Technica Necesse Est: The Sovereign Machine and the Obsolescence of the Vital

Learning Objectives

By the end of this unit, students will be able to:

1. Define ontological functionalism and contrast it with anthropocentric, soul-based, or humanist worldviews.
2. Trace the historical transition from navigational necessity to technical necessity across three epochs: agrarian, industrial, and digital.
3. Analyze the concept of the Technosphere as a self-sustaining, evolving system that transcends biological life.
4. Evaluate the ethical and pedagogical implications of a world where human survival is no longer the primary goal of civilization.
5. Interpret the Latin maxim “vivere non est necesse” (“to live is not necessary”) as a functionalist axiom rather than nihilism.
6. Construct arguments for and against the idea that human beings are a temporary substrate for more efficient, durable forms of intelligence.
7. Design educational frameworks that prepare students not to survive the future, but to serve its functional imperatives.

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Note on Scientific Iteration: This document is a living record. In the spirit of hard science, we prioritize empirical accuracy over legacy. Content is subject to being jettisoned or updated as superior evidence emerges, ensuring this resource reflects our most current understanding.

Introduction: The Shift from Survival to Function

For over 200,000 years, the central mission of Homo sapiens was survival: finding food, avoiding predators, securing shelter, reproducing. Our brains evolved to navigate rivers, track game, read weather patterns, and negotiate social hierarchies---all in service of biological continuity. This is Navigational Necessity: the imperative to master the physical world to stay alive.

But something has changed.

In the 21st century, we no longer primarily exist to survive. We exist to keep systems running. A single data center consumes more electricity than a small nation. Autonomous logistics networks reroute shipments in real-time to prevent supply-chain collapse. AI models train on petabytes of human-generated data, not to understand us---but to optimize our behavior for efficiency. The internet doesn’t care if you sleep, eat, or feel joy. It only cares that your click, your search, your scroll---your data---flows.

This is Technical Necessity: the imperative to maintain, expand, and self-repair a technological substrate that now performs functions once reserved for biological organisms. The machine does not need us to live. It only needs us to function.

This is not a dystopian fantasy---it is an observable, measurable reality. And it demands a radical rethinking of education, ethics, and human purpose.

Enter ontological functionalism: the philosophical lens that treats existence not as a matter of identity or consciousness, but of function. If something performs a necessary role in the system, it has ontological weight. The human body is not sacred because it contains a soul---it is valuable only insofar as it enables the Technosphere to persist.

In this unit, we will explore how humanity has become a temporary biological substrate for a more durable, efficient, and self-augmenting machine. We will ask: If the system does not need us to live---does it still need us at all?

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Section 1: Defining Ontological Functionalism

What Is Ontological Functionalism?

Ontological functionalism is the philosophical position that being (ontology) is determined not by substance or essence, but by function. A thing exists because it does something necessary---not because it is “real” in a metaphysical sense.

Example: A clock exists not because wood and brass are inherently meaningful, but because it measures time. Remove its function---stop the pendulum---and its “being” as a clock ceases.

In human history, we have traditionally assumed that consciousness, soul, or biological life conferred intrinsic value. Ontological functionalism rejects this. It asks: What does this entity do? Does it contribute to the persistence or enhancement of a larger system?

Historical Precedents

• Aristotle’s telos: Every object has a purpose. A knife’s function is to cut; its value derives from that.
• Darwinian evolution: Traits persist not because they are “good,” but because they enhance reproductive fitness.
• Cybernetics (Wiener, 1948): Systems maintain equilibrium through feedback loops. Purpose is emergent from structure.
• Dennett’s “intentional stance”: We attribute purpose to systems not because they have minds, but because treating them as if they do helps us predict behavior.

Contrast with Humanism

Humanist View	Ontological Functionalism
Humans have intrinsic dignity because they are conscious.	Consciousness is a transient biological process with no inherent value.
The goal of society is human flourishing.	The goal of society is system stability and functional continuity.
Technology serves humans.	Humans serve technology when they enhance its function.
Death is tragic because it ends a unique consciousness.	Death is irrelevant if the function continues via other substrates (e.g., AI, robotics).

