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The open model of participation calls into question where value is created in the education system. Gutenberg created a means to duplicate content. The social web creates the opportunity for many-to-many interactions and to add a global social layer on content creation and knowledge growth.

Whatever can be easily duplicated cannot serve as the foundation for economic value. Integration and connectedness are economic value points.

In education, content can easily be produced (it’s important but has limited economic value). Lectures also have limited value (easy to record and to duplicate). Teaching – as done in most universities – can be duplicated. Learning, on the other hand, can’t be duplicated. Learning is personal, it has to occur one learner at a time. The support needed for learners to learn is a critical value point.

Learning, however, requires a human, social element: both peer-based and through interaction with subject area experts

Content is readily duplicated, reducing its value economically. It is still critical for learning – all fields have core elements that learners must master before they can advance (research in expertise supports this notion). - Teaching can be duplicated (lectures can be recorded, Elluminate or similar webconferencing system can bring people from around the world into a class). Assisting learners in the learning process, correcting misconceptions (see Private Universe), and providing social support and brokering introductions to other people and ideas in the discipline is critical. - Accreditation is a value statement – it is required when people don’t know each other. Content was the first area of focus in open education. Teaching (i.e. MOOCs) are the second. Accreditation will be next, but, before progress can be made, profile, identity, and peer-rating systems will need to improve dramatically. The underlying trust mechanism on which accreditation is based cannot yet be duplicated in open spaces (at least, it can’t be duplicated to such a degree that people who do not know each other will trust the mediating agent of open accreditation)

The skills that are privileged and rewarded in a MOOC are similar to those that are needed to be effective in communicating with others and interacting with information online (specifically, social media and information sources like journals, databases, videos, lectures, etc.). Creative skills are the most critical. Facilitators and learners need something to “point to”. When a participant creates an insightful blog post, a video, a concept map, or other resource/artifact it generally gets attention.

Intentional diversity – not necessarily a digital skill, but the ability to self-evaluate ones network and ensure diversity of ideologies is critical when information is fragmented and is at risk of being sorted by single perspectives/ideologies.

The volume of information is very disorienting in a MOOC. For example, in CCK08, the initial flow of postings in Moodle, three weekly live sessions, Daily newsletter, and weekly readings and assignments proved to be overwhelming for many participants. Stephen and I somewhat intentionally structured the course for this disorienting experience. Deciding who to follow, which course concepts are important, and how to form sub-networks and sub-systems to assist in sensemaking are required to respond to information abundance. The process of coping and wayfinding (ontology) is as much a lesson in the learning process as mastering the content (epistemology). Learners often find it difficult to let go of the urge to master all content, read all the comments and blog posts.

e. Learning is a social trust-based process.

Patience, tolerance, suspension of judgment, and openness to other cultures and ideas are required to form social connections and negotiating misunderstandings.

An effective digital citizenry needs the skills to participate in important conversations. The growth of digital content and social networks raises the need citizens to have the technical and conceptual skills to express their ideas and engage with others in those spaces. MOOCs are a first generation testing grounds for knowledge growth in a distributed, global, digital world. Their role in developing a digital citizenry is still unclear, but democratic societies require a populace with the skills to participate in growing a society’s knowledge. As such, MOOCs, or similar open transparent learning experiences that foster the development of citizens confidence engage and create collaboratively, are important for the future of society.

Jarvis never broaches such subtleties. His is a simple world:

why not consider the possibility that the incumbents may be using the same tools, Jarvis’s revered technologies, to tell us what to think, and far more effectively than before? Internet shelf space may be infinite, but human attention is not. Cheap self-publishing marginally improves one’s chances of being heard, but nothing about this new decentralized public sphere suggests that old power structures—provided they are smart and willing to survive—will not be able to use it to their benefit

Jarvis 1.0 was all about celebrating Google, but Jarvis 2.0 has new friends in Facebook and Twitter. (An Internet intellectual always keeps up.) Jarvis 1.0 wrote that “Google’s moral of universal empowerment is the sometimes-forgotten ideal of democracy,” and argued that the company “provides the infrastructure for a culture of choice,” while its “algorithms and its business model work because Google trusts us.” Jarvis 2.0 claims that “by sharing publicly, we people challenge Google’s machines and reclaim our authority on the internet from algorithms.”

