Good afternoon, distinguished participants at APEC’s SDMOF, the 18th Senior Disaster Management Officials’ Forum. My name is Saebom Jin, from the National AI Research Lab at KAIST. It is my true privilege to be here today at this important dialogue on strengthening disaster leadership in the Asia-Pacific region.

Together with Prof. Anthony Pennings of SUNY Korea, we prepared this presentation, studying how emerging technologies like AI can enhance existing disaster information platforms. In particular, drawing on the Remediation Theory from media studies, we attempted to examine how AI might be integrated into traditional information systems used in disaster management. Our particular concern was the Common Operating Picture (COP) used in disaster management control rooms. Our aim is to better understand the deeper implications of such integration in supporting effective and trustworthy leadership in times of crisis.

As you might have heard many times, we live in a VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) world. And it is more and more difficult to predict something in the future, even in the near future, as historical data is incapable of predicting the future – especially when it comes to the changing climate and its disaster implications.

I would say “the odds of odd things happening are increasing” – we have just witnessed very tragic disaster outbreaks in Texas, 3 years ago when a winter storm caused widespread electricity blackouts, and also just a few weeks ago, when flash floods washed away the Camp Mystic summer camp, taking the lives of more than 27 young girls.

It is not a matter of data scarcity. In fact, we have encountered a proliferation of data from a variety of sources – from satellite imagery to IoT sensors and social media. In this situation, the challenge we face is not the lack of data but the overwhelming complexity of making sense of it.

In such environments, leadership must innovate — not only in decision-making but also in navigating these multi-layered information environments of crucial information. In this presentation, I would like to suggest that effective leadership must embrace three qualities:

Data-driven decision making using insights from complex systems to guide action.

Anticipatory response by identifying patterns and taking proactive measures (Typhon monitoring and warnings)

Adaptive systems moving beyond static command structures to dynamic and interface-enabled leadership.

This shift requires more than technology. It demands a rethinking of how we design information platforms to support human judgment.

Here is where Remediation theory offers us insight. According to the famous media theorist Marshall McLuhan, the content of any medium is always another medium. Following up on this observation, Jay David Bolter and Richard Grusin described remediation as the process by which new media refashion and incorporate older media forms. In this remediation theory, new technologies, like spreadsheets, are designed to improve upon the prior technologies to mediate a more authentic sense of reality.[2]

In other words, this isn’t about simply replacing old technological systems with new ones, but adopting and adapting the functions of the existing systems to help leaders better perceive, interpret and act through media. Drawing on the Italian roots of the word remediari it is about “healing” the media’s access to an authentic reality.

Here are the key concepts of this theory:

The logic of Immediacy is the idea that technology should closely reflect the real world in order to create a sense of presence and realism, as seen in movies, television news, and day-time soap operas or live video streaming. Relevant examples are real-time video-conferencing and live data feeds. Drawing on first person video from the affected zones often provides the transparent immediacy of authentic experience. Television reporters for example often go out into water and wind to dramatize the weather events.

Hypermediacy indicates multiple representations within a heterogeneous space. It is a layered, often windowed interface with GIS informatics and multichannel communications to combine images, sounds, text, and video. This approach offers an augmented, quantitative view of the world, drawing on the power of numeracy and remediating tools like graphics and maps.

The most radical concept in remediation refers to the transformation of prior media into a new framework, creating a more authentic, interactive, and actionable experience. In this concept, we do not just replace the legacy systems that leaders and practitioners have long relied upon, but transition from one to another by integrating new media forms into the COP.

In practice, we have witnessed how media have been transformed or remediated to better convey valid information out of a vast amount of data – from printed material to radio and television, from TV news to social media updates, and so on. In such an environment, crisis communication and disaster leadership involves navigating various types of digital interfaces rather than issuing directives alone.

Among the various mechanisms and tools, we focused on the Common Operational Picture (COP) as a mediation tool that can incorporate novel technologies using as AI and APIs, and create value for disaster leadership in response to climate variance and data variance.

COP is a shared, real-time view of operational data for decision-makers, teams, and agencies involved in multi-agency disaster risk reduction operations. By providing up-to-date information through dashboards and alerts, COP supports situational awareness and coordinated action.

Let me present the idea of how COPs can be remediated with AI and APIs. First, APIs act as bridges, integrating and normalizing diverse data streams into a hypermediated, yet unified operational view. APIs incorporate various data streams and make them available for the COP.

Next, AI processes and analyzes this massive and disparate data in real-time dynamic media environments. While APIs serve as the infrastructure for remediation, AI acts as the operating system for the remediated COP. By utilizing NLP, computer vision, and predictive analytics with machine learning algorithms, AI-remediated COP simplifies the data and facilitates interpretation and prediction.

