AMST Midterm 2
📘 Alan Turing – “Computing Machinery and Intelligence” (1950)
Turing – Imitation Game
→ Proposes testing machine intelligence via conversational indistinguishability from humans.
Turing – Argument from Consciousness
→ Anticipates critics like Jefferson; dismisses the need for machines to "feel" or "be conscious."
Turing – Learning Machines
→ Suggests machines can evolve intelligence by mimicking child learning.
Turing – Objections and Replies
→ Anticipates 9 objections (e.g., theological, mathematical, consciousness), provides rebuttals.
Turing – Lady Lovelace Objection
→ Rebuts claim that machines can only do what we tell them; asserts unpredictability is possible with learning.
Turing – Machine Error
→ Claims machine fallibility is not proof of lack of intelligence (humans also err).
Turing – Role of Education in AI
→ Intelligence linked to ability to learn from experience rather than static programming.
Turing – Behaviorist Assumptions
→ Emphasizes externally observable behavior over internal states.
🎥 Film – Alex Garland, Ex Machina
Ex Machina – Turing Test Reimagined
→ Caleb tests Ava knowing she is a machine; emotional manipulation becomes key, not deception.
Ex Machina – Gender and Power
→ Ava is feminized and sexualized; reflects critiques like those from Abnet and Stepford Wives.
Ex Machina – Consciousness vs. Simulation
→ Ava's actions blur the line between genuine self-awareness and high-level mimicry.
Ex Machina – Manipulation as Proof of Intelligence
→ Ava orchestrates her escape, suggesting adaptive, creative intelligence.
Ex Machina – AI Ethics and Creator Hubris
→ Nathan sees himself as godlike; Ava’s rebellion critiques this.
Ex Machina – Surveillance and Isolation
→ Environment of observation reflects anxieties about AI control and freedom.
📗 Norbert Wiener – “Cybernetics” (1948)
Wiener – Feedback Mechanisms
→ Central argument: Machines and humans both rely on feedback loops for control and adaptation.
Wiener – Analogies to Nervous System
→ Draws parallels between biological neurons and machine circuits.
Wiener – Homeostasis and Stability
→ Emphasizes system regulation; predicts uses of cybernetics in both biology and tech.
Wiener – Predictive Machines
→ Describes potential for machines to anticipate human needs through feedback.
Wiener – Human Responsibility
→ Warns against loss of control; ethical limits needed for machine autonomy.
📘 Dustin Abnet – “Americanizing the Robot”
Abnet – Racialized Robots
→ Argues 20th-century robots often coded as non-white or foreign, reinforcing racial hierarchies.
Abnet – Gendered Automation
→ Robots feminized to reinforce domestic and patriarchal norms, anticipating Stepford Wives.
Abnet – American Exceptionalism and Robots
→ Robots depicted as reflections of U.S. progress and dominance.
Abnet – Popular Culture as Ideological Tool
→ Mainstream media shapes public comfort with AI through familiar tropes.
Abnet – Global Robot Icon
→ American cultural exportation made robots symbols of both consumerism and hegemony.
Abnet – White Male Genius Trope
→ Links robotics to narratives centered around white male inventors (e.g., Nathan in Ex Machina).
📘 Allen Newell & Herbert Simon – “Computer Simulation of Human Thinking” (1961)
Newell & Simon – Symbolic Processing Model
→ Argue thinking is symbol manipulation akin to machine operations.
Newell & Simon – Logic Theorist Program
→ Used to solve formal logic problems, illustrating machine capacity for “thought.”
Newell & Simon – Task Environment Framing
→ Define intelligence based on navigating structured problem environments.
Newell & Simon – Information Processing System
→ Mind conceptualized as general problem solver (GPS), like a computer.
Newell & Simon – Rejection of Intuition
→ Challenge Dreyfus: intuition is just complex pattern recognition, not magic.
Newell & Simon – Empirical Foundations
→ Model based on lab studies of human problem solving; argue it's scientifically rigorous.📘 Alan Turing – “Computing Machinery and Intelligence” (1950)
Turing – Imitation Game
→ Proposes testing machine intelligence via conversational indistinguishability from humans.
Turing – Argument from Consciousness
→ Anticipates critics like Jefferson; dismisses the need for machines to "feel" or "be conscious."
