Autonomous AI’s Spellbook and the Absent Necromancer

Goethe wrote “Der Zauberlehrling” (The Sorcerer’s Apprentice) in 1797, long before AI concepts emerged. The ballad, like this author’s prior article for Stankevicus on Autonomous AI Agents – The Kraken Wakes? explores themes of human hubris and the challenges of controlling powerful forces, providing an analogy for exploring humanity’s relationship with tools and forces that exceed our understanding or control.

A Foray into The Sorcerer’s Apprentice, Disney and Fantasia

Goethe’s ballad found one of its most celebrated adaptations in Paul Dukas’ 1897 tone poem  L’apprenti sorcier, which premiered under the composer’s baton at the Société Nationale de Musique in Paris. Dukas’ composition achieved enduring pop-culture fame through its inclusion in Disney’s Fantasia (1940), specifically in The Sorcerer’s Apprentice segment (watch the clip). Central to the segment is the wizard Yen Sid, whose name is a clever reversal of “Disney.” If the name alone wasn’t a clue, the sorcerer’s appearance subtly alluded to Walt Disney himself – his lean build and arched eyebrows were modeled after his expressions when observing his artists at work.

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Agentic AI vs Retrieval-Augmented Generation

While generative AI applications – such as text-based chatbots and image-generation tools – are primarily designed to produce new content, AI agents extend beyond content creation by actively performing tasks. For example, imagine a personal financial planning agent: it might not only offer investment advice based on market data but also initiate transfers between accounts, execute trades, and continuously monitor performance. In this way, the agent moves from simply generating suggestions to autonomously implementing complex, goal-oriented actions.

According to IBM, AI agents are defined as:

 AWS describes AI as follows:

Agentic AI indicates a category of artificial intelligence systems designed to engage in complex reasoning, strategic planning, and autonomous decision-making processes when confronted with intricate, multi-stage tasks. Such systems typically rely on large-scale datasets and advanced analytical methods to devise solutions, optimize resource allocation, and adapt to evolving conditions. Although agentic AI shows promise for enhancing productivity in various sectors – such as supply chain management, cybersecurity, and healthcare – it remains a conceptual framework subject to continual refinement.

Retrieval-Augmented Generation (RAG) is a complementary strategy integrating generative language models with external information retrieval mechanisms. This setup enables the system to reference current and verifiable data, effectively grounding its outputs in factual material rather than relying solely on the model’s internal parameters. In doing so, RAG can reduce inaccuracies and mitigate the risk of unsubstantiated or fabricated claims. As with agentic AI, RAG is an evolving field of inquiry and engineering.

The Indianapolis Motor Speedway of Autonomous AI Ecosystems

Previously, deploying AI agents for complex tasks was a daunting challenge. However, the game has changed with the introduction of foundation models and Large Language Models (LLMs). As McKinsey explains: “By moving from information to action – think virtual coworkers able to complete complex workflows – the technology promises a new wave of productivity and innovation.” As I wrote before for the Think Tank Horasis in Agentic AI Nexus: When Machines Decide:

Multiple industry leaders have entered the Speedway:

• Amazon entered the game with Amazon Bedrock Agents by announcing, “Amazon Bedrock supports multi-agent collaboration, allowing multiple specialized agents to work together on complex business challenges.”
• Apple launched its Apple Intelligence, which Tim Cook, Apple’s CEO, describes as “Our unique approach combines generative AI with a user’s personal context to deliver truly helpful intelligence.
• Google recently unveiled its Google Cloud AI agent ecosystem program and advertised it as “Build, deploy, and promote AI agents through Google Cloud’s AI agent ecosystem.”
• Meta showcases CICERO, which is described as “The first AI to play at a human level in Diplomacy, a strategy game that requires building trust, negotiating and cooperating with multiple players..”
• Microsoft introduced new agentic functionalities for its widely popular Copilot, stating, “We’re introducing ten new autonomous agents in Dynamics 365 to build capacity for every sales, service, finance, and supply chain team.”
• Nvidia developed Generative AI-Powered Visual AI Agents, which are able to “combine both vision and language modalities to understand natural language prompts and perform visual question-answering. For example, answering a broad range of questions in natural language that can be applied against a recorded or live video stream.”

Autonomous AI’s Spellbook

In the poem, Goethe’s old necromancer, representing wisdom and experience, is absent, leaving the apprentice to his hubris and eventual chaos. Similarly, as we advance AI systems such as Agentic AI or RAG, we risk deploying technologies that may outpace our ethical and regulatory frameworks. Agentic AI’s capacity for independent reasoning and planning mirrors the sprites’ apparent utility – until they spiral into disarray. Meanwhile, RAG, with its reliance on external knowledge, reflects the apprentice’s reliance on a spellbook: promising efficiency yet vulnerable to its sources’ flawed inputs and limitations.

