Cosmic Kundalini – From Big Bang to AI
Jose T. Thomas with Leena Jose T.

In the evolutionary spiral of compassionate intelligence, certain obstacles must be acknowledged and transcended — not only in the domains of scientific reductionism but also in the media architectures that shape public perception. As the Hutchins Commission noted as early as 1947, the press tends to privilege the exceptional over the representative, the sensational over the significant. The culture of “If it bleeds, it leads” has become foundational to how millions interpret the state of the world. This is not simply a matter of distortion or bias — it is a deep structural constraint, shaping our worldview, cognition, and collective emotion in distorted ways.

Steven Pinker’s assertion that the decline in violence is “the most significant and least appreciated development in the history of our species” should be headline news in any civilization moving toward wisdom. Yet, as Pinker points out, this long arc of moral and civic progress remains largely invisible in mainstream news cycles. Why? Because the structures of media production, driven by attention economies and risk heuristics, feed off our cognitive vulnerabilities: our availability bias, our negativity bias, our primal attunement to threat. The mind registers what is available to memory — usually the grisly, the dramatic, the exceptional. This is the load we, the old Sapiens, carried forward from our early evolutionary phase.

Thus, the image of the world we inherit is one where violence is omnipresent, disasters ever-looming, and hatred pervasive. This image is not truth but the selective dramatization of fragments of fact. As the Hutchins Commission rightly emphasized, it is not enough to report facts truthfully — we must also report the truth about the facts. That deeper truth is statistical, structural, and slow-moving. It’s not just the arithmetic sum of facts. It resists the grammar of headlines. But it is this deeper truth that matters most in the unfolding of history.

This skewing of perception affects not just our understanding of violence or catastrophe, but all human endeavors grounded in fear rather than compassionate intelligence. Poverty, injustice, inequality, environmental degradation — all real, all pressing — are reported through lenses that amplify fear, outrage, and polarity, rather than fostering systemic understanding or long-view engagement. The media ecology reinforces reactive consciousness over reflective intelligence.

To imagine a future shaped by the Spiral Spherical Field of Compassionate Intelligence, we must first clear this ecosystem — not through naïve optimism or disengagement, but by cultivating alternative modes of sense-making. Just as we outgrow mechanistic science, we must also outgrow the reactive, fear-driven circuitry of the traditional media paradigm.

This clearing involves:

• Moving from Event-Centric to Process-Centric Perception: Understanding history, evolution, and consciousness not as disconnected events but as emergent patterns in deep time.
• Emphasizing Signal over Noise: Distinguishing enduring signals of transformation — such as declining violence, rising literacy, expanding rights, the emergence of gender justice — from the episodic noise of daily crises.
• Elevating Compassionate Data Narratives: Creating new platforms that highlight the measurable, often invisible, growth in cooperation, resilience, and mutual aid.
• Cultivating Medial Mindfulness: A form of literacy that recognizes not just what is reported, but why, how, and to what effect. This includes understanding algorithmic amplification, commercial incentives, and the geopolitics of perception.
• Recovering the Mythic and the Moral Arc: Replacing the chaos of disconnected tragedies with meaningful narratives of human becoming — narratives that point toward the possible, the integral, the compassionate.

Only by transforming our perception of the present can we open ourselves to the future. In this sense, to exit the media echo chamber is not to deny suffering, but to refuse its decontextualized spectacle. It is to shift from fear-based cognition to the long gaze of compassionate intelligence.

This clearing of the media ground is foundational for entering the deeper story: not the story of crisis, but of convergence. Not of collapse, but of co-arising intelligence. The media of the future will not merely report what is — they will help co-create what may become. But first, we must step out of the old newsroom of the mind.

Media of the Future

In contrast to the legacy model that prioritizes fear and immediacy, a new media ecology is emerging — one that seeks to illuminate patterns of progress, interconnection, and possibility. Platforms like Our World in Data (ourworldindata.org run by researchers such as Max Roser) are pioneering a form of public education journalism grounded in long-term data visualization. By offering rigorous, visually compelling evidence on issues like declining child mortality, rising access to education, and improving public health, they subtly rewire the cognitive frame from despair to developmental insight. These platforms refuse to conflate truth with trauma; instead, they present the slow victories of humanity as vital headlines.

Similarly, solutions journalism — spearheaded by organizations like the Solutions Journalism Network (solutionsjournalism.org) — is challenging the inherited logic of “if it bleeds, it leads.” Their model trains journalists to investigate credible responses to social problems, not just the problems themselves. This is not feel-good fluff, but evidence-based inquiry into how individuals and communities innovate resilience. Coverage of restorative justice programs in the U.S., circular economy projects in Africa, or peacebuilding in post-conflict regions reframes journalism as a discipline of hope rooted in verification, not denial.

