TL;DR:

• AI-generated essays are a growing concern in education.
• OpenAI developed a watermarking solution to detect AI-generated text.
• Competition among AI providers hinders the implementation of watermarking.
• Regulatory efforts, like the California Digital Content Provenance Standards, aim to address this issue.
• The future of AI in education requires innovative assessment methods.

In the rapidly evolving world of artificial intelligence (AI), one application has sparked significant debate: AI-generated essays. As the new school year begins, teachers and educators are grappling with the reality that AI tools like ChatGPT can produce essays that are virtually indistinguishable from human-written ones. This shift has rendered traditional essay assignments less effective, forcing educators to adapt their teaching methods.

The Rise of AI in Education

AI has revolutionised many aspects of our lives, and education is no exception. Generative AI, in particular, has proven exceptionally adept at creating essays. This is because there are abundant examples of essays in AI training data, and the demand for such content is high. Additionally, the standards for essay quality and originality in student work are relatively low, making it an ideal task for AI.

The Challenge of Detecting AI-Generated Text

Currently, detecting AI-generated essays is a formidable task. While several tools claim to identify AI-generated text, their reliability is questionable. Accusing students of plagiarism based on unreliable tools can have serious consequences, making it crucial to find a more accurate solution.

The Solution: AI Watermarking

In 2022, a team at OpenAI, led by quantum computing researcher Scott Aaronson, developed a groundbreaking solution known as “watermarking.” This technique makes AI-generated text virtually unmistakable, even if the user makes minor changes. The watermarking process involves altering the AI’s text generation method to include a nonrandom element, favouring certain tokens based on a secret scoring rule.

For example, the AI might favour words containing the letter ‘V’ slightly more than usual. While this change is subtle and unlikely to be noticed by readers, it creates a detectable pattern that OpenAI can use to verify the text’s origin. This innovative solution could significantly reduce the problem of AI-generated essays masquerading as human-written work.

The Competitive Barrier

Despite the potential benefits of watermarking, OpenAI and other AI providers have not implemented this solution. The reason lies in competition. If OpenAI were the only provider to implement watermarking, users would simply switch to other AI tools like Meta’s Llama, Anthropic’s Claude, or Google’s Gemini. This would not solve the plagiarism issue and could lead to OpenAI losing its user base.

The Role of Regulation

To address this competitive barrier, regulatory intervention may be necessary. The California Digital Content Provenance Standards bill, introduced this year, aims to require generative AI providers to make their AI-generated content detectable. OpenAI supports this bill, as they are the only known provider with a working watermarking system. However, other AI providers are largely opposed to such regulations.

While watermarking could be a valuable tool, its implementation faces significant challenges. Open AI models, which can be run on personal computers, are already widely available. Adding watermarking to these models is not feasible, as anyone can use the current versions regardless of future updates.

Adapting to AI in Education

Given the challenges of implementing watermarking, educators must find alternative ways to assess students. Many teachers are already adopting in-class essay requirements and other innovative methods to reduce cheating. Additionally, the use of AI-generated content in college admissions essays is likely to decrease, as these essays may not be the best way to evaluate students.

The Future of AI and Education

The debate over AI-generated essays highlights a broader issue: the rapid pace of AI development often outstrips society’s ability to regulate and adapt. While AI offers numerous benefits, it also presents challenges like impersonation and plagiarism. Finding a balance between harnessing AI’s potential and mitigating its downsides will be crucial as AI continues to evolve.

Comment and Share:

What do you think about the future of AI in education? How can we ensure that AI is used ethically and responsibly in our classrooms? Share your thoughts and experiences in the comments below, and don’t forget to subscribe for updates on AI and AGI developments.

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• To learn more about AI water marking tap.

TL;DR:

• Coursera introduces GenAI for Teams to help businesses apply generative AI skills.
• The program includes hundreds of courses tailored to software, data, and marketing teams.
• Seven new generative AI courses and specializations are now available.
• Eight entry-level Professional Certificates have been updated with generative AI content.

Unleashing Innovation with Coursera’s GenAI for Teams

Coursera, the renowned learning platform, has expanded its Generative AI Academy with a new offering designed specifically for teams. GenAI for Teams aims to equip businesses with the skills and best practices needed to apply generative AI in unique and innovative ways. This program complements the existing GenAI for Everyone and GenAI for Executives programs, offering a comprehensive suite of courses tailored to various business functions.

