Defense Disrupted

Ret. Major General Daniel “D-Day” Simpson on Preparing Warfighters for AI Integration

The assumption that America maintains decisive military superiority might be more dangerous than the threats we're actually facing. Daniel "D-Day" Simpson, Major General USAF (ret), brings decades of intelligence and operational experience to challenge conventional wisdom about peer competition, artificial intelligence, and the pace of defense innovation.
 
D-Day's career trajectory provides unique insights into how military professionals adapt to radically different operational environments. His wisdom spans the evolution from Cold War deterrence through counterterrorism operations to renewed great power competition, offering critical perspective on how technological advantages can create strategic blind spots. Most importantly, his current focus on artificial intelligence integration reflects deep understanding of both operational requirements and implementation challenges that academic discussions often miss.
 
His conversation with Ian also explores why treating China as a "near peer" rather than peer competitor reflects dangerous strategic miscalculation, how artificial intelligence represents evolutionary rather than revolutionary change at revolutionary speed, and why future conflict scenarios will exceed human processing capabilities regardless of personnel increases. 
 
Topics Discussed:
How China's systematic study of American joint operations over three decades has produced specific countermeasures designed to exploit US dependencies on space-based assets and theater access.
The strategic implications of shifting from "near peer" to "peer competitor" language and why this distinction reflects capability gaps rather than political positioning.
Why artificial intelligence represents evolutionary advancement at revolutionary speed, requiring fundamental changes in training and operational integration rather than simple technology adoption.
The critical difference between counterterrorism operations focused on individual targets versus peer conflict across multiple domains with thousands of dynamic targets moving simultaneously.
How the expectation of zero casualties from decades of technological superiority creates operational constraints that peer adversaries specifically exploit in their strategic planning.
Implementing AI-assisted intelligence fusion to compress analysis timelines from days to seconds while maintaining accuracy standards required for kinetic targeting decisions.
The workforce transformation challenge when AI acceleration reduces task completion from days to minutes, requiring strategic personnel reallocation rather than simple headcount reduction.
Why young warfighters must extensively test and break AI systems during peacetime operations to understand limitations and develop trust before combat employment becomes mission-critical.

Military Intel Veterans on Why Process-Obsessed Military Culture Blocks Innovation

Two veteran intelligence officers with distinct naval and marine backgrounds reflect on how military intelligence operations have evolved from exclusive government programs to information-saturated environments where technology frequently fails to deliver. In this candid conversation on Defense Disrupted, Ed Padinske, Retired Navy Captain, who served as senior intelligence officer for Navy special warfare units, and Ed Sullivan, Retired Marine Colonel, who spent years as an intelligence officer in Iraq and later commanded an intelligence battalion, share battlefield perspectives on system failures. 
 
They explain to Ian how acquisition processes designed in the 1960s remain fundamentally unchanged while fighting modern adversaries, comparing it to racing a 1970 Nova in an F1 competition. Their frontline stories — from Padinske's experience in the White House Situation Room on 9/11 to Sullivan's cultural advisor role in Fallujah — illuminate how personality-driven procurement decisions often sabotage effective solutions, and why pushing capabilities to lower echelons could revolutionize warfare. Both agree that defense innovation requires not just technological advancement but a cultural shift from process compliance to mission outcomes.
 
Topics Discussed:
How the proliferation of sensors and data sources has consistently outpaced analysis capabilities, creating environments where critical information exists but can't be effectively leveraged for battlefield decisions.
The tension between forward-deployed personnel holding physical risk and rear-echelon analysts concerned primarily with policy risk, creating dysfunctional relationships and inefficient operations.
How complex networks of stakeholders without decision-making authority create deliberate delays in the acquisition system, originally designed by McNamara in the 1960s to prevent surprising the Soviets.
The stark contrast between veteran operators who struggle with digital interfaces and younger personnel who intuitively understand modern systems, illustrated through F-35 pilot debriefings where younger pilots outperformed veterans.
How service members become accustomed to dysfunctional equipment and stop agitating for better solutions, exemplified by sophisticated systems left unused because of perceived network restrictions.
Why the military acquisition system remains oriented around process compliance rather than mission outcomes, with many program officers simply trying to prevent their programs from being killed.
How emerging technologies are enabling frontline personnel to create custom intelligence models for their specific tactical needs, potentially revolutionizing battlefield awareness and force protection.
The opportunity to leverage Silicon Valley technology to create military advantage that translates into meaningful deterrence against peer adversaries, potentially preventing major conflicts.

TurbineOne’s Chané Jackson on How Human-Machine Teaming Reduces Cognitive Load in Combat

From the frontlines to AI deployment at the tactical edge, Chané Jackson, Former Chief Data Scientist for U.S. Special Operations Command brings 20+ years of military experience to our inaugural episode of Defense Disrupted. 
Chané shares how machine learning and AI are transforming battlefield operations while discussing the challenges of implementing these technologies in disconnected environments for today's warfighters. He also offers specific examples of how biometric systems enabled immediate person identification in the field, accelerating critical decision cycles that previously relied on manual verification. Chané emphasizes that effective military technology must solve specific operational problems rather than applying complex AI solutions universally — sometimes a simple decision tree analysis is more effective than neural networks in tactical environments. 
 
Through conversations like this with military professionals, technology experts, and implementation specialists, our host Ian Kalin, CEO & Co-Founder of TurbineOne, will explore practical insights about deploying machine learning at the edge, emerging trends in field operations, and success stories from those accelerating threat recognition.
 
Topics Discussed:
How Special Operations is evolving from conventional force deployments to small teams operating in denied environments, requiring advanced technology to scale capabilities and minimize personnel exposure in future conflicts.
The transformation from infantry soldier to data science team leader, demonstrating how military career paths can adapt to incorporate technical expertise while maintaining operational relevance.
Implementing battlefield biometrics that enabled rapid identification of persons of interest in combat zones, allowing operators to make faster, more confident decisions with immediate verification capabilities.
The integration of autonomy and human-machine teaming to reduce cognitive load on operators who previously tracked critical battlefield information manually while on the move.
How disconnected environments present unique challenges for deploying AI at the tactical edge, requiring solutions for collaborative autonomy that can maintain functionality without reliable communications.
Adapting mathematical modeling and decision tree analysis for battlefield applications when deep learning neural networks aren't practical due to data constraints in tactical environments.
The evolution of military technology requirements from the 2012 Afghanistan deployment (using handwritten notes on wristbands) to modern data-intensive operations that require AI assistance to process multiple information streams.
Problem-first approach to military technology implementation: focusing on specific operational challenges rather than forcing AI solutions where simpler statistical methods might be more effective.
 
Disclaimer: The views expressed in this podcast are those of the hosts and guests and do not reflect the official policy or position of the Department of Defense, the U.S. Government, or any of its affiliated agencies.