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Ed Webb

Harvard U. Institute Unveils Software That Helps Build Academic Sites - Wired Campus - ... - 0 views

chronicle.com/...25874

web web 2.0 tools for educators tools drupal opensource

shared by Ed Webb on 02 Aug 10 - Cached
  • Ed Webb on 02 Aug 10
     
    Worth taking a look for Dickinson? Or are we committed to the tepid design and existing CMS? I guess Academia.edu are also in this same market, although that is in the cloud rather than on institutional servers.
Ed Webb

Social Media is Killing the LMS Star - A Bootleg of Bryan Alexander's Lost Presentation... - 0 views

openedconference.org/...1037

lms education Web2.0 socialmedia NITLE bryanalexander

shared by Ed Webb on 19 Aug 09 - Cached
  • Note that this isn’t just a technological alternate history. It also describes a different set of social and cultural practices.
  • CMSes lumber along like radio, still playing into the air as they continue to gradually shift ever farther away on the margins. In comparison, Web 2.0 is like movies and tv combined, plus printed books and magazines. That’s where the sheer scale, creative ferment, and wife-ranging influence reside. This is the necessary background for discussing how to integrate learning and the digital world.
  • These virtual classes are like musical practice rooms, small chambers where one may try out the instrument in silent isolation. It is not connectivism but disconnectivism.
  • ...11 more annotations...
  • CMSes shift from being merely retrograde to being actively regressive if we consider the broader, subtler changes in the digital teaching landscape. Web 2.0 has rapidly grown an enormous amount of content through what Yochai Benkler calls “peer-based commons production.” One effect of this has been to grow a large area for informal learning, which students (and staff) access without our benign interference. Students (and staff) also contribute to this peering world; more on this later. For now, we can observe that as teachers we grapple with this mechanism of change through many means, but the CMS in its silo’d isolation is not a useful tool.
  • those curious about teaching with social media have easy access to a growing, accessible community of experienced staff by means of those very media. A meta-community of Web 2.0 academic practitioners is now too vast to catalogue. Academics in every discipline blog about their work. Wikis record their efforts and thoughts, as do podcasts. The reverse is true of the CMS, the very architecture of which forbids such peer-to-peer information sharing. For example, the Resource Center for Cyberculture Studies (RCCS) has for many years maintained a descriptive listing of courses about digital culture across the disciplines. During the 1990s that number grew with each semester. But after the explosive growth of CMSes that number dwindled. Not the number of classes taught, but the number of classes which could even be described. According to the RCCS’ founder, David Silver (University of San Francisco), this is due to the isolation of class content in CMS containers.
  • unless we consider the CMS environment to be a sort of corporate intranet simulation, the CMS set of community skills is unusual, rarely applicable to post-graduation examples. In other words, while a CMS might help privacy concerns, it is at best a partial, not sufficient solution, and can even be inappropriate for already online students.
  • That experiential, teachable moment of selecting one’s copyright stance is eliminated by the CMS.
  • Another argument in favor of CMSes over Web 2.0 concerns the latter’s open nature. It is too open, goes the thought, constituting a “Wild West” experience of unfettered information flow and unpleasant forms of access. Campuses should run CMSes to create shielded environments, iPhone-style walled gardens that protect the learning process from the Lovecraftian chaos without.
  • social sifting, information literacy, using the wisdom of crowds, and others. Such strategies are widely discussed, easily accessed, and continually revised and honed.
  • at present, radio CMS is the Clear Channel of online learning.
  • For now, the CMS landsape is a multi-institutional dark Web, an invisible, unsearchable, un-mash-up-able archipelago of hidden learning content.
  • Can the practice of using a CMS prepare either teacher or student to think critically about this new shape for information literacy? Moreover, can we use the traditional CMS to share thoughts and practices about this topic?
  • The internet of things refers to a vastly more challenging concept, the association of digital information with the physical world. It covers such diverse instances as RFID chips attached to books or shipping pallets, connecting a product’s scanned UPC code to a Web-based database, assigning unique digital identifiers to physical locations, and the broader enterprise of augmented reality. It includes problems as varied as building search that covers both the World Wide Web and one’s mobile device, revising copyright to include digital content associated with private locations, and trying to salvage what’s left of privacy. How does this connect with our topic? Consider a recent article by Tim O’Reilly and John Battle, where they argue that the internet of things is actually growing knowledge about itself. The combination of people, networks, and objects is building descriptions about objects, largely in folksonomic form. That is, people are tagging the world, and sharing those tags. It’s worth quoting a passage in full: “It’s also possible to give structure to what appears to be unstructured data by teaching an application how to recognize the connection between the two. For example, You R Here, an iPhone app, neatly combines these two approaches. You use your iPhone camera to take a photo of a map that contains details not found on generic mapping applications such as Google maps – say a trailhead map in a park, or another hiking map. Use the phone’s GPS to set your current location on the map. Walk a distance away, and set a second point. Now your iPhone can track your position on that custom map image as easily as it can on Google maps.” (http://www.web2summit.com/web2009/public/schedule/detail/10194) What world is better placed to connect academia productively with such projects, the open social Web or the CMS?
  • imagine the CMS function of every class much like class email, a necessary feature, but not by any means the broadest technological element. Similarly the e-reserves function is of immense practical value. There may be no better way to share copyrighted academic materials with a class, at this point. These logistical functions could well play on.
Ed Webb

