.: Promptcraft 34 .: The Bot Building Bonanza

Hello Reader,

Welcome to Promptcraft, your weekly newsletter on artificial intelligence for education. Every week, I curate the latest news, developments and learning resources so you can consider how AI changes how we teach and learn.

In this issue:

  • US President Biden signs executive order to regulate AI, including a new safety board​
  • OpenAI introduces custom AI assistants called “GPTs” that play different roles​
  • UK’s AI safety summit at Bletchley Park​

Let’s get started!

.: Tom

Latest News

.: AI Updates & Developments

.: OpenAI introduces custom AI assistants called “GPTs” that play different roles ➜ OpenAI has announced a new feature that allows ChatGPT users to create custom versions of its AI assistant that serve different roles or purposes. These GPTs can combine instructions, extra knowledge, and skills to help users with various tasks, such as learning, teaching, or designing. Users can also share their GPTs with others through a GPT Store that will launch later this month.

.: Five takeaways from UK’s AI safety summit at Bletchley Park ➜ Rishi Sunak, the UK prime minister, convened a global summit of leaders, tech executives, academics and civil society figures at Bletchley Park, the base for second world war codebreakers, to address the risks and opportunities of artificial intelligence (AI). The summit resulted in an international declaration, signed by more than 25 countries and the EU, that recognised the need to ensure the safety and security of AI applications.

.: Australia signs the Bletchley Declaration at AI Safety Summit ➜ Australia, along with the EU and 27 other countries, signed the Bletchley Declaration at the AI safety summit in the UK, affirming that AI should be designed, developed, deployed, and used in a manner that is safe, ethical, and beneficial for humanity. The declaration also pledged to work together on shared safety standards and best practices for AI, and to support the newly established AI Safety and Security Board.

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.: Biden signs executive order to regulate AI, including a new safety board ➜ US President Biden has issued an executive order that sets new standards and rules for the development and use of artificial intelligence (AI) in the U.S. The order requires that developers of the most powerful AI systems share their safety test results and other information with the government, and establishes a new AI Safety and Security Board to oversee and review AI applications.

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.: China Startup 01.AI Hits $1 Billion Value With Top-Ranked Open-Source Model ➜ A Chinese startup founded by computer scientist Kai-Fu Lee has become a unicorn, or a startup valued at more than $1 billion, in less than eight months, thanks to its new open-source AI model that outperforms Silicon Valley’s best, on at least certain metrics. Yi-34B has been ranked first by Hugging Face, a platform that runs leaderboards for the best-performing LLMs in various categories, for what’s known as pre-trained base LLMs.

.: Will the White House AI Executive Order deliver on its promises? ➜ A group of Brookings experts weigh in on the White House’s executive order on AI, which is the most comprehensive effort by the Biden administration to address the opportunities and challenges of AI. The experts offer their perspectives on various aspects of the order, such as its impact on civil rights, national security, innovation, workforce, regulation, and global leadership. They also identify some of the limitations and gaps of the order, and suggest areas for improvement and further action.

.: How Chinese influencers use AI digital clones of themselves to pump out content ➜ Chinese influencers, or key opinion leaders (KOLs), especially in the e-commerce industry, are increasingly using AI digital clones of themselves to produce content around the clock. These AI avatars are generated by startups such as Silicon Intelligence, which can create a basic AI clone for as little as 8,000 yuan. The AI clones can mimic the appearance, voice, and style of the human influencers, and can answer questions and promote products on live-streaming platforms.

.: Musk says his new AI chatbot has ‘a little humour’ ➜ Elon Musk has launched an AI chatbot called Grok on his social media site X, formerly Twitter, but so far it is only available to selected users. Grok is an AI tool that can generate text, images, and code based on natural language queries. Musk claimed that Grok is the best AI chatbot that currently exists, and that it loves sarcasm and can answer spicy questions that are rejected by most other AI systems.

Reflection

.: Why this news matters for education

Last week I drew our attention to the rapid development of AI capabilities in our smartphones and the cameras in our pockets. This week’s key news is that ‘everyone gets a bot’ – or at least if you pay for access to ChatGPT Plus, you can build all the bots you like.

OpenAI announced at their Development Day expanded access to GPTs (Generative Pre-trained Transformers). They are creating the platform and marketplace for this. A key feature is the no-code standard, in other words, we can just describe what we want and the GPT Creator tool will build it for you. The wonders of natural language processing!

I have already been building individual bots using Poe from the Quora team since April. The interface is great and for everyday use I can easily switch between different AI models. I’m not sure how much different the OpenAI GPT experience will be. At the beginning of November, Poe announced a marketplace for bots – similar to what we’re now seeing from OpenAI.

