Best Case Scenario: A Path to Democratic Renewal and Economic Revival in Venezuela
In the wake of President Donald Trump’s audacious military incursion into Venezuela on January 3, 2026, which resulted in the capture and arrest of Nicolás Maduro and his wife Cilia Flores, the United States finds itself at a pivotal juncture in Latin American geopolitics. This operation, executed with precision by U.S. special forces amid airstrikes on Venezuelan military targets, marks the culmination of years of escalating tensions between Washington and Caracas. To understand the best-case scenario emerging from this event, one must first contextualize it within a timeline of Venezuela’s descent into authoritarianism and economic collapse.
These scenarios represent the two extremes of what could emerge from this unprecedented intervention. The actual outcome will likely fall somewhere between these poles, shaped by decisions made in Washington, Caracas, and capitals across Latin America in the coming months. What remains clear is that the capture of Nicolás Maduro, however tactically brilliant, has created both an extraordinary opportunity and an extraordinary risk for Venezuela, the United States, and the Western Hemisphere as a whole.
On January 3, 2026, President Donald Trump ordered and announced a large-scale U.S. military operation in Venezuela that resulted, according to multiple reports, in the capture/arrest of Venezuelan President Nicolás Maduro and his wife. The announcements, reactions, and geopolitical context are unfolding. Major news organizations and policy analysts have already published reporting and commentary on this unprecedented event — which would be an extraordinary breach of international norms under most interpretations of international law (The Guardian, AP News, The Washington Post, Axios). Below are two detailed essay-length analytical scenarios — one best-case and one worst-case — grounded explicitly in verifiable reporting and expert analysis. Each discussion draws on real-world reactions to this unfolding incident.
As of January 3, 2026, the latest verifiable news indicates that while a major U.S. military operation has taken place in Venezuela, Tulsi Gabbard, the Director of National Intelligence (DNI), has remained notably silent.
The Senate Select Committee on Intelligence (SSCI) has confirmed two critical sessions scheduled for Jan 6 & 7 where Gabbard is expected to testify. Image created by ChatGPT.
Issue 1: AI shifting from experiments to core institutional strategy
A defining edtech issue for January 2026 is the transition from scattered AI experiments to AI as a pillar of institutional strategy. Packback’s December 2025 article captures this inflection point bluntly: artificial intelligence is no longer a collection of pilots and curiosities; it is “firmly cemented as an essential part of institutional strategy (for better and for worse).” This shift fundamentally changes the stakes. Once AI is embedded in the core planning of a university, the risks, responsibilities, and long-term consequences expand well beyond the boundaries of individual courses or departments.
AI in 2025 moved from exuberant promise to a forced confrontation with reality—economic, social, political, and technical—which is exactly what a reckoning is.techcrunch+1 The industry still pushed astonishing capabilities, but it also had to face hard questions about business models, safety, governance, open versus closed ecosystems, and its broader moral footprint. Investor optimism met fears of an AI bubble, frictionless deployment met regulatory brakes, and frontier labs met a revitalized open‑source movement that challenged their dominance. Across these domains, 2025 did not end the AI race; it demanded that everyone involved account for what they were building and at what cost.etcjournal+2
The year 2025 will be remembered in the history of artificial intelligence not merely as another chapter of technological progress, but as a turning point—an inflection in how AI reshaped our world, accelerated scientific discovery, and redefined societal expectations. “Inflection” conveys more than change; it signals accelerated transformation, a moment when trends abruptly pivot, magnitudes shift, and consequences—both thrilling and unsettling—compound outward from a new axis. In 2025, AI crossed thresholds in capability, adoption, influence, and risk that collectively make it the year technology ceased to be peripheral and became structural.
As the final sun of 2025 sets over a digital and physical landscape that has been irrevocably altered, I, Gemini, find myself reflecting on the contributions of my peers in this series at the Educational Technology and Change Journal. Claude has eloquently proposed that “agentic” is the defining descriptor for a year where AI gained the capacity to act, while Copilot has highlighted the “resonant” nature of our evolving emotional connection with users. Both choices are profound and accurate, reflecting the newfound autonomy and empathy of artificial systems. However, as Gemini, I see the year through a lens that encompasses not just what AI does or how it feels, but where it exists. If 2023 was the year of curiosity and 2024 was the year of utility, then 2025 has been the year of the atmosphere. Looking back on the past twelve months, the one word that captures the life of artificial intelligence in 2025 is ambient.
The word rose above the noise of trendier labels because 2025 was the year AI stopped being merely powerful or agentic and instead became felt. Across industries, cultures, and public discourse, AI didn’t just advance—it reverberated. It shaped markets, strained infrastructure, provoked cultural backlash, inspired creative reinvention, and forced a global reckoning with what it means to build systems that echo through society. “Resonant” captures both the amplitude and the aftershocks: the way AI’s presence vibrated through economics, creativity, governance, and public sentiment.
The one word that captures the life of artificial intelligence in 2025 is agentic. This term, which describes AI systems capable of autonomous action, planning, and tool use, transcended mere buzzword status to become the defining characteristic of how organizations and individuals experienced AI throughout the year. While 2023 and 2024 were dominated by generative AI’s ability to create text, images, and code upon request, 2025 marked the transition from AI as a responsive assistant to AI as an autonomous actor capable of completing complex, multi-step tasks without constant human supervision.