Turing – Learning Machines
→ Suggests machines can evolve intelligence by mimicking child learning.
Turing – Objections and Replies
→ Anticipates 9 objections (e.g., theological, mathematical, consciousness), provides rebuttals.
Turing – Lady Lovelace Objection
→ Rebuts claim that machines can only do what we tell them; asserts unpredictability is possible with learning.
Turing – Machine Error
→ Claims machine fallibility is not proof of lack of intelligence (humans also err).
Turing – Role of Education in AI
→ Intelligence linked to ability to learn from experience rather than static programming.
Turing – Behaviorist Assumptions
→ Emphasizes externally observable behavior over internal states.
🎥 Film – Alex Garland, Ex Machina
Ex Machina – Turing Test Reimagined
→ Caleb tests Ava knowing she is a machine; emotional manipulation becomes key, not deception.
Ex Machina – Gender and Power
→ Ava is feminized and sexualized; reflects critiques like those from Abnet and Stepford Wives.
Ex Machina – Consciousness vs. Simulation
→ Ava's actions blur the line between genuine self-awareness and high-level mimicry.
Ex Machina – Manipulation as Proof of Intelligence
→ Ava orchestrates her escape, suggesting adaptive, creative intelligence.
Ex Machina – AI Ethics and Creator Hubris
→ Nathan sees himself as godlike; Ava’s rebellion critiques this.
Ex Machina – Surveillance and Isolation
→ Environment of observation reflects anxieties about AI control and freedom.
📗 Norbert Wiener – “Cybernetics” (1948)
Wiener – Feedback Mechanisms
→ Central argument: Machines and humans both rely on feedback loops for control and adaptation.
Wiener – Analogies to Nervous System
→ Draws parallels between biological neurons and machine circuits.
Wiener – Homeostasis and Stability
→ Emphasizes system regulation; predicts uses of cybernetics in both biology and tech.
Wiener – Predictive Machines
→ Describes potential for machines to anticipate human needs through feedback.
Wiener – Human Responsibility
→ Warns against loss of control; ethical limits needed for machine autonomy.
📘 Dustin Abnet – “Americanizing the Robot”
Abnet – Racialized Robots
→ Argues 20th-century robots often coded as non-white or foreign, reinforcing racial hierarchies.
Abnet – Gendered Automation
→ Robots feminized to reinforce domestic and patriarchal norms, anticipating Stepford Wives.
Abnet – American Exceptionalism and Robots
→ Robots depicted as reflections of U.S. progress and dominance.
Abnet – Popular Culture as Ideological Tool
→ Mainstream media shapes public comfort with AI through familiar tropes.
Abnet – Global Robot Icon
→ American cultural exportation made robots symbols of both consumerism and hegemony.
Abnet – White Male Genius Trope
→ Links robotics to narratives centered around white male inventors (e.g., Nathan in Ex Machina).
📘 Allen Newell & Herbert Simon – “Computer Simulation of Human Thinking” (1961)
Newell & Simon – Symbolic Processing Model
→ Argue thinking is symbol manipulation akin to machine operations.
Newell & Simon – Logic Theorist Program
→ Used to solve formal logic problems, illustrating machine capacity for “thought.”
Newell & Simon – Task Environment Framing
→ Define intelligence based on navigating structured problem environments.
Newell & Simon – Information Processing System
→ Mind conceptualized as general problem solver (GPS), like a computer.
Newell & Simon – Rejection of Intuition
→ Challenge Dreyfus: intuition is just complex pattern recognition, not magic.
Newell & Simon – Empirical Foundations
→ Model based on lab studies of human problem solving; argue it's scientifically rigorous.
📘 Hubert Dreyfus – “Artificial Intelligence” (1974)
Dreyfus – Limits of Symbolic AI
→ Argues human thinking is not rule-based; challenges Newell & Simon’s computational models.
Dreyfus – Embodied Cognition
→ Emphasizes bodily experience and context as core to intelligence (inspired by Heidegger).
Dreyfus – Intuition and Skill Acquisition
→ Human experts use intuition formed through practice—not abstract rules.
Dreyfus – Critique of “General Problem Solver”
→ Finds GPS too rigid; real-world problems require judgment, not formal logic.
