Frankenstein and Banana

Welcome to Digitally Literate, issue #391. Your go-to source for insightful content on education, technology, and the digital landscape.

This week, I posted the following:

Stay tuned for more insights and discussions!

📲 The Ongoing Smartphone Debate

The debate on children’s use of smartphones is still a hot topic. Recently, policy changes have been made in a bid to control smartphone use; Florida has banned children under 14 from using social media, and the UK is tightening restrictions on smartphone use in schools. These actions stem from growing grassroots movements such as the Smartphone Free Childhood campaign, with parents expressing concerns about the impact of screen time and social media on their children’s mental health.

However, are smartphones truly harmful to mental well-being? Opinions vary. Some believe there is overwhelming evidence that smartphones negatively affect wellness. On the other hand, others argue that the data isn’t as damning as it seems. The ongoing discussions and countering viewpoints seem endless, often citing the same studies but interpreting them differently.

As anti-smartphone sentiments grow, understanding its impact on mental health remains complex. With strong opinions from both sides, it becomes crucial to delve into research and nuances as policies continue to develop. The smartphone saga continues with young minds arguably at stake.

🪟 Understanding Algorithms

Algorithms have a significant influence on our daily lives. They determine who passes and who fails in secondary school, who gets arrested and goes to prison, and they curate the news we see and what we miss. Moreover, algorithms drive the business models and revenues of some of the world’s largest digital platforms. Understanding their impact on our lives and society is crucial. Learn more about the omnipresence of algorithms.

LLM, or Large Language Model, is a type of machine learning model that uses a large volume of text data to learn patterns and predict the next word in a sentence. It works by using word vectors to understand the context and make accurate predictions. These models continually improve their predictions over time as they learn from more and more text data. Models like ChatGPT are examples of LLMs. They play a significant role in areas like natural language processing, translation, and content generation. Understanding how language models work involves decoding their ability to reason and predict words based on context. Connect here

The powerful algorithms of Big Tech lack accountability, posing risks to users’ rights and violating human rights standards. Companies harvest user data to optimize algorithms for profit without transparency or public accountability. Initiatives are required to make algorithmic systems transparent, accountable, and aligned with human rights principles. Explore

📝 Innovations in Teaching: AI Applications

Interested in incorporating AI into your teaching? Workshop kits from the Stanford Teaching Commons help you create customized professional development workshops on teaching topics. The DIY kits provide resources, agendas, and activities for educators to enhance their teaching practices using AI. Educators can use this guide to understand and incorporate AI tools in teaching practices. Educators can adapt and remix the workshop kits to meet their audience’s needs and improve the learning experience.

A teacher found a clever way to catch students using ChatGPT for essays by adding a hidden sentence in the prompt. The hidden sentences, like “Frankenstein and banana,” are visible to computers but not humans. This trick may help prevent cheating but could become widely known among students. Learn More

🧬 Honesty in Harmony

You are only afraid if you are not in harmony with yourself. People are afraid because they have never owned up to themselves.

Hermann Hesse

Thank you for being a part of Digitally Literate. Stay tuned for more insights and discussions. Reach out at or connect on social media.

Cover photo credits.

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