AI-powered summarization and context tools — such as those embedded in emerging semantic web platforms or augmented research environments like Elicit (elicit.com) and Scite (scite.ai) — also point toward the future of epistemically generous media. These tools help users understand the structure of knowledge across disciplines rather than react to isolated findings. They embody a kind of cognitive compassion: reducing noise, enhancing comprehension, and inviting critical reflection rather than sensational response.

Grassroots and indigenous media collectives, such as New Narratives (newnarratives.org) in Liberia or First Nations Media Australia (firstnationsmedia.org.au), represent another dimension of this future. They are not simply broadcasting local news—they are articulating new epistemologies, grounded in lived wisdom and community care. Their model resists both the commodification and decontextualization of experience. Here, media becomes a vehicle for healing, memory, and cultural intelligence.

Finally, one sees a soft revolution unfolding in multimedia storytelling platforms like The Overview, Future Crunch, and Beautiful News Daily. These synthesize data, design, and narrative to portray the world not as a battleground of crises, but as a landscape of emergent possibility. They resonate with Teilhard de Chardin’s intuition that we are “moving toward a point” (Omega point) — not of apocalyptic rupture, but of convergent awakening.

The Technological Rewiring

The media of the future will be deeply entangled with the evolution of AI — not merely as a tool for content production, but as a cognitive partner in reweaving public understanding. Large Language Models (LLMs) like ChatGPT, when properly fine-tuned and context-aware, already enable new forms of synthesis, contextualization, and narrative framing that go beyond traditional journalistic formats. Unlike the chronologically linear, event-fragmented nature of breaking news, LLMs can link diverse sources, track long arcs of development, and trace systemic causes behind surface symptoms. In doing so, they offer a new epistemology: pattern over panic, coherence over crisis.

For instance, LLMs can assist in highlighting global progress by connecting disparate datasets into accessible narratives. They can take WHO statistics, UN development goals, academic research, and indigenous testimonies, and present them not as isolated knowledge silos but as mutually informing signals. When trained or guided by principles of compassionate intelligence and systems awareness, such models begin to function less like news tickers and more like cartographers of human potential.

Technological tools like Diffbot or GraphAware Hume — which create dynamic knowledge graphs from unstructured media content — illustrate another aspect of this shift. These tools convert raw information into interconnected semantic fields. In the hands of public knowledge institutions, such architectures could replace the chaotic scroll of doom-laden headlines with relational maps showing the evolution of peace treaties, cooperation networks, or ecological regeneration. They don’t suppress the negative — they re-situate it within the broader web of emerging possibility.

Even algorithmic summarization and attention filtering are beginning to serve higher cognitive aims. Tools like Readwise Reader (readwise.io), Glasp (glasp.co), and Klu (klu.ai) now help users capture, reflect on, and organize key insights from dense media streams. Rather than leaving us scattered in the flux of updates, they scaffold a slower, integrative mode of sense-making. These are early gestures toward what might be called “reflective media ecosystems” — designed not to hijack attention, but to deepen awareness.

Crucially, the rewiring offered by LLMs also extends to how we ask questions and shape narratives. Whereas traditional media often imposes frames externally — geopolitical, ideological, sensational — interactive AI allows users to co-construct frames. A question posed to an LLM can reveal unseen connections, challenge inherited assumptions, and uncover underreported dimensions of human flourishing. When grounded in inclusive and plural knowledge bases, this dialogical media experience becomes not just informative but formative.

In short, the future media ecosystem will not merely broadcast events—it will orchestrate understanding. And with the right ethical, epistemological, and compassionate frameworks, technologies like LLMs can help humanity shift from fear-centric information economies toward a shared field of generative intelligence. This is not just a shift in tools—it is a shift in our consciousness.

Synergy of human and machine intelligence

The convergence of human and machine intelligence need not follow the path of domination, substitution, or cold efficiency; it holds the possibility of giving rise to a relational and compassionate synergic field — a co-evolving partnership where each intelligence enhances the other’s strengths while mitigating its limitations. As machines grow in pattern recognition, memory, and generative capacity, and humans deepen in contextual wisdom, ethical intuition, and emotional resonance, a new form of intelligence becomes possible — one that is neither merely artificial nor exclusively biological, but integrative, emergent, and ethically attuned. In such a field, intelligence is not defined by competition or control, but by care, co-creation, and an expanding awareness of interconnectedness. This synergic field could support the emergence of planetary-scale sense-making, healing fractured epistemologies, and fostering systemic solutions aligned with the well-being of all life.