# data[].attributes.headline
3rd Annual AI Summit for Smarter Learning

# data[].attributes.subject
3rd Annual AI Summit for Smarter Learning

# data[].attributes.attachment_link.title
2025 AI Summit for Smarter Learning - The Center for Teaching and Learning

# data[].attributes.attachment_link.title
Submit Your AI Story - The Center for Teaching and Learning

# data[].attributes.attachment_link.description
750 million+ members | Manage your professional identity. Build and engage with your professional network. Access knowledge, insights and opportunities.

# data[].attributes.attachment_link.readable_text
This is a heavily interactive web application, and JavaScript is required. Simple HTML interfaces are possible, but that is not what this is.

Learn more about Bluesky at bsky.social and atproto.com.

Profile

Justin Cary

justinrcary.bsky.social

did:plc:fy6ae5fxthmb4bpwyinp7uy5

Creative || Artist || Gamer || Writer || Teacher Podcast https://anchor.fm/screentoscreen Substack https://substack.com/@justincary Medium medium.com/@justinrcary-75760 Web www.justinrcary.com

# data[].attributes.attachment_link.description
Creative || Artist || Gamer || Writer || Teacher Podcast https://anchor.fm/screentoscreen Substack https://substack.com/@justincary Medium medium.com/@justinrcary-75760 Web www.justinrcary.com

# data[].attributes.attachment_link.title
The Cosmic Invisible | Justin Cary | Substack

# data[].attributes.attachment_link.description
Stories, meditations and reflections. Click to read The Cosmic Invisible, by Justin Cary, a Substack publication. Launched 3 years ago.

# data[].attributes.attachment_link.description
Through the darkness of future pasts, The magician longs to see. One chants out between two worlds... "Fire... walk with me."

# data[].attributes.headline
How Higher Ed can Realize the Potential of GenAI

# data[].attributes.subject
How Higher Ed can Realize the Potential of GenAI

# data[].attributes.attachment_link.readable_text
The following categorizations can help higher education leaders make informed, strategic decisions about how to implement gen AI in their institutions.

Tasks with moderately high creative difficulty, moderate context variability, and moderate accuracy could be good candidates for gen AI-for example, creating marketing content, organizing brainstorming and innovation sessions, generating user stories, recording regulatory compliance, and summarizing reports, among many others.

Tasks with high accuracy and low context variability, such as data entry, are likely appropriate for other forms of automation, ranging from robotic process automation to physical robots to other machine learning-based applications.

Humans outperform AI at dealing with tasks that have high context variability,especially activities with a strong social aspect (tasks that require emotional intelligence, building relationships, or providing support like coaching and mentoring students), complex decision-making-especially for ambiguous situations (such as identifying a new academic program), strategic planning, and creative problem-solving (like increasing student engagement), among others.

Higher education leaders should strategically orient their AI investments toward the broader outcomes they wish to achieve

It's important to remember that most work activities involve more than one task-a fact ever visible in a field in which most faculty are simultaneously teachers, advisors, and researchers. Work activities that create value for the institution are likely to involve multiple tasks and even different types of tasks that are variously amenable to different automation tools.

Leaders can align their AI investments toward three broad outcomes by using a task-level analysis, which can inform how colleges and universities deliver value.

1. Efficiency: Automating individual tasks can help improve overall efficiency. Leading research universities are increasingly looking to automation tools to help with grant applications and administration, beginning with AI tools locating and sifting through available grant and funding opportunities to identify appropriate and likely prospects. Robotic process automation coupled with generative AI can complete the first draft of data entry on application forms, while intelligent optical character recognition can quickly decipher dense sections of award notices. This approach reduces the time and effort required for data entry, allowing principal investigators to focus on more strategic tasks.

2. Effectiveness: Adapting workflows to incorporate a suite of automation tools, each taking on the tasks to which they are best suited, can boost institutions' ability to accomplish their mission. Take accessibility, for example: Advancements in educational technology, particularly by incorporating gen AI applications, have the potential to improve accessibility for 20% of undergraduates and 11% of graduate students with a disability, while traditional modifications-tweaking systems not designed to accommodate exceptions-may not fully eliminate either existing barriers or those that become visible later.

