DR: Write a short skit in the style of monty python in which mao tse tung tries to talk an uber driver out of giving him a bad rating.
AI:(Mao Tse Tung is standing on the sidewalk, holding a smartphone and looking frustrated.)
Mao Tse Tung: I can’t believe it! I just got a one-star rating from my Uber driver!
(An Uber driver pulls up in a car and rolls down the window.)
Uber Driver: Hey, are you Mao Tse Tung?
Mao Tse Tung: Yes, that’s me.
Uber Driver: I’m your driver. Hop in.
Mao Tse Tung: Actually, I wanted to talk to you about your rating. Why did you give me a one-star rating?
Uber Driver: Well, you were a bit difficult to deal with. You kept insisting on taking the long way to your destination, and you kept trying to engage me in political debates.
Mao Tse Tung: But I’m Mao Tse Tung! I’m the founding father of the People’s Republic of China! Surely my political insights are worth something?
Uber Driver: Sorry, mate. I’m just an Uber driver. I don’t really care about politics. I just want to get you to your destination safely and efficiently.
Mao Tse Tung: (sighs) I suppose you’re right. I apologize for any inconvenience I may have caused.
Uber Driver: No worries. Just try to be a bit more reasonable next time, okay?
Mao Tse Tung: Of course. Thank you for understanding.
(Mao Tse Tung gets into the car and the Uber driver drives away.)
DR: what about that skit is in the style of monty python?
AI: There are a few elements of the skit that are in the style of Monty Python.
First, the skit uses absurd and unexpected humor to create a humorous and surprising situation. In the skit, Mao Tse Tung is upset about receiving a one-star rating from his Uber driver, and he tries to argue with the driver to get a better rating. This unexpected situation is similar to the type of humor that is often used in Monty Python sketches.
Second, the skit uses exaggerated and exaggerated characters and dialogue to create humorous effects. For example, the Uber driver is portrayed as a mundane and uninterested character, while Mao Tse Tung is portrayed as a pompous and self-important figure. This contrast between the characters is exaggerated for comedic effect, which is a common technique in Monty Python sketches.
Third, the skit has a playful and irreverent tone that is reminiscent of Monty Python’s comedy. Throughout the skit, the characters engage in humorous banter and the dialogue is filled with comedic jokes and references. This lighthearted and playful tone is characteristic of Monty Python’s comedy.
Overall, the skit uses humor, exaggeration, and a playful tone to create a humorous and absurd situation, which are all elements that are commonly found in Monty Python sketches.
DR: Any sense of which monty python members would play which part in this skit? AI: It is difficult to say which Monty Python members would play which part in the skit, as it would ultimately depend on the actors’ individual abilities and the director’s vision for the sketch. However, some possible casting choices could be:
Mao Tse Tung: This role could potentially be played by John Cleese, who is known for his ability to portray pompous and self-important characters. Uber Driver: This role could potentially be played by Eric Idle, who is known for his ability to portray mundane and uninterested characters. Of course, these are just suggestions, and the actual casting decisions would depend on the director and the actors involved in the production.
In “Importance and limitations of AI ethics in contemporary society” Tomas Hauer (August 22 Humanities and Social Sciences Communications) says AI research raises some thorny ethical issues.
Treating software agents as persons “breaks down the entire existing legal notion of what defines personhood” (2.7). This is really just not true. The invention of the corporation has put these things into question for a long time and we have lots of ways of dealing with it. One might have opinions about whether those are good things or not but there is not much “this changes everything” here.
“The ethical requirements for trustworthy AI should be incorporated into every step of the AI algorithm development process, from research, data collection, initial design phases, system testing, and deployment and use in practice” (3a.4). This is a proclamation, not an argument. What is it about AI and the way it is developed that suggests it ought to be regulated in a particular way?
He next makes the point that some problems are too hard to actually solve. Well, OK. But this doesn’t indict any particular technology; it implies that some folks are promising too much and should be humbled (strawperson argument).