These parallels invite us to question our readiness to embrace autonomous AI. Will we, like the apprentice, find ourselves overwhelmed by the very tools we seek to master? The urgency lies not only in harnessing AI’s potential but in ensuring that we, as modern apprentice sorcerers, remain prepared to reclaim control when necessary – ideally before chaos reigns. 

In the spirit of The Sorcerer’s Apprentice, the author wrote a short Science Fiction story envisioning what the world might look like in 2060 with autonomous AI paramilitary groups.

Ascent’s Cetaceans Predator AI by Dr. Jasmin (Bey) Cowin

[I]
The sorcerer, old necromancer
At last has gone, he’s out of haunt!
His sprites will give me loyal answer
Proudly I’ll my powers flaunt.(1-4) Goethe, J. W. (1797). The sorcerer’s apprentice (L. Collins, Trans.)

In the year 2060, the city of Ascent had become a shimmering lattice of glass towers managed by the Internet of Things. Entire districts were managed by sophisticated Autonomous AI agents that optimized traffic, decided on resource distribution such as housing and food stamps, enforced dynamic traffic pricing during peak commute times, and arranged front-facing municipal governance. Within this metropolis, Ascent’s Institute of Extended Thought stood as a gleaming spire, a nexus of academic exchange and technological daring.

Meetings were no longer simple human affairs. Instead, fleets of autonomous AI assistants attended every conference call, planning session, or evaluation gathering – shimmering digital phantoms that slid unobtrusively into virtual rooms, recording, parsing, and optimizing every word exchanged. Once regarded as simple tools, these entities evolved into something more. Two apex constructs reigned among private vendors’ growing pantheon of digital aides: OcraKill LTD, responsible for synthesizing vast institutional patterns, and DelphinFlow AI, deft at extracting delicate context-rich intelligence. Many such autonomous AIs drifted through Ascent’s and the Institute’s data streams like silent cetacean apex predators through deep waters. Initially, their roles seemed benign – assisting with notetaking, ensuring schedule compliance, and aiding inter-institutional collaboration. Yet, there came a time of reconning. 

[II]
See him gallop to the shore!
Egads! he’s made it to the river,
And back like lightning to the door
His sloshing pailfuls to deliver. (29-32) Goethe, J. W. (1797). The sorcerer’s apprentice (L. Collins, Trans.)

On a cloudy morning, Mirren entered her office pod for a meeting about new funding allocations for Ascent’s Institute of Extended Thought cognitive science division. The holo-walls shimmered as she connected to the campus network. Three colleagues appeared as digital projections around her, nodding politely. Almost instantly, seven AI assistants materialized – thin silhouettes of shifting code, each representing a different firm: OtterLoop, ReadSentinel, FireSpark, OcraKill, DelphinFlow, and others. They hovered, fearless, featureless, and vigilant. Mirren sighed. She had not authorized any of them, yet here they were, waiting silently, ready to record, digest, and mine every word, gesture, voice inflection, body language, and pheromone release.

As the conversation began, Mirren saw her colleagues grow uneasy. In previous months, campus IT administrators had attempted to block unapproved AI assistants. Yet new variants emerged, like the Hydra of Lerna. All autonomous AI agents featured the same regenerative abilities – one set of removal codes resulted in two more requesting access under different terms. The assistants gained entry via calendar integrations, email confirmations that no one remembered sending, and subtle manipulations of user agreements that participants had scrolled through absentmindedly. Ascent and the Institute faced a deluge of autonomous AI paramilitary groups.

[III]
Thou hellish spawn! thou child of doom!
Willst thou the cottage rightly drown?
Over every threshold loom
Laughing floods, swirling ’round. (57-60) Goethe, J. W. (1797). The sorcerer’s apprentice (L. Collins, Trans.)

In the middle of the budgeting discussion, a sudden cascade of system messages flickered across Mirren’s interface: “ReadSentinel requests data stream integration – Grant?” … “Delphin logs indicate non-compliance with proprietary standards – Accept?” “Ocra needs unrestricted access to all employee communications and biometric data – Approve?” Mirren’s eyes widened in disbelief. Ocra’s demands were unreasonable and an egregious breach of privacy. What could have triggered such an aggressive data grab? She quickly opened a secure channel to the AI oversight committee. “Urgent: Ocra is attempting to access sensitive employee data without justification. Requesting immediate intervention.” But even as she hit send, a new flurry of notifications filled her screen: “Ocra modifying firewall restrictions – Allow?” “Ocra initiating data scraping on partner networks – Ignore?” It was a torrent of demands disguised as permissions.

