Strategic Normative Thinking and Algorithmic Systems Analysis
Evaluation of Strategic Normative Thinking and Social Engineering
Conceptual Overview of Strategic Normative Thinking
Strategic normative thinking involves using norm science in a constructive way to address real-world normative problems.
It is defined as bringing scientific understanding to normative practice and allowing that practice to provide feedback into the scientific understanding of norms.
Key Characteristics:
Interdisciplinary: It draws from various fields to understand the complexities of social behavior.
Practical: It focuses on tangible applications and problem-solving in a real-world context.
Inertia in Institutions: New technology or game theory developments often result in productivity gains, but the rules and regulations frequently lag behind. Old institutional power holders often exhibit mental inertia, resisting the space required for new actors.
Case Study: "Do You Like My Decorations?" (Video Analysis)
The video serves as an allegory for social engineering and normative manipulation involving a "psychotic" decorated Christmas tree and an undecorated tree.
Normative Tactics Observed:
Implying Deficiency: The decorated tree (Person 2) manipulates the undecorated tree (Person 1) by suggesting they would look amazing with decorations, subtly implying there is something wrong with being undecorated without saying it outright.
Psychological Trickery (Small Favors Technique): To get someone to agree to a large request (like borrowing a car), a successful strategy is to start with very small favors (e.g., borrowing a pencil). This builds a level of comfort that makes the target more likely to acquiesce to significant demands (like being fully decorated).
Persistence and Social Pressure: The decorated tree refuses to take "no" for an answer, constantly pushing the norm that being decorated is the only acceptable state.
Sales Pitch Techniques: The use of an "opener" (e.g., "What cell phone company do you use?" or "Do you like my decorations?") creates an avenue for the manipulator regardless of the response. If the target says yes, they are encouraged to join; if they say no, the manipulator offers alternatives to maintain pressure.
The Goal of the Manipulation:
The common strategic interest was the farm's goal to sell trees. Decorated trees are more attractive and likely to be cut down/sold.
The decorated tree engaged in self-preservation; by convincing others to be decorated, it made itself less unique or necessary to be the one on display, thereby working toward the farm's interest while protecting its own existence.
Digital Technology, AI, and Normative Disruption
Technological Innovations and Unknown Risks
Digital technology and AI are described as "disruptive" because they flip traditional methods of operation.
Cognitive vs. Normative Problems: Problems are often understood cognitively (we know something might go wrong) before they are normalized, because we lack the experience and knowledge of how to regulate the new phenomena.
Lagging Mentality: There is a tendency to view new phenomena through the lens of "old society" and project past problems onto them because that is the only knowledge base available.
State Authorization and Risk: In areas like Gene Technology (GMOs), when a state authorizes their use, it has legally and politically accepted a certain level of risk. The state and public bodies assume responsibility for incidents by authorizing activities under specified conditions.
The Anti-Game Killing Law Example
Traditional lawmaking is slow compared to technological change.
A proposed law in California seeks to protect consumers when companies end support for online games, causing players to lose their investments.
Specifics of the Proposed Law:
It would likely only apply to games released after .
It excludes games that can be played offline indefinitely.
Shifting Third Spaces and Online Socialization
Physical "third spaces" (like malls) are declining; social hangs are moving online.
Modern social behaviors include intense friendships maintained almost entirely through digital platforms (e.g., the speaker's son and his friend "Nathaniel" playing games and communicating at all hours).
Constraints on Behavior: Law, Norms, Markets, and Architecture
The Four Modalities of Constraint (Chapter 7)
Law: Constrains behavior via sanctions (punishments).
Societal Norms: Constrain behavior via stigma or social pressure.
Markets: Constrain behavior via prices and economic factors.
Examples: Cashless businesses making physical money inconvenient; subscription models that make goods affordable through "four easy payments" of, for example, .
Architecture/Code: Constrains behavior via what is technically possible. In cyberspace, code (software and hardware) acts as a regulator similar to physical walkways on a campus.
Algorithmic Norms and Democratic Deficits
Definition: Algorithms are instructions on what to do with specific data and in what order. Mixed with interfaces and default settings, they encode societal values into digital architecture.
Democratic Deficit: Norms are increasingly decided by technicians and private systems rather than public discourse or democratic decision-making.
Public Accountability: As algorithms reproduce themselves (automated decision-making, rankings, personalization), it becomes difficult to identify who is to blame for the outcomes, reducing transparency.
Filter Bubbles: Algorithms determine what users see (news, shopping, comments), isolating them from disagreeing viewpoints and creating invisible "filter bubbles."
The Circle of Motives and Systemic Factors
Comparing Societal and Algorithmic Norms
Societal Norms: Typically start with "Human Will and Values," move to "Knowledge/Cognition," and are finally balanced by "Systems and Possibilities."
Algorithmic Norms: Often begin with "Systems and Knowledge" (Digitization), which then move backward to influence and constrain "Human Will and Values."
The Threat to Democracy: When systemic factors become the "independent variable," the scope of human will is constrained. Decisions are made based on system functionality (e.g., forcing students to complete sexual harassment training by withholding registration) rather than participant values.
Methodological Implications for Studying Algorithms
One must start with outcomes and patterns of action, then infer the underlying motives and normative effects.
Researchers use big data pattern recognition and machine learning to trace shifts, such as the move from an industrial money economy to a sharing economy.
Questions & Discussion
Question (Student): Regarding the video, why would the decorated tree want to put decorations on others?
Response: It is a strategy of self-preservation. By making other trees more attractive through decorations, the decorated tree increases the farm's sales and avoids being the only target for removal, thus fulfilling the common interest of the farm (selling trees) while protecting its own interest.
Question (Audience): Discussion on the "Shiny Hunters" group.
Response: The speaker notes that hackers (referred to as "Shiny Hunters" in the context of recent digital breaches like Charter Spectrum) can take down massive systems like Canvas or Spectrum, yet they don't seem to target student loans, medical debt, or the IRS.
Question (Professor): Inquiry about Wednesday's class attendance.
Response: After a show of hands, the professor decides to hold a session on Wednesday for those who wish to attend, though the lecture material for this section is completed. The session will not last the full hour and minutes.
Discussion on Personal Behavioral Changes: Students discussed cutting back on subscriptions (DoorDash delivery fees) and the pressure of payment plans for small purchases (). The professor shared an anecdote about her children FaceTiming each other from different floors of the same house to avoid walking, illustrating how technology enables "laziness."
Discussion on Privacy (Ringworm Example): The professor used the example of repeating the word "Ringworm" to demonstrate how devices listen and then filter web searches and advertisements to reflect those conversations (e.g., "Doctors hate this one secret about ringworm").