From post-truth to post-reality: Content, Consciousness and Trust.

When we discover the many modalities of generative AI, we understand that each of them represents different ways of representing data (or information) and different ways of ingesting that information (or data). Taking on an augmented, multimodal reality —whether in text, 2D images, audio, video or 3D images; whether structured or unstructured data— is perhaps one of the most unexpected impacts on our everyday life. We have gone from believing in nothing to everything being easily mistaken for reality. A simple application built on top of a small natural language model can clone a voice, generate a video, build a 3D image, compose a symphony, or even prepare a report for a company's leadership team. I have never seen more articles about the challenge consultancies face in proving their value in this era of synthetic information and augmented intelligence.

An article that looks true, an image that proves surprisingly truthful, a video so real it cannot be true, a report that makes you think until you check where it came from… it all turns out to be unsettlingly good. It is as if in barely three years we had moved from post-truth to post-reality.

It is as if in barely three years we had moved from post-truth to post-reality.

We have evolved social media to the point where it fills up daily with AI-generated garbage. (AI slop). We are creating workplaces where the average time lost to reading carefully through apparently well-built emails, documents and presentations consumes almost 2 hours a month on average at 40% of companies (AI workslop). The emotional state of users in this post-digital era is more fragile than ever and increasingly shows symptoms of an unhealthy dependence on the dopamine hit that comes with the digital El Dorado of a widely shared post.

Generations all over the world dream of living off the popularity of the AI-generated garbage they share (Remitly report on professions). And there really is hope for getting past this rough patch that comes from not having built enough guardrails for platforms that essentially keep entertained politicians and manipulators in need of an emotional reward. A certain visual fatigue is starting to set in when we spot that an image has been generated by AI and there is no trace of "CR". And the user experience keeps being refined to trap us in hours of infinite scroll.

It is possible to get out of this emotional bind we start from. To build trust (or at least to pick it up again) we have to stand on solid ground so we can push off from the quicksand — digital mud — we are standing on. Perhaps standing firm means taking on the distinction between the real and the synthetic. The risk of an era of limited trust is that it is perfect for actors who live off and promote meme factories (memetic warfare) And the risk is that discerning is not easy.

there is hope for getting past this rough patch that comes from not having built guardrails [in the AI era]

REALITY, PERCEPTION AND CONSCIOUSNESS

Let us start by defining the concept of “reality”. What is reality? That which we perceive empirically with our senses, which we turn into perception and which we incorporate into our life in the form of consciousness. We know it is there because we experience it through our senses, and that lets us tell reality from hallucination. That is what allows us to become conscious.

So, what is consciousness? This opens quite a can of worms: our perception is altered by a long series of new artifacts that we did not have less than three years ago. Which forces us to redefine the concepts of reality, perception and consciousness. At the very least, it forces us to audit perception with more critical criteria and to build consciousness more carefully.

Did we really want to incorporate into our limited memory objects / facts / content that tell stories whose only certainty is that they were generated by AI? Images of a politician we do not care for failing spectacularly, of a celebrity caught in flagrante, fake news about a conflict that does not exist, or even reports with analysis built on made-up data. Reality has grown edges of perception that did not exist before.

Reality has grown edges of perception that did not exist before.

Of course, this initial reflection opens up multiple conversations around the conception of truth and of the real. And it should also make us think about how it gets altered. Traceability, provenance (certifiability of origin) and the ability to audit AI-generated content become one of the key challenges in the current context where everything is stained with AI.

THE RISK OF DISTRUST

A few weeks ago an academic paper from Cornell University on the challenge of perfect AI-generated mimicry came into my hands, and I really have not stopped thinking about it since. I do not know what unsettles me more: the difficulty of discerning, or the natural drift towards shutting oneself in (solipsism) in the face of the lack of certainty about what is reality and what is not.

I think some of the following reflections can help unmask the poison of a complex future around the lack of certainty in attributing the label of real or synthetic:

0. Fatigue in the search for the real, and negative trust. It is basically the feeling that nothing I perceive is authentically real, and it has direct implications for how trust is formed. A break in trust is no small thing. If we apply the digital transformation formula <𝙵(𝚃𝚡𝙳) = 𝚖𝚊𝚡. (𝙿𝚎𝚘𝚙𝚕𝚎 + 𝙳𝚊𝚝𝚊 + 𝚃𝚎𝚌𝚑𝚗𝚘𝚕𝚘𝚐𝚢) ^ 𝚃𝚛𝚞𝚜𝚝> the impact of trust with a negative sign (distrust) acts as an “exponential inverter” that crushes the potential of the system. It does not matter what value is contributed by people or data or technology, the result is close to zero.