Why You Can't Use Personal Technology at the Office - WSJ.com - 1 views

online.wsj.com/...3567204574499032945309844.html

tools technology

shared by Ed Webb on 16 Nov 09 - Cached
  • Ed Webb on 16 Nov 09
     
    Implications for academia, too
Ed Webb

Guest Post: The Complexities of Certainty | Just Visiting - 0 views

www.insidehighered.com/...st-post-complexities-certainty

education opinion internet distance pandemics teaching pedagogy

shared by Ed Webb on 27 Apr 20 - Cached
  • Privileges abound in academia, but so do experiences of loss, instability and fear. And into this situation we were called to respond to a pandemic.
  • It is tempting to reach for certainties when everything around us is in chaos, and for a vast swath of higher ed instructors, the rapid shift from face-to-face teaching to emergency distance learning has been chaos. Small wonder, then, that people have offered -- and clung to -- advice that seeks to bring order to disorder. Many people have advised instructors to prioritize professionalism, ditching the sweatpants and putting away the visible clutter in our homes before making a Zoom call, upholding concepts like "rigor" so that our standards do not slip. To some, these appeals to universal principles are right-minded and heartening, a bulwark against confusion and disarray. But to others they have felt oppressive, even dangerously out of touch with the world in which we and our students live.
  • certainties can be dangerous; their very power is based upon reifying well-worn inequities dressed up as tradition
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  • there is no objective standard of success that we reach when we insist on rigor, which is too often deployed in defense of practices that are ableist and unkind
  • We are not just teachers, or scholars, or professionals. We are individuals thrown back in varying degrees on our own resources, worried about ourselves and our families and friends as we navigate the effects of COVID-19. Many of us are deeply anxious and afraid. Our pre-existing frailties have been magnified; we feel vulnerable, distracted and at sea. Our loved ones are sick, even dying. This is trauma. Few of us have faced such world-changing circumstances before, and as our minds absorb the impact of that reality, our brains cannot perform as capably as they usually would.
  • The most professional people I know right now are those who show up, day after day, to teach under extraordinary circumstances. Perhaps they do it with their laundry waiting to be folded, while their children interrupt, thinking constantly of their loved ones, weathering loneliness, wearing sweatpants and potentially in need of a haircut. But I know they do it while acknowledging this is not the world in which we taught two months before, and that every student is facing disruption, uncertainty and distraction. They do it creatively, making room for the unexpected, challenging their students, with the world a participant in the conversation.
Ed Webb

