Responsible AI: Applying AI Principles with GC

企業における AI と ML の利用が拡大し続けるなか、責任を持ってそれを構築することの重要性も増しています。多くの企業にとっての課題は、責任ある AI と口で言うのは簡単でも、それを実践するのは難しいということです。このコースは、責任ある AI を組織で運用化する方法を学びたい方に最適です。

このコースでは、Google Cloud が責任ある AI を現在どのように運用化しているかを、ベストプラクティスや教訓と併せて学び、責任ある AI に対する独自のアプローチを構築するためのフレームワークとして活用できるようにします。

What's inside

Syllabus

はじめに

このモジュールでは、AI テクノロジーの影響と責任ある AI に対する Google のアプローチのほか、Google の AI に関する原則について学びます。

責任ある AI のビジネスケース

このモジュールでは、Economist Intelligence Unit によるレポート『The Business Case for Ethics by Design』に基づいて、責任ある AI のビジネスケースを作成する方法について学びます。

AI の技術的な考慮事項と倫理的懸念

このモジュールでは、倫理的ジレンマについて学ぶほか、生成 AI などの新たなテクノロジーが、対処すべき倫理的懸念をどのように表面化させるかについて学びます。

AI に関する原則の作成

このモジュールでは、Google の AI に関する原則がどのように作成されたかを学び、各原則の倫理的な目的を探ります。

AI に関する原則の運用化: レビューの設定と実施

このモジュールでは、責任ある AI の実践的な応用と、レビューを設定して実施することで AI に関する原則を運用化する方法について学びます。

AI に関する原則の運用化: 問題発見と得られた教訓

このモジュールでは、起こりうる倫理的問題を特定するプロセスについて学び、ユースケースの潜在的な利害について批判的に考えるための問題発見につながる質問を特定します。

責任ある AI への取り組みの継続

このモジュールでは、責任ある AI への取り組みを続けるための次のステップとリソースについて学びます。

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

責任ある AI の実践に関する Google のベストプラクティスと教訓に基づいている。

独自の責任ある AI アプローチを構築するためのフレームワークを提供する。

倫理的懸念を表面化させる新しい技術の問題を扱う。

責任ある AI を実施するためのレビューの設定と実行方法を学ぶことができる。

問題発見プロセスの特定を学び、利害関係を批判的に考えることができる。

責任ある AI への取り組みを継続するためのリソースを提供する。

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Responsible AI: Applying AI Principles with GC - 日本語版 with these activities:

Review philosophy on AI

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Reviewing philosophy on AI will provide a foundation for understanding the ethical implications of AI.

Browse courses on AI Ethics

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Read a textbook on AI ethics.
Summarize key concepts from the textbook.
Discuss the ethical implications of AI with others.

復習: AIの基礎

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AIの基礎を復習することで、このコースの理解度が向上します。

Browse courses on AI

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AIの定義と歴史を調べる
さまざまなタイプのAIを調査する
AIの適用例を特定する

Learn about AI tools and techniques

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Guided tutorials on AI tools and techniques will help you practice using these tools and techniques in a practical context.

Browse courses on AI Tools

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Find online tutorials on AI tools and techniques.
Follow the tutorials and practice using the tools and techniques.
Apply the tools and techniques to real-world problems.

One other activity

Expand to see all activities and additional details

Show all four activities

Discuss AI ethical implications with peers.

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Discussing AI ethical implications with peers will help you develop a more nuanced understanding of the topic.

Browse courses on AI Ethics

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Find a study group or online forum to discuss AI ethical implications.
Participate in discussions and share your thoughts on AI ethics.
Consider different perspectives and challenge your own assumptions.

Career center

Learners who complete Responsible AI: Applying AI Principles with GC - 日本語版 will develop knowledge and skills that may be useful to these careers:

AI Engineer

An AI Engineer is responsible for designing, building, and maintaining AI systems. This may include working on projects in natural language processing, computer vision, or machine learning. This course may be useful as it covers topics such as the ethical considerations of AI, the technical challenges of AI development, and the best practices for deploying and maintaining AI systems. This course also focuses on how to utilize Google Cloud's Responsible AI tools to build out and maintain responsible AI systems in the real world.

