Co-Intelligence in Orbit:

Human-AI Partnerships for the Spacefaring Future


By Elizabeth (Liz) Ngonzi, MMH and Zaheer Ali, MBA

ISDC 2026 · AI & Space Track

Conceptual visual: Co-intelligence begins with shared perspective: humans, technologies, institutions, and the wider public learning to shape a spacefaring future.

Introduction

At the National Space Society's 2026 International Space Development Conference (ISDC 2026), the AI & Space Track asked a question that reaches far beyond any single technology: what does it mean to build a spacefaring future with artificial intelligence?

The answer that emerged across the track was not that AI will replace human expertise. Nor was it that autonomy alone will carry humanity into orbit, to the Moon, to Mars, or beyond.

The stronger insight was more demanding: the future of space will depend on co-intelligence, carefully designed partnerships among human judgment, machine intelligence, resilient infrastructure, and public imagination.

In space, intelligence is not an abstraction. It is operational. It determines whether a spacecraft can navigate latency, whether a satellite can avoid debris, whether a crew can trust an automated system, whether a robot can extend human reach, and whether society can understand and participate in the next chapter of exploration.

That makes space one of the clearest tests of human-centered AI.

A Track Built on Human Judgment and Machine Intelligence

Organized as part of ISDC 2026, the AI & Space Track brought together space scientists, AI leaders, technologists, entrepreneurs, educators, researchers, and strategic communicators to examine how AI is already reshaping the space sector and how it must be governed, trusted, and applied.

The track was co-chaired by Zaheer Ali, MBA, physicist, technologist, Space Paladin, and Director of the Space MBA Program at the University of Central Florida; Jennifer Rochlis, PhD, CEO of Advancing Frontiers, Inc.; and Allison Nicholls, EMGM, Founder and Principal Consultant of Aligned Orbits.

This synthesis builds on Zaheer Ali's space-sector curation and track leadership, Rochlis's human systems and spaceflight integration expertise, and Nicholls's critical knowledge-capture work, including recording the sessions and generating the transcript foundation that made source-grounded synthesis possible.

The public-facing narrative applies the human-centered AI-enabled storytelling and synthesis methodology of Elizabeth (Liz) Ngonzi, Human-Centered AI Strategist, Platform Architect, Executive Educator, and Originator of AI for Humanity. Grounded in 1+1+AI=10™ and SHINE™, the methodology translates the track's technical, operational, and human-centered insights into an accessible learning asset.

That methodology matters because the quality of AI-enabled storytelling depends on the quality of the source layer. In this case, the transcript foundation, session documentation, and human review process made it possible to move beyond generic summaries toward a more useful public understanding of the track's deeper patterns.

Conceptual visual: The AI & Space Track brought together human judgment, machine intelligence, and source-grounded synthesis to explore how AI can be governed, trusted, and applied in space.

AI as a Digital Crew Member

Conceptual visual: Human-centered AI-enabled storytelling can translate technical space expertise into age-appropriate, imaginative learning experiences.

In "AI for Humanity in Space: Human-Centered AI, Storytelling, and the Next Frontier," Elizabeth (Liz) Ngonzi, MMH, introduced AI for Humanity: Human-Centered Strategies for Innovation and Impact as a living, participatory knowledge platform designed to make complex expertise more accessible across generations, sectors, and educational backgrounds.

One example captured the possibility clearly: a nine-year-old who used generative AI to translate an expert-authored space chapter into an illustrated story. That moment reframed AI not as a shortcut around expertise, but as a bridge to it. Used well, AI can help children, educators, policymakers, institutional leaders, and the broader public engage with ideas that might otherwise remain locked inside specialist language.

But accessibility is only one part of the challenge. In space, AI must also be understood as a "digital crew member," with autonomy that changes according to the distance, latency, and risk profile of the mission. A system supporting a near-Earth operation should not be designed the same way as one supporting a deep-space mission where real-time human control from Earth is impossible.

That requires more than tool adoption. It requires judgment, governance, validation, and humility about what both humans and machines do not know.

"The quality of AI-enabled storytelling depends on the quality of the source layer."