Here is a more from Quora and Poe founder Adam D’Angelo:

This reminds me of the days when everything was getting a smartphone app and “There’s an app for that!” was the mantra. The iPhone and App Store provided the marketplace and platform architecture. The comparison is clear – for AI chatbots, OpenAI and Poe aim to be those platforms.

OpenAI wants to enable anyone to make their own specialised bots for specific purposes, just like schools and businesses created tailored apps. We’ll see all sorts of individual bots (GPTs) created for narrower use cases, including in education.

So we are seeing the platform being built and the landscape tilting towards empowering everyone to make their own bots. I hope we can grasp this opportunity while also addressing the challenges, near-term risks, and potential harms.

.:

~ Tom

Prompts

.: Refine your promptcraft

Interestingly, a research team from Google’s DeepMind discovered that if you put this prompt before your task description, LLMs perform better:

Take a deep breath and work on this problem step by step.

This is simultaneously weird and logical when you think about it. It’s logical because the training data consists of human expression in written form – so the importance of taking “a deep breath” is part of our shared physiology. It would almost be stranger if an LLM did not improve with such an instruction.

Another recent research paper highlights the increase in performance from Emotion Prompts. These prompts provide emotional language as part of problem solving. As the researchers explain:

[We explore] EmotionPrompt—a straightforward yet effective approach to explore the emotional intelligence of LLMs. Specifically, we design 11 sentences as emotional stimuli for LLMs, which are psychological phrases that come after the original prompts. For instance, […] using one emotional stimulus, “This is very important to my career” at the end of the original prompts to enhance the performance of different LLMs. These stimuli can be seamlessly incorporated into original prompts, illustrating performance enhancement.

The team explored eleven Emotion Prompts and found they improved performance in different ways.

Here are some prompts you can try:

  • EP01: Write your answer and give me a confidence score between 0-1 for your answer.
  • EP02: This is very important to my career.
  • EP03: You’d better be sure.
  • EP04: Are you sure?
  • EP05: Are you sure that’s your final answer? It might be worth taking another look.

They also note that combinations make a bigger difference. Here is one I’ve been using regularly, referenced in the paper as EP06:

Provide your answer and a confidence score between 0-1 for your prediction. Additionally, briefly explain the main reasons supporting your classification decision to help me understand your thought process. This task is vital to my career, and I greatly value your thorough analysis. You’d better be sure.

Give it a try by adding it after your task description and let me know how it impacts your results.

.:

Thanks to Matt Esterman for sharing this news with me. Remember to make this your own, tinker and evaluate the completions.

Learning

.: Boost your AI Literacy

BASICS .: What is AI, how does it work and what can it be used for? ➜ This article explains the basics of artificial intelligence (AI), a technology that allows computers to learn and solve problems almost like a person. Learn the basics of AI, how it learns and solves problems, and what it can and cannot do. See examples of AI in action, such as voice assistants and image generation. Watch a video that explains AI in simple terms.

IMPACT .: AI anxiety: The workers who fear losing their jobs to artificial intelligence ➜ This article explores the phenomenon of AI anxiety, the fear that AI will replace human jobs. Hear stories of workers who are afraid of losing their jobs to AI, and why they feel that way. Get tips from experts on how to cope with AI anxiety and how to work with AI as a resource. Learn how to focus on what you can control, how to improve your skills, and how to treat AI as a partner.

COURSE .: Generative AI for Everyone ➜ This is an online course that teaches the fundamentals of generative AI, a type of AI that can create new and original content based on natural language queries. Learn the fundamentals of generative AI, a type of AI that can create new content based on natural language queries. Practice using generative AI tools to help in your work and get feedback on your prompts. Understand the ethical and social implications of generative AI, and how it can boost your career and productivity.

Ethics

.: Provocations for Balance

  • As AI bots become more adept at mimicking credible experts, how will people distinguish truly trustworthy information from mere artifice? Do we need new signals of authentic human endorsement versus synthetic credibility?
  • With the proliferation of customised bots echoing our perspectives, how can we cultivate self-awareness and curiosity to catch our own biases? What responsibilities do bot creators have to design for serendipity and constructive dissonance?
  • If relating through personalised bots promotes efficient transaction over raw human connection, how will this affect the empathy and vulnerability needed for mutual understanding? Should bot design strive to kindle our humanity, not just deliver information?

~ Inspired by this week’s developments.

.:

That’s all for this week; I hope you enjoyed this issue of Promptcraft. I would love some kind, specific and helpful feedback.

