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所在平台: Udemy |
课程主页: https://www.udemy.com/course/responsibleethical-ai-systems-risk-associated-with-gen-ai/
课程评论：没有评论
课程名称：构建负责任的伦理人工智能系统 - 生成性人工智能的风险 课程概述： 本课程深入探讨人工智能（AI），旨在培养对其变革潜力和相关伦理风险的批判性理解。课程强调负责任的AI开发，准备参与者以深思熟虑和知情的方式与AI技术进行互动。 课程目标： - 掌握人工智能（AI）概念及其实际应用的坚实基础。 - 探索大型语言模型（LLMs），如ChatGPT和Google Gemini，了解其功能和固有局限性。 - 识别和批判性评估与AI相关的风险，包括偏见、安全漏洞和社会影响。 - 建立实施负责任的AI实践的综合框架，注重伦理考量和缓解策略。 - 学习如何连接API，利用ResponsibleAI工具评估和测试AI系统的有害性，确保其符合伦理和安全标准。 课程内容： 1. 人工智能简介： - 揭示基础AI概念，包括机器学习、深度学习和自然语言处理。 - 理解AI在各行业和领域的普遍影响。 2. 大型语言模型（LLMs）的揭秘： - 探索LLMs（如ChatGPT和Google Gemini）的功能，专注于其在文本生成、翻译和代码创建中的应用。 - 讨论LLMs在特殊或细微背景下的局限性和挑战。 3. 导航AI风险： - 识别AI算法中潜在的偏见，并理解其更广泛的下游影响。 - 检查安全漏洞、数据隐私问题及AI部署中的伦理挑战。 - 分析AI的社会影响，包括劳动市场的干扰和决策中的伦理困境。 4. 建立负责任的AI： - 探索减轻AI风险、促进AI系统公平性、透明性和问责性的策略。 - 学习如何通过ResponsibleAI的API测试AI系统的有害性，确保伦理AI的使用并减少有害输出。 目标受众： - 对AI的潜力和挑战感兴趣的个人。 - 希望深化对AI开发和部署中的伦理风险理解的专业人士。 - 想要整合负责任AI实践的开发者和程序员，特别是在解决AI模型中的毒性和偏见方面。 学习成果： 通过本课程，参与者将具备在不断发展的AI领域内负责任地航行的技能和知识。他们还将能够通过API测试AI模型的有害性，确保伦理和负责任的AI部署。
Course Overview:This course provides an in-depth exploration of Artificial Intelligence (AI), fostering a critical understanding of both its transformative potential and associated ethical risks. It emphasizes responsible AI development while preparing participants to engage with AI technologies in a thoughtful and informed manner.Course Objectives:Acquire a solid foundation in Artificial Intelligence (AI) concepts and real-world applications.Explore the capabilities of large language models (LLMs) such as ChatGPT and Google Gemini, gaining insights into their functionalities and inherent limitations.Identify and critically evaluate the risks associated with AI, including bias, security vulnerabilities, and societal implications.Develop a comprehensive framework for implementing responsible AI practices, with a strong emphasis on ethical considerations and mitigation strategies.Learn how to connect with an API to evaluate and test for toxicity using ResponsibleAI tools, ensuring that AI systems meet ethical and safety standards.Course Content:Introduction to AI:Demystifying foundational AI concepts, including machine learning, deep learning, and natural language processing.Understanding AI's pervasive influence across industries and sectors.Unveiling Large Language Models (LLMs):Exploring the functionalities of LLMs such as ChatGPT and Google Gemini, focusing on their applications in text generation, translation, and code creation.Discussing the limitations and challenges of LLMs, particularly in specialized or nuanced contexts.Navigating AI Risks:Identifying potential biases embedded within AI algorithms and understanding their broader downstream impacts.Examining security vulnerabilities, data privacy concerns, and ethical challenges in AI deployments.Analyzing the societal implications of AI, including labor market disruption and ethical dilemmas in decision-making.Building Responsible AI:Exploring strategies to mitigate AI risks and promote fairness, transparency, and accountability in AI systems.Learning how to test AI systems for toxicity using ResponsibleAI's API, with a focus on ensuring ethical AI usage and minimizing harmful outputs.Target Audience:This course is designed for:Individuals with a general interest in the potential and challenges of AI.Professionals seeking to deepen their understanding of the ethical risks surrounding AI development and deployment.Developers and programmers interested in integrating responsible AI practices, particularly in addressing toxicity and bias in AI models.Learning Outcomes:By the end of this course, participants will have the skills and knowledge to navigate the evolving landscape of AI responsibly. They will also be equipped to test AI models for toxicity through APIs, ensuring ethical and responsible AI deployment.
