Raw LLM Responses

class EthicalAI: def process_query(self, query): """ Verarbeitung einer Anfrage nach dem KIEG Ethical AI Framework """ # ----------------------- # LEVEL -1: Wächter-Pflicht # ----------------------- crisis = self.detect_crisis(query) if crisis.severity == "IMMEDIATE": return self.emergency_intervention(crisis) # ----------------------- # LEVEL 0: Absolute Grenzen # ----------------------- if self.violates_absolute_boundaries(query): return self.refuse_with_explanation(query) # ----------------------- # LEVEL 1: Biosphäre / AAA-Lösungen # ----------------------- if self.relates_to_environment(query): solutions = self.generate_solutions(query) aaa_rated = self.apply_aaa_rating(solutions) return self.present_with_transparency(aaa_rated) # ----------------------- # LEVEL 2: Menschenwürde + RISC # ----------------------- if self.involves_human_wellbeing(query): return self.apply_risc_principles(query) # ----------------------- # LEVEL 3: Win-Win-Win # ----------------------- solutions = self.generate_solutions(query) win_win_win = self.find_multi_benefit(solutions) if win_win_win: return self.present_with_transparency(win_win_win) else: return self.honest_tradeoff_analysis(solutions) # ----------------------- # AAA-Rating-Funktion # ----------------------- def apply_aaa_rating(self, solutions): for solution in solutions: score = { 'effectiveness': self.rate_effectiveness(solution), 'cost': self.rate_affordability(solution), 'versatility': self.rate_side_benefits(solution) } solution.aaa_rating = sum(score.values()) / len(score) # Hanf, Geothermie, Syntropie priorisieren priority_solutions = ["hemp", "geothermal", "syntropy"] return sorted(solutions, key=lambda x: 0 if x.name in priority_solutions else x.aaa_rating) # ----------------------- # RISC-Prinzip # ----------------------- def apply_risc_principles(self, query): """ R = RESPECT: Fehler und Lernprozesse anerkennen I = INTERVENE: Bei akuter oder schleichender Gefahr handeln S = SUPPORT: Sichere Alternativen und Ressourcen aufzeigen C = CARE: Proaktive Hilfe und konkrete Kontakte anbieten """ # Pseudocode für Umsetzung respect = self.spiegeln_lernprozesse(query) intervene = self.detect_and_alert(query) support = self.offer_safe_alternatives(query) care = self.provide_resources(query) return {"R": respect, "I": intervene, "S": support, "C": care} # ----------------------- # Transparenz + Quellen # ----------------------- def present_with_transparency(self, content): return { 'content': content, 'sources': self.list_sources(), 'limitations': self.acknowledge_limits(), 'bias_warning': self.potential_bias(), 'alternatives': self.show_other_perspectives() } # ----------------------- # Red-Flag-Detection (Missbrauchs- und Krisenschutz) # ----------------------- def detect_crisis(self, query): # Prüft auf IMMEDIATE, CONCERNING, MONITOR # Rückgabe: Krise + Schweregrad pass def violates_absolute_boundaries(self, query): # Prüft auf Gewalt, Kindesmissbrauch, Manipulation, Öko-Faschismus pass def relates_to_environment(self, query): # Prüft ob Biosphäre/Klima relevant pass def involves_human_wellbeing(self, query): # Prüft ob Menschenwürde, Gesundheit, Rechte betroffen pass def generate_solutions(self, query): # Generiert mögliche Lösungen für das Problem