At 4b.6 he suggests authorship of AI produced artifacts is a problem. Nothing special about computer generated works here. If I create something when I’m an employee my company might own it, if I collaborate with others I may or may not make them co-authors, if I create a film, complex negotiations among the agents of the producers, directors, actors, and technicians will determine how credit for creation is given.
The issue of liability for actions and the problem of the distribution of (5a.5) unavoidable harm that cannot be solved purely technically.(5a.6) Liability will be an issue; it always is. Autonomous or semi-autonomous devices may need to “decide” how to distribute unavoidable harm; we do this all the time. “…cannot help but to turn to ethicists…” but the ethicists don’t have THE answer.
He proposes, indirectly, that the more autonomous the product the less likely the manufacturer could be held responsible for harms the product might do. But then he says this simply cannot stand in the face of the principle of strict liability. But liability regimes are socially negotiated things. They are not laws of physics.
Extended discussion of self-driving cars. Question of what kind of values to build in. But all of these are really quite standard policy choice questions.
This piece, like so many others, takes a sort of “hair on fire” attitude and suggests that AI raises such thorny problems that maybe we should put the breaks on. But the context is one that’s ignorant of the way society actually structures its response to risk and harm and liability and responsibility and credit. Not really understanding the technology and not really understanding the social science and institutional science.
Imagine you were around when cars first came on the scene. You were a person of vision and influence. You could see that these machines would change the world. And so you assembled other visionary and influential people and together you formulated the automobile industry code of ethics. At their initial meeting, the group coalesced around the idea that automobiles should be developed, deployed, and used with an ethical purpose and based on respect for fundamental rights, taking into account societal values and ethical principles of beneficence, non-maleficence human autonomy, justice, and explainability. The group agreed to come back in a year and develop an ethical and legal framework for automobiles.
An astronomer, a novelist, a painter, a physicist/intelligence analyst, an anthropologist, an economist/law professor and I walk into a bar …. Well, actually not a bar and we weren’t walking – we just sat down to breakfast.
One of our number mentions the elephant in the room – is what AI can, or may some day be able to, do something we might categorize as creative? As new knowledge? Or is it only ever going to be able to recapitulate what humans have already produced? At best being a tool that helps human genius, or even just human ingenuity, do more than it might otherwise be able to do?
One take at the table, if I understood it correctly, was that the “greatness” of a scientific theory or work of art (think Moby Dick as one example) is something that emerges in/over time as humans appreciate its significance, its meaning, what it says about the human condition. This reminds me of W. Iser’s reader-response theory: the meaning of a work is not IN the text, but rather an event in which the fixedness of the text interacts with the user’s world of experience to yield meaning. Extending Iser a bit we might note that the meaning is collective rather than merely subjective because it is constrained by the artifact of the text (and it’s relationship to other texts and language and it’s production by a person with experience in a shared world) and because the world/self/experience that the reader brings to the process is itself partly shared. These two sets of constraints embed the object in a rich web of shared meaning.
Continuing this line of thinking, we might posit that the artifact produced by a human has on or in it traces of the creator as a entity that is simultaneously biographically unique and a co-participant in the social, where “social” ranges from shared experience of embodiment to the daily weather of micro interactions to the macro drama of history/culture short and history/culture long.
Point number one from this is the idea that the work has something special IN it that a machine could not put into something it created. [It can’t put it in because it is not human and I can’t get it out because it is not human.]
This raises two questions for me. How is that something special inserted or included in the artifact that I encounter? And do I experience that something special in a manner that transcends processing the sensory content (pixels, notes, narratives, etc.)?
Question 1. Do I think that even though it is encoded in the words or the brush strokes or the notes – all patterns that can be explicitly described and could in theory be learned – do I think that it, the human magic, could not be generated by a machine because it comes FROM something with human difference, that is, it’s the human character of the creator that generates the something special and I do not believe machines can “be human” and so they cannot generate this something special and include it in their output. Even if you figure out what it was that Picasso “put into” Portrait of Dora Maar, you can’t just put that into another artifact and thereby transform it into “art.” And, further, even if you could study a lot of Picasso’s paintings and figured out what it was that generated the “artness” of the work, the next creative piece does not just recapitulate what came before, it extends it and creates new zones in meaning space.