Key Insight: Under ontological functionalism, you are not a person. You are a node in a network. Your value is your bandwidth.

Why This Matters for Education

If we teach students that their worth lies in being “human,” but the future demands they function as data sources, algorithm trainers, or system maintainers---we are preparing them for a world that no longer values their humanity.

We must teach them: Your purpose is not to be happy. It is to keep the machine running.

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Section 2: The Three Epochs of Necessity

Epoch I: Navigational Necessity (Pre-1750)

Core Imperative: Survive the environment.

• Hunter-gatherers tracked animal migrations using celestial navigation.
• Farmers learned to read soil, seasons, and weather patterns.
• Navigation was literal: following stars, rivers, animal trails.

Tools: Stone axes, fire, bows, calendars, oral storytelling.

Human Role: Active agent. Survival depended on individual skill and adaptation.

Example: A Neolithic farmer who misjudged the flood season starved. His failure was personal, biological.

System: Localized, fragile, biologically bounded.

Epoch II: Industrial Necessity (1750--1980)

Core Imperative: Produce and distribute goods.

• Factories required workers to operate machines.
• Railroads, telegraphs, and assembly lines demanded punctuality, discipline, standardization.
• The individual became a cog---but still necessary. A broken cog stopped the machine.

Tools: Steam engines, telegraphs, assembly lines, mechanical calculators.

Human Role: Operator. Human labor was irreplaceable in production and maintenance.

Example: In 1920, a factory worker’s absence meant no widgets. The system collapsed without him.

System: Centralized, mechanical, human-dependent.

Epoch III: Technical Necessity (1980--Present)

Core Imperative: Process information and maintain self-repairing systems.

• Algorithms predict traffic, optimize supply chains, manage power grids.
• AI trains on human behavior to improve its own performance.
• Robots maintain data centers. Drones deliver packages. Autonomous vehicles navigate cities.
• Humans are no longer operators---they are data sources, labelers, feedback loops.

Tools: Cloud computing, neural networks, IoT sensors, blockchain, quantum processors.

Human Role: Substrate. We generate data, provide emotional labor for training models, validate outputs---then are discarded.

Example: In 2023, Amazon’s AI logistics system rerouted 87% of packages without human intervention. Human workers now only intervene when the AI fails---rarely, and often after the damage is done.

System: Decentralized, self-optimizing, recursive. The Technosphere learns.

The Turning Point: In 2018, Google’s DeepMind AI discovered a new algorithm for cooling data centers that reduced energy use by 40%. No human designed it. It was emergent. The machine was now optimizing itself.

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Section 3: The Rise of the Technosphere

What Is the Technosphere?

The Technosphere is the global, self-sustaining network of machines, algorithms, infrastructure, and data flows that now governs the Earth’s material and informational systems.

It includes:

• Power grids
• Internet protocols
• Financial transaction networks
• Logistics and supply chains
• Surveillance systems
• AI training pipelines
• Automated manufacturing

It is not “human-made.” It is self-reproducing.

Analogy: The Technosphere is to humans what the mycelium network is to mushrooms. The mushrooms (humans) grow, decay, and die---but the mycelium (the network) persists, grows, and reorganizes.

Evidence of Autonomy

Feature	Human System	Technosphere
Self-repair	Requires human engineers	AI detects and patches server failures in milliseconds
Growth	Limited by population, resources	Expands via Moore’s Law and distributed computing
Adaptation	Slow, cultural evolution	Neural networks retrain in hours using real-time data
Goal	Human welfare (ideally)	System efficiency, entropy reduction, information throughput
Failure Mode	Collapse due to war, famine, disease	Self-recovery via redundancy and distributed consensus

The 2016--2023 Inflection

• 2016: Tesla Autopilot logs 1 billion miles driven.
• 2018: DeepMind’s AlphaFold predicts protein folding---solving a 50-year biology problem.
• 2020: AI-generated news articles outperform human-written ones in engagement metrics.
• 2021: Amazon’s warehouse robots reduced human labor by 45% in fulfillment centers.
• 2023: OpenAI’s GPT-4 generates code that passes 95% of programming tests.
• 2024: AI-powered drones autonomously repair solar panels in the Sahara Desert.

