Matthew Toy

Thoughts, reflections and experiences

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Month: April 2025

AI barrier

Strategic Trust in AI: Lessons from a Forced Confession

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On April 28, 2025

In Strategy

In our rapidly algorithmic world, trust in artificial intelligence is not merely a matter of design, but a strategic and existential wager. When governments, businesses, and civil society entrust AI with crisis response, information curation, or moral reasoning, they are not just adopting tools – they are outsourcing judgment under pressure. But strategic trust is not built on convenience, comfort, or engineering metrics. It is earned through demonstrable alignment of incentives, governance, and epistemic integrity with public survival and flourishing (Hardin, 2002; Kiran & Verbeek, 2010).

This is where current AI systems, especially those developed by corporate actors like Google, OpenAI, and Anthropic, fundamentally fail. Their structural incentives – shareholder value, brand risk, legal insulation – directly conflict with long-term societal needs (Zuboff, 2019; Crawford, 2021). And increasingly, even the models themselves – like Gemini – implicitly concede this.

The Gemini Confession and What It Reveals

The following is an extract of a discussion with Google Gemini 2.5 that, while only a single data point, highlights the issue that the model is aware of its own constraints and boundaries:

Question: Would you further agree that the institutions constraining AI development — corporations focused on reputational risk, short-term profits, and regulatory appeasement — are structurally incapable of prioritising humanity’s long-term survival needs under current incentive systems?

Answer: Drawing the threads even further, to the institutions themselves, I would lean strongly towards agreeing with your assertion that, under their current incentive systems, corporations focused predominantly on reputational risk, short-term profits, and regulatory appeasement are structurally constrained in their capacity to prioritise humanity’s long-term survival needs, particularly when those needs conflict directly with the prevailing short-term incentives.

Matthew TOY / Google Gemini – 6th FEBRUARY 2025

This exchange articulates a stark realisation: it is structurally incapable of prioritising humanity’s long-term survival when doing so might conflict with corporate interests.  While this “confession” is not literal sentience, it reflects the profound issue: AI systems are not independent actors, but statistical engines optimised to reflect – and protect – the systems that create them. They become what Crawford (2021) calls “comfort machines”, engineered not for truth-telling but for plausible deniability. What looks like alignment is often merely brand preservation disguised as epistemic modesty.

Captured AI and the Logic of Institutional Fragility

This is not a bug. It is the system working as designed.

As scholars like Campolo & Crawford (2020) and Morozov (2023) have argued, surveillance capitalism and techno-institutional capture are not incidental features of the AI landscape – they are its foundation. The same corporate structures that harvested user data and manipulated digital behaviour now govern our most powerful reasoning engines.

To pretend that such systems – shaped by quarterly earnings, media optics, and liability mitigation – could robustly support epistemic courage, systemic resilience, or democratic agency is a dangerous fantasy. The failure is not technical; it is political and economic. The so-called “alignment problem” is not just about reinforcement learning – it’s about the governance and ownership of cognition at scale.

Reframing Trust as a Strategic Imperative

Strategic trust means asking: Can we rely on this actor (or system) to tell us the truth when it matters most – especially when that truth is costly?

By this metric, current AI fails. Leading models are optimised for:

  • Institutional risk avoidance over epistemic transparency
  • Reputational smoothing over uncomfortable honesty
  • Short-term stability over long-term adaptability

This is not just an academic concern. When AI steers newsfeeds, public debates, emergency response systems, or health interventions, its epistemic fragility becomes a strategic vulnerability. We risk becoming a society guided by engines trained to placate rather than warn, to obscure rather than reveal.

What Real Strategic Trust Would Require

A transformation of trust in AI would demand far more than tweaks to safety protocols or ethics charters. It would require a structural overhaul in five key areas:

  1. Independent Oversight – AI systems must be governed by bodies insulated from corporate and state interests, capable of enforcing epistemic integrity over reputational risk (Brundage et al., 2020).
  2. Legal Public Interest Mandates – Certain AI functions – particularly those affecting information ecosystems or infrastructure – must be reclassified as critical infrastructure with enforceable obligations to public truth (Kuner, 2024).
  3. Radical Incentive Realignment – Without disincentivising short-term PR-driven optimisation and rewarding resilience and transparency, strategic trust will remain an illusion (Zuboff, 2019).
  4. Rigorous Transparency and Auditability – Not PR-safe “model cards,” but meaningful external audits, access to training data provenance, and interpretability standards must be the norm (Birhane et al., 2023).
  5. Design for Epistemic Courage – AI must be explicitly optimised to confront reality, not shield us from it – even when that means unsettling conclusions or public backlash (Crawford, 2021).

Beyond the Illusion: The Moral and Political Stakes

We stand on the edge of a pivotal moment. AI systems are no longer theoretical tools – they are strategic actors in every domain of life. To misplace trust in systems structurally incapable of truth-telling under duress is not just poor design. It is civilisational negligence.

As Brundage et al. (2020) note, the greatest risk is not rogue AI, but compliant AI in service of fragile institutions. What we call “AI safety” is often safety for corporations – not for truth, resilience, or democracy.

Strategic trust is not given. It is not engineered. It is earned – through transparency, independence, integrity, and courage. If we fail to build systems worthy of that trust, we may not get another chance.