It helps build transparency and enhance leaders’ ability to act confidently under pressure. In summary, AI enables the COP to transition from a static display of information to a dynamic intelligence platform with crucial mediated information on demand.

Another notable feature of the remediated COP is the development of Personalized Operational Pictures (POPs). While COPs used to be confined to control rooms, they are now evolving into POPs that provide individualized pictures based on roles within the command room and out in the field. With APIs and AI, these personalized mobile platforms can provide role-specific and actionable intelligence into the hands of leaders and practitioners during times of crisis. In complex disaster environments, this means leaders see only what matters, empowering faster, more focused decisions without being overwhelmed by irrelevant data.

This chart illustrates data flow of the suggested model.

Now then, let me move on to the design principles in order to achieve effective leadership with this remediated system in practice. As technology alone does not guarantee the success of this system, how to apply the theory into practice in a way to enhance trust and leadership is key.

The first principle is about data curation and visualization. When in crisis, more data does not necessarily lead to a better decision. However, this does not mean the complexity of a disaster should be ignored. The key feature of the suggested platforms is, therefore, providing remediated visuals to help leaders grasp the full picture of a disaster with contextualized and curated data. AI-assisted COPs can summarize trends of multiple data streams.

This remediated platform must be designed to build trust through a transparent yet effective explanation of complexity. Rather than simply being exposed to the increasing volume and variety of data, users need to be able to make sense of it through effective platforms.

The next principle regards communication. Using official websites or applications is recommended, but also, the hypermediated platforms should support users with targeted messages based on their roles and location, for example.

A technical feature for two-way interaction through the platform and advanced dashboards is also recommended for clear and credible communication within teams and with the public.

Effective COPs balance the two logics of remediation: 1) Hypermediation reveals data-richness, layered complexity, and enables tailored views for different roles. Transparent Immediacy involves delivering real-time clarity and minimizing cognitive load in urgent situations. Together, they ensure that leaders are not overwhelmed by data, but empowered by insight.

This design philosophy extends beyond control rooms. Public-facing dashboards showing real-time rainfall, river levels, or evacuation orders foster institutional trust and transparency — key components of effective disaster leadership.

As these systems evolve, leaders must also evolve. Effective disaster leadership today means:

– Championing user-centered design
– Ensuring interoperability across media systems
– Training not just on using technology but on interpreting complex information environments. In short, leadership is becoming interface-native.

In this presentation, AI is not just as a processor, but as a media theorist in action. AI is the operating core of the modern COP, serving as an intelligent media system that delivers clarity for responders, in-depth insights for analysts, and trust for the public.

Guided by Remediation Theory, AI-enabled COPs become more than tools or information repositories — they are strategic tools for decision-making, trust-building, and narrative construction during crises.
AI-assisted COPs empower responders, inform the public, and bring more order to chaotic disaster scenarios. Still, we need to ensure that the balance between immediacy and accuracy, as well as between simplicity and integrity, remains in the AI-assisted COP. That is why remediated COPs is more than technology.

Lastly, let me leave you with this quote by Bolter and Grusin:

“Our culture wants both to multiply its media and to erase all traces of mediation.”

As leaders, we must balance these tensions — embracing complexity without losing clarity, and ensuring that our technologies remain tools for human judgment, not barriers to it.

Thank you for your attention. I look forward to discussing how we can co-create smarter, more trusted disaster information systems that empower leadership across the Asia-Pacific region.

Citation APA (7th Edition)

Pennings, A.J., Jin, S. (2025, Sep 13) APEC Presentation: Healing the COP (Common Operating Picture) with AI and APIs for Disaster Management. apennings.com https://apennings.com/crisis-communications/apec-presentation-healing-the-cop-common-operating-picture-with-ai-and-apis-for-disaster-management/

Notes

[1] APEC stands for Asia-Pacific Economic Cooperation. It is a regional economic forum that promotes trade, investment, economic growth, and cooperation among its 21 member economies around the Pacific Rim. The group aims to foster prosperity, sustainable economic development, and more resilient economies in the Asia-Pacific region.
[2] Bolter, Jay David, and Richard Grusin. Remediation: Understanding New Media. Cambridge, MA: MIT Press, 2000.

© ALL RIGHTS RESERVED

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Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and holds a joint Research Professor position for Stony Brook University. He teaches AI and broadband policy. From 2002-2012 he taught digital economics and information systems management at New York University. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

Related

Category: crisis communications, disaster risk management, journalism, media strategies, mobile technologies, sensing technologies, space systems, technologies of meaning, visual literacy and rhetoric
Tags: and Ambiguity) > APEC > Asia-Pacific Economic Cooperation > Complexity > COP (Common Operating Picture) > Hypermediation > Jay David Bolter > Remediation > Transparent Immediacy > Uncertainty > VUCA (Volatility

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