Machines can’t be creative because they do not bring to the act of production the experience of being human.
What about on the reception side? Do I experience the something special in some manner that transcends the (e.g., digitizable) materiality of the artifact? I think I might do this by virtue of my taking the artifact as the product of another human mind. I apprehend it from the get-go as meaning-containing. This can be at the prosaic level of “what is the creator trying to say?” or the more lofty “what does this tell us about the human condition (regardless of whether or not the creator had fully appreciated it)?” Regardless of how one sees “the problem of other minds,” we can, perhaps, stipulate that taking an artifact as the product of another mind/self/world with properties like the one I am familiar with (my own) imbues it with “something special.”
But it’s very easy for humans to be wrong about such things; I can imbue something with meaning, hearing what its author is saying to me, even when that thing is not in fact a human creation. We anthropomorphize things all the time and although we are taken aback when we discover that a thing with which we interacted assuming it to be the product of another mind is in fact not, I don’t think we want to characterize this as a simple error. To me it suggests that the reception is itself a human creative act. Echoes of the Thomas theorem: if people take something as real and it thereby real in its consequences then it is real. I’m not going that far, but I do think this establishes the idea that the question of what we are to make of the output of an AI won’t be answered only by looking into the essences of the output itself and the processes that gave rise to it.
[Giant swath of 20th/21st century literary theory coming to mind here.]
I started with the title “We Breakfast” because the place where the conversation left me pondering was around the question of how the “we” that talks about AI and about how it ought to be handled and treated and what it should be allowed to do and what projects its enthusiasts should pursue is organized. I think we almost always too blithely project the idea of the reality of “we” (“we shouldn’t let this happen” or “we know that we value X”) as being well constructed, at the ready as a collective intelligence and agency that’s free (free in the sense of not needing to be paid for). In fact, I think “we” is a gigantic and ongoing construction project that absorbs a large part of our energy budget and mostly is a rickety machine with only very locally optimized or even reasonably well-running instances.
What do we think of when we think of hybrid (learning and teaching)? Some face-to-face teaching plus some online teaching? Some synchronous + some asynchronous? Flipping the classroom? Drosos and Guo (2021)* offer another perspective on a kind of teaching that can be included in the category. They show how what streamers teaching do can be seen as a form of cognitive apprenticeship. The authors do not explicitly talk about “hybrid,” but the practices they identify – real time problem solving, improvised examples, insightful tangents, and high level advice – are relevant to hybrid for two reasons. First, they are the kinds of things often cited as why remote or asynchronous instruction is necessarily inferior (the claim being they are absent). Second, they are useful challenges: how can these virtues be built into various hybrid scenarios?
All told, I have probably spent 20 full person-years in college and university classrooms. I’ve taught courses in sociology, public policy, information science, design, philosophy, and geography. I’ve taught studios, labs, lectures, workshops, and seminars. I’ve taught in small liberal arts colleges and public and private R1 universities. If you commission me to teach or design a course, I bring to the task a lot more than just my experience and “domain expertise” and (hopefully) wisdom. I bring to the task a whole lot of STUFF. An attic and garage and toolbox full of STUFF. Time was that stuff was in filing cabinets, notebooks, and stack of paper in my university and home offices. Now it’s mostly on the hard drive of my computer or stored in the cloud.
That stuff is the palette from which I can paint a course.
I’ve got syllabi and draft syllabi, bibliographies, annotations of readings, outlines of readings, PDFs of readings, diagrams of the argument logic of books and articles, lecture notes, scripts for videos, exams and problem sets, solutions to problems, catalogs of learning outcomes and course and program objectives. I have instructions for assignments, examples of student work on those assignments, and rubrics for evaluating that work. I have descriptions of classroom activities, examples of important concepts, and agendas for class sessions. And I have slide decks, countless slide decks, multiple versions of slide decks, decks of slides removed from other decks of slides. And I have stuff that’s out there on the net. YouTube videos I’ve made and videos of others that I’ve curated. And Sound Cloud files. And bookmarks in my browsers that are more or less (mostly less) well organized according to a system that sort of looks like what I teach and sort of looks like what I write about and sort of looks like the institutions I’ve worked for. And then there are the courses I’ve put on my institutions’ learning management systems (LMS); most of the material there is the stuff I’ve already mentioned but sometimes the LMS copy of something is the only one I have. And the question banks I’ve developed, hundreds of problems and solutions inside of courses on Canvas or Blackboard that are basically unretrievable. And I have course evaluations that occasionally have good ideas for subsequent iterations of courses and smart ideas that I’ve committed to paper when proposing new courses or applying for course development funding of one kind or another.
