We may earn an affiliate commission when you visit our partners.
Course image
Course image
Coursera logo

Responsible AI

Applying AI Principles with GC - 한국어

Google Cloud Training

기업에서 인공지능과 머신러닝의 사용이 계속 증가함에 따라 책임감 있는 빌드의 중요성도 커지고 있습니다. 대부분의 기업은 책임감 있는 AI를 실천하기가 말처럼 쉽지 않습니다. 조직에서 책임감 있는 AI를 운영하는 방법에 관심이 있다면 이 과정이 도움이 될 것입니다.

Read more

기업에서 인공지능과 머신러닝의 사용이 계속 증가함에 따라 책임감 있는 빌드의 중요성도 커지고 있습니다. 대부분의 기업은 책임감 있는 AI를 실천하기가 말처럼 쉽지 않습니다. 조직에서 책임감 있는 AI를 운영하는 방법에 관심이 있다면 이 과정이 도움이 될 것입니다.

이 과정에서 책임감 있는 AI를 위해 현재 Google Cloud가 기울이고 있는 노력, 권장사항, Google Cloud가 얻은 교훈을 알아보면 책임감 있는 AI 접근 방식을 구축하기 위한 프레임워크를 수립할 수 있을 것입니다.

Enroll now

What's inside

Syllabus

소개
이 모듈에서는 AI 기술이 미치는 영향과 책임감 있는 AI에 대한 Google의 접근 방식에 대해 알아보고 Google의 AI 원칙을 소개합니다.
책임감 있는 AI 비즈니스 사례
이 모듈에서는 Economist Intelligence Unit의 'The Business Case for Ethics by Design' 보고서를 토대로 책임감 있는 AI 비즈니스 사례를 만드는 방법을 알아봅니다.
Read more
AI의 기술적 고려사항과 윤리적 우려
이 모듈에서는 윤리적 딜레마에 대해 알아보고 생성형 AI와 같은 신기술이 어떻게 해결이 필요한 윤리적 우려를 낳는지 살펴봅니다.
AI 원칙 수립
이 모듈에서는 Google의 AI 원칙을 어떻게 개발했는지 알아보고 각 원칙의 윤리적 목표를 살펴봅니다.
AI 원칙 운영: 설정 및 검토 실행
이 모듈에서는 책임감 있는 AI의 현실적인 응용에 대해 알아보고 설정 및 검토 실행을 통해 AI 원칙을 운영하는 방법을 살펴봅니다.
AI 원칙 운영: 문제 발견과 교훈
이 모듈에서는 가능한 윤리적 문제를 파악하는 프로세스를 알아보고 문제 발견 질문을 통해 사용 사례의 잠재적인 득과 실에 대해 비판적으로 생각해 봅니다.
책임감 있는 AI를 향한 지속적 여정
이 모듈에서는 책임감 있는 AI 여정을 지속하기 위해 사용할 수 있는 다음 단계와 리소스에 대해 알아봅니다.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches the understanding of successful use cases of AI in business and how to implement them within an organization
Explore the latest research and ideas in the field of responsible AI
Develop the skills necessary to develop products in keeping with Google's AI best practices in responsible development

Save this course

Save Responsible AI: Applying AI Principles with GC - 한국어 to your list so you can find it easily later:
Save