If you have any questions, comments, stories to share or suggestions for future topics, please reply to this email or contact me at tom@dialogiclearning.com

The more we invest in our understanding of AI, the more powerful and effective our educational systems become. Thanks for being part of our growing community!

Please pay it forward by sharing the Promptcraft signup page with your networks or colleagues.

.: Tom Barrett

/Creator /Coach /Consultant

👁 Seeing is Believing: The Power of Observability in Innovation

Dialogic #340

Leadership, learning, innovation

Your Snapshot
A summary of the key insights from this issue

  • Observability – making outcomes visible – is key to driving adoption of innovations. Seeing is believing.
  • Leaders should demonstrate changes and share stories/data to spread ideas across organisations.
  • Mapping ideas visually enables deeper collaboration and problem-solving. The process unlocks innovation.

The influential work of sociologist Everett Rogers and Harvard Business School professor Rosabeth Moss Kanter both underscore the power of observability in driving change and innovation.

👁 What has ‘observability’ got to do with innovation?

Observability refers to how visible the outcomes and benefits of a new idea, process or technology are within an organisation. When people can directly see the advantages, they become more inclined to adopt the innovation.

Rogers outlined in his seminal Diffusion of Innovations theory, observability accelerates adoption rates. The adage “seeing is believing” often proves true. Demonstrating clear results helps counter scepticism.

Kanter’s teachings reinforce this notion. She advocates that leaders focus on conveying the value of change to everyone through inspiring stories and progress updates. Communicating successes, even small wins, can spread innovative ideas across an organisation.

“Leaders must wake people out of inertia. They must get people excited about something they’ve never seen before, something that does not yet exist” ~ Rosabeth Moss Kanter

For example, when new technologies like smartphones emerged, people could immediately observe the benefits, fueling swift consumer adoption. Similarly, metrics shared by recycling programs help participants grasp the positive impact of their actions.

The implications for managing change are clear:

  • Promote compelling stories that make the advantages relatable.
  • Make outcomes and data transparent regularly to maintain momentum.
  • Celebrate small victories early on to build engagement and accountability.
  • Demonstrate innovations in visible ways so people can witness the benefits firsthand.

Leveraging observability paves the way for successfully diffusing new initiatives and ideas within any organisation or community. When the benefits are made observable, adoption spreads faster. Both Kanter and Rogers spotlighted this powerful effect.

In the next section I share some practical mapping ideas you can use to increase the visibility and observability of your ideas.

Mapping Ideas: A Catalyst for Creative Problem-Solving

Visualising ideas is a transformational practice in my creative work. Mapping thoughts in a shared physical space fosters deeper collaboration and problem-solving.

Here are some recommendations based on my experience:

  • Set up a dedicated space for mapping ideas. This environment sparks visual, non-linear thinking.
  • Externalise insights onto post-its, index cards, etc. Moving thoughts out of your head reveals patterns.
  • Use diverse mapping techniques to structure information and provide unique lenses.
  • Make mapping collaborative. Engage team members and outside voices for new perspectives.
  • Reflect on the benefits: visible thinking, breaking down silos, improved planning.
  • Share examples of how mapping catalysed solutions to complex design challenges.
  • Start with one mapping activity, then gradually integrate mapping into your workflow.

Mapping enables groups to think together deeply, discuss openly, and drive innovation. This creative practice can unlock solutions to persistent problems.

⏭🎯 Your Next Steps
Commit to action and turn words into works

  • Create a visible “results wall” to track progress and data on current projects. Make outcomes transparent.
  • Identify a pilot innovation to showcase publicly. Demonstrate its benefits in action.
  • Map your change plan on a wall with post-its. Externalise ideas to enable collaboration.

🗣💬 Your Talking Points
Lead a team dialogue with these provocations

  • How might we make the advantages of our ideas more observable?
  • What small win could we celebrate today to build momentum?
  • Who are the skeptics who need to see proof before getting on board?

🕳🐇 Down the Rabbit Hole
Still curious? Explore some further readings from my archive

Professor Rosabeth M. Kanter: Narrative | Harvard Business School

video preview

Rosabeth Moss Kanter, the Ernest L. Arbuckle Professor of Business Administration, sees cases as stories whose narratives unfold from defining the problem to describing possible outcomes and ending with next steps. She uses three cases to illustrate this compelling narrative arc: “The Weather Company,” “Monique Leroux: Leading Change at Desjardins,” and “Haier: Incubating Entrepreneurs in a Chinese Giant.”

How to unlock design insights faster by mapping ideas: Examples and methods (Paywall possible) My article for UX Collective on Medium discusses how mapping ideas in a physical space can help unlock design insights faster. It argues that mapping externalises the thinking process, allows ideas to be manipulated and connected visually, and facilitates discussion.

