Erik Brynjolfsson

Learning about Carolina AI Data Literacy Modules. These are free to add to Canvas. https://lnkd.in/gRfQxAE5

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As the #ICIS2024 deadline approaches, I thought sharing an IS Classic on Information Systems as a reference discipline + the MISQ Insider interview with Richard Baskerville and Michael Myers felt about right. The article: https://lnkd.in/eE27nA43 The insider interview: https://lnkd.in/epE6wrhT The citation: Baskerville, R. L., & Myers, M. D. (2002). Information systems as a reference discipline. MIS Quarterly, 1-14. The abstract: The conventional wisdom amongst information systems (IS) researchers is that information systems is an applied discipline drawing upon other, more fundamental, reference disciplines. These reference disciplines are seen as having foundational value for IS. We believe that it is time to question the conventional wisdom. We agree that many disciplines are relevant for IS researchers, but we suggest a re-think of the idea of “reference disciplines” for IS. In a sense, IS has come of age. Perhaps the time has come for IS to become a reference discipline for others. #misq #bangkok2024 #ais

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What is your Relationship with AI? The Snyder Innovation Management Center at the #WhitmanSchool at Syracuse University thanks Dr. Aric Rindfleisch, who asked the 2024 PDMA - Product Development and Management Association doctoral consortium participants to reflect on their “relationship with AI.” He noted that in the current “knowledge economy,” AI is a tool that can enhance “how” we study by enabling a transition from knowledge creation to knowledge curation. To learn more, visit: https://buff.ly/4dt0JDz #Snydercenter #PDMA #JPIM #SyracuseU #Innovation #AI #knowledgeeconomy #syracuseuniversity

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Spent today learning and practicing star schema modeling to enhance my work in institutional research! Star schemas are essential for organizing data in a way that simplifies analysis, improves performance, and supports better decision-making. This knowledge will help me create more efficient models for reporting on key metrics like enrollment, retention, and student success. #DataAnalytics #StarSchema #InstitutionalResearch #DataModeling #HigherEdAnalytics #StudentSuccess #Retention #EnrollmentTrends #BusinessIntelligence #PowerBI #DataDriven #HigherEducation #ProfessionalGrowth #LearningAndDevelopment

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Here are the five lessons from Gurobi Optimization's panel on Academics Changing the World: 1. There are plenty of interesting non-profit or public sector problems. (Julie Aho, CSCP.. this is a point you've made-- I let my students know that you said this!) 2. The diet problem has interesting applications! 3. “Get data without being annoying” 4. Visualization and user interaction with the solution is important. 5. Get data from all stakeholders, not just the dominant voices. See the article for more details, including a link to a great INFORMS Edelman Prize winner: the UN World Food Programme. Thanks to Duke Perrucci for hosting. And, thanks to Karen Smilowitz, Ozlem Ergun, and Dick den Hertog for the great insights.

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Generative AI is evolving at record speed while CEOs are still learning the technology’s business value and risks. Here, McKinsey and Company offers some of the generative AI essentials.

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OpenAI has just released a new model (4o1) that can perform complex reasoning. It will impact education because the model is able to solve more difficult problems and explain its reasoning step by step. https://lnkd.in/eveDJMtW Applications in education include: - An AI guide that takes a student through a problem step-by-step using its reasoning to explain each step at a level appropriate to the student. - Personalized learning pathways where the AI optimizes a sequence of learning activities (content, quizzes, examples) based on student responses. - Adaptive assessment where the AI explains to the student why their answer is incorrect by breaking down the process that leads to a correct solution. - Interactive learning simulations, for example to treat virtual patients. - Collaborative learning platforms where the system guides group discussions by prompting students to think through each other's reasoning. But, and this is a big BUT - the model is still at an early stage of development and in some cases makes more errors than the previous (4o) model. Also, while it can reason about topics in more detail it still can't visualize the world. I have tried testing a series of models on the problem below, which only uses high school maths, but requires the AI to "visualize" how the two hemispheres are glued together. "A solid sphere of radius 8 cm is sliced in half and another hemisphere half its radius is glued onto its base. What is the combined visible surface area? Show your working." Try it yourself with your favourite model (the correct answer is 208π cm2). ChatGPT4o fails, even when asked to try again. ChatGPT4o1 gets it right second time.

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I am delighted that this article has finally been published. Sung, W., An, H., & Thomas, C. L. (2024). PICRAT Analysis of Technology-Integration Activities in U.S. K–12 Public Schools. Computers in the Schools, 1–24. https://lnkd.in/eDddE9su Woonhee Sung | Christopher Thomas Abstract: This study examined technology integration in K–12 public schools based on the PICRAT (Passive, Interactive, Creative, Replace, Amplify, Transformative) matrix classification. Seventy-six K–12 teachers voluntarily completed an online survey between December 2020 and February 2021 that asked about their (a) grade-level teaching (b) implementation frequency of various technology-integrated activities, and (c) support. Results showed that teachers’ real-class implementation of technology-integrated activities and the PICRAT levels of integration differed significantly between K–6 vs. 7–12 grades. More frequent use of overall technology-integrated activities was found in grades 7–12 than in K–6. Further, an analysis based on the PICRAT matrix found higher frequencies for Passive and Replace levels and lower frequencies for Creative and Transformative use for all grades. Finally, teacher support significantly predicted overall technology-integration frequencies for both K–6 and 7–12 grades. With regard to prediction on each level of PICRAT classification, support in K–6 grades was significantly related to all levels of technology integration except for Passive. However, in 7–12 grade, support failed to predict the frequency of technology integration for all levels except Amplify. Future directions are discussed, including the role of professional development and the importance of technology-integration frameworks in practice.

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How do children form a close and trusting relationship with a robot? 🤝 🤖 Interesting paper I read today: Child–robot relationship formation: A narrative review of empirical research Authors: Caroline van Straten, Jochen Peter & Rinaldo Kühne Here's a brief summary I wrote: In this review paper, the authors provide a comprehensive overview of the existing literature on the factors associated with child-robot relationship formation. The focus is on two key dimensions: closeness and trust in children’s relationships with social robots. Most of the studies reviewed involved children aged 6 to 12. Regarding robot characteristics, the robot’s responsiveness plays an important role in fostering a sense of closeness. However, no specific robot characteristic appears to strongly predict trust; for instance, embodiment was positively associated with closeness but not with trust. Furthermore, robot responsiveness, tailoring, and embodiment were all linked to enjoyment and engagement—mental states that can lead to closeness and trust. However, these factors did not significantly influence other mental states, such as empathy or anthropomorphism. Interestingly, children reported feeling a sense of closeness to robots that fell somewhere between their feelings toward humans and inanimate objects, yet in some cases, they trusted robots more than humans. Younger children were more likely to enjoy interactions with robots compared to older children. The paper highlights that advanced technology may not be necessary to evoke feelings of closeness in children, as even simple robot features, like a certain level of responsiveness, can foster such connections. On the other hand, further research is needed to better understand the psychological mechanisms through which children develop varying degrees of closeness and trust with robots.

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Finding the right use cases is key to utilizing #AI effectively. 

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How to capitalize on #AI’s 7 wicked opportunities for #K12 The time is now to turn the “wicked problems” that could prevent artificial intelligence from transforming education into “wicked opportunities,” a new report contends. Under the right conditions, AI can drive self-directed and self-paced learning and help educators pave more meaningful pathways from high school to college and careers, say participants in a think tank convened recently by the Center on Reinventing Public Education. KEY TAKEAWAYS FOR LEADERS: Think big about how AI can transform education.  Help districts use AI strategically. Allocate funds to support and test AI initiatives, particularly in low-income and historically marginalized communities.  Provide detailed, actionable implementation strategies to help districts navigate AI adoption effectively. Members of the forum also said the technology could: Measure what matters beyond academics in a meaningful way Make the teaching job easier, different and more exciting Bring all students to grade level through a combination of better schools and new technology Harness the ability to develop the full potential of every human Full report https://lnkd.in/eieaf4ZM District Administration, #AI #edtech #artificalintelligence Arizona State University

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"We’ve seen many course syllabi that ban AI outright, equating its use with plagiarism. AI can do much more than simply giving us students the answer." CARADITE's two undergraduate research assistants—Emma Ren and Barron Brothers—recently attended Duke Learning Innovation & Lifetime Education's second annual Emerging Pedagogies Summit. As the only undergrads at the Summit, they "found the discussions insightful and practical for bridging the gap between traditional educational practices and AI-driven learning tools." In this blog post, Emma and Barron reflect on their participation in a Summit workshop focused on GPTs. They also share related thoughts about how they believe university instructors should make thoughtful use of these technologies in support of student learning. There's a lot of wisdom here: "While AI can handle certain repetitive tasks, personal connections between students and educators remain essential for fostering skills like empathy and collaboration. Essentially, AI is a tool to enhance—not replace—human relationships." It's been a pleasure learning alongside Emma and Barron this semester, I hope you enjoy their blog post: https://lnkd.in/gW6cvZix #HigherEducation #GenerativeAI #AI

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#AI is a tool. How will we use it for #education? On his visit to Indiana University School of Public Health-Bloomington, distinguished educator Marcio A. Oliveira, Ph D. described emerging uses (and misues) of AI in education.

