Sign up to save your podcasts
Or
Share The AI Shift: How Leaders Can Avoid Falling Behind? | Dr. Steven Miller
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
The AI Shift: How Leaders Can Avoid Falling Behind? | Dr. Steven Miller
What makes some research organizations produce meaningful, high-impact work while others struggle, even with talent and resources?
In this episode of Why Research Matters, Varunika Goyal speaks with Professor Steven Miller, Professor Emeritus of Information Systems at Singapore Management University and founding dean of SMU’s School of Computing and Information Systems. Drawing on his experience across academia, industry, government, Carnegie Mellon University, Fujitsu, and SMU, Professor Miller explains how research cultures are built, why feedback systems matter, and what leaders can do to help researchers do their best work.
The conversation explores research leadership, innovation, grant strategy, interdisciplinary collaboration, post-COVID work culture, AI as a collaborator, automation vs augmentation, quality control, and why skeptical voices are essential when adopting powerful new tools.
Subscribe to Why Research Matters for conversations with researchers, educators, and leaders about the work behind discovery.
#ResearchLeadership #ArtificialIntelligence #WhyResearchMatters
00:00 Introduction to Professor Steven Miller
01:27 What creates impactful research?
02:07 Why research environments matter
04:41 Leadership, feedback, and innovation culture
05:28 Lessons from SRI International
07:59 Why polished work is not enough
11:43 AI tools and the need for better critique
12:27 Early feedback vs polished research
16:24 Research funding and creative partnerships
19:16 Building SMU’s computing school
25:17 Choosing new research areas strategically
29:19 The dean as “chief enabler”
31:38 Bureaucracy, grants, and research infrastructure
35:30 COVID and institutional resilience
39:27 Work from home, hybrid work, and collaboration
41:45 Serendipity and hallway conversations
43:31 Yin-yang tensions in research and AI
45:35 AI errors, validation, and feedback systems
46:04 AI as a collaborator
47:18 Are organizations adopting AI fast enough?
51:41 Augmentation vs automation
53:36 Why automation needs control
58:28 Should everyone use AI tools?
1:04:32 Why skeptics matter in AI adoption
1:08:30 Responsible innovation and risk
1:10:21 AI dashboards, usage, and quality
1:12:19 Quality control in the age of AI
View all episodes
By Varunika GoyalWhat makes some research organizations produce meaningful, high-impact work while others struggle, even with talent and resources?
In this episode of Why Research Matters, Varunika Goyal speaks with Professor Steven Miller, Professor Emeritus of Information Systems at Singapore Management University and founding dean of SMU’s School of Computing and Information Systems. Drawing on his experience across academia, industry, government, Carnegie Mellon University, Fujitsu, and SMU, Professor Miller explains how research cultures are built, why feedback systems matter, and what leaders can do to help researchers do their best work.
The conversation explores research leadership, innovation, grant strategy, interdisciplinary collaboration, post-COVID work culture, AI as a collaborator, automation vs augmentation, quality control, and why skeptical voices are essential when adopting powerful new tools.
Subscribe to Why Research Matters for conversations with researchers, educators, and leaders about the work behind discovery.
#ResearchLeadership #ArtificialIntelligence #WhyResearchMatters
00:00 Introduction to Professor Steven Miller
01:27 What creates impactful research?
02:07 Why research environments matter
04:41 Leadership, feedback, and innovation culture
05:28 Lessons from SRI International
07:59 Why polished work is not enough
11:43 AI tools and the need for better critique
12:27 Early feedback vs polished research
16:24 Research funding and creative partnerships
19:16 Building SMU’s computing school
25:17 Choosing new research areas strategically
29:19 The dean as “chief enabler”
31:38 Bureaucracy, grants, and research infrastructure
35:30 COVID and institutional resilience
39:27 Work from home, hybrid work, and collaboration
41:45 Serendipity and hallway conversations
43:31 Yin-yang tensions in research and AI
45:35 AI errors, validation, and feedback systems
46:04 AI as a collaborator
47:18 Are organizations adopting AI fast enough?
51:41 Augmentation vs automation
53:36 Why automation needs control
58:28 Should everyone use AI tools?
1:04:32 Why skeptics matter in AI adoption
1:08:30 Responsible innovation and risk
1:10:21 AI dashboards, usage, and quality
1:12:19 Quality control in the age of AI