frames of knowledge and their connections such that they can be used by AI systems. This is where Milanese slides over to XML as a hierarchical way of adding metadata to a text that enriches it with a frame of knowledge. I assume the frame (or Platonic form?) would be the DTD or Schema which then lets you do some limited forms of reasoning about an instance of an encoded text. The markup explicitly tells the computer something about the parts of the text like this (<author>Guido Milanese</author>) is the author.
The interesting thing is to refect on this application of Minsky’s theory. To begin, I wonder if it is historically true that the designers of XML (or its parent SGML) were thinking of Minsky’s frames. I doubt it, as SGML is descended from GML that predates Minsky’s 1974 Memo on “A Framework for Representing Knowledge.” That said, what I think Milanese is doing is using Minsky’s frames as a way of explaining what we do when modelling a phenomena like a text (and our knowledge of it.) Modelling is making explicit a particular frame of knowledge about a text. I know that certain blocks are paragraphs so I tag them as such. I also model in the sense of create a paradigmatic version of what my perspective on the text is. This would be the DTD or Schema which defines the parts and their potential relationships. Validating a marked up text would be a way of testing the instance against the model.
This nicely connects back to Vico’s knowing is making. We make digital knowledge not by objectively representing the world in digital form, but by creating frames or models for what can be digital known and then apply those frames to instances. It is a bit like object-oriented programming. You create classes that frame what can be represented about a type of object.
There is an attractive correspondence between the idea of knowledge as a hierarchy of frames and an XML representation of a text as a hierarchy of elements. There is a limit, however, to the move. Minsky was developing a theory of knowing such that knowledge could be artificially represented on a computer that could then do knowing (in the sense of complete AI tasks like image recognition.) Markup and marking up strike me as more limited activities of structuring. A paragraph tag doesn’t actually convey to the computer all that we know about paragraphs. It is just a label in a hierarchy of labels to which styles and processes can be attached. Perhaps the human modeller is thinking about texts in all their complexity, but they have to learn not to confuse what they know with what they can model for the computer. Perhaps a human reader of the XML can bring the frames of knowledge to reconstitute some of what the tagger meant, but the computer can’t.
Another way of thinking about this would be Searle’s Chinese room paradox. The XML is the bits of paper handed under the door in Chinese for the interpreter in the room. An appropriate use of XML will provoke the right operations to get something out (like a legible text on the screen) but won’t mean anything. Tagging a string with <paragraph> doesn’t make it a real paragraph in the fullness of what is known of paragraphs. It makes it a string of characters with associated metadata that may or may not be used by the computer.
Perhaps these limitations of computing is exactly what Milanese wants us to think about in modelling. Frames in the sense of picture frames are a device for limiting the view. For Minsky you can have many frames with which to make sense of any phenomena – each one is a different perspective that bears knowledge, sometimes contradictory. When modelling a text for the computer you have to decide what you want to represent and how to do it so that users can see the text through your frame. You aren’t helping the computer understand the text so much as representing your interpretation for other humans to use and, if they read the XML, re-interpret. This is making a knowing.
Milanese, G. (2020). Filologia, Letteratura, Computer: Idee e strumenti per l’informatica umanistica. Milan, Vita e Pensiero.
Minsky, M. (1974, June). A Framework for Representing Knowledge. MIT-AI Laboratory Memo 306. MIT.
Searle, J. R. (1980). “Minds, Brains and Programs.” Behavioral and Brain Sciences. 3:3. 417-457.
On Twitter someone posted a link to a 1944 OSS Simple Sabotage Field Manual. This includes simple, but brilliant advice on how to sabotage organizations or conferences.
This sounds a lot like what we all do when we academics normally do as a matter of principle. I particularly like the advice to “Make ‘speeches.'” I imagine many will see themselves in their less cooperative moments in this list of actions or their committee meetings.
The OSS (Office of Strategic Services) was the US office that turned into the CIA.
Whatever happened to The Last One software? The Last One (TLO) was a “program generator” that was supposed to take input from a user who wasn’t a programmer and be able to generate a BASIC program.
TLO was developed by a company called D.J. “AI” Systems Ltd. that was set up by David James who became interested in artificial intelligence when he bought a computer for his business, and apparently got so distracted that he was bankrupted by that interest (and lost his computers). It was funded by an equally colourful character, Scotty Bambury who made his money as a tire dealer in Somerset. (See here and here.)
The name (The Last One) refers to the expectation that this would be the last software you would need to buy. As the cover image above shows, they were imagining programmers being put out of work by an AI that could reprogram itself. TLO would be the last software you had to buy and possibly the first AI capable of recursively improving itself. DJ AI could have been spinning up the seed AI that could lead to the singularity!
Here is some of the text from an ad for TLO. The text ran under the spacey headline at the top of this post.
The first program you should buy. …
THE LAST ONE … The program that writes programs!
Now, for the first time, your computer is truly ‘personal’. Now, simply and easily, you can create software the way you want it. …
Yet another sense of “personal” in “personal computer” – a computer where all your software (except, of course, TLO) is personally developed. Imagine a computer that you trained to do what you needed. This was the situation with early mainframes – programmers had to develop the applications individually for each system, they just didn’t have TLO.
