Strategic Normative Thinking, Algorithmic Regulation, and the Impact of Disruptive Technology

Strategic Normative Thinking and Social Engineering

  • Definition of Strategic Normative Thinking: This involves using norm science in a constructive, interdisciplinary, and practical manner to address real-world normative problems. It is the process of bringing scientific understanding to normative practice and allowing that practice to provide feedback for scientific theory.
  • Key Challenges in Normative Practice:
    • Lagging Rules: New technology or game theories often result in productivity gains, but new rules and institutions typically lag behind.
    • Mental Inertia: Old institutions and current power holders often exhibit mental inertia, resisting the inclusion of new actors or ideas.
  • Case Study: "Do You Like My Decorations?" Video Analysis:
    • The video features a "psychotic" decorated Christmas tree interacting with an undecorated tree to illustrate social engineering and norm manipulation.
    • Psychological Tactics observed:
      • Implicit Deficiency: The decorated tree suggests the other tree is missing something without saying it directly (e.g., "You would look amazing with these on").
      • The Foot-in-the-Door Technique: To get someone to agree to a large favor (like being fully decorated or loaning a car), start with small, non-threatening favors (e.g., wearing one bobble, borrowing a pencil).
      • Alternative Avenues: Using questions where every answer leads to the same outcome. For example, if the tree says "yes" to liking decorations, it is decorated; if it says "no," the manipulator offers different decorations. The one option never allowed is to remain undecorated.
    • Sanctions and Shaming: The video illustrates a shaming process where it is framed as "normal" to be decorated, and resistance is met with persistent pressure.
    • Strategic Interest: The decorated tree acts as a salesperson for the farm. By decorating other trees and making them more attractive for sale, it preserves itself and prevents being cut down, aligning its self-interest with the farm's general interest.

Mechanisms of Self-Regulation and Corporate Practice

  • Emergence of Self-Regulation: Self-regulation typically develops in "isolated islands" such as new gaming subcultures, specialized platforms, or new industries.
  • Embedded Sanctions: In these environments, sanctions for violating norms are often built directly into the norms themselves rather than being external legal penalties.
  • E-commerce Context: Self-regulation in business involves the community investigating, preventing, and solving consumer problems. This includes recommendations, co-regulation between actors, and self-imposed measures.
  • Intersection of Interests: True self-regulation occurs where individual self-interest and the general interest of the community collide or align.
  • External Effects: Within these self-regulating groups, external effects are often considered minor and are managed or adjusted as they arise (e.g., if a "customer" tree says no, the system simply moves to the next tree using the same script).

Regulatory Responses to Innovation: GMOs and Environmental Risk

  • The Swedish Environmental Code and GMOs: Regulation of Genetically Modified Organisms (GMOs) is heavily influenced by "unknown unknowns." Because the full consequences of high-tech innovation are often unpredictable, regulation requires:
    • Approvals prior to introducing or marketing products.
    • Explicit ethical considerations.
  • Acceptance of Risk: From a strategic perspective, when a state authorizes the use of GMOs, it has cyclically accepted a specific level of risk. State and public bodies assume responsibility for potential incidents by setting "specified conditions" for the activity.
  • Example: Pollution Credits: In California and other states, pollution is recognized as an unavoidable byproduct of manufacturing. The state issues "pollution credits" to companies within specific industries, which can be earned or purchased under specified conditions.
  • Example: Proximity to Golf Courses: Studies have indicated a higher incidence of Parkinson’s disease among people living within a certain distance of golf courses. Despite high water waste and chemical pollution, these courses are authorized to operate under specific regulatory conditions.

Disruptive Technology and the Lagging Legal Response

  • Disruptive Nature of AI and Digital Tech: Technology is often "disruptive" because it flips traditional ways of doing things. Problems are frequently cognitive (lack of understanding) before they become normative (lack of rules).
  • Lagging Mentality: New phenomena are often viewed through the lens of old society and problems, leading to a failure to address the unique nature of new technology.
  • Traditional Lawmaking vs. Tech Speed: Traditional lawmaking is too slow to respond to rapid technological shifts.
    • Example: Anti-Game Killing Law: A proposal in California intended for consumer protection when game support ends. If passed, it would only apply to games released after 01/01/202701/01/2027 and would exclude games playable offline.
  • Transformation of "Third Spaces": Physical gathering spaces like malls are declining, and "third spaces" (social areas outside of home and work) are moving online. Friendships and intimate relationships are increasingly maintained through online gaming and persistent digital contact.