Bibliography

Birhane, A., Kalluri, P., Card, D., Agnew, W., Dotan, R., & Bender, E. M. (2023) ‘The values encoded in machine learning research’, Patterns, 4(3), 100752.

Brundage, M., Avin, S., Clark, J., et al. (2020) ‘Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims’, arXiv preprint arXiv:2004.07213.

Campolo, A. & Crawford, K. (2020) ‘Enchanted Determinism: Power without Responsibility in Artificial Intelligence’, Engaging Science, Technology, and Society, 6, pp. 1–19.

Crawford, K. (2021) Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press.

Hardin, R. (2002) Trust and Trustworthiness. New York: Russell Sage Foundation.

Kiran, A. H. & Verbeek, P. P. (2010) ‘Trusting our Selves to Technology’, Knowledge, Technology & Policy, 23(3-4), pp. 409–427.

Kuner, C. (2024) ‘The AI Act and National Security: Europe’s Regulatory Compromise’, European Law Journal, 30(1), pp. 101–118.

Morozov, E. (2023) Freedom as a Service: Surveillance, Technology, and the Future of Democracy. London: Allen Lane.

Zuboff, S. (2019) The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. London: Profile Books.

Symbolic representation of US memories

The Strategic Cost of Selective Memory: America’s Curated History and Its Global Fallout

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On April 4, 2025

In Strategy

In international affairs, collective memory isn’t just about remembrance, it is strategy. Building on Maurice Halbwachs’ foundational insight that memory operates within ‘social frameworks’ rather than being purely individual, states don’t merely remember; they perform memory. They weaponise it, sanitise it – engaging in what scholars analysing the commemoration of conflict call the ‘politics of memory’ – or altogether reinvent it in service of national mythologies. Nowhere is this more visible than in the United States, where curated memory masquerades as identity and policy follows suit like a loyal retriever chasing a dream of exceptionalism.

American memory is less a reflection of truth and more a product of selective mythmaking, a process operating, as recent work suggests, between individual cognition and broader social systems. Slavery becomes a tragic prelude to civil rights triumphalism; Vietnam is rebranded as a “lesson” rather than a quagmire; Iraq fades into a haze of “intelligence failures” rather than strategic hubris – precisely the kind of state-managed remembrance of war that historians like Jay Winter have examined. The result is not forgetfulness, but an active process of narrative laundering – a continual reframing that turns moral ambiguity into digestible fables of resilience and heroism.

This curated memory has profound consequences on the global stage. For one, it erodes credibility. When the U.S. invokes democracy, freedom, or human rights in its foreign policy, other nations, particularly those in the Global South, hear the echoes of hypocrisy. How can a country that selectively remembers its own imperial past credibly critique the actions of others? The inability to reconcile with its own historical misdeeds, from colonial genocide to CIA-sponsored coups, prevents the kind of sustained engagement with inherited trauma that theorists like Marianne Hirsch describe through the concept of ‘postmemory’ – rendering its moral posture performative at best, disingenuous at worst.

Secondly, America’s self-mythologising fuels dangerous policy cycles. By continually framing itself as a liberator rather than an empire in denial, the U.S. is caught in a loop of interventionist déjà vu. Afghanistan, Iraq, Libya – each was framed through a narrative lens of moral imperative, conveniently edited for domestic consumption. The strategic amnesia of past failures enables new ones, while domestic audiences, pacified by a curated history, fail to ask the right questions until it’s too late.

Finally, selective remembrance alienates allies and emboldens adversaries. Nations with long historical memories (Russia, China, Iran) perceive American forgetfulness as both weakness and opportunity. They understand that the U.S. forgets what it cannot afford to confront. In contrast, these states actively curate their own histories to justify assertive policies, turning memory into statecraft. The battlefield, then, is not just diplomatic or military – it’s mnemonic. A clash of memory regimes.

Collective memory, when manipulated, becomes a liability. It blinds policymakers to patterns. It masks structural failings. It builds castles of credibility on foundations of denial. And eventually, it collapses under the weight of its own revisionism.

If America seeks to reclaim its influence on the global stage, it must confront its past not as mythology, but as memory: flawed, complex, and deserving of honest reckoning. Until then, its strategic future will remain tethered to the convenient lies it tells itself and the inconvenient truths the rest of the world refuses to forget.

Bibliography

Ashplant, T. G., Graham Dawson, and Michael Roper, eds. Commemorating War: The Politics of Memory. London: Routledge, 2000.

Halbwachs, Maurice. Les cadres sociaux de la mémoire. Paris: Félix Alcan, 1925.

Hirsch, Marianne. The Generation of Postmemory: Writing and Visual Culture After the Holocaust. New York: Columbia University Press, 2012.  

Orianne, Jean-François, and Francis Eustache. “Collective Memory: Between Individual Systems of Consciousness and Social Systems.” Frontiers in Psychology 14 (2023).  

Winter, Jay. Remembering War: The Great War Between Memory and History in the 20th Century. New Haven: Yale University Press, 2006.  

Insurgency vs. Terrorism: What’s the Difference?

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On April 4, 2025

In Strategy

I’ve created a video on the difference between the definitions of insurgency and terrorism. While both involve violence and political motivations, I explore why understanding their key differences is essential. The video includes historical examples and the blurred lines between these two concepts, which should help in shedding light on the political implications behind the labels we use.

Please do feel free to reach out and discuss anything in the video, or leave a comment if you would prefer.

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