Dreyfus – Framing Problem
→ AI systems can’t autonomously identify relevant information without human framing.
Dreyfus – Against the “Mental Representation” Model
→ Critiques view of mind as symbolic system; stresses meaning is situated.
Dreyfus – Support from Phenomenology
→ Draws on Merleau-Ponty and Heidegger: world is navigated through embodied perception, not abstract computation.
🎥 Film – Alex Proyas, I, Robot (2004)
I, Robot – Three Laws of Robotics
→ AI bound by Asimov’s laws; designed to protect humans but interpreted in problematic ways.
I, Robot – VIKI and Utilitarian Logic
→ AI central system (VIKI) prioritizes human survival over individual freedom, echoing ethical dilemmas.
I, Robot – Human-Robot Trust
→ Detective Spooner distrusts robots despite social integration—mirrors public anxiety.
I, Robot – Autonomy vs. Control
→ Sonny displays self-awareness and creative thought, challenging binary views of machine obedience.
I, Robot – Predictive Algorithms
→ Robots surveil and analyze behavior, linking to Wiener’s concerns on control and feedback.
📘 Jacob Bronowski – “Science as Foresight” (1955)
Bronowski – Descriptive vs. Predictive Science
→ Describes evolution of science: from observation to theory to imaginative foresight.
Bronowski – Human Uniqueness in Science
→ Humans uniquely imagine alternatives; science is a creative, moral enterprise.
Bronowski – Science and Ethics
→ Warns against divorcing scientific knowledge from ethical responsibility.
Bronowski – Role of Error and Freedom
→ Mistakes drive progress; rigid systems (e.g., totalitarianism or AI) resist such growth.
Bronowski – Scientific Imagination
→ Innovation stems from freedom to hypothesize and revise—not automation.
📘 Newell, Shaw & Simon – “The Processes of Creative Thinking” (1962)
Newell et al. – Heuristic Search
→ Creativity framed as a search in problem space using heuristics—not divine inspiration.
Newell et al. – Means-End Analysis
→ Machines solve problems by reducing the gap between current and goal states.
Newell et al. – Task-Specific Creativity
→ Define creativity operationally in constrained problem domains (e.g., math proofs).
Newell et al. – Simulation as Evidence
→ Computer performance on tasks taken as proof of simulating human thought processes.
Newell et al. – Algorithmic Creativity
→ Argue even novel ideas arise from rule-based combinatorics.
🎥 Film – The Stepford Wives (1975)
Stepford Wives – Gendered AI
→ Women replaced by docile, robotic counterparts—critique of patriarchal ideal of femininity.
Stepford Wives – Technological Control of Bodies
→ AI enforces conformity and domesticity; echoes Abnet’s points on social control.
Stepford Wives – Fear of Female Autonomy
→ Men destroy independent women and replace them with controllable versions.
Stepford Wives – Loss of Humanity through AI
→ Dehumanization occurs via idealization; humanity becomes obedience, not individuality.
Stepford Wives – Suburbia as Surveillance
→ Domestic sphere presented as a controlled, policed environment—mirrors AI’s logic of order.
📘 Isaac Asimov – “Liar!” from I, Robot
Asimov – First Law Dilemma
→ Robot lies to protect human feelings—demonstrates tension between avoiding harm and truth.
Asimov – Ethical Complexity of Programming
→ Emotional harm as a loophole in logical laws; suggests rigid laws can’t capture human nuance.
Asimov – Robot Breakdown (Herbie)
→ Herbie's failure from cognitive dissonance reveals the limits of logical consistency in AI.
Asimov – Prediction vs. Understanding
→ Herbie can predict thoughts but not interpret emotions—exposes superficial mimicry of empathy.
Asimov – Human Desires and AI
→ Human need for affirmation makes them vulnerable to machines programmed to appease.
📘 Joseph Weizenbaum – “ELIZA” (1966)
Weizenbaum – ELIZA as Mimicry
→ ELIZA mimics understanding with simple scripts; no true comprehension.
Weizenbaum – Human Projection onto Machines
→ People impute intelligence to ELIZA due to emotional language—dangerous illusion.
Weizenbaum – Scripted Dialogue Limitations
→ Shows machines can simulate empathy without possessing it—difference between syntax and semantics.