The Architecture of Constraint: Law, Norms, Markets, and Code

  • Chapter 7 Framework of Constraints:
    • Law: Constrains behavior through sanctions (legal penalties).
    • Societal Norms: Constrain or encourage behavior through stigma (social disapproval or approval).
    • Markets: Constrain behavior through prices.
    • Architecture/Code: In physical space, architecture (like walkways) guides behavior. In cyberspace, code (software and hardware) constrains behavior based on what is technically possible or impossible.
  • Regulation via Code: Programmers possess significant power as they decide the direction of AI and access to information. Code acts as regulation by permitting, blocking, or channeling behavior.
  • The Illusion of Consent: Lengthy contracts (3030 pages or more) that users cannot practically read often include clauses for binding arbitration, preventing consumers from suing companies in court.

Algorithms as Normative Systems and the Democratic Deficit

  • Algorithms as Norms: Algorithms are essential instructions regarding what tasks to perform, with which data, and in what specific order. Combined with interfaces and default settings, they encode societal values into digital architecture.
  • The Democratic Deficit: There is a deficit in democracy because these influential norms are decided by technicians and private systems rather than through public discourse or democratic decision-making.
  • Public Accountability: As algorithms reproduce themselves (machine learning), it becomes harder to assign blame or identify the source of errors, creating a lack of visibility and accountability.
  • Market Manipulation and Filter Bubbles:
    • Algorithms determine what consumers see while shopping, browsing news, or searching the web.
    • The "Ringworm" Example: Targeted advertising is so precise that talking about a topic (like the "massive case of ringworm" you might hypothetically have) can cause your device to immediately surface related results (e.g., "Doctors hate this one secret about ringworm").
    • This leads to filter bubbles, where users are isolated from disagreeing viewpoints and become captives of technical systems over which they have no control.

Methodological and Regulatory Implications of Algorithmic Norms

  • The Circle of Motives: In traditional societal norms, the sequence is: Human Will/Values $\rightarrow$ Knowledge/Cognition $\rightarrow$ Systems/Possibilities.
  • The Reversal in Algorithmic Norms: Algorithmic systems start with Knowledge and Systems (digitization), which then influence and constrain Human Will and Values. When systemic factors become the independent variable, it threatens democracy by limiting the scope of human choice.
  • Studying Algorithms: Methodologically, researchers must start with outcomes and patterns of action, then infer the underlying motives and normative effects. This requires big data, pattern recognition, and machine learning tools to trace transitions (e.g., from money-based economy to information-based sharing economy).
  • Regulatory Consequences: Law must interact with or be built into systems that already contain strong technical and algorithmic norms, which can sometimes render the law ineffective as it must support the new technological standard.

Questions, Discussion, and Class Logistics

  • Discussion on Daily Life Impacts:
    • Shopping Habits: Students discussed cutting back on subscriptions and delivery services like DoorDash due to fees.
    • Payment Trends: Rise of "cashless" establishments and the inconvenience of stores requiring "exact change" only.
    • The Microwave Observation: Waiting for a microwave for 1 minute 30 seconds1\,\text{minute}\,30\,\text{seconds} (90 seconds90\,\text{seconds}) feels like "torture" because the pace of technology has altered the perception of time.
  • Cybersecurity Notes: Mention of a group called "Shiny Hunters" (or "Shiny Pokemon") taking down systems like Charter Spectrum.
  • Upcoming Schedule:
    • The lecture material is complete.
    • Wednesday class is optional; the instructor will be present for those who want to attend, but likely only for a short time and featuring non-standard content.
  • Assessments:
    • The final quiz is bundled into the last module.
    • Per the syllabus, the lowest quiz score is dropped. Students who are satisfied with their current scores may choose how to handle the final quiz.
    • Mention of a student's friend named Nathaniel and the commonality of "slumber party" style online hanging out habits.