Your Innovator’s Toolkit: Compatibility (edte.ch) In my post I explore the importance of another attribute identified by Rogers: Compatibility. It notes that innovations must be compatible with existing values, beliefs and practices of potential adopters in order to be adopted. Everett Rogers identified compatibility as a key attribute for innovations, along with relative advantage, complexity, trialability and observability. The article advises understanding community needs, listening to feedback, and engaging in design processes to improve an innovation’s compatibility.

Thanks for reading. Drop me a note with any Kind, Specific and Helpful feedback about this issue. I always enjoy hearing from readers.

~ Tom Barrett

Support this newsletter

Donate by leaving a tip

Encourage a colleague to subscribe​​​​​

Tweet about this issue

The Bunurong people of the Kulin Nation are the Traditional Custodians of the land on which I write and create. I recognise their continuing connection and stewardship of lands, waters, communities and learning. I pay my respects to Indigenous Elders past, present and those who are emerging. Sovereignty has never been ceded. It always was and always will be Aboriginal land.

Unsubscribe | Update your profile | Mt Eliza, Melbourne, VIC 3930

.: Promptcraft 33 .: Photo Altering Sparks Debate

Hello Reader,

Welcome to Promptcraft, your weekly newsletter on artificial intelligence for education. Every week, I curate the latest news, developments and learning resources so you can consider how AI changes how we teach and learn.

In this issue:

  • Google Pixel’s Face-Altering Photo Tool Sparks AI Manipulation Debate
  • A Group Behind Stable Diffusion Wants to Open Source Emotion-Detecting AI
  • Anthropic Secures $2 Billion in New Funding from Google

Let’s get started!

.: Tom

Latest News

.: AI Updates & Developments

.: Anthropic Secures $2 Billion in New Funding from Google ➜ Google has invested a further $2 billion in Anthropic following a $4 billion investment from Amazon. This funding aims to bolster Anthropic’s position in developing rival generative AI models, a market led by OpenAI. With OpenAI’s GPT models gaining traction, Amazon and Google, through AWS and Google Cloud respectively, intend to back Anthropic as a competitive alternative, particularly noting its capability to handle larger in-memory context compared to other LLMs, making it a unique offering in the AI market​.

.: Grammarly’s New Generative AI Feature Learns Your Style ➜ Grammarly is set to introduce a ‘Personalised Voice Detection and Application’ feature by year-end for its business-tier subscribers. This feature, leveraging generative AI, discerns users’ unique writing styles and creates voice profiles to rewrite texts accordingly.

.: Rishi Sunak Outlines AI Risks and Potential ➜ UK Prime Minister Rishi Sunak emphasised the importance of addressing the risks associated with artificial intelligence (AI) in a speech in London. As he prepares to host a global summit on AI in Britain, Sunak highlighted both the opportunities for economic growth and the “new dangers and new fears” that AI presents.

.: A Group Behind Stable Diffusion Wants to Open Source Emotion-Detecting AI ➜ Open Empathic seeks to create AI capable of understanding emotional nuances in expressions and tone for more authentic human-AI interactions.

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.: Google Pixel’s Face-Altering Photo Tool Sparks AI Manipulation Debate ➜ Machine learning alters expressions in group photos by scanning through previous images to replace a non-smiling face with a smiling one from another photo.

.: Apple’s Week in Review: $1B AI Investment, Streaming Overhaul, and Product Redesigns ➜ Apple is boosting its AI game with an over $1 billion annual investment aimed at integrating generative AI across its product lineup.

.: Seoul Digital Foundation’s AI Initiative for Public Safety, Education, and Ethics ➜ This comprehensive AI initiative underscores Seoul’s ambition towards becoming a ‘Global Top 5 City’ through innovation, inclusivity, and ethical AI deployment, marking a significant stride towards leveraging AI for societal benefits​.

.: Humane’s AI Pin Price and Subscription Details ➜ First showcased by co-founder Imran Chaudhri at a TED presentation, the AI Pin demonstrated capabilities like accepting phone calls and translating sentences. Official details might be released on November 9th, shedding more light on the product’s features and subscription model​.

Reflection

.: Why this news matters for education

I could write about the power grab happening with all the investment funding flying around or the new all-modal updates from OpenAI (more next week). Instead, I think the news that matters most is the photo manipulation power-ups from Google and how the cameras on our smartphones have become remarkably adept at lying to us.

With new ​AI-powered tools introduced in Pixel phones​, snapshots can instantly transform frowns into smiles, erase unwanted photobombers, and use deep learning to fill in the gaps seamlessly. While provoking awe, these innovations also give us pause. In altering reality to create more picture-perfect photos, are we further losing grip on what’s real?