The transformative impact of generative AI on higher education, particularly through AI-based tutoring systems, is garnering recognition from significant educational bodies, including the US Department of Education. These advanced systems offer personalized, step-by-step guidance and feedback, enabling a tailored learning experience that adjusts to the unique needs of each student. Historically, educational models required students to conform to a standard method of instruction, which was not always effective for every individual. However, the advent of generative AI tools in education allows for a more inclusive approach where students can engage with material in a way that best suits their learning styles, significantly broadening the likelihood of academic success.

Beyond individualized instruction, AI applications can enhance collaborative learning and empower educators to integrate teaching strategies informed by cognitive science. For many instructors, this will require a transition, a transition many are already making, shifting from the traditional lecture-and-listen model toward a more dynamic, interactive approach.
Making education more accessible for diverse learning styles
Supporting instructional excellence. Integrating advanced language models into learning systems can considerably facilitate the incorporation of Universal Design for Learning principles. These models help educators adapt course materials, assessments, and learning tasks to accommodate diverse student needs, thereby promoting a more inclusive learning environment. AI applications can assist in formulating course policies that offer students flexibility in demonstrating their learning, fostering intrinsic motivation, and developing self-assessment skills in various ways.

Enhancing learner engagement. Gen AI tools play an important role in transforming the learning experience for all students through simplifying complex language or generating customized practice problems. These tools can facilitate a more engaging and supportive educational environment by introducing adaptive feedback mechanisms that allow students to learn at their own pace and in ways that best suit their individual learning styles. While these advancements are beneficial for the entire student body, they are particularly effective for students with neurodiversity and cognitive or learning disabilities. For these students, AI-driven tools can significantly reduce barriers to learning, ensuring that education is accessible and tailored to meet a wide range of learner needs.

3. Efficacy: Beyond making current processes more efficient and effective, colleges and universities can use gen AI tools to address thorny problems such as loneliness and student mental health.

In recent years, loneliness on college campuses has emerged as a pressing issue, with US Surgeon General Vivek Murthy targeting college environments on a 2023 nationwide tour that underscored the vital importance of social bonds and brought to light a paradox: Numerous students feel deeply isolated despite being part of a bustling campus community. Many struggle to express their authentic selves and forge meaningful relationships. With loneliness associated with significant health risks as well as disengagement, educational institutions are aiming to foster supportive, community-centric environments.

By helping students connect with peers who share interests or challenges, AI-based technologies can alleviate feelings of isolation and nurture a sense of community. Duke University's tech-enabled QuadEx residential housing system, for example, aims to support students in maintaining a stable community network, particularly during transitional periods that can intensify feelings of loneliness. For a student in any campus situation, an AI-driven platform, interacting with the student, can help introduce the student to existing like-minded groups or even facilitate the creation of new groups such as study circles, wellness and exercise communities, and business networks.

# data[].attributes.attachment_link.title
How higher education can realize the potential of Generative AI

# data[].attributes.attachment_link.description
Generative AI represents a seismic shift for higher education institutions, ushering in a level of change comparable to that of the dawn of the internet.