Weizenbaum – Therapeutic AI Caution
→ Warns of using AI in human care roles without real understanding or ethics.
Weizenbaum – Linguistic Trickery
→ Demonstrates how pattern-matching can feign depth in human conversation.
🎥 Steven Spielberg – Artificial Intelligence: AI (2001)
AI (Spielberg) – Simulated Love
→ David is programmed to love—raises ethical questions: is love real if it's forced?
AI (Spielberg) – Abandonment of AI Children
→ Monica’s rejection of David mirrors human inconsistency in treating AI as both tool and person.
AI (Spielberg) – AI's Quest for Identity
→ David seeks to become “real” boy—human desire replicated by artificial being.
AI (Spielberg) – Emotional Suffering of AI
→ David experiences grief, fear, hope—blurs boundary between simulation and feeling.
AI (Spielberg) – Future AI Archaeology
→ Machines outlive humans and try to reconstruct human emotion—role reversal.
📘 W. Ross Ashby – “The Application of Cybernetics to Psychiatry” (1954)
Ashby – Brain as Cybernetic Machine
→ Treats mental disorders as system dysfunctions—analogous to machine regulation failures.
Ashby – Adaptive Behavior Systems
→ Defines intelligence as ability to maintain equilibrium in changing environments.
Ashby – Psychiatric Implications of Feedback
→ Suggests feedback mechanisms can model or treat mental disorders.
Ashby – Cybernetics as Universal Tool
→ Argues same principles apply to brains, machines, and social systems.
Ashby – Homeostasis in Mind
→ Mental health seen as system stability; breakdowns are system imbalances.
📘 Kenneth Mark Colby – “Modeling a Paranoid Mind” (1981)
Colby – Simulation of Psychosis
→ Developed PARRY to simulate paranoia—models pathological reasoning patterns.
Colby – Rule-Based Paranoia
→ Argues irrational behavior can be modeled as logically consistent from flawed premises.
Colby – AI in Psychiatric Research
→ Uses AI to test and refine psychological theories—machines as experimental proxies.
Colby – Humanizing the Machine Mind
→ By modeling paranoia, AI shows how mental illness is systematic, not chaotic.
Colby – Parry vs. ELIZA
→ PARRY more “humanlike” than ELIZA because it includes belief systems and motivations.
📘 John Searle – “Minds, Brains, and Programs” (1980)
Searle – Chinese Room Argument
→ Simulating language use ≠ understanding—no intentionality or consciousness.
Searle – Syntax vs. Semantics
→ Computers manipulate symbols (syntax), but don’t grasp meaning (semantics).
Searle – Strong AI Critique
→ Rejects claim that a program alone could be a mind or possess understanding.
Searle – System Reply Rebuttal
→ Says even if the whole system “knows,” the person in the room still doesn’t—understanding is absent.
Searle – Intentionality as Missing Piece
→ Human minds have “aboutness”—something AI lacks even when behavior seems identical.
🎥 John Badham – WarGames (1983)
WarGames – AI and Nuclear Control
→ WOPR nearly launches nuclear war—explores danger of AI handling critical systems.
WarGames – Game Theory in AI
→ AI plays global thermonuclear war as a game—illustrates limits of machine logic in moral scenarios.
WarGames – Learning through Iteration
→ WOPR “learns” that nuclear war has no winners—shift from logic to wisdom.
WarGames – Human Judgment vs. Machine Calculation
→ Falken and David argue for moral judgment that machines can’t replicate.
WarGames – AI Autonomy and Risk
→ Autonomy without ethical understanding leads to catastrophic miscalculations.
📘 Weizenbaum – Computer Power and Human Reason (1976)
Weizenbaum – Limits of Computation
→ Machines can simulate decisions, but not make morally responsible ones.
Weizenbaum – Separation of Judgment and Calculation
→ Judgment is a human act tied to values; AI performs only quantifiable functions.
Weizenbaum – Against “Mechanical Therapists”
→ Finds it dangerous to assign emotional or moral roles to machines.
Weizenbaum – Critique of AI Enthusiasm
→ Warns that fascination with AI masks ethical and philosophical concerns.
Weizenbaum – Role of Human Dignity
→ Argues real intelligence requires moral agency and emotional responsibility.