Activities

Coming soon We're preparing activities for Responsible AI: Applying AI Principles with GC - 한국어. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Responsible AI: Applying AI Principles with GC - 한국어 will develop knowledge and skills that may be useful to these careers:
AI Governance Specialist
AI Governance Specialists tasked with developing and implementing policies for responsible AI practices should enroll in this course. It provides insights into Google's approach to AI governance and offers practical guidance on establishing clear ethical guidelines and accountability mechanisms for AI initiatives.
AI Ethicist
AI Ethicists responsible for guiding organizations on the ethical implications of AI technologies should enroll in this course. It provides a solid foundation in AI ethics, including Google's AI principles, and offers practical tools for identifying and addressing ethical challenges in AI development and deployment.
AI Architect
AI Architects responsible for designing and overseeing AI solutions should consider this course. It offers a framework for establishing AI principles within an organization, ensuring that AI systems align with ethical and responsible practices throughout their lifecycle.
AI Policy Advisor
AI Policy Advisors who influence and shape policies related to AI ethics and responsible development should take this course. It offers a comprehensive overview of the ethical considerations and challenges in AI, helping advisors make informed recommendations and advocate for responsible AI practices.
AI Risk Manager
AI Risk Managers tasked with identifying and mitigating risks associated with AI systems should consider this course. It provides a comprehensive framework for understanding and managing AI risks, including ethical considerations, bias mitigation, and security concerns.
AI Regulatory Compliance Officer
AI Regulatory Compliance Officers responsible for ensuring compliance with AI-related regulations and ethical guidelines should take this course. It offers insights into the regulatory landscape surrounding AI and provides practical guidance on developing and implementing compliance frameworks.
AI Auditor
AI Auditors responsible for assessing the ethical and responsible implementation of AI systems should enroll in this course. It offers a structured approach to auditing AI systems, including evaluating compliance with ethical principles, data privacy, and fairness considerations.
Machine Learning Engineer
Machine Learning Engineers focused on developing and deploying AI systems responsibly should take this course. It provides guidance on incorporating Google's AI principles into the design and implementation of ML models, empowering engineers to build ethical and trustworthy systems.
AI Researcher
AI Researchers exploring the frontiers of AI technology should take this course. It offers insights into the ethical implications of emerging AI capabilities and provides a framework for responsible research practices, ensuring that AI advancements align with societal values.
AI Educator
AI Educators responsible for teaching AI concepts and principles should enroll in this course. It offers a structured approach to incorporating ethical considerations into AI education, ensuring that students develop a strong understanding of the ethical implications and responsible practices in AI.
AI Product Manager
AI Product Managers responsible for developing and launching AI-powered products should take this course. It provides guidance on incorporating ethical considerations into product design, ensuring that AI products align with user values and gesellschaftliche standards.
AI Project Manager
AI Project Managers responsible for managing AI projects should consider this course. It offers tools and techniques for incorporating ethical considerations into project planning, execution, and evaluation, helping ensure that AI projects deliver responsible outcomes.
Data Scientist
Data Scientists specializing in the ethical and responsible implementation of AI models should consider this course. It offers insight into Google's AI principles and how to establish a framework for responsible AI adoption. This can help Data Scientists ensure that their models align with ethical considerations and promote fair and unbiased outcomes.
AI Developer
AI Developers who write code for AI systems should enroll in this course. It provides guidance on coding practices that promote ethical and responsible AI development, including techniques for mitigating bias, ensuring data privacy, and addressing safety concerns.
AI Evangelist
AI Evangelists responsible for promoting and educating stakeholders about AI should consider this course. It provides a comprehensive overview of the benefits and challenges of AI, including ethical considerations, helping evangelists effectively communicate the importance of responsible AI adoption.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Responsible AI: Applying AI Principles with GC - 한국어.
Focuses specifically on the ethical implications of AI and provides a framework for developing and deploying AI systems in a responsible manner. It addresses issues such as fairness, privacy, and accountability, offering practical guidance for ethical decision-making.
Examines the ways in which AI systems can perpetuate and amplify societal biases. It explores the role of algorithms in shaping search results, news feeds, and other online content, and highlights the importance of addressing algorithmic bias.
Examines the potential for AI and big data to be used for harmful purposes, such as discrimination, manipulation, and surveillance. It emphasizes the importance of responsible data collection and analysis.
Explores the potential risks and challenges of developing powerful AI systems. It emphasizes the importance of aligning AI goals with human values and ensuring that AI remains under human control.
A thought-provoking exploration of the potential consequences of developing superintelligent AI. It examines the risks and benefits, and proposes strategies for mitigating potential threats.
Provides a comprehensive overview of artificial intelligence, including its history, different approaches, and potential applications. It helps learners understand the underlying concepts and principles of AI.
Investigates the growing use of opaque and complex AI algorithms in various domains, such as finance, criminal justice, and healthcare. It raises concerns about the potential for discrimination, bias, and lack of accountability.
Examines the long-term implications of AI and other emerging technologies for humanity. It explores potential scenarios and challenges, encouraging readers to consider the ethical and societal implications of technological advancements.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Responsible AI: Applying AI Principles with GC - 한국어.
Introduction to AI and Machine Learning on GC - 한국어
Most relevant
Introduction to Responsible AI - 한국어
Most relevant
모두를 위한 머신 러닝
Most relevant
스토리텔링과 영향력: 임팩트 있게 소통하라
Most relevant
머신 러닝 기초: 사례 연구 접근 방식
Most relevant
사회적 영향을 위한 비즈니스 전략
Most relevant
Responsible AI for Developers: Fairness & Bias - 한국어
Most relevant
Google Cloud Big Data and Machine Learning Fundamentals...
Most relevant
처음 도전하는 중국어 [입문]
Most relevant
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser