Data Strategy Lab at the Ostrom Workshop转发了
Data Strategy Lab at the Ostrom Workshop
高等教育
Bloomington，Indiana 46 位关注者
Working together to design governance frameworks that bring data to life
关于我们
The Problem: In both the public and private sectors, companies and organizations lack the skills and/or the strategy to manage the large amounts of data they have collected. Their data efforts may have adequate technological support but lack strategic vision, stakeholder input, and clear goals of productivity, security, and equitable and responsible conduct. Current approaches to strategic data planning are either too narrow, too technical, or too siloed. The Solution: The Data Strategy Lab at the Ostrom Workshop, Indiana University will help public institutions, companies, and organizations to create a human-centered data strategy and train future data managers in stakeholder and community engagement as an essential component of such strategy. Our mission is to promote responsible data practices that prioritize privacy, security and ownership when using data. The Lab will do this by producing and supporting projects that focus on under-resourced organizations and ensure community building, stakeholder engagement, and institutional coordination. The Lab will develop toolkits and metrics to align organizational goals and needs as well as monitor and evaluate data-related activities. The Inner Workings of the Lab: The Data Strategy Lab will be led by Indiana University faculty and staff who will train and supervise students from the Luddy, Maurer, Kelley, and Lugar Schools as they are paid to work with identified clients to develop and implement human-centered data strategies. In its initial phase, the Data Strategy Lab will serve clients drawn from government, non-profit, and private-sector organizations who are otherwise unable to secure funding to develop and implement a human-centered comprehensive data strategy.
- 网站
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https://ostromworkshop.indiana.edu/
Data Strategy Lab at the Ostrom Workshop的外部链接
- 所属行业
- 高等教育
- 规模
- 2-10 人
- 总部
- Bloomington，Indiana
- 类型
- 非营利机构
- 创立
- 2023
地点
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主要
获取路线
513 N Park Ave
US，Indiana，Bloomington，47408
Data Strategy Lab at the Ostrom Workshop员工
动态
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Data Strategy Lab at the Ostrom Workshop转发了
Executive Director, Ostrom Workshop; Executive Director, Center for Applied Cybersecurity Research; Provost Professor, IU Kelley School of Business
We are recruiting a cybersecurity postdoc at The Ostrom Workshop and IU Center for Applied Cybersecurity Research with a priority application deadline of February 15 and an August 1, 2025 start date. The posting is for one year but is renewable for an additional year, and comes with opportunities to work with other university partners including the Center for Long-Term Cybersecurity. The opportunity is unique in that it is focused on advancing the research of The Consortium of Cybersecurity Clinics, and more broadly the public interest technology movement. As such, candidates should discuss in their cover letters: (1) what in their backgrounds speaks to an interest in clinical education generally, and applied cybersecurity in particular; (2) what interests them about the types of interdisciplinary cybersecurity research undertaken at the Ostrom Workshop and?CACR; (3) how they are well positioned to lead pedagogical and/or empirical cybersecurity research projects with other members of the Consortium of Cybersecurity Clinics; and (4) what opportunities you see to utilize Consortium data and practice to answer novel research questions. Would appreciate your help in spreading the word! https://lnkd.in/gUnaFFCq Link to cyber consortium site: https://lnkd.in/gvxJ_Tea
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Data Strategy Lab at the Ostrom Workshop转发了
???2025 WINIR Young Scholars Pre-Conference Workshop!??? https://lnkd.in/gEqdR9gW Institutions, Entrepreneurship & Shared Prosperity ?? Prague University of Economics and Business, Prague, Czechia ???9 September 2025 This workshop, co-organized by?World Interdisciplinary Network for Institutional Research (WINIR), Law as Science and?Young Scholars Initiative (YSI), invites early-career researchers to explore how institutions shape and are shaped by innovation and entrepreneurship. The event is a precursor to the?WINIR Conference on Institutions, Entrepreneurship & Shared Prosperity?(10–12 September 2025). ???Workshop Themes: ???Institutions, Innovation, and Resilience?– Institutional frameworks, innovation ecosystems, and governance structures. ???Entrepreneurial Responses to Institutional Pressures?