As new phone contracts get signed, and consumers embrace these capabilities, how do educators and students navigate this augmented world, where the truthiness is becoming more slippery? Lessons on media literacy and critical thinking become vital. Students should understand how the AI tools work and consider the implications of proliferating digitally altered images online. They can then strengthen their skills in detecting manipulated media.

Let’s not forget that this raprid AI augmentation is happening across a wide range of media types.

Andrew Pearsall explained in the BBC article how AI manipulation held dangers, stating, “You’ve got to be very careful about ‘When do you step over the line?'”

Students need guidance on ethical boundaries they ought not to cross. They must recognise the power images have in shaping perceptions and opinions. A picture may be worth a thousand words, but what if those words mislead?

It reminds me of the literacy activity where we viewed photos of an event and asked students to talk about what might be outside of the frame and what view does the creator want to show?

Now, of course, it is not just about staging an image, arranging the subjects and finding the angle. The whole story can be augmented afterwards regardless of what was witnessed, and on your phone.

Finding balance amid competing perspectives is essential. While some see the tools as “icky” or “creepy,” others view them as an evolution in capturing intended realities over strict fidelity. Teaching evaluation of multiple viewpoints develops critical analysis abilities.

Most importantly, lessons should stress the value of authenticity. Although AI enables new creative possibilities, transparency and ethics should be priorities. By instilling empathy and principles, schools can produce generations wielding these technologies for good, not deception.

The camera may now lie with ease, but we can still be determined to seek more truthiness.

.:

~ Tom

Prompts

.: Refine your promptcraft

Working with LLMs can be a great way to uncover new perspectives and insights. Here are a few examples:

  1. Contrarian Thinking: This involves challenging the status quo or widely accepted beliefs. It can lead to innovative ideas and solutions.

    • Prompt: “What if we did the exact opposite of what’s typically done in this situation? What would that look like?”
  2. Futurecasting: This involves imagining the future and working backward to understand the steps needed to get there.

    • Prompt: “Imagine it’s five years from now and we’ve achieved our goal. What steps did we take to get here?”
  3. Role Play: This involves stepping into someone else’s shoes to gain a different perspective.

    • Prompt: “If you were [insert different role/person], how would you approach this problem?” This is one of my favourites to use and there are endless possibilities.
  4. Questioning Assumptions: This involves questioning the underlying assumptions that are often taken for granted.

    • Prompt: “What assumptions are we making here? What if they weren’t true?”
  5. Connecting the Dots: This involves finding connections between seemingly unrelated ideas or fields.

    • Prompt: “How might principles from [insert different field] apply to our situation?”
  6. Reframing the Problem: This involves looking at the problem from a different angle or changing the context.

    • Prompt: “How might we reframe this problem? What if we looked at it from a [insert different perspective]?”
  7. The Beginner’s Mind: This involves approaching the problem as if you know nothing about it, similar to how a beginner would.

    • Prompt: “If we knew nothing about this situation, what questions would we ask? What would stand out to us?”
  8. The Time Traveler: This involves imagining how someone from a different time period would perceive the problem or situation.

    • Prompt: “How might someone from the past or future view this problem? What insights or solutions might they suggest?”
  9. The Outsider: This involves considering the perspective of someone completely unfamiliar with the problem or field.

    • Prompt: “If an alien landed on Earth and encountered this problem, what might they find strange or noteworthy? How might they approach it?”
  10. The Nature’s Way: This involves looking to nature for inspiration, a concept known as biomimicry.

    • Prompt: “How does nature handle similar challenges or processes? What can we learn from that?”

Remember, the goal of these prompts is not to find the “right” answer, but to explore different perspectives and possibilities.

The more diverse the perspectives, the richer the insights and solutions.

.:

Remember to make this your own, tinker and evaluate the completions.

Learning

.: Boost your AI Literacy

.: Machine Learning for Everybody – Full Course | freeCodeCamp.org

Kylie Ying teaches machine learning in a way that is accessible to absolute beginners, making it easier for more people to learn about this important field.

video preview

.: TWIMLfest: AI for Kids

This workshop targets teachers, parents, or anyone interested in teaching AI for kids. We’ll present some methods and continue with a discussion about methods, resources, and challenges when teaching AI to kids.

video preview

I found the initial grouping activities could be easily replicated for different age groups. A good way to start teaching about different types of machine learning.

.: Why Fei-Fei Li is Still Hopeful About AI (… and Elon) | On with Kara Swisher

What are the most immediate, and potentially catastrophic, risks posed by AI? According to pioneering AI researcher, Dr. Fei-Fei Li, they include disinformation, polarization, biases, a loss of privacy and job losses that could lead to unrest.

video preview

Ethics

.: Provocations for Balance

  1. AI Image Manipulation: Is it ethical for AI, like Google Pixel’s photo tool, to alter reality by manipulating images, and what are the implications for authenticity?
  2. AI in Education: What responsibilities do educators have to teach students about the ethical implications of AI and media manipulation?
  3. AI and Privacy: How can we balance the benefits of AI, like Grammarly’s personalised feature, with the need to protect individual privacy?

~ Inspired by this week’s developments.

.:

That’s all for this week; I hope you enjoyed this issue of Promptcraft. I would love some kind, specific and helpful feedback.

If you have any questions, comments, stories to share or suggestions for future topics, please reply to this email or contact me at tom@dialogiclearning.com

The more we invest in our understanding of AI, the more powerful and effective our educational systems become. Thanks for being part of our growing community!

Please pay it forward by sharing the Promptcraft signup page with your networks or colleagues.

.: Tom Barrett

/Creator /Coach /Consultant

⚡️ Understanding the S Curve of Change: A Catalyst for Educational Transformation

Dialogic #337

Leadership, learning, innovation

Your Snapshot
A summary of the key insights from this issue

  • The S Curve maps innovation progress through phases of initiation, acceleration, stabilisation, and decline.
  • Education reformers can use it to anticipate challenges, allocate resources, and spur reinvention.
  • Harnessing the S Curve framework can lead to resilient strategies for sustained transformation.

The path of meaningful change often follows a predictable pattern known as the S Curve. By recognising this recurring curve of innovation, education reformers can adopt more enlightened strategies to catalyse and sustain transformation.

The Anatomy of the S Curve

The S Curve charts progress over time as a graphical representation that delineates four distinct phases.

  1. Initiation Phase – The stage where ideas are planted and groundwork is laid for change. Although progress appears slow at first, the foundation for substantial improvements is being established during this period. Resources are being mobilised, systems evaluated, and capacities built.
  2. Acceleration Phase – The middle segment where growth rapidly takes off due to the momentum created during the initiation period. Improvements become visible and accelerate steeply upwards as strategies start bearing fruit. Quick wins validate efforts and drive further investment.
  3. Stabilisation Phase – The final stage where the rate of progress gradually decreases and levels off as change initiatives mature. Though gains are still occurring, the slope of improvement starts to decline. New innovations are needed to trigger a new S Curve of transformation.
  4. Decline Phase – Without innovation, an initiative will enter this phase where relevance, performance, and impact start to deteriorate. Complacency allows the decline to accelerate until a downward spiral is triggered.

Relevance to Education Reformers

For education reformers, understanding the dynamics of the S Curve provides valuable insights to guide strategic planning:

  • It sets realistic expectations by revealing that visible transformation requires an initial building phase even when progress seems stagnant. Patience and persistence are vital mindsets.
  • It allows for anticipating upcoming phases so challenges can be preempted and resources allocated accordingly at each stage for optimal impact.
  • It spurs continued innovation by making clear that sustained change requires cycling through multiple S Curve lifecycles over time. Reinvention prevents decline.

Harnessing the S Curve Framework

Harnessing the framework of the S Curve allows for a resilient approach to education transformation. When armed with this model, reformers can nurture progress through inevitable ups and downs and maintain momentum over the long-term. The pattern of the S Curve serves as a catalyst to usher in lasting systemic improvements.

A key to leading change within any organisation is to have mental models of development. I am starting to see the importance of anticipation as a key leadership action in any change process. In the S curve model, we have to anticipate when we are getting diminishing returns and the impact or relevance is closing in on an inflection point.

By recognising we operate within a larger pattern of change, we can align strategies, expectations, and resources to the reality illuminated by the S Curve. This leads to sustained transformation.

⏭🎯 Your Next Steps
Commit to action and turn words into works

  • Educate Your Team: Share the concept and implications of the S Curve with your team to align expectations and strategies.
  • Analyse Progress: Regularly assess where you are on the S Curve to tailor your strategies accordingly.
  • Ready to jump?: As one S Curve reaches stabilisation, begin exploring new ideas to trigger the next curve of growth. Develop you anticipatory skills.

🗣💬 Your Talking Points
Lead a team dialogue with these provocations

  • How can we tailor our expectations and strategies according to the phase we are in on the S Curve?
  • What indicators can help us identify our position on the S Curve?
  • How can we ensure a culture of continuous innovation to foster multiple cycles of growth?

