At Annual Meeting, Tech Transfer Professionals Embrace 'Team Sport' Approach to AI

In the standing-room only sessions on artificial intelligence at last month’s Annual Meeting, attendees heard repeatedly that the future of AI isn’t just about technology, and it’s definitely not just about prompts. It’s about collaboration—and that’s very good news for technology transfer, where AI is already inspiring innovative partnership opportunities.

Tech transfer offices that have a head start in tailoring closed AI systems to streamline TTO-specific tasks like agreement generation and review are sharing their experiences—and even access to their custom technology—with colleagues at other institutions. Other TTOs are looking to collaborate with industry players that will bring AI expertise to the partnership.

That ability to collaborate is key to successfully navigating the opportunities and pitfalls that AI is bringing to many different industries, said keynote speaker Hilary Mason, co-founder of AI-driven gaming experience company Hidden Door.

“This is a team sport,” Mason said. “It’s not for computer scientists to try alone. It’s for a team of people to do together.”

That team approach benefited the tech transfer team for New York University and NYU Langone Health, who had the opportunity to help test and train NYUTron, the closed AI system that the institution invested in last year. Because the system had to be HIPAA compliant, the Technology Opportunities and Ventures (TOV) staff was able to experiment in the system and train it on tech transfer-specific data, knowing confidential intellectual property information would have protections not provided by open AI systems like Chat GPT.

Now that the system has been trained and proof of concept verified—AI assistance has been associated with up to 95% greater efficiencies for some tech transfer workflow tasks—the TOV team is paying it forward. Marc Sedam, TOV vice president, announced during an Annual Meeting presentation that his team would be offering other tech transfer offices free access to the NYU models via a non-exclusive license for non-commercial use by universities and academic medical centers.

“The prompts being made available are based on NYU agreements, so they won’t be perfect for your institution,” Sedam told session attendees. “You’ll need to play with it.”

As a bonus, any future updates made to the existing models by NYU would also be available to users from other institutions. Those future updates will include “disclosure bot” technology now being developed to save inventors the inconvienience of manually filling out invention disclosure forms.

“When we develop new things, we’ll disseminate them through the model,” Sedam said. “So when we ‘kill the disclosure,’ you get to kill the disclosure.”

Another Annual Meeting session explored the potential benefits of partnerships between universities and physical science or digital companies that are using AI to improve internal processes such as software and product development. Attendees heard presentations by representatives from three industry players with AI experience.

“There is a lot of room for growth and improvement for universities to work with engineering and software companies,” said session moderator Daniel Dardani, Director of Physical Sciences and Digital Innovations Licensing and Corporate Alliances at Duke University. “Both sides are vested in researching AI and using the fruits of AI to push their businesses and improve society, and it makes a lot of sense for universities to connect, collaborate and explore pathways for working with these companies to leverage respective strengths for collective innovation.” 

Those industry-academia collaborations could potentially involve license agreements, sponsored research agreements, joint collaboration agreements or partnership agreements—depending on the interests of both parties, said Dardani, who is also a member of the AUTM Board of Directors.

Mason advised Annual Meeting attendees to envision an AI future that is less about prompts—which she believes will not constitute anyone’s job description a decade from now—or the possibility of being replaced by an AI. Instead, she encouraged greater focus on using AI’s efficiencies to improve collaborative efforts and other human elements of doing business.

“I have a lot of faith in human creativity and capability,” she said.

Sedam concurred.

“Whether you work at a huge university of a small one, our problems are the same. We spend too  much time on administration instead of the fun things, like talking to faculty about inventions” he said. “AI will replace the parts of your job you mostly hate, but it won’t replace you. It will allow you to focus on other aspects of your job.”

AI-Related Sessions at the 2024 AUTM Annual Meeting
Chat GPT and Generative AI: What is it and how to Monetize it?
Participants: Charles Macedo, Matan Arazi, Nima Badizadegan, Stephanie Curcio, Jonathan Gortat, Justin Rerko

AI & IP: A Match Made in Tech Transfer Marketing Heaven
Participants: Dvorah Graeser, Reid Blackman, Jericho Wilkerson

The Present and Future of Artificial Intelligence and Machine Learning
Participant: Hilary Mason

Role of AI in Tech Transfer Offices
Participants: Sadhana Chitale, John Keary, Marc Sedam, Declan Weldon

The AI Ecosystem: How Universities and Industry Innovate Together
Participants: Daniel Dardani, David Marr, Mary Hardy, Dinesh Divakaran

Emergent Intellectual Property Issues for Artificial Intelligence Technologies
Participants: Charles Kim, Daniel Dardani

Protecting AI Inventions When Computers Aren’t Authors or Inventors
Participants: Thomas Hart, David Chang, Scott McEvoy, Shilpa Patel