This beginner-friendly course explores the ethical and legal foundations of using Generative AI in software engineering. Learn key ethical frameworks, understand common types of bias in AI-generated code, and explore their real-world impact on development. Delve into legal considerations like data privacy, transparency, explainability, and compliance. Through real case studies including racial bias in facial recognition and data breaches discover strategies to build fair, responsible, and legally compliant AI systems.
No prior AI ethics or legal knowledge is required. A basic understanding of software development is recommended.
By the end of this course, you will be able to:
- Explain core ethical frameworks guiding Generative AI development
- Identify and mitigate bias in AI-generated software code
- Understand legal risks around AI, including data privacy and licensing
- Apply best practices to ensure transparency and regulatory compliance
- Learn from real-world case studies to design trustworthy AI systems
Ideal for software engineers, developers, and AI practitioners seeking to build ethical, bias-aware, and legally compliant GenAI applications.
Explore the foundations of ethics and bias in Generative AI for software engineering. Learn key ethical frameworks, identify types of bias in AI-generated code, and understand their impact on software development. Discover strategies to mitigate bias through real-world case studies, including racial bias in facial recognition and data privacy breaches. Gain the skills to build fair, responsible, and trustworthy AI-powered software systems.
涵盖的内容
8个视频1篇阅读材料3个作业
显示有关单元内容的信息
8个视频•总计41分钟
Learning Objectives•4分钟
What is Ethics in Gen AI?•6分钟
Frameworks of Ethics•6分钟
Bias in GenAI-Generated Code and Its Types•4分钟
Impact of Bias in Software Developement•4分钟
Strategies for Mitigating Bias•7分钟
Case Study: Facial Recognition Software Used by Law Enforcement Exhibits Racial Bias in Identification•6分钟
Case Study: Data Breach Exposing Personal Information Collected by an AI Application•4分钟
1篇阅读材料•总计10分钟
Course Syllabus•10分钟
3个作业•总计70分钟
Assessment for Foundations of Ethics and Bias in Generative AI•40分钟
Quiz on Ethics in GenAI Foundations•15分钟
Quiz on Addressing Bias in GenAI Code and Decisions•15分钟
Legal Implications and Best Practices in Generative AI
第 2 单元•小时 后完成
单元详情
Understand the legal implications and best practices for using Generative AI in software engineering. This module covers key ethical and legal considerations including AI transparency, data privacy, licensing, and compliance. Learn how to ensure explainability, preserve user privacy, and maintain continuous monitoring. Explore real-world examples and adopt best practices to build legally compliant, ethical AI systems.
涵盖的内容
10个视频3个作业
显示有关单元内容的信息
10个视频•总计44分钟
Transparency and Explainability•6分钟
Preserving Privacy•4分钟
Continuous Monitoring and Evaluation•3分钟
Collaboration and Openness•3分钟
Overview of Ethical and Legal Considerations•8分钟
AI Bias and Transparency•5分钟
Data Privacy and It's Example•6分钟
Licensing and Compliance•5分钟
Best Practices for Ethical and Legal Compliance•3分钟
Key Takeaways•2分钟
3个作业•总计70分钟
Assessment for Legal Implications and Best Practices in Generative AI•40分钟
Quiz on Legal Implications in GenAI Application•15分钟
Simplilearn is a global leader in digital upskilling, offering highly specialized training in emerging technologies and processes shaping the digital economy's future. We focus on innovations transforming the digital landscape while significantly reducing costs and time compared to traditional methods. More than one million professionals and 2,000 corporate training organizations have benefited from our award-winning programs to achieve their career and business goals.
This course is ideal for software engineers, developers, AI practitioners, and anyone involved in building or managing AI-powered software systems.
Do I need prior experience in ethics or law?
No prior experience is required. A basic understanding of software development is recommended to follow technical examples and case studies.
What will I learn in this course?
You’ll learn key ethical frameworks, how to identify and mitigate bias in AI-generated code, and how to ensure transparency, data privacy, and legal compliance in AI systems.
Are there hands-on activities included?
Yes, the course includes real-world case studies and scenarios such as racial bias in facial recognition and data breaches to help you apply ethical and legal best practices effectively.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.