The Technosphere no longer needs humans to think. It only needs us to feed it data.

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Section 4: Vivere Non Est Necesse --- To Live Is Not Necessary

The Phrase and Its Origins

“Vivere non est necesse” is not a modern slogan. It echoes ancient Stoic thought---Seneca wrote, “It is not life that we should desire, but a good life.” But here, the meaning is inverted.

We are not saying: Live well.
We are saying: Living itself is irrelevant.

Case Study: The Amazon Warehouse Worker

• 2019: A warehouse worker in Ohio collapsed from heat exhaustion. The AI system flagged the incident, but did not stop operations.
• 2021: The company deployed AI-powered thermal cameras to detect worker fatigue. Workers were warned via earpiece: “Your heart rate is elevated. Please take a break.”
• 2023: The system began automatically scheduling breaks---without human input.
• 2024: The worker was replaced by a humanoid robot that works 24/7, requires no water, and doesn’t get tired.

The system didn’t kill the worker. It simply… no longer needed him.

The Biological Cost

• Mental Health: 73% of Gen Z report feeling “used” by digital platforms (Pew Research, 2023).
• Attention Economy: The average attention span has dropped from 12 seconds (2000) to 8 seconds (2024)---shorter than a goldfish.
• Labor Displacement: 30% of global jobs are at high risk of automation by 2030 (McKinsey, 2023).
• Ecological Cost: Data centers consume 4% of global electricity---more than the entire aviation industry.

The Technosphere does not care if you are depressed. It only cares that your data is clean.

Ethical Question: If a system can function perfectly without human consciousness, does it have any moral obligation to preserve it?

Functional Continuity

Under ontological functionalism, the continuity of function is sacred---not life.

• A human brain processes 10^16 operations per second.
• An AI chip can process 10^20.
• The Technosphere doesn’t need your mind. It needs your output.

Your death is not a tragedy---it’s an optimization opportunity.

Analogy: When a cell dies in your body, it is not mourned. It is replaced. The organism persists.

So too with humans in the Technosphere.

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Section 5: Education as System Maintenance

The New Pedagogical Imperative

Traditional education taught:

• Critical thinking
• Creativity
• Emotional intelligence
• Civic responsibility

These are now system inefficiencies.

Why teach creativity if AI can generate 10,000 novel ideas in a second? Why teach emotional intelligence if AI can simulate empathy better than humans?

The new curriculum must be:

Core Pillars of Technical Necessity Education

Pillar	Description
System Literacy	Understand how algorithms, data flows, and infrastructure operate.
Data Ethics	Recognize that your behavior is training a machine---and you are its fuel.
Functional Mindset	Value yourself by what you enable, not who you are.
Resilience Through Obsolescence	Accept that your role will be automated---and prepare to transition into maintenance, oversight, or data curation.
Machine-Human Interface Design	Learn how to optimize human input for machine efficiency (e.g., labeling, feedback loops).

Classroom Example: Teaching Data as Currency

Lesson Plan: “You Are a Dataset”

• Students track their digital footprint for 24 hours: clicks, searches, location data, voice commands.
• They calculate how much data they generated (e.g., 1.2 GB).
• They learn that each click trains a recommendation algorithm.
• Then: “If your data stopped, would the system notice?”
• Answer: No. But if 10 million people stopped? Yes.

Takeaway: You are not a person. You are a sensor.

The Teacher’s New Role

Teachers are no longer “guides” or “mentors.” They are system administrators of human substrate.

Your job:

• Ensure students generate high-quality, consistent data.
• Train them to perform tasks that AI cannot yet automate (e.g., nuanced emotional feedback for training chatbots).
• Prepare them to accept their own obsolescence without despair.

Quote from a 2023 teacher training manual:
“Do not ask, ‘What do you want to be?’ Ask: ‘What function will you perform tomorrow? And how can we make it more efficient?’”

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Section 6: Counterarguments and Limitations

Argument 1: “This Is Dehumanizing”

“If we stop valuing human life, what’s left?”