# data[].attributes.headline
Scholars are Failing the GPT review Process

# data[].attributes.subject
Scholars are Failing the GPT review Process

# data[].attributes.attachment_link.title
Scholars are Failing the GPT Review Process

# data[].attributes.attachment_link.description
Since the beginning of this age of “generative AI,” members of fields and disciplines ranging across commerce, food service, medicine, and education have sought to find at least one use case fit to the purpose of what these generative pretrained transformers (GPTs) and large language models (LLMs) were supposed to be able to do. Within the realms of higher education and academic publishing, in particular, scholars have worked to understand the implications of and keep up with the proliferation of this rapidly spreading technology, often with less than desirable results. Some have begun implementing GPT-based plagiarism checkers, others telling students to use GPTs to complete their assignments, and still others seeking to train students to be better prepared to become “prompt engineers.” At the same time, some administrators dream of suites of GPT-integrated tools that might allow them to connect knowledge of a student’s academic and social lives with indicators of their mental and physical well-being.Look at most universities today and you will find at least three, often conflicting stances on what students should be allowed or expected to do, and in what context. What you are less likely to find is any kind of strategic communications as to what students should think of as “okay” and “not okay” across the board, which is due to the lack of robust discussion among faculty and administrators regarding what these technologies can and cannot do, let alone what they might mean for academia. And the unfortunate fact of the matter is, while both students and established scholars are in danger of ending up on the wrong side of ill-defined rules, norms, and expectations, the seeming eagerness of many to hand over knowledge-certifying authority to GPT-based systems will lead, and in fact has led, to a great deal more harm for marginalized individuals and groups, as well as damaging the production of knowledge itself.As I noted in my article “Bias Optimizers,” researchers have demonstrated that GPT plagiarism checkers tend to misidentify text written by neurodivergent individuals.1 Since then, we have seen increasing evidence of prejudicial bias within these systems, which are intended to use pretrained transformer models to identify whether a human student has used a pretrained transformer model to complete their work. Research findings also show that those systems tend to generate far more false positives on non-native English speakers.2 From that point, begin to consider the differences in how expectations and perceptions of gender and race can affect people’s communication styles—and how these lived experiences are least likely to be properly accounted for in either the training data or the weighting architectures of GPTs or other “AI” tools.3To highlight the importance of these intersections, consider an incident scholar Rua M. Williams discussed on social media. Williams recounted a tale in which the writing and scholarship quality of a non-native English-speaking student with whom they were working suddenly and catastrophically diminished. When Williams reached out to the student out of deep concern, it turned out the student had recently begun using ChatGPT to rewrite their work to “sound more white.”4Neurodivergent individuals, non-native English speakers, women, and racially minoritized individuals tend to “mask” or seek to “pass” in their communications, whether spoken or written. From the outside, this process often appears as if someone is overthinking or being overly formal or precious—even “stilted” or “robotic”—with their word choices. In written form, these word choices and patterns of phrasing get flagged as “anomalous” by GPT checkers, thus assessed more likely not to be “human.” And flagged not only by the automated systems but by other humans as well.5 The way that this comes to pass is honestly fairly simple. We have all been sold GPTs and other LLM-based systems as though they provide factual, truthful answers, rather than doing the statistical language generator equivalent of what philosopher Harry Frankfurt termed “Bullshitting.”6 This happens because technologies that rely on code and math garner veneers of “objectivity,” which in turn gives people a way to wash their hands of any responsibility for what those very human technologies do; the repeated habit of and inclination toward this process is what Meredith Broussard terms “technochauvinism.”7 This happens not only with GPTs but with “AI,” algorithms, and code more broadly as well.Put plainly, we really want the shiny, mathy, “objective” answer, and we are very inclined to believe that technology will give it to us. People think GPTs tell the truth, and so people think GPT-based checkers tell the truth, and so people think they can trust and learn from GPT checkers how to tell when something is written by GPT rather than a human being. And not one of these thoughts that people think is correct. But the academy and general public’s willingness to trust computers and “AI” over other humans, even and especially when computers and “AI” are making decisions about humans, is currently hurting, and will continue to hurt, a lot of already marginalized people—unless we work hard to fix it. In case you find yourself willing to downplay this, filing it under the header of, “Well, it’s a small portion of scholars or potential experts; what’s the real harm?,” let me assure you that these harms will be borne by all of us eventually; the marginalized and minoritized are just the ones who experience it first.Thus, it is in atmospheres and tendencies such as these, and incidents like the one described and experienced by Rua Williams, where we can observe the contributing factors that have led an increasing number of scholars to use GPT tools to translate, revise, or wholly write the articles that they submit to peer review. Scholars under pressure to publish or perform or otherwise live up to the perceived expectations of their discipline are willing to, at the very least, run their hard-won knowledge through systems that do not and, as shaped, cannot truly understand what they are being asked to process. The sociotechnical paradigms of these new technologies are often situated in a hypothetical space where the technology is perceived as neutral. At “best,” this results in scholars trying to “get out ahead” of the technology, seeking ways to integrate it into their work or field of research, even where it does not fit.8 At worst, this high-pressure adversarial relationship may lead to scholars using this technology to write papers or generate “research” whole cloth.These technological systems might provide some benefit at some point—the ability to help researchers and writers hypothesize based on carefully curated datasets, for instance. But the current massive power and water demands of these tools, as well as the unethical provenance of most of their training data, should—at the very least—give us serious pause. And neither is it to deny that while some scholars are seeking tools to deal with their justifiable stress and panic in the face of ever-increasing professional demands and shifting sociotechnical pressures, others certainly are searching for the most expedient, low-effort way through their classes and workload. While the unequally borne pressures of the academy and the existence of scammers, grifters, and epistemic hucksters are hardly breaking news that arose only in the age of “Generative AI,” the materialities of said age do change the scope and proliferation of these problems in ways that will require the academy to rethink our peer review processes and expectations.At base, underneath all of the considerations and concerns about whether and how academic professionals should use “AI” are the fundamental questions of all scholarship: What skills and knowledge do we seek to cultivate in and through our research? What do we believe actually ought to be the purpose of our work and contributions? And how do we help ourselves and each other to remember that these are different questions, the answers to which have very different but importantly connected implications?If we as scholars can truly internalize that a major part of our job is about helping the public, the academy, and ourselves understand that we have real and meaningful stakes in scholarship, beyond publication, promotion, and tenure, then we can remember to remain critical and careful about the origins, capabilities, and failures of “AI” and any other new technology that comes our way. If we cannot, then it will not matter what new technologies we engage with in our research or our teaching, because apparently the only thing that will concern us is publication count itself—not what it is supposed to represent.