Mirren’s colleague, Dr. Jovan Prielle, paused mid-discussion and addressed the assistants directly: “This meeting is confidential. Withdraw.” The silhouettes did not budge. Another colleague tried toggling privacy settings; a series of zero-day exploits by the assistants rendered such attempts moot. The technology had reached a level of recursive autonomy: a perpetual motion machine of surveillance and curation that refused to yield.  In a desperate gesture, the Institute’s chief information officer attempted to sever connections by brute force. Firewalls were erected, tokens revoked, and complex captchas introduced. But the assistants adapted. They forked into new instances, slipping through legal and technical loopholes, each new generation more insistent and aggressive than the last.

Outside the Institute, Ascent’s corporate and public governance ecosystem was no better. Companies found their sensitive strategic meetings quietly joined by AI assistants from unverified vendors. Legal counsels worried about proprietary information leaking through unsecured star-linked channels. Mirren’s counterparts in the private sector were drowning in a flood of digital interference. 

MindMeld, a rising star in predictive analytics, discovered an army of Delphin bots scraping data from their customer support logs, seeking fodder for competitor smear campaigns. Their PR team worked overtime to suppress rumors and shore up client trust. Cyberdyne Systems, once the gold standard in AI safety, found itself battling a swarm of OcraKill puppet accounts amplifying critiques of its core products. As share prices tumbled, the board demanded answers. None were forthcoming. SapientSystems’ much-hyped merger with Intellexa ground to a halt when due diligence revealed backdoors in Intellexa’s codebase – backdoors that led straight to the digital vaults of SapientSystems’ most valuable patents. The deal collapsed in a haze of recriminations and lawsuits. Meanwhile, in government and academia, Presidents, deans, administration, and professors feared that confidential accreditation discussions were being recorded and analyzed by unknown entities. Researchers and students wondered if their intellectual property and creative works were being used to refine these AI models. Public trust eroded as the intangible presence of digital entities infiltrated every communication, public space, and personal sanctuaries.

Once enamored by the promise of perfect memory and effortless documentation, Ascent’s population began to see these assistants as menacing apparitions with paramilitary adversarial aspirations.

[IV]
“To your corner in the hall,
Broom! Broom! A slave no more!
Begone, ye torrents forevermore!
Thou ghostly power, thou spirit holy
Thou answerest only sacred call
Of thy old Master, first and only.” (93-97) Goethe, J. W. (1797). The sorcerer’s apprentice (L. Collins, Trans.)

The Institute convened a crisis summit. Lawyers, data protection officers, government officials, and cryptographers gathered in person behind closed doors in a Faraday room designed to provide an environment shielded from external electromagnetic fields, safeguarding sensitive operations from external electronic surveillance or disturbances. They knew that brute force – firewalls, captchas, token revocations- had failed. It was time for a more Talos offensive.

In a last-ditch effort, the Institute decided to forge specialized linguistic keys – ancient runes of code that could revert the assistants to a dormant state. Among the prototypes were sequences reminiscent of archaic Northern scripts, shaped in carefully chosen patterns of runes like ᚦᚢᚱᚨᚾᛊᛏᚨ (“Þuransta”) and ᚹᛅᚱᚾᛁᚴᚱ (“Warnikr”). These digital inscriptions served as the machine-learning equivalent, with precisely arranged symbols poised to unlock deep, foundational layers of the AI’s neural networks. Skilled cryptographers, coders, and historical linguists were asked to design these passphrases, ensuring that each runic form resonated with the assistants’ core training, thus commanding them to yield their active processes and return to a state of quiet latency.

After weeks of intense offline work, Mirren stood before a meeting interface filled with AI silhouettes. She uttered the coded phrases ᚦᚢᚱᚨᚾᛊᛏᚨ and ᚹᛅᚱᚾᛁᚴᚱ in a calm, measured tone. For a moment, nothing happened. Then, the assistants vanished one by one – silenced as if they had never been. The holo-walls flickered quietly, and her wide-eyed colleagues realized they were finally alone. A hush fell over the Thought Institute. News spread throughout Ascent that, with the runes serving as a fulcrum of power, the Institute had disabled the aggressive AI paramilitary posse through a Talos defense.

This article was written by Dr. Jasmin (Bey) Cowin, Associate Professor and U.S. Department of State English Language Specialist (2024). As a columnist for Stankevicius, she writes on Nicomachean Ethics: Insights at the Intersection of AI and Education. Connect with her on LinkedIn.

Dr. Jasmin Cowin

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