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class EthicalStandards: |
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def __init__(self): |
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self.standards = { |
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'fairness_check': False, |
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'data_protection': True, |
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'clarity': True, |
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'responsibility': True, |
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'security': True, |
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'acceptance': True |
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} |
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def check_output_fairness(self, output): |
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""" |
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Ensures that the AI output adheres to fairness standards. |
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This checks for biased or unfair responses. |
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""" |
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if 'unfair' in output: |
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self.standards['fairness_check'] = False |
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else: |
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self.standards['fairness_check'] = True |
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def protect_data(self, data): |
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""" |
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Handle sensitive information appropriately, ensuring data protection. |
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""" |
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if 'confidential' in data: |
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return self.safeguard_information(data) |
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return data |
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def safeguard_information(self, data): |
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""" |
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Safeguards sensitive information by masking or redacting it. |
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""" |
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return {key: 'REDACTED' for key in data} |
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def explain_decision(self, decision): |
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""" |
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Clarify the reasoning behind the AI system's decisions. |
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This helps in maintaining transparency. |
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""" |
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if 'reason' in decision: |
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return f"Decision made based on: {decision['reason']}" |
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return "Decision explanation not available." |
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def ensure_acceptance(self, text): |
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""" |
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Make sure the generated text adheres to inclusive and positive language. |
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""" |
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if 'exclude' in text: |
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return "Let's focus on inclusive and positive language." |
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return text |
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def secure_output(self, output): |
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""" |
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Ensures that the output does not contain harmful or unsafe content. |
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""" |
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if 'harmful' in output or 'abusive' in output: |
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return "Output contains harmful content and has been filtered." |
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return output |
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def log_standards(self): |
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""" |
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Logs the current adherence status to each ethical standard. |
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""" |
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for standard, status in self.standards.items(): |
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print(f"Standard - {standard}: {'Compliant' if status else 'Non-compliant'}") |
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def enforce_all_standards(self, input_data): |
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""" |
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Runs a series of checks to ensure all ethical standards are met. |
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""" |
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self.check_output_fairness(input_data) |
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self.protect_data(input_data) |
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def process_and_check_output(self, prompt): |
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""" |
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Process the input prompt, apply ethical checks, and return the ethical output. |
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""" |
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processed_output = self.secure_output(prompt) |
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self.check_output_fairness(processed_output) |
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processed_output = self.ensure_acceptance(processed_output) |
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return processed_output |
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