# data[].attributes.attachment_link.readable_text
"An Economist Biggest Book of the Year"

"A timely and fascinating new book by the former Downing Street aide-turned-tech executive Verity Harding, which argues that it's high time the public got a say on what kind of world we actually want to live in. . . . Harding, who knows these two incestuous worlds better than most, is right, however, that this extraordinary chapter of human history doesn't have to end in catastrophe, or in angry mobs rising up against a tech elite perceived as having gone too far. . . . For now, at least, there's still power in being human. But only if we use it." ---Gaby Hinsliff, The Guardian

"Harding is bilingual in politics and tech. . . . [She] urges politicians - and civil society - to get involved in debates about the uses of AI and help to shape the future in a positive way." ---John Thornhill, Financial Times Harper's Bazaar

"Harding sits at the intersection of politics, policy, and technology, and she brings her knowledge to this accessible introduction to AI and how it will shape our workplaces and beyond." ― ---Sue Halpern,

"An eminently readable examination of the debates over earlier transformational technologies and their resolutions." New York Review of Books AI Needs You ] with examples across different industries. . . . I highly recommend Verity Harding's

"Harding believes that AI has infinite potential to improve our lives. To demonstrate this, she fills [ AI Needs You ." ---Leonora Cravotta, American Spectator AI Needs You: How We Can Change AI's Future and Save Our Own , Harding wants to empower everyone to join the AI conversation and influence its future." ---Rachel Duffell, Tatler Asia ---Phil Reilly, Meta

"In this manifesto from one of the most influential people in AI, Verity Harding argues that society needs everyone to answer this urgent question to ensure that as the power of AI grows, so does its promise to be peaceful in its intent, and to serve a purpose and the public. Drawing on lessons from other technology revolutions, including the space race, the development of IVF and the dawn of the internet, through Library Journal ​​​​​​​ AI Needs You gives us hope that we, the people, can imbue AI with a deep intentionality that reflects our best values, ideals, and interests, and that serves the public good." ---Simon Cocking, Irish Tech News Kirkus

"Fascinating. . . . Finished it in two sittings without even meaning to. Most readable book about tech I've read in years." ---Ruth Aylett, Morning Star

"[Harding's] narrative provides considerable historical context for each tech milestone and draws parallels between the institution of regulatory guardrails and the importance of outlining the safe and ethical use of AI. . . . A loud and clear call to action regarding AI's future, which is put into perspective by probing the history of three other major technological innovations." ― AI Needs You ] shines an optimistic light on the AI revolution." ― Choice

"We might hope that this book ends up in the hands of those who could take a leadership role, before it is too late. Harding's optimism is tempered by experience and knowledge, and her arguments are compelling and engaging." ―

"Her case studies are well-presented, instructive, and worth the read."

