AI Dialog Event Charts the Future of Artificial Intelligence at FTMS and HVL

The event featured key administrative leaders at the Faculty, including Professor Stig Erik Jakobsen, Vice-Dean for Research, and Professor Kristin Fanebust Hetland, Head of Departement, demonstrating high-level commitment to advancing AI capabilities across the institution. The event was moderated by Professor Reza Arghandeh, leader of the Data Science and AI Group.

Using Mentimeter for real-time feedback collection, the event generated rich discussions and valuable insights across four critical areas:

1. Strategi AI Development and Research

Participants emphasized the crucial importance of securing research funding to support AI projects and elevate HVL’s capabilities. The development of robust ethical frameworks for responsible AI implementation emerged as a key priority, alongside the need for expanding AI programs and technical training opportunities in all BS, MS, and PhD levels. The dialogue revealed strong support for creating a collaborative environment where AI researchers at HVL, especially in IDER, can effectively support other colleagues in developing their AI expertise.

Key Feedback:

• Strong emphasis on establishing ethical frameworks and responsible AI implementation in courses contents and research projects.
• Need for systematic competency building through student and staff training, as well inviting prominent national and international expers to visit HVL for lectures and workshops.
• Focus on securing external research funding and resources from industry and private sectores for AI initiatives.
• Importance of creating collaborative environments in HVL for knowledge sharing among colleagues with focus on inclusin, diversity and internalization.

2. Institutional Positioning 

The discussion highlighted potential opportunities for establishing a dedicated AI center to serve as a hub for research and education. Participants emphasized the importance of developing distinctive programs that differentiate HVL from other institutions such as UiB, NTNU, and NHH, while maintaining strong connections with local and national industries.

The focus on creating forward-looking AI programs and engaging students in real-world applications and internship opptunities emerged as crucial elements for HVL’s competitive positioning as an applied science institute.

Key Feedback:

• Support for establishing a new AI center to coordinate AI initiatives across the faculty.
• Emphasis on developing forward-looking programs and courses with industry relevance and real-world applications with internship opprtunities.
• Need to focus on HVL campuses unique strengths and differentiation from competitors.
• Recognition of the importance of maintaining high academic standards across BS, MS, and PhD programs.

3. Partnership Development

There was strong support for fostering collaborations through internal seed grants and collaborative projects. The importance of building interdisciplinary partnerships with public and private sectores and pursuing applied research was emphasized as essential for connecting both nationally and internationally. Participants also highlighted the critical need for maintaining project delivery standards and internal quality control to build trust and long-term partnership success.

Key Feedback:

• Strong support for seed grants and interdisciplinary research initiatives to strengthen partnerships.
• Emphasis on building and utilizing international networks effectively to expand HVL’s reach.
• Focus on delivering high-quality collaborative projects on time to maintain trust with external partners with sufficent admistrative support in HVL.
• Need for sustained dialogue with local and national industry leadership to foster long-term collaboration.

4. Student Recruitment and Campus Utilization

To enhance student attraction and better utilize campus resources, participants recommended strengthening industry collaboration and offering flexible learning options, including English courses and online programs.

The importance of maintaining high academic standards while offering unique, internationally branded, and applied programs was emphasized as key to differentiating HVL from competitors like UiB and NHH. The feedback highlighted opportunities to leverage HVL’s existing strengths in engineering, nursing, and teaching, while building new capabilities in AI and technology.

Key Feedback:

• Focus on developing unique, industry-aligned programs to attract students.
• Emphasis on flexible learning options and integrating modern technology into the curriculum.
• Need for targeted marketing and brand-building in both Norwegian and English to reach a broader audience.
• Importance of maintaining high academic standards and reserch culture while ensuring programs are practically relevant to industry needs.

Looking Forward

Building on the success of this initial dialogue, the HVL Data Science and AI Group will host a follow-up event in February 2025. Recognizing the importance of inclusive participation across all HVL campuses, the upcoming session will feature enhanced hybrid meeting capabilities, including improved hardware and Zoom integration to facilitate active contribution from colleagues and students at campuses outside Bergen.

The feedback from this session will inform FTMS’s ongoing strategic planning process, particularly in areas of resource allocation, program development, and partnership initiatives. The faculty remains committed to building a strong foundation for AI education and research while maintaining its focus on practical applications and industry relevance.

Faculty members and students interested in participating in the February 2025 follow-up session are encouraged to watch for forthcoming announcements. The event will continue to prioritize interactive dialogue and collaborative solution-finding, with enhanced capabilities for remote participation and engagement.

For more information about Data Science and AI Group events or to contribute to ongoing discussions, please visit the HVL Data Science and AI Group webpage.