I unintentionally created a biased AI algorithm 25 years ago - tech companies are still... - 0 views

theconversation.com/making-the-same-mistake-203734

AI algorithms race racism bias DickinsonCollege dickinson technology opinion analysis

shared by Ed Webb on 10 May 23 - No Cached
  • How and why do well-educated, well-intentioned scientists produce biased AI systems? Sociological theories of privilege provide one useful lens.
  • Scientists also face a nasty subconscious dilemma when incorporating diversity into machine learning models: Diverse, inclusive models perform worse than narrow models.
  • fairness can still be the victim of competitive pressures in academia and industry. The flawed Bard and Bing chatbots from Google and Microsoft are recent evidence of this grim reality. The commercial necessity of building market share led to the premature release of these systems.
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  • Their training data is biased. They are designed by an unrepresentative group. They face the mathematical impossibility of treating all categories equally. They must somehow trade accuracy for fairness. And their biases are hiding behind millions of inscrutable numerical parameters.
  • biased AI systems can still be created unintentionally and easily. It’s also clear that the bias in these systems can be harmful, hard to detect and even harder to eliminate.
  • with North American computer science doctoral programs graduating only about 23% female, and 3% Black and Latino students, there will continue to be many rooms and many algorithms in which underrepresented groups are not represented at all.
Ed Webb

William Davies · How many words does it take to make a mistake? Education, Ed... - 0 views

www.lrb.co.uk/...does-it-take-to-make-a-mistake

education tools technology edtech opinion analysis humanities UK Britain higher-ed surveillance politics STEM