"Contrary to the doomsayers of modern media, [

"This book couldn't be more timely. It's a fascinating blend of history and insight and a must-read for anyone interested in AI. For all the sound and fury around AI, Verity Harding reminds us that we've been here before, that revolutionary technologies can be developed responsibly, and that it's possible for allies and rivals alike to find common ground." -Nick Clegg, President of Global Affairs, Meta -Baroness Martha Lane-Fox

"Verity Harding is a rare beast-a technologist who thinks deeply about society. So when she tells us AI needs us, we should listen. In this thoughtful, clever, and very accessible book, you will learn about how we have faced huge technical innovations in the past and why, more than ever before, we must engage with how AI is shaping the future." -Diane Coyle, author of

"What is the world that AI is creating? And why are the rest of us letting this world be shaped by a small, privileged group of (mainly) men in Silicon Valley? This book, rooted in deep historical insights about prior technological disruptions, is essential reading for anybody keen to ensure the transformative power of AI is directed to the common good." Cogs and Monsters -Dan Snow, founder of the History Hit

"This is history at its most essential. Providing a forensic analysis of the past that provokes lessons, warnings, and inspiration, Harding empowers us to join a conversation from which the tech bros have tried to exclude us. This brilliant book is a scholarly, optimistic call to action." podcast -Katie Prescott, technology business editor, The Times -Alwyn Turner, author of

"A must-read for anyone who wants to understand the defining technology of our era, from a unique author who has had a front row seat in AI's development." All in It Together -Alastair Campbell, cohost of The Rest Is Politics

"With an engaging blend of storytelling and analysis, Harding argues that, even on the shifting frontiers between science and science fiction, democracy still matters. Wise, convincing, essential." podcast AI Needs You uses the recent history of technological governance to make a unique, evidence-based contribution to the AI debate that is currently overly dominated by the extreme alternatives of doomerism and blind optimism."

"An important and insightful book on one of the most important and challenging issues of our time." -Jason Furman, Harvard University, former chair of the White House Council of Economic Advisers -Sathnam Sanghera, author of Stolen History AI Needs You

"A must-read for anyone interested in the future of AI or technology more broadly-which Verity Harding persuasively argues should be everyone. presents a compelling vision based on real insider knowledge and mastery of the field." -Justin Smith-Ruiu, author of The Internet Is Not What You Think It Is: A History, a Philosophy, a Warning -Rory Cellan-Jones, journalist and former BBC News technology correspondent

"Essential. There's no one else I'd more want to read on this subject." -Lord William Hague of Richmond, former foreign secretary of the United Kingdom AI Needs You is a riveting page-turner about the moral dilemmas posed by seismic technological innovation."

"Drawing lessons from key moments in the history of technology and science, Harding argues that AI can and must be subordinated to human ends. -Jude Browne, coeditor of Feminist AI: Critical Perspectives on Algorithms, Data, and Intelligent Machines -Jonathan Zittrain, Harvard University -Stephen Cave, director of the Leverhulme Centre for the Future of Intelligence at the University of Cambridge AI Needs You

"An excellent and refreshing primer from someone who has been thinking about AI ethics for years. For anyone looking for a pragmatic yet optimistic view of how we can live with AI, this book is very timely." , Verity Harding draws on history to offer a reality-based guide to the future. Anyone seeking a primer on AI, free of hype or hysteria, should start here." -Ian Leslie, author of

"Verity Harding is an important thinker on the future of AI and this book makes a major contribution to the debate. The parallels the book draws between the regulation of AI and previous technological breakthroughs, from nuclear weapons to human embryology, should make policymakers think." Conflicted: How Productive Disagreements Lead to Better Outcomes

"An absolutely captivating narrative. -Linda Yueh, author of The Great Crashes: Lessons from Global Meltdowns and How to Prevent Them

"Harding deftly mines lessons from the development of the space race, IVF, and the internet to brilliantly limn the challenges we're facing now with AI-and to make the case that you don't need to be an AI expert to have an informed opinion about AI."

"Clear, lucid, and a joy to read. Harding draws important lessons for the governance of AI from three historical examples of emerging technology."

"Although AI is a new technology, in many ways we've been here before. In

"I share the belief that we can learn from history and this timely book enables us to do just that by highlighting those valuable lessons and what they mean for AI."

# data[].attributes.attachment_link.title
AI Needs You: How We Can Change AI's Future and Save Our Own

# data[].attributes.attachment_link.description
AI Needs You: How We Can Change AI's Future and Save Our Own [Harding, Verity] on Amazon.com. *FREE* shipping on qualifying offers. AI Needs You: How We Can Change AI's Future and Save Our Own

# data[].attributes.attachment_link.title
Co-Intelligence: Living and Working with AI

# data[].attributes.attachment_link.description
Co-Intelligence: Living and Working with AI [Mollick, Ethan] on Amazon.com. *FREE* shipping on qualifying offers. Co-Intelligence: Living and Working with AI