Source: AI & Space Track synthesis methodology

Trust Is Not the Same as Faith

Across the "AI in Space" and "State of AI" panels, one message came through repeatedly: AI should augment human cognition, not replace it.

The ‘AI in Space’ panel, led by Track Co-Chair Zaheer Ali and moderated by Jennifer Rochlis, PhD, brought together Amanda Fetch, PhD, Brett Mecum, MS, MBA, Kaylon Paterson, ME, EMGM, and Colleen McLeod Garner Garner to examine how AI is changing the operational realities of the space sector.

Panelists emphasized that AI can take on "dull, dirty, and dangerous" work, especially where scale and speed exceed human capacity. It can synthesize large datasets, accelerate workflows, support space domain awareness, and assist with risk detection. But in space, speed is never enough.

The "State of AI" panel, moderated by Chris Cochran, with Jennifer Rochlis, PhD, and Zachary Elewitz, PhD, MBA, explored what it means to introduce AI into the zero-fail culture of spaceflight.

One of the sharpest warnings from the track was against "AI-first" thinking. Mission objectives must come first. AI should serve the mission, not become the mission.

Trust, in this context, cannot be treated as faith. It has to be engineered.

That means predictable behavior, confidence scores, reproducibility, transparency where possible, and human validation where necessary. It also means building systems that can acknowledge uncertainty, fail safely, and keep humans appropriately in the loop.

This is especially important for workforce transformation. Several speakers raised concerns about the gap between AI-assisted productivity and actual engineering capability. If emerging professionals rely on AI-generated outputs without developing the foundational knowledge to evaluate them, organizations may gain speed while losing competence.

That is a dangerous tradeoff in any field. In space, it can become existential.

Trust Architecture

Mission Before AI

AI should serve the mission, not become the mission.

Calibrated Trust

Predictable behavior, confidence scores, reproducibility, and validation.

Human Judgment

Human expertise remains essential in zero-fail environments.

In zero-fail environments, trust is designed, tested, and continuously recalibrated.

"Trust, in this context, cannot be treated as faith.

It has to be engineered."

Source: AI & Space Track Synthesis, ISDC 2026

Scaling Safety in a Crowded Orbit

The most concrete examples of co-intelligence appeared in discussions of space debris and space situational awareness.

In "Tackling Space Debris with AI," Kaylon Paterson, M.E., E.M.G.M, Founder and CEO of Patterson Aerospace Systems, addressed the challenge of tracking the vast number of small debris objects that current systems struggle to detect. His company's work focuses on in-orbit sensor networks and machine learning-enabled collision avoidance, designed to help satellites maneuver away from immediate threats without creating new risks in already crowded orbital environments.

In "Advancing Space Situational Awareness Through Density-Based Clustering," Amanda Fetch, PhD, presented work applying machine learning to large orbital datasets. Using density-based clustering, her approach helps identify patterns of normal behavior and isolate anomalies that human analysts can prioritize.

These examples matter because they show AI doing what it does best: reducing the scale of an overwhelming problem so that human experts can focus attention where it matters most.

That is co-intelligence in practice. Not the removal of the human analyst, but the strengthening of human judgment through better filtering, pattern recognition, and decision support.

In an orbital environment where one collision can create cascading consequences, AI-enabled safety systems are not just technical conveniences. They are part of the stewardship architecture of a shared domain.

Co-Intelligence in Practice

In-Orbit Sensor Networks

Machine learning-enabled collision avoidance for crowded orbital environments

Density-Based Clustering

Pattern recognition across large orbital datasets to isolate anomalies for human review

Human-AI Stewardship

AI filters at scale; human analysts focus judgment where it matters most

Shared orbital safety depends on better sensing, better filtering, and better human decisions.

The Edges of Intelligence

Some of the most provocative sessions pushed beyond immediate operational use cases and asked what space reveals about intelligence itself.

In "AI and Space: The First Seventy-Five Years," Bryant Cruse, MS, partnered with former NASA astronaut Paul Richards, MS (Chief Science Officer of Revolution Space) to ground AI's history in real-world spaceflight. Tracing a timeline from early science fiction to the expert systems used in Hubble Space Telescope operations, their reflections merged engineering theory with Richards' first-hand perspective as an astronaut. Their session raised a foundational question: in extreme, zero-fail space environments, what kinds of intelligent systems can be safely trusted, tested, and constrained?