– Navigating institutional complexity and driving systemic change. ???Social and Sustainable Entrepreneurship?– Addressing global challenges through entrepreneurial activity. ???Entrepreneurship Beyond the Private Sector?– Innovation in public institutions and cross-sectoral collaborations. We welcome submissions from doctoral students and recent graduates (within three years) in economics, law, sociology, anthropology, development studies, and related disciplines. Successful applicants will present their research to a supportive community of peers and senior scholars. Key Dates: ???Submission Deadline: 15 February 2025 ???Notifications of Acceptance: 5 March 2025 Submission Guidelines: 1?? A 500-word abstract (LastName_FirstName_Title.pdf) 2?? A short bio (LastName_FirstName_Bio.pdf) 3?? A CV (LastName.FirstName.CV.pdf) Submit your materials using the designated form: https://lnkd.in/g-Vhk8s9 Let’s reimagine how institutions, innovation, and entrepreneurship can foster shared prosperity and sustainable futures. ?? For inquiries, contact us at?[email protected]. Convenors: Christina Mosalagae (Young Scholars Initiative, Italy) | Nikhilesh Sinha (Hult International Business School, UK) | Simon Sun (National Yang Ming Chiao Tung University School of Law, Taiwan) | Vanessa Villanueva (European University Institute & Università Bocconi, Italy) Looking forward to seeing you in Prague! ?? #WINIR2025 #Innovation #Entrepreneurship #InstitutionalTheory #YoungScholars https://lnkd.in/gEqdR9gW ___________________________? Simon Sun?|?Vanessa Villanueva Collao?|?Patrick Chung-Chia Huang?|?Daniel Haefke?|?Marilyn Hajj?|?Stuti Shah?|?Tsung-Chun Chen?|?Shih-wei Chao?|?Kai-Ping Chang?|?Choky Ramadhan?|?Zabdi Salazar?|?Justin Sucgang?|?Ami Acary?| Ann Wang?|?Luis David Briceno Perez?|?Christabel R.?|?Zijin Yan?|?Dah-Wei Yih?|?Gesare M. ?|?Altay Mustafayev?|?Sharlene Chen?|?Vicente Antonio Caputo Sanhueza | Annissa Khanna
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Data Strategy Lab at the Ostrom Workshop转发了
There is a lot of speculation and concern around AI. People are afraid of the idea of artificial intelligence coming alive. This is due to the public’s confusion regarding “sentient algorithms”. Many see pictures of Terminator-style robots in AI articles and automatically feel biased against artificial intelligence. The authors of AI Snake Oil, Sayash Kapoor and Arvind Narayanan, argue that the key to the acceptance of generative AI is education. The first step in understanding AI is realizing that the term is vague. Kapoor and Narayanan divide AI into two subcategories: predictive AI and generative AI. Predictive AI uses data to forecast future outcomes or trends based on historical patterns. Generative AI creates new content, such as text or images, by learning patterns from existing data, and generates probable outputs to the prompt resembling the original data. Kapoor and Narayanan urge users of AI to take some time to understand concepts like neural networks and machine learning to demystify the technology for themselves. Narayanan believes that in the modern world, AI education needs to start at the elementary level. In conclusion, AI is not alive to destroy the world, it is here to help the user with their tasks, and humans need to educate themselves to develop a more precise idea of AI moving forward. Summarized by Jake Parker Generative AI Hype Feels Inescapable. Tackle It Head On With Education https://lnkd.in/e77yCS5g
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There is a lot of speculation and concern around AI. People are afraid of the idea of artificial intelligence coming alive. This is due to the public’s confusion regarding “sentient algorithms”. Many see pictures of Terminator-style robots in AI articles and automatically feel biased against artificial intelligence. The authors of AI Snake Oil, Sayash Kapoor and Arvind Narayanan, argue that the key to the acceptance of generative AI is education. The first step in understanding AI is realizing that the term is vague. Kapoor and Narayanan divide AI into two subcategories: predictive AI and generative AI. Predictive AI uses data to forecast future outcomes or trends based on historical patterns. Generative AI creates new content, such as text or images, by learning patterns from existing data, and generates probable outputs to the prompt resembling the original data. Kapoor and Narayanan urge users of AI to take some time to understand concepts like neural networks and machine learning to demystify the technology for themselves. Narayanan believes that in the modern world, AI education needs to start at the elementary level. In conclusion, AI is not alive to destroy the world, it is here to help the user with their tasks, and humans need to educate themselves to develop a more precise idea of AI moving forward. Summarized by Jake Parker Generative AI Hype Feels Inescapable. Tackle It Head On With Education https://lnkd.in/e77yCS5g
