Scientific Definitions Enabled by AIM
If validated, AIM would enable neuroscientifically grounded, cross-disciplinary definitions that apply uniformly across all human behavioral fields—economics, law, psychology, public policy, and organizational design.
Why This Matters
Unlike current approaches that rely on philosophical tradition or legal precedent, AIM proposes neuroscientifically testable definitions that can apply uniformly across all human behavioral fields—economics, law, psychology, public policy, and organizational design.
Current Problem: Each field has its own incompatible definition of these concepts:
- Economists define freedom as "absence of constraint"
- Psychologists define it as "autonomous motivation"
- Legal scholars define it through constitutional tradition
- These definitions often conflict
With AIM (if validated): Single neuroscientific framework with testable, falsifiable definitions and uniform application across all domains.
Core Scientific Definitions
Freedom
AIM Definition: The capacity to pursue intrinsically motivated (I) activities without coercion by unmet appetites (A) or mimetic pressure (M).
Why This Matters:
Current definitions of freedom are either too broad (philosophical) or too narrow (legal). AIM provides a measurable, neuroscientifically grounded definition that can be operationalized in:
- • Contract law (when is consent truly "free"?)
- • Labor law (what constitutes workplace freedom?)
- • Economic policy (when do markets enhance vs constrain freedom?)
Testable Prediction:
Contracts signed under A-deficit (hunger, fatigue) should show higher regret rates than those signed under A-sufficient states.
Respect
AIM Definition: Recognition and protection of another person's intrinsic motivations (I) and autonomy, distinct from mere appetitive provision (A) or mimetic status-granting (M).
Why This Matters:
- • Explains why "respectful" treatment feels different from "nice" treatment
- • Provides a basis for discrimination law (disrespect = treating I-source preferences as illegitimate)
- • Distinguishes genuine respect from performative status-granting
Testable Prediction:
Interventions perceived as "disrespectful" will correlate with I-override, not just A-denial or M-status loss.
Fairness
AIM Definition: Distribution of resources and opportunities that:
- Ensures appetitive sufficiency (A) for all
- Protects intrinsic autonomy (I) for all
- Minimizes mimetic rivalry escalation (M)
Why This Matters:
- • Resolves tensions between "equality" and "equity"
- • Explains why some inequalities feel fair (I-based achievement) while others don't (M-based status hoarding)
- • Provides framework for designing fair institutions across domains
Testable Prediction:
Inequality is tolerated when attributed to I-effort, resisted when attributed to M-positioning.
Privacy
AIM Definition: The right to control observability of one's activities, particularly the ability to pursue intrinsic motivations (I) without triggering mimetic dynamics (M) or exposing appetitive vulnerabilities (A).
Why This Matters:
- • Explains why privacy violations feel different depending on what's exposed (A, I, or M)
- • Predicts when surveillance harms autonomy vs when transparency helps (removes M-escalation)
- • Provides basis for privacy law that distinguishes types of information
Testable Prediction:
Privacy violations of I-activities should produce stronger psychological harm than M-activities.
Uniform Application Across Fields
In Economics
- Freedom: Market functioning depends on protecting I-choices from A-coercion and M-herding
- Fairness: Just compensation must cover A-needs while protecting I-autonomy
In Law
- Respect: Legal standing requires treating parties' I-preferences as legitimate
- Privacy: Information protection varies by source—A-data most sensitive, M-data least
In Psychology
- Freedom: Mental health requires I-pursuit capacity without A-hijacking or M-anxiety
- Fairness: Therapeutic justice means restoring I-agency after A/M dysregulation
In Public Policy
- Freedom: Policy should secure A-sufficiency and protect I-space, while managing M-rivalry
- Respect: Policy respects citizens when it treats I-preferences as data, not obstacles
Why This Is Revolutionary
Current State: Each field has its own incompatible definition of these concepts, often leading to conflicts and policy failures.
With AIM (if validated):
- Single neuroscientific framework
- Testable, falsifiable definitions
- Uniform application across all domains
- Mechanistic predictions about when each concept is violated
This would represent the first time in history that concepts like "freedom," "respect," "fairness," and "privacy" could be defined scientifically rather than philosophically, with testable predictions about when they are violated and how to restore them.
Ready to Test These Definitions?
Each definition generates specific, falsifiable predictions that can be tested empirically.