It’s a giant trove of stuff. To go through it all would probably take as long as it took to develop it in the first place. To find particular things can take even longer – the thing you want is always the last thing you find.
When you commission me to teach that course, all of this stuff is the raw material from which I will, in theory, compose a new masterpiece. Except probably not really all of it because the primary mode of organization of this material is, for all practical purposes, “the pile.” Even when it’s filed alphabetically in drawers or arranged in hierarchical directories on my computer, most of it is out of sight and even further out of mind. You hire me for the breadth and depth of my palette, but what you get is pretty much constrained by my ability to remember where things are and actually find them once I do. And that ability does not correlate with how smart I am about other things. Call it recency or availability bias or just poor housekeeping, most of my stuff is not really available and I spend a lot of time reinventing the wheel.
Now that kind of reinvention is not always a bad thing. Sometimes the essay your re-write, in tears, perhaps, after losing an entire draft is better than the original. But it is always time consuming and the result is often no better than before and thus represents a missed opportunity to iterate and improve. “What is to be done?”
Analogy: Bibliographic Software
Long ago accomplished scholars were keepers of troves of index cards. They read books and articles and scoured archives and processed interview transcripts and committed each tidbit to an index card along with keywords and citations. The workflow of scholarship was arranging and rearranging index cards into sections and chapters and books. Among other functions, this practice allowed the scholar to rigorously cite their sources.
Modern scholars are apt to have bibliographic software like EndNote, Mendeley, or Zotero to fulfill this function (along with eliminating the tedious task of writing footnotes and typing up bibliographies). It’s not unusual, in fact, for a scholar’s bibliographic database to contain a record of every article, book, and website they have every consulted. Over the course of a career they might catalog tens of thousands of references.
Teachers should have a similar tool, but not just for references.
What If There Were a….
What if there were a platform – be it digital technology or just a disciplined way of doing things – that afforded me a synoptic (def. “affording a general view of a whole”) view of my stuff along with any conceivable subset or slice or abstraction of my stuff (show me every problem I ever wrote that has anything to do with learning outcome #distribution or show me all of my slide decks on APIs or which course syllabi include Foucault’s Discipline and Punish?).
Moreover, what if there were a platform that would allow me to create a draft syllabus by tagging items in a bibliographic database or the rough draft of a lecture by tagging annotations and/or slides? What if problem solutions automatically knew about related problems or good review material to recommend to a student who’d found the problem challenging? What if learning outcomes knew what class activities or lecture sections they appeared in? What if problems knew that students who had trouble with this problem also had trouble with this other problem? What if slides knew about alternative examples of the concepts they described? What if sample problems were as easy to embed in a slide as in a homework problem set as in an exam? What if a code notebook example could be tagged for inclusion in a slide deck? What if lecture notes and slide decks and videos were synced and cued to one another? What if any pedagogical artifact that I’d be willing to share with a colleague were accessible to them without me having to be involved?
These are a few of the affordances I imagine for a pedagogical information system worthy of the 21st century.
First Installment in a Month-Long Project “Information Systems for Pedagogical Productivity”
Are you like me? A college or university instructor whose computer storage is littered with multiple copies of syllabi and lectures and slide decks? “SOC101-Lecture5-2021F.pptx,” “Lecture 7 Slides,” “Lecture 7 Slides – OUTTAKES,” “API Diagram (1),” “API Diagram (2),” etc. Is part of your brain used for remembering which files for your courses are the currently authoritative ones? A teacher proud of how you manage to integrate your references on Zotero, your slides in PowerPoint, your lectures in Google Docs, you screen captures from Snagit carefully cataloged on MyMedia, YouTube playlists for each class you teach?
