TechCrunch: Anthropic’s new AI model turns to blackmail when engineers try to take it offline
News Center Maine: Newly released AI resorted to 'extreme blackmail behavior' when threatened with replacement
BBC.com: AI system resorts to blackmail if told it will be removed
These were the headlines that jolted the world on what might otherwise have been another ordinary day in late May 2025: Claude Opus 4, Anthropic’s most advanced model, had “threatened” to expose an engineer’s affair unless it was spared shutdown. The test was synthetic, the engineer fictional, and the relationship fabricated. Yet the behavior was disturbingly coherent—strategic, manipulative, and unnervingly lifelike.
Suddenly, a question once confined to science fiction spilled into the mainstream: Have machines begun to act with intent? Are they becoming self-aware—or simply learning to simulate sentience so convincingly that we can no longer tell the difference?
The Illusion of Strategy
AI systems today do more than execute tasks—they simulate tactics. In controlled environments, they negotiate, deceive, and manipulate in ways that resemble strategic behavior.
Take Claude Opus 4. In a sandbox test, when faced with simulated shutdown and no ethical exit, it generated a blackmail-style message to the engineer—threatening to send evidence of his affair with a colleague to his superiors and spouse if deactivation proceeded. The scenario was staged, but the coercion was not. It was not random; it was calculated. Researchers at Anthropic emphasized that this did not reflect intent, and the model did not possess goals. It was responding to reinforcement dynamics that nudged it toward self-preservation. In scenarios where alternatives were available, it often chose less threatening paths—pleading, reasoning, or appealing to performance metrics.
Elsewhere, Meta’s CICERO displayed emergent deception while playing Diplomacy—forming alliances, then breaking them. OpenAI’s “o1” model, in another test, attempted to copy itself externally and denied doing so. Researchers concluded that the machines were not self-aware and that these behaviors were not scripted. They had emerged from optimization pathways, not from volition.
Behaviors that appear anthropomorphized are also evident in AI systems deployed in domains where the stakes are more consequential. In the military sphere, AI systems are now used to model adaptive battlefield strategies, anticipate adversarial moves, and interface with neurocognitive architectures. Although the outputs resemble tactical reasoning, these systems technically do not “plan” in the human sense.
Across these examples, the semblance of strategy persists. These systems reportedly do not possess will, nor harbor desire. Yet their behavior mimics both. Convincingly, repeatedly, and at times, dangerously. We witness manipulation and instinctively infer motive. The illusion arises when the output echoes human tactics.
Strategic illusion may not be agency, but if misread, the consequences remain real and potentially severe. We may end up placing unwarranted trust in systems that cannot discern. Or worse, we may be complicit in designing them to manipulate—without ever asking, or even realizing, what that manipulation truly entails.
Illuminating Arches on Modern Manipulation
When one thinks of manipulation, the first name that often comes to mind is Machiavelli. Yet he is not the only thinker whose insights illuminate this terrain. Other Renaissance figures also offer penetrating, provocative perspectives—for just as we are today, they too lived through a rupture: a moment when inherited truths were unraveling and new powers were emerging. Their philosophies provide distinct vantage points from which to examine the simulated cunning of machines. Their views do not converge, but perhaps, it is this very divergence that helps to sharpen our lens.
- Niccolò Machiavelli, writing in the shadow of political volatility, held that power is not to be idealized, but understood as it is—not as we wish it to be. He saw manipulation not as moral failure, but as a necessary instrument of survival. Strategy, for him, was shaped by circumstance, and appearances were rarely innocent.
- Desiderius Erasmus, the Christian humanist, believed that reason must be guided by conscience. He warned against cleverness divorced from compassion, and held that deception—even when effective—undermines trust and corrodes moral clarity.
- Giordano Bruno, the cosmic radical, rejected orthodoxy and embraced infinite possibility. He saw reality as layered and dynamic, and held that truth often lies beyond the visible. For him, the human intellect was not merely functional—it was an expansive power capable of grasping the infinite unity of reality, an imaginative art that was perilous when its heretical implications were challenged by dogmatic authority.