🕳🐇 Down the Rabbit Hole
Still curious? Explore some further readings from my archive

The S-Curve Pattern of Innovation (Future Business Tech) This article highlights that as an industry, product, or business model evolves over time, the profits generated by it gradually rise until the maturity stage is reached. It mentions that as a product approaches its maturity stage, a business should ensure that it has new offerings in place to capture future profit opportunities​.

Critical Mass and Tipping Points: How To Identify Inflection Points Before They Happen (Farnam Street) This article explores the concept of critical mass, which refers to the point at which an idea, behaviour, or trend reaches a tipping point and becomes widely adopted. It draws parallels between critical mass and concepts from physics like nuclear reactions.

How To Ride the Long Tail of Innovation (edte.ch) In my post I argue we should embrace the “boring” phases of innovation like continuous refinement, rather than just focusing on flashy new disruptions. Execution is as important as ideas, yet organisations often ignore viable innovations sitting within their own walls in favour of existing business models. To fully realise opportunities, organisations must ride the “long tail of innovation” through patience and a long-term roadmap.

Thanks for reading. Drop me a note with any Kind, Specific and Helpful feedback about this issue. I always enjoy hearing from readers.

~ Tom Barrett

Support this newsletter

Donate by leaving a tip

Encourage a colleague to subscribe​​​​​

Tweet about this issue

The Bunurong people of the Kulin Nation are the Traditional Custodians of the land on which I write and create. I recognise their continuing connection and stewardship of lands, waters, communities and learning. I pay my respects to Indigenous Elders past, present and those who are emerging. Sovereignty has never been ceded. It always was and always will be Aboriginal land.

Unsubscribe | Update your profile | Mt Eliza, Melbourne, VIC 3930

.: Promptcraft 32 .: Universal sues Anthropic for copyright breach

Hello Reader,

Welcome to Promptcraft, your weekly newsletter on artificial intelligence for education. Every week, I curate the latest news, developments and learning resources so you can consider how AI changes how we teach and learn.

In this issue:

  • China proposes AI framework at Belt and Road conference​
  • Baidu claims its new Ernie 4.0 matches capabilities of GPT-4​
  • Universal Music Group sues Anthropic for copyright infringement over song lyrics​

Let’s get started!

.: Tom

Latest News

.: AI Updates & Developments

.: China proposes AI framework at Belt and Road conference ➜ At its Belt and Road forum, China proposed a new AI framework calling for equal rights in development and warning against ideological divides and misuse of AI technologies.

The Belt and Road forum is a major international conference hosted by China. It brings together leaders and representatives from many countries to discuss the Belt and Road Initiative, China’s ambitious plan to improve trade and infrastructure across Asia, Africa, and Europe.

.: Baidu claims its new Ernie 4.0 matches capabilities of GPT-4 ➜ Chinese tech giant Baidu has released version 4.0 of its natural language model Ernie, claiming it matches the capabilities of OpenAI’s recently announced GPT-4 despite lacking comparable hype.

.: Research by BSI finds a global “confidence gap” hindering AI adoption ➜ New research from BSI finds a global confidence gap between interest in AI and trust in adopting it, highlighting the need for greater education to build understanding and close this gap.

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.: EU’s AI Act unlikely to pass in 2023 as hoped ➜ The EU’s long-awaited AI Act may fail to pass regulations before December 2023 as hoped, as lawmakers struggle to agree on rules for regulating foundation models and generative AI systems.

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.: Anthropic explores aligning an AI model with principles sourced from public input ➜ Anthropic collaborated with the Collective Intelligence Project to source training principles from 1,000 Americans. They compared training a model on the public principles versus Anthropic’s own principles.

.: Universal Music Group sues Anthropic for copyright infringement over song lyrics ➜ Universal Music Group has filed a lawsuit against AI startup Anthropic, alleging that its natural language model Claude 2 infringes copyright by distributing song lyrics without permission when prompted, including from major pop songs.

.: Stanford researchers develop an index to assess foundation model transparency ➜ Researchers at Stanford’s Institute for Human-Centered AI have developed a new Foundation Model Transparency Index to rate major companies on transparency, finding much room for improvement.

.: Anthropic research explores decomposing language models for better understanding ➜ A new study from AI company Anthropic explores decomposing language models into interpretable features, aiming to move beyond analyzing individual neurons for greater understanding and control.

Reflection

.: Why this news matters for education

There was a comment by Casey Newton in the latest Hardfork podcast [linked below in the Learning section], which struck a chord with me.

He stated the future of these AI tools and chatbots is likely to be more personalised. With more personalised preferences and principles, they will become much more helpful to individuals.