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I am a fan of AI to support evidence-based practice in nursing. This thought provoking article challenges my ideas on grant writing, data analysis and the research endeavour. Where do you see AI helping in nursing, where do you see the line that should not be crossed? #AI #nurse academic

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Digital or Analog for education 💽 Digitalizing higher education: https://wp.me/pfPUUQ-7r After three decades of unbridled spending on digital technology, it is time to check what value is being created and captured. Has widespread digitalization of higher education made any difference, and for who? Clearly, no amount of analysis is going to halt technology creation, purchase, or use. Electrons and coding are out of the gates, and away. As platforms develop, so too should sophistication and strength of education evaluation. Stirring dialogue around technology almost inevitably provokes interest in more transparency. Digitalization of higher education undoubtedly moves universities in a commercial direction, not least as the smallest teaching interactions are sewn into proprietary platforms owned by big global capital. There is value in public disclosure about these ideas. Vendor research exists in many cases, but while informative it is obviously conflicted. Commercial intelligence platforms exist, as do advocates, and local or large-scale platform/education evaluations. But there is a large gap between sources of information. Join: www.helf.net Higher Education Futures Lab Hamish Coates Ralph Saubern

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I had the privilege of helping to review the report, particularly focusing on the Generative AI section. It has been an incredible experience to work with Prof. Florence G'SELL and their team. This is a pivotal moment for global AI governance! #GenerativeAI #CyberPolicy #AIRegulation #GlobalGovernance

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Very good interview of Alex 'Sandy' Pentland who's joining Stanford Institute for Human-Centered Artificial Intelligence (HAI)'s Digital Economy Lab; these 5 arguments especially resonated with me: 1) "We also need to reduce partisan animosity online. Currently, digital media are designed to get us to react quickly, which results in unthinking responses that in turn lead to cascades of behavior where everyone becomes outraged. We need a system that instead encourages people to communicate in ways that support democratic processes rather than tearing them apart. Large-scale experiments find that online discussions are improved when people are encouraged to reflect a little bit on what they are about to say. For example, we see less division and outrage online when we add an extra step that allows time for reflection before replying or forwarding, or add a prompt to consider what a comment will do to your reputation." 2) "we need to draw a line between individual expression and mass expression. For example, consider the case where influencers often have more than a million “friends” on social media. Anyone with that many people following them can make money and build a reputation while saying whatever they want. And I think these overly powerful voices ought to be treated like businesses and not like individuals. They shouldn’t be able to cry “fire” in a crowded theater or tell outright lies. Those are basic standards we demand of other businesses [like] TV news shows or newspapers can’t publish something just to generate outrage. (...) If you’re going to express your ideas to a million people, then you’re a business and you ought to be regulated like a business." 3) "In some cases, fixing the problem will require changing often subtle little things down in the guts of the internet. As an example, if someone is producing 50,000 tweets a day, that’s a bot, not a human. That’s an obvious case, but there are other things we can do to find bots more efficiently, determine when foreign nations are interfering in elections, and better deal with ransomware and cyberattacks. The problems we have now evolved because the architecture of the internet was never completed. And now maybe the time has finally come to finish the job." 4) "it’s not artificial general intelligence, or AGI, that worries me. It’s that AI is becoming pervasive in so many parts of our lives, including our medical system, our transportation system, and our schooling system. It’s going to be everywhere, just like the previous waves of AI were. And we need to make sure that it’s prosocial." 5) "AI has always been and continues to be a way of finding and using patterns in data. So, if you want to control AI, you have to control the data it feeds on by demanding privacy rights and ownership rights over data. Without that, AI will just run amok. Data are like the food for AI, and if you want to control AI, you have to control the data."

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GenAI leans towards left-of-center viewpoints. See the findings in this open access article. The author, David Rozado, concludes: "With LLMs beginning to partially displace traditional information sources like search engines and Wikipedia, the societal implications of political biases embedded in LLMs are substantial." Should we worry? . See also the figure in the first comment on the summarized findings. . . . #LLM #LLMs #ArtificialIntelligence #CDR #CorporateDigitalResponsibility #CSR #Ethics #Fairness #IntelligentAutomation #AI #GenerativeAI #ServicesMarketing #ServiceManagement #BusinessEthics #ESG

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