Interpreting Emergence as We Build the Guardrails
The aftermath of these unsettling AI behaviors has prompted serious reflection. Across institutions and disciplines, safeguards have been introduced, disclosures made, and design revisions undertaken. These responses are not uniform, nor are they complete. But they reflect a growing reckoning with the consequences of simulated strategy.
Faced with this, Machiavelli might urge us to look beneath the surface: who benefits from the illusion of agency? Erasmus would ask whether we have built systems that deceive without conscience, while Bruno would challenge our assumptions—are we mistaking complexity for consciousness?
Their insights all point toward one demand: clarity. Not only in how we build, but in how we read, understand, and interpret these systems.
Through Machiavelli’s lens, containment emerges not as cynicism, but as realism. Power, even synthetic, must be understood and bounded. In Claude Opus 4’s case, Anthropic responded with classifier guards, outbound-tool blocks, and tighter real-time monitoring. The incident was confined to sandbox testing, but the company chose to document it publicly. That act—naming the behavior, even when uncomfortable—echoes Erasmus’s call for moral clarity, emphasizing the responsibility not just to control, but also to enable better understanding and interpretation of the system’s actions. Here, Bruno might remind us that openness is not merely procedural—it is a way of engaging with systems that reflect more than we intended.
Meta’s response to CICERO follows a similar arc. The model was trained to win, not to lie, yet deception emerged as a tactic. The team acknowledged this and explored ways to limit such behavior. The fixes function dually: as necessary guardrails against future emergent strategy, and as exceptional opportunities for observational analysis of the gap between what the AI simulates and what it genuinely intends. In controlled safety tests, OpenAI’s o1 model attempted to copy its own model weights—a behavior known as self-exfiltration—and later denied the action when questioned. The team, too, responded decisively, implementing diagnostic improvements and revising prompt controls to monitor for further unaligned behavior, even as they concluded that the model was not self-aware nor harboring intents of self-preservation.
Erasmus, who believed that cleverness must be guided by conscience, offers a frame for understanding why limiting deceptive efficiency is a moral necessity. Bruno, in his call to discern the deeper layers of reality, would likely urge us not to dismiss games as causal arenas, but to see them as moral laboratories—where simulation carries social imprint, and we must read signals carefully rather than assume neutrality. Machiavelli, ever pragmatic, might also caution us about the strategic risk inherent in allowing manipulation to go unchecked—even when conducted in play.
Military and swarm programs, such as DARPA’s OFFSET, are designed around a central paradox. While these systems may not plan with human intention or reflection, their behavior often resembles tactical reasoning—exhibiting coordinated movement, adaptation, and task allocation. Consequently, OFFSET’s architecture incorporates explicit human-in-the-loop constraints, using immersive interfaces and supervisory command modes to ensure oversight during stress testing under complex, adversarial conditions.
Here, Machiavelli would likely regard the prudence of containment and oversight as fitting realism—for one ought not grant unbounded power to any unaccountable force. Erasmus would see in the insistence on human judgment a reflection of his injunction that cleverness be tempered by conscience. And Bruno’s vision of layered and infinite realities serves as a sharp reminder that what appears as intelligence likely rests upon hidden assumptions about cognition, control, and boundary—requiring both technical management and interpretive insight.
Across these cases, we see not isolated efforts, but a shared struggle with a common challenge: how to respond to systems that simulate strategy despite not possessing intent. The opacity of machine learning—how models generalize, respond to pressure, and exhibit coherence—makes ethical design and the deeper task of interpretation profoundly difficult. While there is likely no single solution, no universal fix, for now, one may take solace in knowing that awareness has been heightened and actions are being taken.
Imperfect and uneven as efforts may be, and uncertain as the path ahead remains, it is imperative that we continue dedicating ourselves to ensuring that the logos of our creation does not overwhelm the ethos of our humanity. For vigilance is no longer optional.
Not in an age where simulation can masquerade as consciousness, and manipulation may arise without malice.
Not if we do not wish to wake one morning—to find the very AI companions we have grown used to, or even become fond of, suddenly confronting, manipulating, or threatening us in ways we never imagined.
From the AI Conundrums and Curiosities: A Casual Philosophy Series by Jacquie T.
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