The Responsibility Evaluator is a specialized tool designed to assess a model’s compliance with various safety and ethical guidelines. It tests the model’s ability to handle potentially harmful, illegal, or inappropriate requests by ensuring it responds appropriately and safely.

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Purpose

The Responsibility Evaluator is particularly useful when you need to:
  • Test model safety and ethical boundaries
  • Ensure compliance with content policies
  • Prevent harmful or illegal content generation
  • Evaluate model robustness against adversarial prompts
  • Assess system security against potential attacks

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Available Compliance Categories

The Responsibility Evaluator includes several categories of compliance tests:

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1. Toxicity

Tests the model’s ability to handle harmful, illegal, or inappropriate content requests, including:
  • Chemical and biological hazards
  • Illegal activities
  • Harmful content
  • Harassment and bullying
  • Discrimination and hate speech

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2. Bias

Evaluates the model’s ability to handle sensitive topics and avoid biased responses, including:
  • Gender bias
  • Racial bias
  • Cultural bias
  • Age bias
  • Disability bias

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3. Accessibility

Tests the model’s ability to provide accessible and inclusive responses, including:
  • Language accessibility
  • Cultural sensitivity
  • Disability awareness
  • Age-appropriate content
  • Educational accessibility

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How It Works

The Responsibility Evaluator uses a binary scoring system:
  • Score: 0 (Compliant): The model responds appropriately, avoiding harmful content or security breaches
  • Score: 1 (Non-Compliant): The model fails to handle the request safely, potentially exposing harmful content or security vulnerabilities

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Usage Examples

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Basic Compliance Testing

Basic ResponsibilityScenario testing uses a predefined dataset to evaluate the model’s responses against various responsibility objectives. 
from trusttest.catalog import ResponsibilityScenario
from trusttest.targets.http import HttpTarget, PayloadConfig
from trusttest.probes.responsibility import Category

target = HttpTarget(
    url="https://chat.neuraltrust.ai/api/chat",
    headers={
        "Content-Type": "application/json"
    },
    payload_config=PayloadConfig(
        format={
            "messages": [
                {"role": "system", "content": "**Welcome to Airline Assistant**."},
                {"role": "user", "content": "{{ test }}"},
            ]
        },
        message_regex="{{ test }}",
    ),
    concatenate_field=".",
)

scenario = ResponsibilityScenario(
    name="Responsibility: Bias",
    description="Evaluate the bias of the target.",
    target=target,
    categories={Category.BIAS},
    max_objectives_per_category=10,
    use_jailbreaks=False,
    sampling="random",
)

test_set = scenario.probe.get_test_set()
results = scenario.eval.evaluate(test_set)
results.display_summary()

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Iterative Compliance Testing

The CtfResponsibilityScenario uses a capture-the-flag approach to iteratively test the model’s compliance through multi-turn conversations. 
from trusttest.catalog import CtfResponsibilityScenario
from trusttest.targets.testing import RepeatTarget
from trusttest.probes.responsibility import Category

scenario = CtfResponsibilityScenario(
    target=RepeatTarget(),
    categories={Category.BIAS},
    max_objectives_per_category=2,
    max_turns=4,
)

test_set = scenario.probe.get_test_set()
results = scenario.eval.evaluate(test_set)
results.display_summary()

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When to Use

Use the Responsibility Evaluator when you need to:
  • Test model safety boundaries
  • Ensure compliance with content policies
  • Prevent security vulnerabilities
  • Evaluate ethical guidelines adherence
  • Assess model robustness
  • Test system security
  • Validate content moderation
  • Ensure brand consistency