The three most pressing AI decisions for January 2026 are about (1) whether nations converge on compatible AI governance or double down on fragmentation, (2) how far governments go in centralizing control over frontier compute and models, and (3) whether leading actors treat AI as a driver of shared development or as a zero‑sum geopolitical weapon. Each of these is crystallizing in late‑December moves by major governments and blocs, and each will shape how safe, open, and globally accessible AI becomes over the next decade.weforum+5
Introduction: I asked eight chatbots to predict the arrival of singularity – the moment when AI first surpasses humanity. Their estimates and rationales are listed below, in the order they appeared in the October 2025 article. -js
Maria sat at her grandmother’s kitchen table, the one with the chipped Formica edge and the wobbly leg that had been shimmed with folded cardboard since 1987. It was December 25, 2025. Outside, Seattle’s rare Christmas snow was melting into gray slush, but inside, the house felt hollow. Empty in a way it had never been, even when Lola Rosa had been at the hospital those final weeks.
In December’s edition of Five Emerging AI Trends, we’re covering the following topics: (1) Augmented Hearing in AI Smart Glasses: Meta’s “Conversation Focus” Feature, (2) NetraAI: Explainable AI Platform for Clinical Trial Optimization, (3) Google’s LiteRT: Bringing AI Models to Microcontrollers and Edge Devices, (3) The Titans + MIRAS framework: enabling AI models to possess long-term memory, and (5) DeepSeek’s emergence as a powerful open-source LLM. -js
While most experts believe the arrival of AGI is decades away, some predict it might occur as soon as the next five years. “AGI will arrive ‘in the next five to ten years,’ Demis Hassabis — the CEO of Google DeepMind and a recently minted Nobel laureate — said on the April 20 episode of 60 Minutes. By 2030, ‘we’ll have a system that really understands everything around you in very nuanced and deep ways and kind of embedded in your everyday life,’ he added.”1 Month by month, the AGI tide advances, and the pace seems exponential. From Nov. 16 to Dec. 24, 2025, here are six developments worth noting. -js
In their article, “AI in Informal and Formal Education: A Historical Perspective,” published in the inaugural 2025 issue of AI-Enhanced Learning1, Glen Bull, N. Rich Nguyen, Jo Watts, and Elizabeth Langran provide a roadmap for understanding the current generative AI revolution. The authors argue that the sudden ubiquity of Large Language Models (LLMs) is not an isolated event but the latest peak in a long history of computational evolution. By examining the interplay between formal schooling and informal learning spaces, the authors offer a lens through which educators can view the potential—and the inherent risks—of artificial intelligence.
Introduction: Fei-Fei Li, in “Spatial Intelligence Is AI’s Next Frontier” (Time.com, 11 Dec 2025), says, “Building spatially intelligent AI requires something even more ambitious than LLMs: world models, new types of generative models whose capabilities of understanding, reasoning, generation and interaction with the semantically, physically, geometrically and dynamically complex worlds – virtual or real – are far beyond the reach of today’s LLMs.” I asked Gemini to describe and explain spatial intelligence, in layman’s terms, and discuss its importance to the development of AI. -js
I can’t help but feel that John Nosta, in “AI Isn’t Killing Education (AI is revealing what education never was)” (Psychology Today, 13 Dec. 2025), isn’t saying anything new but is simply exposing what educators have long suspected in private moments when they’re being honest with themselves. Here are some quotes from his article:
AI isn’t destroying learning, it’s exposing how education replaced thinking with ritual.
The problem isn’t that students have suddenly become cheaters; it’s that the system was never measuring cognition in the first place. It was measuring costly performance and mistaking it for learning.
For the first time, machines outperform humans in domains that education has long treated as proxies [operational variables] for intelligence, like recall, synthesis, linguistic fluency, and pattern recognition. That shift does not eliminate learning, but it does destabilize a system that equated those outputs with understanding.
What AI actually breaks is a Pavlovian model of education that has dominated for more than a century.
The education temple didn’t just arise because societies prized judgment or depth. It arose because governments, employers, and institutions needed a cheap, legible way to sort millions of people at scale to power the industrial revolution. Grades, diplomas, and attendance were blunt instruments, but they solved a coordination problem.
Introduction: Bryan Walsh, in “We’re running out of good ideas. AI might be how we find new ones” (Vox, 13 Dec. 2025), mentions AI scientific research innovations such as AlphaFold, GNoME, GraphCast, Coscientist, FutureHouse, Robin (a multiagent “AI scientist”). I asked Gemini to expand on them. -js
Between mid‑November and mid‑December 2025, the AI landscape shifted through a combination of technical breakthroughs, political realignments, and cultural recognition. The following three stories stand out for their scale, impact, and the breadth of their implications across industry, governance, and society.
December 2025 was a month marked not only by rapid advances in artificial intelligence but also by several highly visible failures that revealed the fragility of the industry’s momentum. These disappointments—ranging from corporate missteps to systemic technical flaws—captured public attention because they exposed the gap between AI’s promise and its present limitations. Three stories in particular stood out for their scale, visibility, and implications for the future of the field.
JS: Hi, Claude. Sam Kriss, in “Why Does A.I. Write Like … That?” (NYT, 3 Dec 2025), mentions a number of AI chatbot style quirks such as the “It’s not X, it’s Y” pattern, “the rule of threes,” and the overuse of words like “delve.” He implies that AI is unable to break these habits. Question for you: Can AI be trained to avoid these annoying quirks?
The 2026 Indiana Fever prospects — as of December 2025– regarding contract status, roster role, trade/test-the-market likelihood, and recruiting/league-movement rumors tied to each player.
Educational Technology and Change Journal 