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Humans, in general, are biased against AI. We overly criticize AI for the actions it performs and fail to recognize that humans don’t do any better. There are many decisions made with human error that would benefit from a better decision-making process. If AI becomes better than the human status quo, which is a “low bar”, we would want it to make these decisions for us. Tomas notes that AI learns from us, so when it appears to act in a sexist or racist manner, that is what it has learned from the millions of humans who express these thoughts. We may blame AI without taking responsibility for the human biases embedded in AI systems. This turns AI into a scapegoat, and can ignore the source of the issue which is our attitudes and actions. Summarized by Jake Parker Why Are Humans Biased Against AI? https://lnkd.in/gH8PWub6
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Tech giants Amazon, Google, and Microsoft are investing in nuclear power to try to keep up with the energy demands tied to AI. Modern large language models consume massive energy due to their complexity, nonstop availability, and reliance on energy-intensive GPUs or TPUs over standard CPUs. Though tech companies are the largest buyers of wind and solar power and continue to burn fossil fuels to keep up with energy demand, they are looking for new ways to produce clean energy at a high rate. Google and Amazon are supporting the commercial construction of small modular nuclear reactors (SMRs). Historically, nuclear energy production has been slow and costly, but SMRs appear more appealing because of their size and scalability. Google signed a deal with Kairos Power to fund about seven reactors to add 500 megawatts by the decade’s end. Amazon signed an agreement with Washington and Virginia to back the development of SMRs and is partnering with X-energy for the Washington project. Microsoft signed a 20-year power-purchase agreement with Constellation to restart the failed reactor at Pennsylvania’s Three Mile Island. We have not commercially deployed a SMR in the US, and it seems like they have a long, but promising, road ahead of them. The AI revolution has challenged big tech’s sustainability goals. In the last 3-4 years both Microsoft and Google’s carbon emissions have surged by 40-50% as they try to compete in the AI market. Fossil fuels continue to power data centers, so companies like Dominion Energy, a utility company that provides electricity in Virginia, are expanding both carbon-free and natural gas plants to meet growing demand. In conclusion, tech companies are investing in all things energy as it will be a key aspect in sustaining their competitive edge in the rapidly evolving AI landscape. Summarized by Jake Parker Nuclear-Powered AI: Big Tech’s Bold Solution or a Pipedream? https://lnkd.in/g4dTTQ5q
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Thomas Edison’s 1913 prediction that motion pictures would replace books in schools has yet to come true. However, modern tools like Khanmigo, an AI-powered chatbot by Khan Academy, are reviving hopes for tech-driven transformation in education. Khanmigo allows students to interact with historical figures, solve math problems, write stories, and more. Khamigo will guide students in getting the answer themselves instead of giving it to them immediately. While traditional schooling is criticized for catering to an "average" student, leaving some bored and others behind, AI could address these issues through personalized learning normally reserved for wealthy kids with access to tutors. AI-driven education is most visible in math complementing classroom instruction or replacing homework. Advocates envision a broader transformation where flexible schedules and independent learning are paired with group projects to balance screen time with teamwork. They believe this will also free up time for the teacher and allow them to be more involved with their students. However, generative AI faces challenges like factual errors and limited classroom suitability. Additionally, motivation remains a hurdle, as students often engage better with human teachers and peers than with AI tools. Skeptics acknowledge AI's role in classrooms but argue it should complement, not replace traditional methods. Group learning fosters debates and helps students learn who they are as people. Chatbots may assist with specific tasks, but the social dynamics of a classroom