Unlocking Productivity Across Critical Functions

GenAI for Teams provides a rich catalog of hundreds of courses aimed at unlocking innovation and productivity across critical business areas. The program is divided into three main topic areas:

Gen AI for Software and Product Teams

• Generative AI for Software Developers by IBM
• Developing with GitHub Copilot and VS Code by Microsoft
• Responsible AI for Developers by Google Cloud

Gen AI for Data Teams

• Generative AI for Data Scientists by IBM
• GenAI in Data Analytics by Meta
• Practical Steps for Building Fair AI Algorithms by Fred Hutch Cancer Center

Gen AI for Marketing Teams

• GenAI for Social Media Marketing by Meta
• Content Marketing Using Generative AI by the University of Virginia Darden
• Generative AI for the Resilient Pricer by Dartmouth College

New Generative AI Courses and Specializations

Coursera has also introduced seven new generative AI courses, specializations, and certificates to help learners develop their skills in this cutting-edge field:

• Generative AI for Software Development Skills Certificate from DeepLearning.AI
• Artificial Intelligence Graduate Certificate from the University of Colorado Boulder
• Generative AI in Marketing Specialization from UVA Darden
• Programming with Generative AI course from Indian Institute of Technology Guwahati
• Responsible Generative AI Specialization from the University of Michigan
• Change Management for Generative AI course from Vanderbilt University
• Generative AI for Kids, Parents, and Teachers course from Vanderbilt

Updated Professional Certificates with Generative AI Content

Eight of Coursera’s entry-level Professional Certificates have been updated to include generative AI-related content, such as projects, readings, and videos. These certificates include:

• Data Analyst from IBM
• Data Engineering from IBM
• Data Science from IBM
• Full Stack Software Developer from IBM
• Cybersecurity Analyst from Microsoft
• Power BI Data Analyst from Microsoft
• Marketing Analytics from Meta
• Social Media Marketing from Meta

The Importance of Generative AI Skills

Generative AI is transforming industries by enabling the creation of new content, products, and services. As businesses increasingly adopt these technologies, the demand for professionals with generative AI skills is growing. Coursera’s GenAI for Teams program is designed to meet this demand by providing comprehensive training that empowers teams to leverage generative AI effectively.

“Generative AI has the potential to revolutionize how we work and innovate. Our new GenAI for Teams program is designed to equip professionals with the skills they need to harness this powerful technology and drive meaningful change in their organizations.” – Jeff Maggioncalda, CEO of Coursera

By offering a rich catalog of courses and resources, Coursera is empowering professionals to drive innovation and productivity in their organisations.

External Resources for Further Learning

For more information on Coursera’s Generative AI Academy and the GenAI for Teams program, visit the Coursera blog.

Additionally, you can explore case studies and examples of AI and AGI applications in Asia through resources like the AI in Asia website, which provides insights into the latest developments and innovations in the region.

Comment and Share:

What generative AI skills do you think are most important for your field? How do you plan to apply what you learn from Coursera’s GenAI for Teams program? We invite you to share your thoughts and experiences in the comments below. Don’t forget to subscribe for updates on AI and AGI developments.

You may also like:

For more information on Coursera’s Generative AI Academy and the GenAI for Teams program, visit the Coursera blog.

TL;DR:

• Stanford offers 5 free AI courses to help you become an AI expert.
• Over 70% of companies are looking for AI experts, making it a high-demand skill.
• Courses cover Python, Machine Learning, AI principles, and the societal impact of AI.

Become an AI Expert with These 5 Free Stanford Courses

Are you eager to learn about Artificial Intelligence (AI)? You’re in luck! Stanford University offers five fantastic courses to help you kickstart your AI journey, and the best part is, they’re all free! In today’s world, AI has been applied in numerous businesses, creating immense value. Consequently, there’s a high demand for AI experts, with over 70% of companies seeking professionals who can leverage AI tools effectively.

So, let’s dive into these AI courses from Stanford University and help you become an AI expert!

Statistical Learning with Python

To excel in AI, you must first understand statistical methodologies and Python programming. This course teaches you basic statistical methods, supervised learning, and the use of Python. You’ll become familiar with statistical modeling, which will help you grasp the concepts in the subsequent courses. Stanford also provides a free book to accompany this course on their website.

CS229: Machine Learning

Machine Learning (ML) is a crucial subset of AI, and modern AI tools require a strong ML foundation. In this course, you’ll learn about supervised learning, unsupervised learning, learning theory, reinforcement learning, adaptive theory, and ML applications. This course will strengthen your ML foundation, which is essential for understanding and developing AI.

Intro to Artificial Intelligence

This course covers the basics of AI, making it perfect for beginners. With 22 lessons and 9 practice exams, you’ll learn about probability, ML, game theory, computer vision, robotics, and natural language processing. These lessons will give you the confidence to explore AI in more depth.

CS221: Artificial Intelligence: Principles and Techniques

This advanced course delves deeper into AI, teaching various techniques for implementing AI systems. You’ll learn about search, Markov decision processes, game playing, constraint satisfaction, graphical models, and logic. It’s recommended that you revisit the foundational courses before taking this one.

The AI Awakening: Implications for the Economy and Society

In this short course, you’ll learn about the impact of AI on the economy and society. It covers the risks and benefits of AI, helping you understand the broader implications of this technology. This course is essential for anyone looking to make a difference in the AI field.

Comment and Share:

Have you taken any of these Stanford AI courses? How have they helped you in your AI journey? Share your experiences below and don’t forget to subscribe for updates on AI and AGI developments at AI in Asia. Let’s build a community of AI enthusiasts and learn together!

You may also like:

• Top AI Courses to Boost Your ChatGPT Skills for Free
• Unleash Your Potential with Google’s Free AI Courses
• Unleash Your Potential with IBM’s Free AI Fundamentals Course
• To check out Stanford’s free online courses tap here.