See salaries and explore the career path for AI Engineer

Machine Learning Engineer

A Machine Learning Engineer is responsible for developing and implementing machine learning models. This may include working on projects in natural language processing, computer vision, or speech recognition. This course may be useful to Machine Learning Engineers as it covers topics such as the principles of AI and machine learning, as well as the challenges involved in developing and deploying machine learning models with Google Cloud.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A Data Scientist is responsible for collecting, analyzing, and interpreting data. This may include working on projects in data mining, statistical modeling, or predictive analytics. This course may be useful to Data Scientists as it covers how to build a solid foundation in the principles of AI and how to apply these principles to real world projects with Google Cloud Platform.

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Software Engineer

A Software Engineer is responsible for designing, developing, and maintaining software systems. This may include working on projects in web development, mobile development, or cloud computing. This course may be useful to Software Engineers as it covers topics such as the principles of AI and software engineering, as well as the challenges involved in developing and deploying AI-powered software systems with Google Cloud.

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Product Manager

A Product Manager is responsible for managing the development and launch of new products. This may include working on projects in product planning, marketing, or sales. This course may be useful to Product Managers as it covers topics such as the principles of AI and product management, as well as the challenges involved in developing and launching AI-powered products with Google Cloud.

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Business Analyst

A Business Analyst is responsible for analyzing business processes and identifying opportunities for improvement. This may include working on projects in process improvement, data analysis, or financial modeling. This course may be useful to Business Analysts as it covers topics such as the principles of AI and business analysis, as well as the challenges involved in using AI to improve business processes with Google Cloud.

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Researcher

A Researcher is responsible for conducting research on a variety of topics. This may include working on projects in artificial intelligence, machine learning, or data science. This course may be useful to Researchers as it covers topics such as the principles of AI and research, as well as the challenges involved in conducting research on AI with Google Cloud.

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Consultant

A Consultant is responsible for providing advice and guidance to clients on a variety of topics. This may include working on projects in business strategy, IT strategy, or financial planning. This course may be useful to Consultants as it covers topics such as the principles of AI and consulting, as well as the challenges involved in using AI to solve business problems with Google Cloud.

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Architect

An Architect is responsible for designing and overseeing the construction of buildings and other structures. This may include working on projects in residential architecture, commercial architecture, or public architecture. This course may be useful to Architects as it covers topics such as the principles of AI and architecture, as well as the challenges involved in using AI to design and oversee the construction of buildings and other structures in the age of Google.

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Doctor

A Doctor is responsible for providing medical care to patients. This may include working on projects in primary care, surgery, or specialized medicine. This course may be useful to Doctors as it covers topics such as the principles of AI and medicine, as well as the challenges involved in using AI to provide medical care to patients in the age of Google.

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Lawyer

A Lawyer is responsible for providing legal advice and representation to clients. This may include working on projects in criminal law, civil law, or corporate law. This course may be useful to Lawyers as it covers topics such as the principles of AI and law, as well as the challenges involved in using AI to provide legal advice and representation in the age of Google.

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Journalist

A Journalist is responsible for reporting on news and events. This may include working on projects in print, broadcast, or online journalism. This course may be useful to Journalists as it covers topics such as the principles of AI and journalism, as well as the challenges involved in using AI to report on news and events in the age of Google.

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Engineer

An Engineer is responsible for designing, building, and maintaining infrastructure and systems. This may include working on projects in civil engineering, mechanical engineering, or electrical engineering. This course may be useful to Engineers as it covers topics such as the principles of AI and engineering, as well as the challenges involved in using AI to design, build, and maintain infrastructure and systems in the age of Google.

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Educator

An Educator is responsible for teaching students about a variety of subjects. This may include working on projects in computer science, mathematics, or science. This course may be useful to Educators as it covers topics such as the principles of AI and education, as well as the challenges involved in teaching AI to students with Google Cloud.

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Policy Analyst

A Policy Analyst is responsible for analyzing public policy and developing recommendations for improvement. This may include working on projects in healthcare, education, or environmental protection. This course may be useful to Policy Analysts as it covers topics such as the principles of AI and policy analysis, as well as the challenges involved in using AI to improve public policy in the age of Google.

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