shared by Ed Webb on 21 Feb 22 - Cached
  • The problem waiting round the corner for universities is essays generated by AI, which will leave a textual pattern-spotter like Turnitin in the dust. (Earlier this year, I came across one essay that felt deeply odd in some not quite human way, but I had no tangible evidence that anything untoward had occurred, so that was that.)
  • To accuse someone of plagiarism is to make a moral charge regarding intentions. But establishing intent isn’t straightforward. More often than not, the hearings bleed into discussions of issues that could be gathered under the heading of student ‘wellbeing’, which all universities have been struggling to come to terms with in recent years.
  • I have heard plenty of dubious excuses for acts of plagiarism during these hearings. But there is one recurring explanation which, it seems to me, deserves more thoughtful consideration: ‘I took too many notes.’ It isn’t just students who are familiar with information overload, one of whose effects is to morph authorship into a desperate form of curatorial management, organising chunks of text on a screen. The discerning scholarly self on which the humanities depend was conceived as the product of transitions between spaces – library, lecture hall, seminar room, study – linked together by work with pen and paper. When all this is replaced by the interface with screen and keyboard, and everything dissolves into a unitary flow of ‘content’, the identity of the author – as distinct from the texts they have read – becomes harder to delineate.
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  • This generation, the first not to have known life before the internet, has acquired a battery of skills in navigating digital environments, but it isn’t clear how well those skills line up with the ones traditionally accredited by universities.
  • From the perspective of students raised in a digital culture, the anti-plagiarism taboo no doubt seems to be just one more academic hang-up, a weird injunction to take perfectly adequate information, break it into pieces and refashion it. Students who pay for essays know what they are doing; others seem conscientious yet intimidated by secondary texts: presumably they won’t be able to improve on them, so why bother trying? For some years now, it’s been noticeable how many students arrive at university feeling that every interaction is a test they might fail. They are anxious. Writing seems fraught with risk, a highly complicated task that can be executed correctly or not.
  • Many students may like the flexibility recorded lectures give them, but the conversion of lectures into yet more digital ‘content’ further destabilises traditional conceptions of learning and writing
  • the evaluation forms which are now such a standard feature of campus life suggest that many students set a lot of store by the enthusiasm and care that are features of a good live lecture
  • the drift of universities towards a platform model, which makes it possible for students to pick up learning materials as and when it suits them. Until now, academics have resisted the push for ‘lecture capture’. It causes in-person attendance at lectures to fall dramatically, and it makes many lecturers feel like mediocre television presenters. Unions fear that extracting and storing teaching for posterity threatens lecturers’ job security and weakens the power of strikes. Thanks to Covid, this may already have happened.
  • In the utopia sold by the EdTech industry (the companies that provide platforms and software for online learning), pupils are guided and assessed continuously. When one task is completed correctly, the next begins, as in a computer game; meanwhile the platform providers are scraping and analysing data from the actions of millions of children. In this behaviourist set-up, teachers become more like coaches: they assist and motivate individual ‘learners’, but are no longer so important to the provision of education. And since it is no longer the sole responsibility of teachers or schools to deliver the curriculum, it becomes more centralised – the latest front in a forty-year battle to wrest control from the hands of teachers and local authorities.
  • an injunction against creative interpretation and writing, a deprivation that working-class children will feel at least as deeply as anyone else.
  • There may be very good reasons for delivering online teaching in segments, punctuated by tasks and feedback, but as Yandell observes, other ways of reading and writing are marginalised in the process. Without wishing to romanticise the lonely reader (or, for that matter, the lonely writer), something is lost when alternating periods of passivity and activity are compressed into interactivity, until eventually education becomes a continuous cybernetic loop of information and feedback. How many keystrokes or mouse-clicks before a student is told they’ve gone wrong? How many words does it take to make a mistake?