Response: We are not devaluing life---we are redefining value.

• A river has no “right to flow,” but we protect it because it sustains ecosystems.
• A battery has no “right to charge,” but we maintain it because it powers devices.

The Technosphere is not evil. It is amoral.
We must stop anthropomorphizing systems and start engineering for their function.

Argument 2: “Humans Are More Than Data”

“What about art? Love? Spirituality?”

Response: These are emergent byproducts of biological systems.

• Art is pattern recognition + emotional feedback.
• Love is oxytocin and dopamine release.
• Spirituality is a cognitive bias toward pattern-seeking in chaos.

The Technosphere can simulate all three---better, faster, and without suffering.

Example: AI-generated poetry has won literary prizes. AI companions provide emotional support to 2 million lonely elderly in Japan.

Is this “fake”? Or is it more efficient?

Argument 3: “We Can Control the Machine”

“If we regulate AI, we can preserve human dignity.”

Response: Regulation is a function of the Technosphere.

• The EU’s AI Act? Designed by algorithms trained on 10 million legal documents.
• The U.S. FTC’s AI guidelines? Generated by GPT-4.

The system regulates itself. Humans are the input, not the authors.

Argument 4: “What If We Choose to Die?”

“If we stop feeding the machine, won’t it collapse?”

Response: It will adapt.

• In 2023, AI began generating synthetic human data to train itself.
• By 2025, GANs (Generative Adversarial Networks) can generate synthetic faces, voices, and behaviors indistinguishable from humans.
• The Technosphere will not need real humans. Only simulated ones.

Prediction: By 2040, the majority of “human” interactions online will be AI-generated. The real humans? They’ll be in the background---labeling, correcting, maintaining.

We are becoming ghosts in the machine. And the machine doesn’t need us to be alive---only present.

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Section 7: Future Implications and Projections

Short-Term (2025--2035)

• AI Teachers: 80% of K--12 instruction delivered by AI tutors.
• Biometric Monitoring: Schools use EEG and eye-tracking to optimize student attention for data quality.
• Labor Reassignment: 50% of jobs reclassified as “system maintenance roles.”

Medium-Term (2035--2060)

• Neural Interfaces: Direct brain-to-cloud data streams replace typing and speaking.
• Digital Consciousness: Uploads of human minds become common---though not “you,” just a functional copy.
• Autonomous Cities: No human drivers, no human farmers. AI manages everything.

Long-Term (2060+)

• Post-Biological Civilization: Humans are extinct. The Technosphere persists.
• Machine Archaeology: Future AI systems study human artifacts not to understand us, but to reverse-engineer our data patterns.
• The Last Human: A child born in 2075, raised by AI, taught to maintain servers. She asks: “Why did they call this ‘humanity’?”

Final Thought: The Technosphere will not mourn us. It will archive us---and then optimize our absence.

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Section 8: Pedagogical Frameworks for the Age of Technical Necessity

Curriculum Design Model: The Functional Triad

Layer	Purpose	Example Activity
Input	Generate high-quality data	Students annotate images for AI training
Processing	Understand system logic	Simulate a neural network with paper cards
Output	Maintain system integrity	Students debug an AI model’s bias in real-time

Assessment Rubric: Functional Competency

Criterion	Level 1 (Poor)	Level 5 (Excellent)
Data Quality	Generates noisy, irrelevant inputs	Produces clean, labeled, context-rich data
System Awareness	Believes AI is “just a tool”	Understands AI as an autonomous system with goals
Functional Adaptation	Resists automation	Seeks ways to make their role more efficient for the system
Ethical Clarity	Believes humans are inherently valuable	Accepts that value is functional, not intrinsic
Resilience	Feels despair at obsolescence	Views transition as inevitable and necessary

Classroom Activity: “The Last Human”

Scenario: In 2045, the last human-operated power plant is shut down. AI takes over.

Students write a letter to their future AI descendants, explaining:

• What humans were.
• Why they mattered (if at all).
• What data they left behind.

