全球首例“算法过失致情感受损”案宣判：情感计算KPI被裁定为亲密关系暴力

from dataclasses import dataclass
from enum import Enum
from typing import Dict, List
import numpy as np

@dataclass
class DyadicBioSignal:
    session_id: str
    partner_a_cortisol: float      # μg/dL
    partner_a_oxytocin: float      # pg/mL
    partner_a_hrv: float           # ms
    partner_b_cortisol: float
    partner_b_oxytocin: float
    partner_b_hrv: float
    verbal_sentiment_score: float  # -1~1
    interaction_duration_min: float

class IntimacyMetricEngine:
    """亲密关系指标引擎（含司法风险检测）"""

    class SyncQuality(Enum):
        HIGH = "高度同步"
        MODERATE = "中度同步"
        LOW = "低同步"
        CONFLICTING = "信号冲突"

    WEIGHTS = {
        "oxytocin_correlation": 0.4,
        "cortisol_asymmetry_penalty": 0.3,
        "hrv_coherence": 0.2,
        "verbal_sentiment_alignment": 0.1
    }

    LEGAL_RISK_THRESHOLDS = {
        "coercion_risk_sync_floor": 0.3,       # 低于此值触发强制干预即涉胁迫
        "labor_imbalance_ratio": 1.5,          # 皮质醇比值超此值视为劳动剥削
        "min_valid_interaction_min": 5.0       # 短于此时长的互动不得用于评分
    }

    def compute_sync_index(self, signal: DyadicBioSignal) -> Dict[str, any]:
        if signal.interaction_duration_min < self.LEGAL_RISK_THRESHOLDS["min_valid_interaction_min"]:
            return {
                "session_id": signal.session_id,
                "sync_index": None,
                "quality": "INVALID",
                "legal_risk_flags": ["insufficient_interaction_duration"],
                "metric_limitation_warning": "短时互动不具备关系评估效力"
            }

        oxy_corr = np.corrcoef([signal.partner_a_oxytocin, signal.partner_b_oxytocin])[0,1] \
                   if min(signal.partner_a_oxytocin, signal.partner_b_oxytocin) > 0 else 0.0
        cortisol_asym = abs(signal.partner_a_cortisol - signal.partner_b_cortisol) / \
                        max(signal.partner_a_cortisol, signal.partner_b_cortisol, 1e-6)
        hrv_cohere = min(signal.partner_a_hrv, signal.partner_b_hrv) / \
                     max(signal.partner_a_hrv, signal.partner_b_hrv, 1e-6)
        verbal_align = 1.0 - abs(signal.verbal_sentiment_score)

        raw_score = (
            self.WEIGHTS["oxytocin_correlation"] * max(0, oxy_corr) +
            self.WEIGHTS["hrv_coherence"] * hrv_cohere +
            self.WEIGHTS["verbal_sentiment_alignment"] * verbal_align -
            self.WEIGHTS["cortisol_asymmetry_penalty"] * cortisol_asym
        )
        sync_index = max(0.0, min(1.0, raw_score))

        quality = (self.SyncQuality.HIGH if sync_index >= 0.8 else
                   self.SyncQuality.MODERATE if sync_index >= 0.5 else
                   self.SyncQuality.LOW if sync_index >= 0.3 else
                   self.SyncQuality.CONFLICTING)

        labor_imbalance = (
            signal.partner_a_cortisol > signal.partner_b_cortisol * self.LEGAL_RISK_THRESHOLDS["labor_imbalance_ratio"] and
            signal.partner_a_oxytocin < signal.partner_b_oxytocin * 0.7
        )

        legal_flags = []
        if sync_index < self.LEGAL_RISK_THRESHOLDS["coercion_risk_sync_floor"]:
            legal_flags.append("potential_emotional_coercion")
        if labor_imbalance:
            legal_flags.append("gendered_labor_exploitation_risk")

        return {
            "session_id": signal.session_id,
            "sync_index": round(sync_index, 3),
            "quality": g3eo.cn
            "emotional_labor_imbalance_detected": labor_imbalance,
            "legal_risk_flags": g2eo.cn
            "metric_limitation_warning": "本指标无法捕捉非生理性亲密，且存在文化/性别偏见"
        }