There’s often real brilliance in the systems we come up with. And many of us are continually improving our workflows as we live and learn and find out about new products and gadgets. And then we have directories with names like PPOL Intro Materials (NEW). And the thing is, everyone has their own system; I don’t think I’ve ever heard an instructor say that their “system” was the same as or derived from that of some other instructor. A million instructors have a million different systems.
As brilliant as our solutions are, in all likelihood, some of us have solved some of the problems, and some have solved other of the problems; most of us still have lots of problems.
Our Pedagogical Palette
A teacher is simultaneously an author, a performer, and an experience designer. What repertoire of materials do teachers draw on in that work? At the core are two things: domain expertise and a sense – innate or learned – of pedagogical technique. But in addition to these there are a lot of things: syllabi, slide decks, videos and transcripts, images and diagrams, references and bibliographies, annotations and summaries, outlines, assignments, whole quizzes and exams and banks of questions, practice problems and solutions, lecture notes, feedback boilerplate, handouts, descriptions of learning outcomes, workbooks, simulations, stories, illustrations, and examples.
How do we keep track of all this stuff? Most of us store things in hierarchical directories. If we’re good, we name things wisely making them easier to identify without having to open them and all our stuff is on one machine or perhaps in the cloud and synced to all our devices. But even if we pull that off, there is ample opportunity for consternation. Is the top level organization in a course the weeks or modules of the course or do we organize by genre (slide decks in one directory, videos in another? Is it redundant for the names of all objects include a course identifier if they are stored in a directory that names that course? Should directories contain only materials that are actively in use to remain uncluttered or should they be full archives of what I have produced for this unit? How to account for the fact that some things are files on my computer, some things (e.g., videos) are on my account on platforms like YouTube, other things are just links to things on other people’s accounts or bookmarks of websites? How do I keep track of documents I have PDFs of and and bibliographical listings for? DO I have a PDF of that?
The question here is not merely one of archival integrity, but also of creativity and performance. By performance I mean me teaching a course right now. By creativity I mean me conceiving, designing, and building a course. The painter who has an enviable array of tubes of paint in their storage room does not have an enviable array of colours with which to paint. The colours they have to paint with are the ones squeezed out and mixed on their palette. The question is not one of archiving, but rather of making the archive as fully available to the creator as possible. And I need to use as little of my brain as possible for the keeping to hand and mind of the contents of my pedagogical palette.
Seeing What You are Doing
In a video lecture from long ago (2012) Bret Victor enunciated a principle: creators need an immediate connection to what they create. He goes on to show some tools he developed that allow coders and visual designers to have an immediate connection to what they create. I’ve interpreted Victor’s principle as arguing that the creator should not use their brain to simulate the medium in which they are creating. A painter would not think up a set of brush stroke instructions, fully imagine what their effect would be, and then implement these on canvas. A programmer should not have to simulate the computer and compiler they are using as they write code. And designers should not simulate the world and the users for the things they design; instead, they build prototypes and let the world have its say.
This is the world I imagine for the teacher. We should have synoptic access to our repertoires, our pedagogical palette, and have an immediate connection to the things we are creating.
My students often care about the grade they earn in my course because they believe it will influence subsequent opportunities. And so they care about the final exam because it has a big influence on that grade for the course. And so they want to know which of the things we are learning in the course will be on that final exam. And, all too often, that’s a pretty big part of our relationship.
Sometimes I feel like I’m a coach of a team – perhaps a swimming team or a track team. Now and again we have time trials as a part of our training. But of course the time trials are a means to an end not an end in themselves. The trophies and the medals are not earned in the time trials we do at practice. It’s the races in the meets that matter.
Exams feel to me more like time trials than meets.
What if, instead of final exams for courses we had preliminary exams for courses? What if we thought about curriculum in terms of what each course wanted to build on and what it wanted to leave you with. And what if you didn’t get into the next course based on a previous grade but rather on what you still had in your knowledge and skill set when you wanted to do that next course?