Jarvis has another reference point, another sacred telos: the equally grand and equally inexorable march of the Internet, which in his view is a technology that generates its own norms, its own laws, its own people. (He likes to speak of “us, people of the Net.”) For the Technology Man, the Internet is the glue that holds our globalized world together and the divine numen that fills it with meaning. If you thought that ethnocentrism was bad, brace yourself for Internet-centrism

Why worry about the growing dominance of such digitalism? The reason should be obvious. As Internet-driven explanations crowd out everything else, our entire vocabulary is being re-defined. Collaboration is re-interpreted through the prism of Wikipedia; communication, through the prism of social networking; democratic participation, through the prism of crowd-sourcing; cosmopolitanism, through the prism of reading the blogs of exotic “others”; political upheaval, through the prism of the so-called Twitter revolutions. Even the persecution of dissidents is now seen as an extension of online censorship (rather than the other way around). A recent headline on the blog of the Harvard-based Herdictproject—it tracks Internet censorship worldwide—announces that, in Mexico and Morocco, “Online Censorship Goes Offline.” Were activists and dissidents never harassed before Twitter and Facebook?

Most Internet intellectuals simply choose a random point in the distant past—the honor almost invariably goes to the invention of the printing press—and proceed to draw a straight line from Gutenberg to Zuckerberg, as if the Counter-Reformation, the Thirty Years’ War, the Reign of Terror, two world wars—and everything else—never happened.

even their iPad is of interest to them only as a “platform”—another buzzword of the incurious—and not as an artifact that is assembled in dubious conditions somewhere in East Asian workshops so as to produce cultic devotion in its more fortunate owners. This lack of elementary intellectual curiosity is the defining feature of the Internet intellectual. History, after all, is about details, but no Internet intellectual wants to be accused of thinking small. And so they think big—sloppily, ignorantly, pretentiously, and without the slightest appreciation of the difference between critical thought and market propaganda.

existing efforts "focus on the interpretive responsibilities of the individual,"

"if bad actors intentionally dump disinformation online with an aim to distract and overwhelm, is it possible to safeguard against media manipulation?"

A 2012 meta-analysis by academic researchers found that media literacy efforts could help boost students' critical awareness of messaging, bias, and representation in the media they consumed. There have been small studies suggesting that media-literacy efforts can change students' behaviors—for example, by making them less likely to seek out violent media for their own consumption. And more recently, a pair of researchers found that media-literacy training was more important than prior political knowledge when it comes to adopting a critical stance to partisan media content.

the roles of institutions, technology companies, and governments

LLMs usually cannot do a good job of explaining how a particular passage from a longer text illuminates the whole of that longer text. Moreover, ChatGPT’s outputs on comparison and contrast are often superficial. Typically the system breaks down a task of logical comparison into bite-size pieces, conveys shallow information about each of those pieces, and then formulaically “compares” and “contrasts” in a noticeably superficial or repetitive way. 

In-class writing, whether digital or handwritten, may have downsides for students with anxiety and disabilities

ChatGPT can produce outputs that take the form of  “brainstorms,” outlines, and drafts. It can also provide commentary in the style of peer review or self-analysis. Nonetheless, students would need to coordinate multiple submissions of automated work in order to complete this type of assignment with a text generator.  

No one should present auto-generated writing as their own on the expectation that this deception is undiscoverable. 

LLMs often mimic the harmful prejudices, misconceptions, and biases found in data scraped from the internet

Show students examples of inaccuracy, bias, logical, and stylistic problems in automated outputs. We can build students’ cognitive abilities by modeling and encouraging this kind of critique. Given that social media and the internet are full of bogus accounts using synthetic text, alerting students to the intrinsic problems of such writing could be beneficial. (See the “ChatGPT/LLM Errors Tracker,” maintained by Gary Marcus and Ernest Davis.)

Since ChatGPT is good at grammar and syntax but suffers from formulaic, derivative, or inaccurate content, it seems like a poor foundation for building students’ skills and may circumvent their independent thinking.

Good journalism on language models is surprisingly hard to find since the technology is so new and the hype is ubiquitous. Here are a few reliable short pieces.     “ChatGPT Advice Academics Can Use Now” edited by Susan Dagostino, Inside Higher Ed, January 12, 2023  “University students recruit AI to write essays for them. Now what?” by Katyanna Quach, The Register, December 27, 2022  “How to spot AI-generated text” by Melissa Heikkilä, MIT Technology Review, December 19, 2022  The Road to AI We Can Trust, Substack by Gary Marcus, a cognitive scientist and AI researcher who writes frequently and lucidly about the topic. See also Gary Marcus and Ernest Davis, “GPT-3, Bloviator: OpenAI’s Language Generator Has No Idea What It’s Talking About” (2020).

“On the Dangers of Stochastic Parrots” by Emily M. Bender, Timnit Gebru, et al, FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, March 2021. Association for Computing Machinery, doi: 10.1145/3442188. A blog post summarizing and discussing the above essay derived from a Critical AI @ Rutgers workshop on the essay: summarizes key arguments, reprises discussion, and includes links to video-recorded presentations by digital humanist Katherine Bode (ANU) and computer scientist and NLP researcher Matthew Stone (Rutgers).