Generative AI Can Revolutionize Higher Education’s Research Enterprise
Generative artificial intelligence (GenAI) is on a trajectory to transform the academic landscape through strategic, cutting-edge technologies. As more universities explore GenAI’s capabilities its impact and potential will help inform and shape innovations across all research enterprise divisions.
Artificial intelligence (AI) technologies and applications are at the forefront of revolutionizing operations in high-tech industry, healthcare, finance, and higher education institutions. Recently, generative AI (GenAI), a type of AI that learns patterns and styles from existing data, then generates the latest content like code, text, and images, has seen increasing adoption and interest. Gen AI-enabled products are expected to contribute $4.4 trillion to the global economy annually.
Evidence of GenAI’s rising benefits include support for data augmentation and analysis, simulation and modeling, content generation, interdisciplinary collaboration, and personalized research assistance, e.g., literature review. Despite these advantages, integration into higher education institutions has been cautious. While transformative, GenAI is linked with issues related to supporting academic integrity, managing the literacy gap, upholding ethical standards and social implications, protecting data and privacy, and ensuring intellectual property (IP) rights. In a recent survey of academic leaders and funders, only 23% are well prepared for AI governance and ready to address these issues.
U.S. public universities, such as Michigan State University (MSU), are carefully exploring GenAI’s potential for research and creative activities. In August 2023, just a few months after ChatGPT, a form of GenAI, was publicly released, MSU issued guiding principles that cover equity, inclusivity, ethical use, and data compliance and risk, as well as IP, preparation of publications, peer review, and grant development.
“Embracing GenAI is not merely a choice now but a strategic imperative for research-intensive universities to excel in the rapidly evolving higher education and global research landscapes,” said Douglas Buhler, MSU’s Associate Vice President for Research and Innovation.
MSU, as other U.S. universities, continues to revisit its policies and provide access to valuable resources. A series of consultations with MSU’s research community around transparency, accountability, and computing safety is ongoing.
Research and innovation offices at higher education institutions can also help shape GenAI adoption. MSU AgBioResearch, the research arm of MSU’s College of Agriculture and Natural Resources, is exploring GenAI to revamp its business processes. GenAI helps automate repetitive tasks and streamline administrative processes in internal grant management, data storage, insight generation, document processing, and metrics reporting. It also assists with scoping studies and understanding research strengths, gaps, and challenges and helps identify partnership opportunities. Similar efforts are underway at other U.S. institutions, including the University of Michigan, the University of Illinois at Urbana-Champaign, the University of Arkansas, and Harvard University.
Proposal development and research administration teams can use GenAI to generate concise summaries of lengthy funding announcements, automate information sharing with faculty and academic staff, and ensure alignment with funding agency priorities and requirements. Post-award support groups are able to use existing AI software capabilities to understand budgets, manage research spending, and automate sharing relevant insights with critical stakeholders. AI-powered chatbots and virtual assistants can provide personalized communication on initiatives, funding opportunities, and administrative processes presented on research offices' websites. In partnership with communication teams, research offices can also leverage AI-generated content and prompts to increase visibility on social media platforms, reach a broader audience, and foster engagement with the research community.
As with any transformative tool, the integration of GenAI into the research landscape demands strategic investment. Research and innovation offices, through their internal funding programs, can facilitate and fund innovative research and real-world cases of how GenAI solutions can be applied effectively and responsibly across disciplines. They can also partner with industry groups and big GenAI users to offer training and development programs and workshops. This will help enhance researchers’ skills and knowledge in GenAI applications and ensure effective and ethical use. Infrastructure and access to datasets for GenAI and equitable tools such as cloud computing platforms, AI development tools, and software are necessary at the university level for the research community to put advanced technology into practice.
Higher education institutions can unlock GenAI’s promises through guideline development, frequent stakeholder consultation, collaboration, learning from peers with advanced GenAI initiatives, careful exploration, and infrastructure and resource support. Rather than resisting, the higher education community should leverage the opportunities that GenAI presents and be prepared to adapt to this new paradigm to revolutionize the research enterprise.
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