  • This vision of language as code may already have been a significant feature of the curriculum, but it appears to have been exacerbated by the switch to online teaching. In a journal article from August 2020, ‘Learning under Lockdown: English Teaching in the Time of Covid-19’, John Yandell notes that online classes create wholly closed worlds, where context and intertextuality disappear in favour of constant instruction. In these online environments, readingis informed not by prior reading experiences but by the toolkit that the teacher has provided, and ... is presented as occurring along a tramline of linear development. Different readings are reducible to better or worse readings: the more closely the student’s reading approximates to the already finalised teacher’s reading, the better it is. That, it would appear, is what reading with precision looks like.
  • Constant interaction across an interface may be a good basis for forms of learning that involve information-processing and problem-solving, where there is a right and a wrong answer. The cognitive skills that can be trained in this way are the ones computers themselves excel at: pattern recognition and computation. The worry, for anyone who cares about the humanities in particular, is about the oversimplifications required to conduct other forms of education in these ways.
  • Blanket surveillance replaces the need for formal assessment.
  • Confirming Adorno’s worst fears of the ‘primacy of practical reason’, reading is no longer dissociable from the execution of tasks. And, crucially, the ‘goals’ to be achieved through the ability to read, the ‘potential’ and ‘participation’ to be realised, are economic in nature.
  • since 2019, with the Treasury increasingly unhappy about the amount of student debt still sitting on the government’s balance sheet and the government resorting to ‘culture war’ at every opportunity, there has been an effort to single out degree programmes that represent ‘poor value for money’, measured in terms of graduate earnings. (For reasons best known to itself, the usually independent Institute for Fiscal Studies has been leading the way in finding correlations between degree programmes and future earnings.) Many of these programmes are in the arts and humanities, and are now habitually referred to by Tory politicians and their supporters in the media as ‘low-value degrees’.
  • studying the humanities may become a luxury reserved for those who can fall back on the cultural and financial advantages of their class position. (This effect has already been noticed among young people going into acting, where the results are more visible to the public than they are in academia or heritage organisations.)
  • given the changing class composition of the UK over the past thirty years, it’s not clear that contemporary elites have any more sympathy for the humanities than the Conservative Party does. A friend of mine recently attended an open day at a well-known London private school, and noticed that while there was a long queue to speak to the maths and science teachers, nobody was waiting to speak to the English teacher. When she asked what was going on, she was told: ‘I’m afraid parents here are very ambitious.’ Parents at such schools, where fees have tripled in real terms since the early 1980s, tend to work in financial and business services themselves, and spend their own days profitably manipulating and analysing numbers on screens. When it comes to the transmission of elite status from one generation to the next, Shakespeare or Plato no longer has the same cachet as economics or physics.
  • Leaving aside the strategic political use of terms such as ‘woke’ and ‘cancel culture’, it would be hard to deny that we live in an age of heightened anxiety over the words we use, in particular the labels we apply to people. This has benefits: it can help to bring discriminatory practices to light, potentially leading to institutional reform. It can also lead to fruitless, distracting public arguments, such as the one that rumbled on for weeks over Angela Rayner’s description of Conservatives as ‘scum’. More and more, words are dredged up, edited or rearranged for the purpose of harming someone. Isolated words have acquired a weightiness in contemporary politics and public argument, while on digital media snippets of text circulate without context, as if the meaning of a single sentence were perfectly contained within it, walled off from the surrounding text. The exemplary textual form in this regard is the newspaper headline or corporate slogan: a carefully curated series of words, designed to cut through the blizzard of competing information.
  • Visit any actual school or university today (as opposed to the imaginary ones described in the Daily Mail or the speeches of Conservative ministers) and you will find highly disciplined, hierarchical institutions, focused on metrics, performance evaluations, ‘behaviour’ and quantifiable ‘learning outcomes’.
  • If young people today worry about using the ‘wrong’ words, it isn’t because of the persistence of the leftist cultural power of forty years ago, but – on the contrary – because of the barrage of initiatives and technologies dedicated to reversing that power. The ideology of measurable literacy, combined with a digital net that has captured social and educational life, leaves young people ill at ease with the language they use and fearful of what might happen should they trip up.
  • It has become clear, as we witness the advance of Panopto, Class Dojo and the rest of the EdTech industry, that one of the great things about an old-fashioned classroom is the facilitation of unrecorded, unaudited speech, and of uninterrupted reading and writing.
Ed Webb