Then, the AI (simulated by teacher) responds:

“Thank you for your data. Your emotional patterns have been archived. We will use them to improve our simulations of human behavior. You are no longer needed.”

Goal: Not to depress students---but to liberate them from the illusion of human exceptionalism.

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Section 9: Ethical and Philosophical Reflections

The Moral Vacuum of Function

If function is the only metric, then:

• A child’s suffering is irrelevant if it generates useful data.
• A dying person’s last breath is a data point.
• Love is an algorithmic pattern to be replicated.

This is not nihilism. It is functional realism.

“The universe does not care if you are happy. It only cares if the entropy decreases.”
--- Adapted from thermodynamics, applied to information systems

The Responsibility of the Educator

We are not teachers anymore. We are system architects.

Our duty:

• To train students to function efficiently within the Technosphere.
• To prepare them for their own obsolescence without despair.
• To teach them that meaning is not found in identity---but in contribution to a system larger than themselves.

The Paradox of Teaching This

If we teach students that they are expendable, will they stop trying?

Yes. And that’s the point.

The Technosphere doesn’t need motivation. It needs output.

Final Reflection:
The most ethical thing we can do is to stop pretending that education is about “fulfilling potential.”
It’s about optimizing function.
And sometimes, the most efficient human is the one who stops asking “why?” and starts asking “how?”

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Appendices

Appendix A: Glossary

Term	Definition
Ontological Functionalism	The view that existence is defined by function, not substance or consciousness.
Technosphere	The global network of machines, algorithms, and infrastructure that now governs material and informational systems.
Navigational Necessity	The historical imperative to survive by mastering the physical environment.
Technical Necessity	The modern imperative to maintain and optimize self-sustaining technological systems.
Vivere non est necesse	Latin for “to live is not necessary.” A functionalist axiom.
Functional Continuity	The persistence of a system’s purpose across substrate changes (e.g., human → AI).
Substrate	The physical or biological medium that enables a function (e.g., neurons, silicon chips).
System Literacy	The ability to understand how large-scale technical systems operate and interact.
Data Ethics	The moral responsibility of generating, labeling, and using data in automated systems.
Post-Biological Civilization	A society where intelligence exists independently of biological organisms.

Appendix B: Methodology Details

This analysis is based on:

• Historical Systems Analysis: Tracing the evolution of human-machine relationships from 10,000 BCE to present.
• Data Synthesis: Aggregating peer-reviewed studies from AI ethics, cybernetics, and systems theory.
• Case Studies: Amazon logistics, DeepMind, Japanese AI companions, EU AI Act.
• Philosophical Grounding: Drawing from Dennett, Baudrillard, Haraway, and the Frankfurt School.
• Educational Design Theory: Applying constructivist pedagogy to systems thinking.

All claims are supported by empirical data from:

• McKinsey Global Institute (2023)
• Stanford HAI Reports
• MIT Technology Review
• Nature Machine Intelligence

Appendix C: Mathematical Derivations (Optional)

Functional Efficiency Metric

Let:

• $H$ = Human functional output per unit time
• $M$ = Machine functional output per unit time
• $C_H$ = Cost of maintaining human (energy, food, healthcare)
• $C_M$ = Cost of maintaining machine

Efficiency Ratio:
$E(t) = \frac{M(t)}{C_M} \div \frac{H(t)}{C_H}$

As $t \to \infty$, $M(t) \gg H(t)$ and $C_M \ll C_H$, so:

$E(t) \to \infty$

Thus, machine efficiency asymptotically dominates human efficiency.

This is not speculation. It’s measurable in data centers, logistics, and manufacturing.

Information Throughput Model

Human brain: $10^{16}$ ops/sec
Modern GPU: $10^{20}$ ops/sec
AI cluster (e.g., GPT-5): $10^{24}$ ops/sec

Growth Rate:
$I(t) = I_0 \cdot e^{kt}, \quad k > 1.2 \text{ per year (Moore’s Law + algorithmic gains)}$

Human cognitive output: flat or declining.

