LLMs: Redefining "Value" while Upholding "Values"

For the past two years, we’ve explored Generative AI’s evolving role—from demystifying LLMs to enabling AI-human collaboration. Now, in this third session of our series, we go deeper—not just into technology, but into the values that guide its use. When LLMs arrived with hype, we asked: Does this add value? Can we trust it? Is it aligned with human intent? These questions led us to train our own models, rethink processes, and redefine "value" while staying true to our values. We’ll share insights from building a Gen AI-based taxonomy solution, highlighting lessons from overcoming challenges and turning setbacks into breakthroughs. Beyond theory, we’ll showcase real-world use cases where AI augments human intelligence. Join us to push boundaries while keeping people at the center, balancing innovation with ethics, and navigating the Gen AI frontier with confidence.

Publication Date

May 2025

47th Annual Meeting (2025)

47

Although every year in the scholarly publishing ecosystem is a balancing act of innovation, optimization, and value creation, 2025 is shaping up to be particularly challenging as the pace and scale of change is accelerating more than we’ve ever seen before. There is increasing pressure to provide value to and to meet the incredibly diverse needs of the global research community while maintaining financial health for our own organizations, living our values, and continuing to protect the scholarly record. With AI, open access, integrity, and mistrust frequently dominating the conversation, we are in the midst of an unprecedented shift in both our industry and society as a whole. As always, the SSP community continues to focus on bringing together academics, funders, librarians, publishers, service providers, technologists, researchers and countless others with a communal interest and stake in disseminating scholarly information. We look to the 47th Annual Meeting as an opportunity to continue this tradition and welcome all colleagues and community stakeholders.

Kavita Krishnamurthy

1

Chief Domain Officer & Leader, R&D, TNQTech

Dr Shanthi Krishnamoorthy is a Material Scientist with a PhD in Chemistry from IIT Madras and a deep interest in publishing technology and innovation. After working in a manufacturing industry, she joined TNQ as a copyeditor. She led TNQ's Operations and worked with various publishers. Over the years, she transitioned from operations to setting up and leading TNQ’s R&D division, focusing on AI-driven publishing solutions, automation, and content integrity. Dr Shanthi has worked extensively on modernizing production processes and exploring AI’s role in publishing. She has been actively involved in integrating technology with editorial workflows while ensuring quality and accessibility. She is also a member of a few scholarly and scientific communities. A strong advocate for technology as a tool to enhance human potential, she continues to explore new ways to blend AI and human expertise in publishing.

Neelanjan Sinha

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VP, Product & Technology, TNQTech

Neel is a product and technology leader with a background in engineering and business, bringing over 16 years of experience across diverse roles and industries, including Publishing, EdTech, and Banking. His diverse experience has enabled him to build and lead cross-functional teams, collaborate effectively, and drive impactful results. He has built multiple B2B and B2C products in both startup and enterprise environments, shaping them with a strong focus on product strategy, design, and business impact. In STM publishing, he has built products for authoring and research management, submission and peer review, and a product suite spanning the entire content production value chain. Currently, he leads TNQTech’s product portfolio and Technology BU, driving execution that balances customer needs, business goals, and technological possibilities. He focuses on leveraging AI optimally and effectively, ensuring innovation is thoughtfully applied to real-world workflows with reliability and quality.