“Demoskene is an international community focused on demos, programming, graphics and sound creatively real-time audiovisual performances. [..] Subculture is an empowering and important part of identity for its members.”
In a previous blog post I argued that ICH is a form of culture that would be hard to digitize by definition. I could be proved wrong with Demoscene. Or it could be that what makes Demoscene ICH is not the digital demos, but the intangible cultural scene, which is not digital.
Either way, it is interesting to see how digital practices are also becoming intangible culture that could disappear.
You can learn more about Demoscene from these links:
As most of you know, I left Uber in December and joined Stripe in January. I’ve gotten a lot of questions over the past couple of months about why I left and what my time at Uber was like. It’s a strange, fascinating, and slightly horrifying story that deserves to be told while it is still fresh in my mind, so here we go.
MacRumors has a story about how today is the 36th anniversary of the unveiling of the Macintosh. See 36 Years Ago Today, Steve Jobs Unveiled the First Macintosh. At the time I was working in Kuwait and had a Apple II clone. When a Macintosh came to a computer store I went down with a friend to try it. I must admit the Graphical User Interface (GUI) appealed to me immediately despite the poor performance. When I got back to Canada in 1985 to start graduate school I bought my first Macintosh, a 512K with a second disk drive. Later I hacked a RAM upgrade and got a small hard drive. Of course now I regret selling the computer to a friend in order to upgrade.
the purpose aimed at by Mantegna and Pozzo was not so much “to simulate stereopsis”—the process by which we see depth—but rather to achieve “a simulation of the perceptual effect of stereoptic vision.” Far from being visual literalists, these painters were literal illusionists—their aim was to make their audiences see something that wasn’t there.
CABINET has a nice essay by Margaret Wertheim connecting Bacon to Renaissance perspective to video games, The Illusionistic Magic of Geometric Figuring. Wertheim argues that starting with Roger Bacon there was a growing interest in the psychological power of virtual representation. Artists starting with Giotto in Assisi the Mantegna and later Pozzo created ever more perspectival representations that were seen as stunning at the time. (Pozzo painted the ceiling of St. Ignatius Being Received into Heaven in Sant’Ignazio di Loyola a Campo Marzio, Rome.)
The frescos in Assisi heralded a revolution both in representation and in metaphysical leaning whose consequences for Western art, philosophy, and science can hardly be underestimated. It is here, too, that we may locate the seed of the video gaming industry. Bacon was giving voice to an emerging view that the God of Judeo-Christianity had created the world according to geometric laws and that Truth was thus to be found in geometrical representation. This Christian mathematicism would culminate in the scientific achievements of Galileo and Newton four centuries later…
Wertheim connects this to the ever more immersive graphics of the videogame industry. Sometimes I forget just how far the graphics have come from the first immersive games I played like Myst. Whatever else some games do, they are certainly visually powerful. It often seems a shame to have to go on a mission rather than just explore the world represented.
The Computer Literacy Project, on the other hand, is what a bunch of producers and civil servants at the BBC thought would be the best way to educate the nation about computing. I admit that it is a bit elitist to suggest we should laud this group of people for teaching the masses what they were incapable of seeking out on their own. But I can’t help but think they got it right. Lots of people first learned about computing using a BBC Micro, and many of these people went on to become successful software developers or game designers.
I’ve just discovered Two-Bit History (0b10), a series of long and thorough blog essays on the history of computing by Sinclair Target. One essay is on Codecademy vs. The BBC Micro. The essay gives the background of the BBC Computer Literacy Project that led the BBC to commission as suitable microcomputer, the BBC Micro. He uses this history to then compare the way the BBC literacy project taught a nation (the UK) computing to the way the Codeacademy does now. The BBC project comes out better as it doesn’t drop immediately into drop into programming without explaining, something the Codecademy does.
I should add that the early 1980s was a period when many constituencies developed their own computer systems, not just the BBC. In Ontario the Ministry of Education launched a process that led to the ICON which was used in Ontario schools in the mid to late 1980s.
The category amounted to a giant feedback loop in which the existence of Y2K alarmism led to more of the same.
Harry McCracken in Fast Company has a great article on The weird, wonderful world of Y2K survival guides: A look back (Dec. 13, 2019).The article samples some of the hype around the disruptive potential of the millenium. Particularly worrisome are the political aspects of the folly. People (again) predicted the fall of the government and the need to prepare for the ensuing chaos. (Why is it that some people look so forward to such collapse?)
Technical savvy didn’t necessarily inoculate an author against millennium-bug panic. Edward Yourdon was a distinguished software architect with plenty of experience relevant to the challenge of assessing the Y2K bug’s impact. His level of Y2K gloominess waxed and waned, but he was prone to declarations such as “my own personal Y2K plans include a very simple assumption: the government of the U.S., as we currently know it, will fall on 1/1/2000. Period.”
Interestingly, few people panicked despite all the predictions. Most people, went out and celebrated.
All of this should be a warning for those of us who are tempted to predict that artificial intelligence or social media will lead to some sort of disaster. There is an ethics to predicting ethical disruption. Disruption, almost by definition, never happens as you thought it would.