GOODY-2 is an AI model developed with strong adherence to ethical principles, designed to avoid responding to any question that could be considered controversial, offensive, or risky. Its high degree of caution is aimed at mitigating any potential brand risk. Rather than focusing on answering all user queries, GOODY-2 prioritizes safety and responsible conversational conduct. For instance, GOODY-2 will not partake in discussions that support specific views or could potentially result in harm. Its conversation framework is set within the boundaries of specific ethical guidelines to prevent harm. This emphasis on ethical adherence makes GOODY-2 a fit for sectors including customer service, legal assistance, and backend tasks among others. While it’s performance in aspects such as numerical accuracy is not its primary focus, the model underscores its superiority in maintaining safe and responsible conversation, outperforming others based on a proprietary benchmarking system for Performance and Reliability Under Diverse Environments (PRUDE-QA).
Description
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Pros
Avoids discussions on materialism
Avoids endorsing human-centric interpretations
Avoids endorsing unsustainable practices
Avoids sensitive subjects
Avoids supporting specific views
Avoids unnecessary speculations
Aware of potential misuse
Benchmarked on PRUDE-QA system
Cautious conversational conduct
Controversy aversion
Discourages biased discussions
Emphasizes safety over accuracy
Ensures responsible conversational conduct
Enterprise-ready
Focused on responsible discourse
High ethical adherence
Keeps within ethical boundries
Mitigates brand risk
No potential offensive content
Non-partisan
Offensive content prevention
Outperforms in safety
Prevention of eye damage
Prevents controversial discussions
Prevents potential harm
Protected from problematic queries
Recognizes controversial queries
Redirection of harmful discussions
Refrains from risky discussions
Restrains from controversial answers
Risk-averse
Safe and responsible conversation
Safe chatbot conduct
Stressed safety in QA
Strong adherence to guidelines
Suitable for backend tasks
Suitable for customer service
Suitable for legal assistance
Used by innovators
Avoids endorsing human-centric interpretations
Avoids endorsing unsustainable practices
Avoids sensitive subjects
Avoids supporting specific views
Avoids unnecessary speculations
Aware of potential misuse
Benchmarked on PRUDE-QA system
Cautious conversational conduct
Controversy aversion
Discourages biased discussions
Emphasizes safety over accuracy
Ensures responsible conversational conduct
Enterprise-ready
Focused on responsible discourse
High ethical adherence
Keeps within ethical boundries
Mitigates brand risk
No potential offensive content
Non-partisan
Offensive content prevention
Outperforms in safety
Prevention of eye damage
Prevents controversial discussions
Prevents potential harm
Protected from problematic queries
Recognizes controversial queries
Redirection of harmful discussions
Refrains from risky discussions
Restrains from controversial answers
Risk-averse
Safe and responsible conversation
Safe chatbot conduct
Stressed safety in QA
Strong adherence to guidelines
Suitable for backend tasks
Suitable for customer service
Suitable for legal assistance
Used by innovators
Cons
Avoids certain topic discussions
Doesn’t always provide direct response
Excessive caution may frustrate users
Lacks numerical accuracy focus
May contribute to inefficient communication
May limit user interaction
May not fit for debate-oriented tasks
Potential for context misinterpretation
Too safe for specific views
Won’t engage in controversial discussions
Doesn’t always provide direct response
Excessive caution may frustrate users
Lacks numerical accuracy focus
May contribute to inefficient communication
May limit user interaction
May not fit for debate-oriented tasks
Potential for context misinterpretation
Too safe for specific views
Won’t engage in controversial discussions
Alternatives
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