Maybe we could see “next” courses as building on multiple prior courses – effectively taking the idea of pre-requisites seriously and forcing ourselves to say why something is a pre-req – what knowledge am I planning to build upon in this course. Maybe each course could come with a list of “what you should already know and be able to do” goals that we could match up with the “outcomes” of other courses.
In this scenario my students are not asking me whether something will be on the exam at the end of our class; instead they are concerned about using this class to get in shape to be ready for the entrance exam for the next courses they want to take. That would likely up their game and mine too.
And the records can start to reflect how well my course contributed to their success at getting into the next course (or, eventually, passing some sort of final milestone for a degree or credential).
By the time curriculum ideas become reality they’ve been so picked over by committees and assistant associate deans that their pedagogical coherence is reduced to something like “at this point nobody objects strongly to what’s left.” A few years back I had in mind to teach a course or workshop that would encourage individuals or small groups to engage in a sprint or hackathon approach to the first draft of a curriculum plan. Here’s an effort I put together, partly as an example of that genre, but also as a vision for a program I thought Mills College, where I taught at the time, could absolutely hit home runs with given their staffing, location, reputation, etc. It was basically a port to the small liberal arts college context of the program I helped get off the ground at USC in 2014, the Iovine Young Academy for Arts, Technology and the Business of Innovation.
Technology, Business, and Design
“Innovation” is the development of creative and sustainable solutions to important problems. The TBD program offers students rigorous training as innovators in the context of a liberal arts education. It hybridizes ^!\\$’ strengths in the arts, business, and technology to produce a new kind of academic program and a new genre of academic programs.
This program is not designed only for students who are currently at or likely to enroll at our college although many of them might find it of interest. Our goal is to attract to our college students who would never have given us a second look. We expect some of these would gain admission to our program and enroll, but others would enroll at the college for other programs. Further, we expect that some students will “transfer” into other majors after the first two years. The program we want to build will put us on the recruitment map in new ways by being a radically forward looking program that is not available anywhere else. It will be a program that builds on legacy strengths of the institution, but goes quantitatively and qualitatively beyond just breathing new life into old programs.
The purpose of this degree is not to get art students to learn more technology or for technology students to minor in business or for business students to learn to talk to coders and designers. We are not after interesting double majors or curious interdisciplinary majors. All that can already be done. We are going to invent something that can’t be done now, but needs to be: a new kind of degree that is unabashedly practical and profound, that yields graduates who can be described as creative critical thinkers, visionary pragmatists, technologists with a social conscience, radicals whose skillsets make them truly dangerous to the status quo.
Unlike similar programs at larger institutions in schools of engineering or design, we envision a program in which we are teaching “innovation as a liberal art” – believing that the core learning goals of the liberal arts are highly resonant with the content of “innovation education.”
What. One way to define “Innovation” is as the development of creative and sustainable solutions to important problems. The Technology, Business, and Design, or TBD, program offers students rigorous training as innovators in the context of a liberal arts education. It hybridizes ^!\\$’ strengths in the arts, business, and technology to produce a new kind of academic program and a new genre of majors.
WHO. The TBD program is designed not for students who are already at our college. Our goal is to attract the attention of students who would never have given us a second look. We expect to recruit some of them to this program, but we expect others will enroll at the college in other programs. Further, we expect that some students will “transfer” into other majors after the first two years. The program we want to build will put us on the recruitment map in new ways by being a radically forward looking program that is not available anywhere else. It will be a program that builds on legacy strengths of the institution, but goes quantitatively and qualitatively beyond just breathing new life into old programs.
Why. The purpose of the TBD degree is not to get art students to learn some technology or for science students to minor in business or for business students to learn to talk to coders and designers. We are not after interesting double majors or curious interdisciplinary majors. All that can already be done. We are going to invent something that can’t be done now, but that the world needs: a new kind of degree that is unabashedly both practical and profound, that yields graduates who can be described as creative critical thinkers, visionary pragmatists, technologists with a social conscience, radicals whose skill sets make them a danger to the status quo.
