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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。
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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。
Read more
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。
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause 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。
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Reviews summary
責任あるaiの実践的運用ガイド
学習者によると、このコースは責任あるAIの概念からGoogle Cloudでの実践的な運用方法までを体系的に学ぶ上で非常に有用です。特に、AI原則の運用化に関する具体的なレビュー設定や問題発見のプロセス、そしてビジネスケースの作成といった実務に役立つガイダンスが高く評価されています。生成AIを含む最新の倫理的課題への言及も時勢に合っていると評されます。一部の学習者は、概念的な内容が中心で技術的な深掘りが少ないと感じ、中級者以上の開発者には物足りない可能性を指摘していますが、ビジネスリーダーやプロジェクトマネージャー、あるいはAI倫理の初心者には最適な導入として推奨されています。全体として、明確な指針と実践的な視点が提供される高品質なコースと認識されています。
生成AIなどの倫理的懸念に触れており、時勢に合致。
"生成AIに関する倫理的懸念のセクションも時勢に合っていて良かったです。"
"特に、生成AIにおける倫理的課題への言及は、最新のトレンドを反映しており評価できます。"
内容が分かりやすく、体系的にまとめられている。
"責任あるAIの概念からGoogle Cloudでの実践的なアプローチまで、非常に分かりやすく体系的に学べました。"
"各モジュールが簡潔にまとまっており、スキマ時間に学習を進めやすいです。"
"講義の内容は非常にクリアで理解しやすかったですが..."
"責任あるAIのフレームワークとGoogle Cloudにおける実践例が詳細に解説されており、非常に勉強になりました。"
AI倫理の基礎を学ぶのに最適で、ビジネスサイドに有用。
"組織での導入を考えている方には強くお勧めします。"
"ビジネスサイドの人には役立つかと。"
"初心者向けとしては良いかもしれませんが、中級者以上には物足りないです。"
"これからAI倫理を学ぶ方には良いかもしれません。"
"技術的な詳細は控えめなので、ビジネスリーダーやプロジェクトマネージャー向けだと感じました。"
AI原則を実務に落とし込む具体的な方法を習得。
"特に、AI原則の運用化に関するモジュールは、具体的なレビュー設定や問題発見のプロセスが示されており、実務に役立つ内容でした。"
"AI倫理の概念が抽象的でなかなか理解しにくいと感じていましたが、このコースは具体的な事例やGoogle Cloudの取り組みを通して、非常に実践的に学べました。"
"責任あるAIの重要性を再認識し、そのための具体的なフレームワークを学ぶことができました。特に運用化のセクションは明確な指針を与えてくれました。"
"企業でAIを導入する上で不可欠な倫理的側面を、非常に実用的な視点から教えてくれる素晴らしいコースでした。"
理論的側面が強く、技術的な深掘りは少ない。
"ただし、技術的な側面をもう少し深掘りする内容があれば、さらに多くの開発者にとって魅力的になると思います。"
"期待していたほど技術的な深掘りはありませんでした。主に概念的な内容とGoogleの事例紹介が中心で、より具体的な実装方法やコード例を求めている人には物足りないかもしれません。"
"全体的にGoogleのAI原則の説明が長く、期待したほど応用的な内容が少なかったです。すでにAI倫理についてある程度の知識がある人には既知の情報が多いと感じるかもしれません。"
"講義の内容は非常にクリアで理解しやすかったですが、ハンズオンの機会がほとんどないため、自分で手を動かして学びたい人には向かないかもしれません。"
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
Show steps
Reviewing philosophy on AI will provide a foundation for understanding the ethical implications of AI.
Browse courses on
AI Ethics
Show steps
-
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
Show steps
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
Show steps
-
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
Show steps
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
Show steps
-
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.
Show steps
Discussing AI ethical implications with peers will help you develop a more nuanced understanding of the topic.
Browse courses on
AI Ethics
Show steps
-
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.
Review philosophy on AI
Show steps
Reviewing philosophy on AI will provide a foundation for understanding the ethical implications of AI.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- 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
Show steps
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
Show steps
Show steps
Show steps
- 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
Show steps
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
Show steps
Show steps
Show steps
- 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.
Show steps
Discussing AI ethical implications with peers will help you develop a more nuanced understanding of the topic.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- 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
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.
Machine Learning 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.
Data Scientist
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.
Software Engineer
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.
Product Manager
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.
Business Analyst
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.
Consultant
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.
Researcher
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.
Educator
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.
Policy Analyst
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.
Journalist
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.
Lawyer
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.
Doctor
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.
Engineer
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.
Architect
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.
For more career information including salaries, visit:
OpenCourser.com/course/b38q3b/responsible
Reading list
We've selected ten 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 - 日本語版.
"The Ethical Algorithm" explores the ethical challenges of designing and deploying AI systems, with a focus on fairness, accountability, and transparency. It provides practical guidance and case studies on how to develop AI systems that align with ethical principles.
"Human Compatible" delves into the long-term implications of AI, exploring the potential threats and benefits of advanced AI systems. It discusses the concept of value alignment and the challenges of ensuring that AI systems are aligned with human values.
For those interested in the technical implementation of AI models, "Deep Learning for Coders with Fastai and PyTorch" offers a practical guide to building and deploying deep learning applications using popular tools and libraries. It requires some programming experience and provides hands-on examples.
"The Alignment Problem" explores the fundamental challenge of aligning AI systems with human values. It discusses the complexities of defining and measuring human values and the implications for the development of safe and beneficial AI.
Save
"Rebooting AI" argues for a more cautious approach to AI development, emphasizing the need for safety, transparency, and accountability. It critiques some of the current approaches to AI and proposes alternative frameworks for responsible AI development.
"The Fourth Industrial Revolution" provides a broader context for understanding AI within the context of the broader technological and societal changes brought about by the digital revolution. It explores the implications of AI for the economy, society, and the future of work.
Save
"The Future of Humanity" takes a long-term perspective on the potential of AI, exploring its implications for the future of humanity and the universe. It discusses the potential for AI to transform society, solve global problems, and even lead to the creation of a new species.
"Hello, World" offers a more accessible introduction to AI and its implications for society, written for a general audience. It explores the potential benefits and risks of AI, as well as the ethical and societal challenges it raises.
Save
"Life 3.0" explores the potential of AI to transform human life and civilization. It discusses the potential for AI to enhance human intelligence, create new forms of life, and lead to a fundamental change in the nature of our existence.
Save
"Superintelligence" delves into the hypothetical concept of superintelligent AI, exploring its potential benefits and risks and discussing strategies for managing its development and use.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/b38q3b/responsible
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Effort
1 hour to complete
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
日本語
Transcript
English
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