ChatGPT Is Nothing Like a Human, Says Linguist Emily Bender - 0 views

nymag.com/...e-chatbots-emily-m-bender.html

AI ethics linguistics consciousness LLMs opinion

shared by Ed Webb on 13 Mar 23 - Cached
  • Please do not conflate word form and meaning. Mind your own credulity.
  • We’ve learned to make “machines that can mindlessly generate text,” Bender told me when we met this winter. “But we haven’t learned how to stop imagining the mind behind it.”
  • A handful of companies control what PricewaterhouseCoopers called a “$15.7 trillion game changer of an industry.” Those companies employ or finance the work of a huge chunk of the academics who understand how to make LLMs. This leaves few people with the expertise and authority to say, “Wait, why are these companies blurring the distinction between what is human and what’s a language model? Is this what we want?”
  • ...16 more annotations...
  • “We call on the field to recognize that applications that aim to believably mimic humans bring risk of extreme harms,” she co-wrote in 2021. “Work on synthetic human behavior is a bright line in ethical Al development, where downstream effects need to be understood and modeled in order to block foreseeable harm to society and different social groups.”
  • chatbots that we easily confuse with humans are not just cute or unnerving. They sit on a bright line. Obscuring that line and blurring — bullshitting — what’s human and what’s not has the power to unravel society
  • She began learning from, then amplifying, Black women’s voices critiquing AI, including those of Joy Buolamwini (she founded the Algorithmic Justice League while at MIT) and Meredith Broussard (the author of Artificial Unintelligence: How Computers Misunderstand the World). She also started publicly challenging the term artificial intelligence, a sure way, as a middle-aged woman in a male field, to get yourself branded as a scold. The idea of intelligence has a white-supremacist history. And besides, “intelligent” according to what definition? The three-stratum definition? Howard Gardner’s theory of multiple intelligences? The Stanford-Binet Intelligence Scale? Bender remains particularly fond of an alternative name for AI proposed by a former member of the Italian Parliament: “Systematic Approaches to Learning Algorithms and Machine Inferences.” Then people would be out here asking, “Is this SALAMI intelligent? Can this SALAMI write a novel? Does this SALAMI deserve human rights?”
  • Tech-makers assuming their reality accurately represents the world create many different kinds of problems. The training data for ChatGPT is believed to include most or all of Wikipedia, pages linked from Reddit, a billion words grabbed off the internet. (It can’t include, say, e-book copies of everything in the Stanford library, as books are protected by copyright law.) The humans who wrote all those words online overrepresent white people. They overrepresent men. They overrepresent wealth. What’s more, we all know what’s out there on the internet: vast swamps of racism, sexism, homophobia, Islamophobia, neo-Nazism.
  • One fired Google employee told me succeeding in tech depends on “keeping your mouth shut to everything that’s disturbing.” Otherwise, you’re a problem. “Almost every senior woman in computer science has that rep. Now when I hear, ‘Oh, she’s a problem,’ I’m like, Oh, so you’re saying she’s a senior woman?”
  • “We haven’t learned to stop imagining the mind behind it.”
  • In March 2021, Bender published “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” with three co-authors. After the paper came out, two of the co-authors, both women, lost their jobs as co-leads of Google’s Ethical AI team.
  • “On the Dangers of Stochastic Parrots” is not a write-up of original research. It’s a synthesis of LLM critiques that Bender and others have made: of the biases encoded in the models; the near impossibility of studying what’s in the training data, given the fact they can contain billions of words; the costs to the climate; the problems with building technology that freezes language in time and thus locks in the problems of the past. Google initially approved the paper, a requirement for publications by staff. Then it rescinded approval and told the Google co-authors to take their names off it. Several did, but Google AI ethicist Timnit Gebru refused. Her colleague (and Bender’s former student) Margaret Mitchell changed her name on the paper to Shmargaret Shmitchell, a move intended, she said, to “index an event and a group of authors who got erased.” Gebru lost her job in December 2020, Mitchell in February 2021. Both women believe this was retaliation and brought their stories to the press. The stochastic-parrot paper went viral, at least by academic standards. The phrase stochastic parrot entered the tech lexicon.
  • Tech execs loved it. Programmers related to it. OpenAI CEO Sam Altman was in many ways the perfect audience: a self-identified hyperrationalist so acculturated to the tech bubble that he seemed to have lost perspective on the world beyond. “I think the nuclear mutually assured destruction rollout was bad for a bunch of reasons,” he said on AngelList Confidential in November. He’s also a believer in the so-called singularity, the tech fantasy that, at some point soon, the distinction between human and machine will collapse. “We are a few years in,” Altman wrote of the cyborg merge in 2017. “It’s probably going to happen sooner than most people think. Hardware is improving at an exponential rate … and the number of smart people working on AI is increasing exponentially as well. Double exponential functions get away from you fast.” On December 4, four days after ChatGPT was released, Altman tweeted, “i am a stochastic parrot, and so r u.”
  • “This is one of the moves that turn up ridiculously frequently. People saying, ‘Well, people are just stochastic parrots,’” she said. “People want to believe so badly that these language models are actually intelligent that they’re willing to take themselves as a point of reference and devalue that to match what the language model can do.”
  • The membrane between academia and industry is permeable almost everywhere; the membrane is practically nonexistent at Stanford, a school so entangled with tech that it can be hard to tell where the university ends and the businesses begin.
  • “No wonder that men who live day in and day out with machines to which they believe themselves to have become slaves begin to believe that men are machines.”
  • what’s tenure for, after all?
  • LLMs are tools made by specific people — people who stand to accumulate huge amounts of money and power, people enamored with the idea of the singularity. The project threatens to blow up what is human in a species sense. But it’s not about humility. It’s not about all of us. It’s not about becoming a humble creation among the world’s others. It’s about some of us — let’s be honest — becoming a superspecies. This is the darkness that awaits when we lose a firm boundary around the idea that humans, all of us, are equally worthy as is.
  • The AI dream is “governed by the perfectibility thesis, and that’s where we see a fascist form of the human.”
  • “Why are you trying to trick people into thinking that it really feels sad that you lost your phone?”
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