In "Homo artificialis spatialis: The Artificially Intelligent Android Astronaut," Pascal Lee, PhD, explored the possibility of artificially intelligent android astronauts. His argument was not merely that robots can go where humans cannot. It was that long-duration exploration may require embodied machine partners that do not depend on food, oxygen, or conventional life-support systems.

In "Nearly Human AI," Jamison Rotz, BS, argued that intelligence itself is becoming central to the next phase of space exploration. His session emphasized the need to operationalize AI tools that can synthesize data, accelerate mission planning, and support autonomous systems while remaining grounded by human expertise.

Jennifer T. O'Connor, PhD's session, "If the Aliens Don't Speak Human: AI, Animal Communication, and the Future of First Contact," moved in another direction entirely. Drawing on research involving animal communication and AI-assisted interpretation, including work with a parrot named Ellie, she asked how humans might prepare for communication with non-human intelligence.

Her session suggested that interface design can either reveal or obscure intelligence. AI may help humans detect patterns in communication that we would otherwise miss, but it cannot eliminate the need for careful human interpretation.

Together, these sessions widened the frame. Space is not only a frontier of travel. It is a frontier of relationship: between humans and machines, humans and non-human life, humans and uncertainty, humans and the unknown.

Four Frontiers of Intelligence

Historical Intelligence

Bryant Cruse
New Sapience
AI and Space: The First Seventy-Five Years

Embodied Intelligence

Pascal Lee, PhD
SETI Institute & Mars Institute
Homo artificialis spatialis

Operational Intelligence

Jamison Rotz
Nearly Human AI
Nearly Human AI

Non-Human Intelligence

Jennifer T. O'Connor, PhD
Texas A&M University
If the Aliens Don't Speak Human

Conceptual visual inspired by the discussion of android astronauts and embodied machine partners in deep-space exploration.

"In space, intelligence is not an abstraction.

It is operational."

Source: AI & Space Track Synthesis, ISDC 2026

The Hardware Behind the AI-Space Future

The AI & Space Track also made clear that the future will not be built by software alone. The Space Edge Accelerator Showcase highlighted companies working on the physical infrastructure required for space systems to function.

Swift Coat

Peter Firth, PhD, presented space-adaptive glass designed to improve solar panel efficiency and address supply chain bottlenecks.

X-Foam / Semplastics

Joshua McConkey introduced an ultra-lightweight ceramic foam with potential applications in reusable thermal protection systems.

Rayn Innovations

Nicole Ray, PhD, presented advanced thin-film antenna technology, pointing to the importance of lighter, smaller, more capable communications hardware.

Conceptual visuals: Advanced materials, coatings, and communications hardware are part of the physical infrastructure that makes AI-enabled space systems possible.

These presentations were important because they grounded the AI conversation in material reality. AI-enabled space systems still depend on antennas, sensors, glass, coatings, thermal protection, energy systems, launch economics, and manufacturing capacity. A spacefaring civilization cannot be powered by intelligence alone. It needs infrastructure that can survive the environment it seeks to enter.

"A spacefaring civilization cannot be powered by intelligence alone."

Source: AI & Space Track Synthesis, ISDC 2026

The Emotional Frontier

Conceptual visual: Public imagination, education, and storytelling help make a spacefaring future more accessible and participatory.

The track also explored a quieter but equally important question: how does the public learn to trust, imagine, and participate in a spacefaring future?

Aimei Helen Yang's session, "AI, Trust, and Space-Themed Innovation in China," approached this through culture, communication, and emotional connection. Her work suggested that before people live in space, societies need ways to rehearse the idea of space psychologically and culturally.

Space-themed experiences, including creative consumer concepts such as "space art cuisine," may seem far from spacecraft autonomy, but they address a crucial layer of adoption: public imagination.