are irreplaceable. Critics argue that AI is best suited to easing teacher workloads, such as creating quizzes, adapting reading materials, or handling administrative tasks. This allows educators to focus more on teaching and student engagement. AI has the potential to enhance teaching practices by providing feedback and supporting educators. Tools like TeachFX, Stanford's AI, and the University of Colorado’s AI analyze class recordings to help teachers reflect on their methods, assist remote tutors with real-time, and aim to guide students during group work, respectively. Rather than overhauling education, AI should refine existing practices. Dr. Reich of MIT argues schools function effectively because of established structures, like age-graded classes, and AI can complement these by improving what schools already do well. Summarized by Jake Parker Will artificial intelligence transform school? https://lnkd.in/gYzVyY63
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Data Strategy Lab at the Ostrom Workshop转发了
Join us! There's still time to register for our next event, held on November 6th at 12:00 PM E.T. For our next event of Fall 2024, Professor Kimberly Krawiec from University of Virginia School of Law will share "WHO Says Countries Should Be Self-Sufficient In (Unremunerated) Organs And Blood” Registration link:?https://lnkd.in/gWCHTKDw ___________________________ Read the Law as Science project statement:?https://lnkd.in/grq9G-Fv? Please visit our YouTube channel where you can view past Law as Science sessions:?https://lnkd.in/g2D-jHkn? Join the community:?https://lnkd.in/gHJKxvuz ___________________________ Taking place at?University of Virginia School of Law, this session is part of a series of events organized by?Law as Science. The Law as Science initiative is constituted of U.S. law school doctoral candidates from?Columbia Law School,?Fordham University School of Law,?University of Illinois College of Law,?Indiana University Maurer School of Law,?University of Pennsylvania Carey Law School, and?University of Virginia School of Law?that share an interest in research methodologies. ___________________________ Simon Sun?|?Vanessa Villanueva Collao?|?Patrick Chung-Chia Huang?|?Daniel Haefke?|?Marilyn Hajj?|?Stuti Shah?|?Tsung-Chun Chen?|?Shih-wei Chao?|?Kai-Ping Chang?|?Choky Ramadhan?|?Zabdi Salazar?|?Justin Sucgang?|?Ami Acary?|?Luis David Briceno Perez?|?Christabel R.?|?Zijin Yan?|?Dah-Wei Yih?|?Gesare Mogusu, LLB, CSBFP, LLM |?Altay Mustafayev?|?Sharlene Chen?|?Vicente Antonio Caputo Sanhueza | Annissa Khanna ___________________________ ?#LawasScience?#LegalMethodLab?#methodology?#SJD #JSD?#PHD?#DoctorofJuridicalScience?#lawschool?#law?#lawyer?#lawstudent?#lawyers?#academics?#doctoralstudies #science?#research?#blog?#community?#legal?#legalknowledge?#legalstudies
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Data Strategy Lab at the Ostrom Workshop转发了
Our next speaker is Professor?Chaumtoli Huq from?City University of New York School of Law. The topic of the lecture is "Critical Legal Research Methods:?Who is the Scholar & Redefining Legal Scholarship.” The event will be held on September 23 at 12:00 PM (E.T.) Registration link:?https://lnkd.in/g55mgKzP ___________________________ Read the Law as Science project statement:?https://lnkd.in/grq9G-Fv Please visit our YouTube channel where you can view past Law as Science sessions:?https://lnkd.in/g2D-jHkn Join the community:?https://lnkd.in/gHJKxvuz ___________________________ Taking place at?Columbia Law School, this session is part of a series of events organized by?Law as Science. The Law as Science initiative is constituted of U.S. law school doctoral candidates from?University of California, Berkeley - School of Law,?Columbia Law School,?Fordham University School of Law,?University of Illinois College of Law,?Indiana University Maurer School of Law,?University of Pennsylvania Carey Law School, and?University of Virginia School of Law?that share an interest in research methodologies. ___________________________ Simon Sun?|?Vanessa Villanueva Collao?|?Patrick Chung-Chia Huang?|?Daniel Haefke?|?Marilyn Hajj?|?Stuti Shah?|?Tsung-Chun Chen?|?Shih-wei Chao?|?Kai-Ping Chang?|?Choky Ramadhan?|?Zabdi Salazar?|?Justin Sucgang?|?Ami Acary?|?Luis David Briceno Perez?|?Christabel R.?|?Zijin Yan?|?Dah-Wei Yih?|?Gesare M. ?|?Altay Mustafayev?|?Sharlene Chen?|?Vicente Antonio Caputo Sanhueza ___________________________ #LawasScience?#LegalMethodLab?#methodology?#SJD?#JSD?#PHD?#DoctorofJuridicalScience?#lawschool?#law?#lawyer #lawstudent?#lawyers?#academics?#doctoralstudies?#science?#research?#blog?#community?#legal?#legalknowledge #legalstudies
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