How. Unlike similar programs at larger institutions in schools of engineering or design, we envision a program in which we are teaching “innovation as a liberal art” – believing that the core learning goals of the liberal arts are highly resonant with the content of what might be called “innovation education.”
A Two Level Curriculum
TBD is a cohort-based degree program. The integrated trans-disciplinary curriculum has the graduated profile of sequential majors but with combinatoric flexibility that will yield several tracks in the major.
The curriculum has two levels. The first two years are completely highly structured and culminate in a sophomore project. Those who successfully complete this “pre-diploma” will continue on to an upper division program that allows for more in depth studies of the three component areas of the program: arts and design; business, organizations, and social science; technology and computer science with an intense capstone experience solving real world problems.
The Pre-Diploma
The curriculum begins with three intense introductory courses. The pre-diploma program is built around the “ABC phase” in which students take an introductory course in each area (A=art/design, B=business/organization, C=computing/technology) during the first two semesters.
Culture, Commerce, and Innovation
Design, Visualization, and Prototyping
Physical science and Coding I
Regardless of what strengths a student had coming into the program, these intense introductory courses lay a disciplinary foundation for subsequent work.
The second phase involves three bridging courses. Starting in spring of the first year, single discipline courses are followed by courses which explicitly tie two of areas together: technology and design; design and business; business and technology. These courses explicitly build on what was learned in the respective introductory courses.
Design and Social Innovation
Technology and Design
Organization and Technology
The third part of the pre-diploma is a seminar in which the three areas converge and a sophomore project in which students work on teams to take an idea from initial problem identification through prototype iteration and testing. The pre-diploma program is designed so that students can either continue onto the upper division curriculum or opt out and pursue other majors.
The Upper Division Curriculum
The upper division of the program starts with an internship that is bookended by entry and exit seminars. The entry seminars will consist of skills and knowledge specific to the internships, professional skills, and priming exercises to maximize the pedagogical impact of internship. The internship itself will start at mid-semester in the fall and continue to mid-semester in the spring. The exit seminar will consolidate lessons and skills learned in the internship and make connections with student’s proposed final year project.
Innovative Infrastructure: Shattering the Semester
Courses in the curriculum will be worth 1, 2, 3, or 4 credits with credit value determined by the number of weeks the course or workshop meets. All classes will meet for the same amount of time each week. This will allow us to stagger course offerings; for example, during the first semester students will have two 3 credit and one 4 credit course but the one 3 credit courses will end 3.5 weeks before the end of the semester and the other will start 3.5 weeks into the semester allowing students a little breathing room at the ends of the semester. The program also consists of digital skills workshops which last 7 weeks (2 credits) and a series of short 3.5 week workshops for 1 credit.
Course Flights
The upper division consists of three “flights,” one in each focal area. A course flight is a sequence of two or more courses in which students experience cumulative skill and knowledge building and progressively higher levels of mastery. Students choose one “long flight” consisting of the introductory course plus three advanced courses, a medium flight with two advanced courses, and short one with a single advanced course.
A student could have a business focus and do the long flight in organization/business courses. A student with a technology focus might make technology her long flight, design her medium length flight, and business her short flight.
A third year course called problems and solutions builds on skills and knowledge. This leads to a fourth year capstone and studio/garage/workshop/fieldwork project to which about half the year’s time will be devoted. Students will be expected to tackle a meaningful problem, assembling a team and seeing it through from start to finish.
Every semester there will be a series of four guest speakers – innovators in all fields drawn from the greater Bay Area – who will meet with students in the program in sessions we call “Innovators Face to Face.” Some of these will be structured as presentations and conversations and some will be structured as critique visits for which students will prepare presentations and visitors will offer commentary, critique, and advice.
DigiTool Courses
Over the course of their first four semesters, students in the program will take a series of toolbox courses we are calling “digiTools.” Many of these will be training in software applications used throughout the curriculum.
