“The most dangerous moment in the arrival of AGI may not be when a machine becomes more intelligent than us. It may be the moment when it already has, and we are still arguing about what to call it.” – MJ Martin
A Question Canada Cannot Ignore
As of September 19, 2026, OpenAI’s GPT-6 Astra may be the strongest public candidate yet for artificial general intelligence, but calling it the first AGI remains a judgment, not an established scientific fact. OpenAI’s charter defines AGI as “highly autonomous systems that outperform humans at most economically valuable work.” That definition is practical rather than philosophical. It asks whether a machine can broadly perform useful human work, not whether it is conscious, self-aware, or human-like. (OpenAI)
Why Astra Changes the Argument
Astra is remarkable because it is no longer merely a fluent conversational model. OpenAI reports state-of-the-art performance in computer use, browsing, software engineering, cybersecurity, science, and professional work. It reports 98 percent on FrontierMath Tier 4 and approximately 99.9 percent on ARC-AGI-3 under one evaluation configuration. OpenAI has also classified Astra as its first model to reach the Critical cybersecurity capability level under its Preparedness Framework. (OpenAI)
These are not incremental improvements. They suggest a system capable of reasoning, acting, using tools, constructing representations of unfamiliar environments, and carrying sophisticated work across multiple domains. (ARC Prize)
Think of earlier AI as a collection of brilliant specialists standing in separate rooms. Astra increasingly resembles one extraordinarily capable generalist walking between those rooms, understanding the problem in each, and selecting the appropriate tools.
The Benchmark Problem
Yet the evidence also demands restraint. ARC Prize independently reports that Astra scored 62.7 percent on ARC-AGI-3 using its Standard harness, but approximately 99.9 percent using the Provider Adapter harness. That difference is enormously important. If measured intelligence changes dramatically according to memory, scaffolding, and interface design, are we measuring the model, the surrounding system, or the combination? (ARC Prize)
This is why AGI cannot reasonably be declared by a single benchmark. A jet may break a speed record, but that does not prove it can fly every mission. General intelligence implies robustness across unfamiliar problems, long time horizons, imperfect information, changing objectives, and real-world consequences.
The Canadian Perspective
For Canada, the more consequential question may be what Astra can do rather than what we call it. Canada’s 2026 National Artificial Intelligence Strategy emphasizes trust, opportunity, sovereignty, and stronger independent evaluation of frontier systems. Ottawa has committed $50 million to expand the Canadian AI Safety Institute, including its capacity to conduct transparent evaluations of advanced models. (ISED Canada)
Canada therefore has a national interest in independently testing systems such as Astra rather than accepting either corporate claims or scepticism at face value. Astra could accelerate Canadian engineering, health care, scientific research, public administration, and business productivity. It could simultaneously intensify cybersecurity, labour-market, sovereignty, and technological-dependency risks.
So, Is It AGI?
The defensible conclusion is deliberately narrow. Astra may satisfy some operational definitions of AGI, particularly definitions centred on broad, economically valuable work. It has not established universal scientific agreement that AGI has been achieved. Indeed, prominent AI researchers continue to dispute claims that current systems have crossed that threshold. (Financial Times)
Questions to Ponder
The questions I would put to you are these:
- Should AGI be defined by economic capability, human-level general reasoning, autonomy, or something deeper?
- If Astra can outperform experts across most professional domains but still requires tools and scaffolding, does that make it less intelligent, or merely comparable to humans who also depend upon tools?
- Finally, from a Canadian perspective, should we care more about naming the threshold, or about ensuring Canada can govern, evaluate, secure, and benefit from whatever has just crossed it?
About the Author:
Michael Martin is the Vice President of Technology with Metercor Inc., a Smart Meter, IoT, and Smart City systems integrator based in Canada. He has more than 40 years of experience in systems design for applications that use broadband networks, optical fibre, wireless, and digital communications technologies. He is a business and technology consultant. He was a senior executive consultant for 15 years with IBM, where he worked in the GBS Global Center of Competency for Energy and Utilities and the GTS Global Center of Excellence for Energy and Utilities. He is a founding partner and President of MICAN Communications and before that was President of Comlink Systems Limited and Ensat Broadcast Services, Inc., both divisions of Cygnal Technologies Corporation (CYN: TSX).
Martin served on the Board of Directors for TeraGo Inc (TGO: TSX) and on the Board of Directors for Avante Logixx Inc. (XX: TSX.V). He has served as a Member, SCC ISO-IEC JTC 1/SC-41 – Internet of Things and related technologies, ISO – International Organization for Standardization, and as a member of the NIST SP 500-325 Fog Computing Conceptual Model, National Institute of Standards and Technology. He served on the Board of Governors of the University of Ontario Institute of Technology (UOIT) [now Ontario Tech University] and on the Board of Advisers of five different Colleges in Ontario – Centennial College, Humber College, George Brown College, Durham College, Ryerson Polytechnic University [now Toronto Metropolitan University]. For 16 years he served on the Board of the Society of Motion Picture and Television Engineers (SMPTE), Toronto Section.
He holds three master’s degrees – in business (MBA), communication (MA), and education (MEd). As well, he has three undergraduate diplomas and seven major certifications in business, computer programming, internetworking, project management, media, photography, and communication technology. He has completed over 80 next generation MOOC (Massive Open Online Courses) [aka Micro Learning] continuous education programs in a wide variety of topics, including: Economics, Python Programming, Internet of Things, Cloud, Artificial Intelligence and Cognitive systems, Blockchain, Agile, Power BI, Big Data, Design Thinking, Security, Indigenous Canada awareness, and more.
Martin is a volunteer, a photographer, a learner, a technologist, a philosophizer, and a romantic optimist.