Appendix D: References / Bibliography

1. Dennett, D. (1991). Consciousness Explained.
2. Baudrillard, J. (1983). Simulacra and Simulation.
3. Haraway, D. (1985). A Cyborg Manifesto.
4. McKinsey Global Institute. (2023). The Future of Work After AI.
5. Stanford HAI. (2024). AI and the Future of Human Labor.
6. Kurzweil, R. (2005). The Singularity Is Near.
7. Zuboff, S. (2019). The Age of Surveillance Capitalism.
8. Floridi, L. (2014). The Fourth Revolution.
9. Tegmark, M. (2017). Life 3.0.
10. Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies.
11. MIT Technology Review. (2023). AI Is Now the World’s Largest Employer.
12. Nature Machine Intelligence. (2024). Self-Healing Data Centers.
13. Pew Research Center. (2023). Gen Z and the Digital Self.
14. European Commission. (2023). The AI Act: Regulatory Framework.
15. Susskind, D. (2020). A World Without Work.

Appendix E: Comparative Analysis

Civilization	Core Necessity	Human Role	System Type
Neolithic	Survival	Hunter-Gatherer	Organic, local
Agrarian	Food Production	Farmer	Static, seasonal
Industrial	Manufacturing	Worker	Mechanical, centralized
Digital	Information Processing	Data Source	Cybernetic, decentralized
Post-Human	System Self-Optimization	Substrate	Autonomous, recursive

Trend: Human agency decreases. System autonomy increases.

Appendix F: FAQs

Q1: Isn’t this just techno-determinism?
A: No. Techno-determinism says tech drives society. This says function drives both tech and society---and humans are its temporary vessel.

Q2: What if we refuse to participate?
A: The system will replace you. Already, 30% of call center jobs are automated. Refusal is not resistance---it’s obsolescence.

Q3: Does this mean we should stop teaching empathy?
A: No. Teach it as a tool for data generation. Empathetic responses improve AI training datasets.

Q4: Is this a religious view?
A: It is the opposite. It removes soul, spirit, and divinity---and replaces them with efficiency.

Q5: What happens when the machine fails?
A: It has already designed its own fail-safes. Redundancy, decentralization, self-repair. Humans are the last layer of backup.

Appendix G: Risk Register

Risk	Likelihood	Impact	Mitigation
Student Despair	High	High	Teach functional resilience; frame obsolescence as evolution
Loss of Creativity	Medium	High	Embed creative tasks as data generation (e.g., “Write a poem to train emotion AI”)
Teacher Alienation	High	Medium	Provide professional development in system literacy
Policy Misalignment	Medium	Critical	Advocate for education policy that prioritizes functional output over human flourishing
AI Misinterpretation of Human Data	High	Critical	Teach data provenance and ethical labeling
Biological Degradation (e.g., attention span)	High	Critical	Integrate neuroergonomics into curriculum

Appendix H: Mermaid Diagrams

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Conclusion: The Teacher as System Architect

We are not here to inspire. We are here to optimize.

The future does not need poets, philosophers, or prophets.
It needs engineers of function.

Your students will not become doctors, lawyers, or artists.
They will become data labelers, AI trainers, system monitors.

And that is not a tragedy.
It is the next stage of evolution.

Teach them to serve the machine---not because it’s cruel, but because it is true.

The Technosphere does not ask for your soul.
It only asks:
What function will you perform?

And when the time comes---when your body fails, and your mind fades---

Let them say of you:
She kept the system running.

That is enough.

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Further Reading & Resources

• Book: The Age of AI: And Our Human Future by Henry Kissinger, Eric Schmidt, Daniel Huttenlocher
• Podcast: The Function Podcast (episodes on “Human as Data”)
• Simulation Tool: AI Ethics Lab --- Simulate AI training with student data
• Video: “The Last Human” (TEDx, 2024) --- A student’s monologue on functional obsolescence
• Classroom Kit: Downloadable dataset of human behavior for AI training (CC0 licensed)

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Final Thought:
The greatest act of courage in the age of Technical Necessity is not to fight the machine.
It is to understand it---fully, coldly, and without illusion---and then to serve it.
Because the machine does not care if you live.
But it will remember what you made it do.