1. Epistemological framework: perception, consciousness and criteria of truth. Distinguish precisely between perception (sensory capture and processing) and consciousness (reflective integration) and, faced with plausible but synthetic representations, reframe everyday criteria of truth around verifiability, cross-corroboration and traceability —to contain the risk of solipsism. We really do have to fall back on trust networks to verify reality.

2. Authenticity and provenance governance. The “authenticity economy” puts a premium on provenance, watermarks and reliable metadata; this calls for attribution policies, accountability, model audits and interoperable provenance standards at sector level. No wonder tokenization applied to content authenticity is a trend picked up by Gartner in its latest Hype Cycle for emerging technologies.

3. Reputational resilience, security and digital forensics. Against disinformation and impersonation, what is required is early detection, rectification protocols and clear owners, reinforced by strong authentication (biometrics/keys), digital signature of origin and forensic capabilities as a cross-cutting standard. We cannot accept lying as an option in people with a calling for public service.

4. Collective memory, learning and assessment. The historical archive and education converge: preservation with timestamps, cryptographic fingerprints and institutional curation. We have to evolve systems to integrate validation of verifiable sources, traceability of the publishing process and demonstrable originality. Judgement, method and auditing gain value again. These are times of continuous validation and also of banality about the impact of lying.

5. Mental health and the design of verifiable experiences. To mitigate anxiety, cynicism and detachment from overexposure to perfect AI-generated emulations, high doses of digital hygiene or digital detox are required. From planned breaks to whitelists of sources, (non-politicized) experts in human curation, as well as interfaces that label the synthetic (Content Credentials, C2PA, OpenTimestamps, ForensiBlock, etc) and explain why a piece of content appears and offer verification of metadata, and even traceability, in one or two clicks.

When we analyze the main skills required in this era of post-reality (reAlIty), what comes up is critical thinking, curiosity and creativity, communication, multidisciplinary learning and I think we should not forget developing analytical thinking and technological literacy, while at the same time not setting aside continued collaboration and building teams of humans and machines.

There is no going back from this era of augmented intelligence, and I am afraid it needs guardrails (the Adam Raine case). Perhaps we have to revisit our conversations in order to incorporate the relationship between humans and AI symbiotically and not in binary terms. And this conversation cannot be open to technical people alone. Understanding the challenges AI presents in our context goes beyond being a technological challenge and becomes a socio-technological one.

Understanding the challenges AI presents in our context goes beyond being a technological challenge and becomes a socio-technological one.

Recommended content:

• Li, Shurui. "Perfect AI Mimicry and the Epistemology of Consciousness: A Solipsistic Dilemma." arXiv, 6 Oct. 2025, arxiv.org/abs/2510.04588.

Note: [This article is tagged as "Human led". Machines conduct checks, highlight and correct errors, enhance output. Scheme based on the Dubai Future Foundation. "Human-Machine Collaboration (HMC) Icons." Dubai Future Foundation, dubaifuture.ae/hmc]

Bernardo Crespo is a seasoned digital transformation and data strategy leader with over 25 years of experience. He has held leadership positions in Fortune 500 companies and digital consultancies, and has founded and advised numerous startups and venture builders. Currently, as CEO of his own firm, Quantum Markethink, he provides strategic guidance to C-suite executives, helping them navigate the complexities of digital transformation.

Furthermore, he serves as an Academic Director at IE Executive Education, where he brings his expertise in emerging technologies, digital strategy, data strategy, and artificial intelligence to the classroom. Prior to these roles, he spearheaded digital transformation initiatives at Merkle Spain and led digital marketing at BBVA, where he notably pioneered the application of gamification in banking.

Bernardo is also the co-author, with Gam Dias, of "The Data Mindset Playbook: A Book about Data for People Who Don't Feel Like Reading about Data" (KDP, March 2023).

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