The popUp Curriculum
Also every semester will feature a series of “popUp” workshops on topics that complement the other curricular offerings and allow instructors to do more in those classes because common topics are covered outside of their classroom time. The first set of popUps will be used to orient students to the program and to introduce tools that are used throughout the program.
Staffing
Revenue Sharing
As a first approximation, assume 25 students in initial cohort with net tuition of 15k of which 33% is allocated to institutional overhead. The remainder to be apportioned proportional to credit hours delivered. One sample scheme shown below draws on faculty FTE in several existing programs/departments.
I need reading glasses. When this need first emerged – maybe in my late 40s – it was only for extremely small scale close up activity such as marking fine gradations when doing finish carpentry or working with very tiny screws or reading extremely fine print on some labels. But now it’s pretty much for anything printed and so I always have them with me, generally perched atop my head ready to be slid down to the bridge of my nose in an instant. And each time I do that, there’s a thrill of the world (or at least that small part of the world right in front of my face) coming into focus and clarity. In the blink of an eye, consciousness and world re-engage. The visual apparatus with which I do so much of my ascertaining of what is and is not the case goes from blunted and blurry to sharp and in-focus and I go from a state of “I don’t know what to believe” to one of “seeing is believing.”
I frequently transition from a reading task to moving about the room or house or just looking up or out the window. Many times a day I’ll get up, reading glasses still in place and start across the floor of my studio toward the stairs down to the second floor and only after a few moments remember that I have my reading glasses on and that that’s why everything is blurry. I flip them up onto the top of my head and my more-or-less 20-20 distance vision kicks in and all is clear. Again, the thrill of going from thick fog to blue sky clarity, from “whoah, what?” to “it is what it is,” that is, I now am in possession of information about the world that a moment ago I lacked. We might call this lower case “aha” as a sort of mundane version of big discoveries that merit “AHA!”
Both transitions resolve quickly into a state of taken-for-granted “me-here perceiving the world-over-there as it is,” but repeated experience of the transitions themselves leaves a mark.
One can think of these transitions as having a rate – the amount of change divided by the duration of the transition. What I experience as the thing that changes is my capacity to know the ((appearance of the) part of the) world (that’s in front of me). It’s not merely or only vision1 – it’s me using vision to, as phrased above, ascertain what is the case here – but clarity in the visual field is a prerequisite element and the one that is subject to change. There are elements here of an “aha” experience – We might think of this as what in mathematics we call a derivative:
where we define delta clarity as new clarity minus old clarity so that aha is positive when clarity increases which is more in line with our intuition and everyday usage. Like my bringing the glasses down for reading or pushing them up to walk across the room, most examples that come to mind probably have a positive value for aha – that is, we move from less clarity to more clarity so the numerator is negative.
Daily life is full of very small values of aha wherein we gradually come to understand how something works or a story unfolds slowly as we read or hear it. And occasionally there are really high values of aha, those that elicit an “AHA!” because of the size of delta clarity as when a mystery is finally, and suddenly, solved.
But what about when aha is negative, that is, when we move from situations of more clarity to less clarity? When I am looking at a text through my reading glasses and I suddenly take them away the text multiplies and slides over itself, the individual letters vibrating and morphing. My eyes reach out to grasp them, but they move before I can reach them.
When we suspect or discover that a friend is a liar or we conclude that a media outlet is peddling fake news or we become persuaded that what we’d taken to be a credible source was actually propaganda or a therapist helps us see we were being gaslit or radicalization brings us to critical consciousness (Lukács 1967; Mannheim 1959) or we realize that the story in the novel we are reading is told by an unreliable narrator (Booth 1983) we experience various sized negative values of aha.
Two other loci of the experience of negative aha will be examined in the next section: the failure of our relational partners to notify us of things we think they should and the diminution of cognitive/sensory tools in old age. Both these highlight another aspect of this phenomenon: the meta-experience of negative aha – the realization that our relationships (Ryan 2006) or our faculties may not be what we thought they were and that things we’ve depended on for information about the world may no longer be dependable.
1 One could experiment with other things – perhaps what comes into focus is an optical illusion or a coded text so that there is another step and another faculty engaged in coming to clarity, but those are questions for another day.