This connects directly to the purpose of human-centered AI-enabled storytelling. Technical progress alone does not create durable public commitment. People need pathways into complex ideas. They need language, images, stories, and experiences that allow them to see themselves in the future being built.

That is why the nine-year-old learner example matters. When a child can use generative AI to translate expert knowledge into her own creative language, the space conversation expands. It becomes less exclusive, less opaque, and more participatory.

The Human Task Ahead

The ISDC 2026 AI & Space Track revealed a field moving past simplistic debates about whether AI is good or bad, helpful or harmful, autonomous or subordinate. The more important question is how AI is designed into systems of responsibility.

In space, the margin for error is thin. Communication delays, orbital debris, equipment failure, cyber risk, environmental extremes, and human vulnerability all force clarity. AI systems must be useful, but they must also be governable. They must be powerful, but also constrained. They must extend human capability without eroding human judgment.

That is the promise and discipline of co-intelligence.

The future of space will not be built by humans alone. It will not be built by machines alone. It will be shaped by the quality of the partnerships we design among people, technologies, institutions, and the wider public.

If we get that right, AI will not merely help us reach space.

It will help us become wiser about why we are going there, who gets to participate, and what kind of future we intend to build when we arrive.

Conceptual visual: Shared judgment, accountability, and responsibility are central to designing AI systems for space.


"The future of space will depend on co-intelligence."

Source: AI & Space Track Synthesis, ISDC 2026

Explore the AI & Space Track Notebook Experience

Explore the ISDC 2026 AI & Space Track through an interactive, source-grounded Notebook experience.

Ask questions in the language you prefer, at the educational level, technical depth, or age-appropriate framing that works for you.

Whether you are a student, educator, policymaker, technologist, space professional, or curious learner, the notebook is designed to help you explore the sessions, connect ideas, and make your own meaning.

Interactive Notebook Experience

Explore the Notebook Experience →

Preview of the interactive Notebook experience, designed to help readers explore the ISDC 2026 AI & Space Track sources through their own questions, language, learning level, and technical depth.

Featured Voices Across the AI & Space Track

Across the track, featured voices included space scientists, AI leaders, technologists, entrepreneurs, educators, researchers, and strategic communicators. Below are the sessions and speakers who shaped the conversation.

To connect with the speakers and contributors, click on their names to visit their LinkedIn profiles.

AI for Humanity in Space

Elizabeth (Liz) Ngonzi, MMH
Presenter

AI in Space Panel

Zaheer Ali, MBA — Track Co-Chair / Session Lead
Jennifer Rochlis, PhD — Track Co-Chair / Moderator
Amanda Fetch, PhD — Panelist
Brett Mecum, MS, MBA — Panelist
Kaylon Paterson, M.E., E.M.G.M — Panelist
Colleen McLeod Garner — Panelist

State of AI Panel

Chris Cochran — Moderator
Jennifer Rochlis, PhD — Panelist
Zachary Elewitz, PhD, MBA — Panelist

AI and Space: The First Seventy-Five Years

Bryant Cruse, MS — Presenter
Paul Richards, MS — Presenter

Tackling Space Debris with AI

Kaylon Paterson, M.E., E.M.G.M
Presenter

Advancing Space Situational Awareness Through Density-Based Clustering

Amanda Fetch, PhD
Presenter

AI, Trust, and Space-Themed Innovation in China

Aimei Helen Yang, MBA
Presenter

Homo artificialis spatialis: The Artificially Intelligent Android Astronaut

Pascal Lee, PhD
Presenter

Nearly Human AI

Jamison Rotz, BS
Presenter

If the Aliens Don't Speak Human

Jennifer T. O'Connor, PhD
Presenter

Swift Coat

Peter Firth, PhD
Presenter

X-Foam

Joshua McConkey
Presenter

Green Innovations / Rayn Innovations

Nicole Ray, PhD
Presenter

AI & Space Track

Allison Nicholls, E.M.G.M.
Track Co-Chair


Gamma.app & Gemini Notebook

Article © 2026 Elizabeth (Liz) Ngonzi, MMH and Zaheer Ali, MBA

Site and visual synthesis experience © 2026 Elizabeth Ngonzi LLC.