AI/ML in the News - Highlights 15 Nov 2024

The articles this week cover a wide range of AI/ML developments, from technical breakthroughs in large behavior models to novel applications in accounting, education, and creative fields. Key themes include the expanding capabilities and use cases of AI, ongoing challenges around ethics and regulation, and debates about AI’s impact on human skills and jobs - all highly relevant topics for university stakeholders to consider as AI reshapes education and the workforce.

There were some notable contradictions in perspectives on AI’s impact. While some articles highlighted AI’s potential to automate tedious tasks and augment human capabilities, others warned of AI eroding critical thinking skills and replacing human jobs. Additionally, views varied on whether current AI detection tools in education are reliable or prone to false positives.

A. Developments in AI/ML models

• Eliot (2024) describes the emergence of large behavior models (LBMs) that combine language models with behavioral capabilities, enabling more advanced AI for robotics. This development suggests AI is progressing beyond language processing to more complex physical world interactions.
• Mann (2024) provides a guide on fine-tuning large language models, explaining how techniques like QLoRA allow customization with less computational resources. This demonstrates how AI model development is becoming more accessible to a wider range of practitioners.

B. Applications of AI/ML for consumers and businesses

• Nuñez (2024) details how Puzzle’s AI-powered accounting platform aims to automate up to 90% of routine accounting tasks. This application shows how AI is being leveraged to transform traditional business processes and potentially reshape professional roles.
• Morrison (2024) describes O2’s AI-powered “granny” chatbot designed to waste scammers’ time, demonstrating a creative use of conversational AI for consumer protection. This illustrates how AI can be applied in unexpected ways to address societal issues.
• Robinson (2024) provides additional details on O2’s AI “granny” scam-fighting tool, explaining how it uses multiple AI models to engage scammers in lifelike conversations. This further demonstrates the sophistication of current AI conversation capabilities.

C. Social, Ethical and Regulatory Issues

• Hurley (2024) discusses a case where a student was falsely accused of using AI for an assignment, highlighting challenges with AI detection tools in education. This raises important questions about the reliability and fairness of AI detection methods in academic settings.
• Young (2024) explores educators’ mixed reactions to AI tools in classrooms, including concerns about critical thinking skills and potential benefits for students with disabilities. This debate reflects the complex implications of AI integration in education.
• Bramwell (2024) presents teachers’ firsthand accounts of AI’s impact on their classrooms, revealing both positive and negative effects on student learning and engagement. These perspectives offer valuable insights into the practical challenges of AI in education.
• Cordova (2024) argues that AI won’t make people better writers, emphasizing the importance of human creativity and intention in the writing process. This viewpoint challenges assumptions about AI’s role in creative fields.

The articles collectively paint a picture of AI/ML as a rapidly evolving field with far-reaching implications across industries and society. While technical advancements are expanding AI’s capabilities and applications, significant challenges remain in terms of ethics, regulation, and societal impact. For university stakeholders, staying informed about these developments is crucial for preparing students for an AI-transformed future and navigating the integration of AI in educational settings.

1. For marketing educators, the rapid advancement of AI technologies like large behavior models (Eliot 2024) and fine-tuning techniques (Mann 2024) suggests a need to continually update curricula to reflect the latest AI capabilities and their potential marketing applications. Educators should consider how these developments might reshape marketing strategies and consumer interactions.

2. The growing use of AI in business processes, as exemplified by Puzzle’s accounting platform (Nuñez 2024), indicates that marketing students should be prepared for AI-augmented work environments. Courses might need to incorporate training on AI tools and focus on higher-level strategic thinking that complements AI capabilities.

3. The ethical and social challenges surrounding AI, such as false accusations of cheating (Hurley 2024) and debates over AI’s impact on critical thinking (Young 2024; Bramwell 2024), highlight the importance of integrating ethics and critical analysis of AI into marketing education. Students should be equipped to navigate the complex implications of AI use in marketing and broader societal contexts.

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