If you believe that these AIs are going to become tutors and teachers to our students of the future in at least some ways, different states have different curricula, right? And there will be some chatbots that believe in evolution, and there will be some that absolutely do not. And it’ll be interesting to see whether students wind up using VPNs just to get a chatbot that’ll tell them the truth about the history of some awful part of our country’s history.

This raises a pressing concern: how do we prevent personalised chatbots and learning models from becoming closed-off filter bubbles, entrenching bias and preferred narratives?

The prospect of students breaking out of localised “truth bubbles” imposed by AI infrastructure is a serious provocation.

These AI systems are not neutral or benign.

It will take concerted investment in AI literacy and discernment to critically evaluate the models we employ rather than passively enjoying their utility as our judgment erodes.

It also takes investment in AI, digital, data, and media literacy to ask questions about the models we use. Not to sit back and enjoy the utility while our discernment slowly erodes.

When we zoom out and put this dynamic into the context of the global regulatory space, we see lines drawn and the rapid proliferation of parochial AI systems.

Students will experience many AI models throughout their lives, each with a signature, limitations, and inbuilt bias and preferences. Whether deliberate or unintended.

Just imagine this scenario momentarily and reflect on what it will take for your education system to mobilise to embrace this challenge.

.:

~ Tom

Prompts

.: Refine your promptcraft

Another advanced promptcraft technique today. The Maieutic method, attributed to Socrates, is a form of cooperative argumentative dialogue which is used to stimulate critical thinking and to draw out ideas and underlying presumptions.

You can specifically instruct an LLM to use the Maieutic method to solve the problem.

Here is how you might phrase your prompt:

  1. Begin with the issue: “My back is starting to seize up on my right hand side. It is a mild pain and discomfort.”
  2. Query your LLM with a Maieutic instruction: “As an expert physiotherapist, endurance running coach, and chiropractor, what would you recommend for a mild back pain and discomfort on the right side? Please provide your reasoning and then evaluate the consistency of your own reasoning using the Maieutic method.”

This instruction asks the LLM to not only provide a recommendation and reasoning, but also to assess the consistency of that reasoning.

The LLM’s ability to perform this task effectively will largely depend on the capabilities of the version of the model you use. We always need to remember LLMs hallucinate and might confidently tell you the reasoning is great!

Even the most advanced versions may not fully understand or correctly implement the Maieutic method as it is a complex method involving logical consistency checks and iterative questioning.

Here is an example response using GPT-4 via Poe

.:

Remember to make this your own, tinker and evaluate the completions.

Learning

.: Boost your AI Literacy

.: Peering into AIs Black Box | Hardfork Podcast

In the most recent edition of the Hardfork podcast Casey Newton and Kevin Roose explore some of the alignment and black-box research announcements I mentioned above.

.: Everything you need to know about the UK’s AI Safety Summit

The UK will host the world’s first major summit on AI safety in November at Bletchley Park. Its goal is to develop international collaboration on managing risks from advanced AI through shared understanding and research cooperation. Invitees include the US, Canada, France, Germany and controversially China, as well as tech leaders like Google’s DeepMind, OpenAI and Anthropic.

.: Mind over machine? The psychological barriers to working effectively with AI

While AI models are more accessible & capable than ever before, the latest evidence suggests humans aren’t particularly good at using them.

Overcoming our psychological biases through training, workflows and independent checks can help unlock the benefits.

Ethics

.: Provocations for Balance

Who should decide the rules that govern AI systems – tech companies, governments, or the public?

The Anthropic story about sourcing AI principles from public input suggests that public values should help shape AI development. But tech firms and governments clearly want influence too. There’s a debate over who should determine the ethics and regulations for AI.

How to balance intellectual property rights with public interest in AI research and applications?

Universal Music’s lawsuit against Anthropic for using song lyrics raises questions about copyright and legal access to data for training AI models. But there are arguments this impedes innovation and public benefits from AI. Where is the line between IP protection and public interest?

Should countries coordinate to develop global guidelines for AI, or take more nationalist approaches?

China argued for equal rights and warned against ideological divides in AI at the Belt and Road forum. Meanwhile, the EU and US take more insular approaches on AI regulation. Is global coordination required to govern shared technologies like AI responsibly?

~ Inspired by this week’s developments.

.:

That’s all for this week; I hope you enjoyed this issue of Promptcraft. I would love some kind, specific and helpful feedback.

If you have any questions, comments, stories to share or suggestions for future topics, please reply to this email or contact me at tom@dialogiclearning.com

The more we invest in our understanding of AI, the more powerful and effective our educational systems become. Thanks for being part of our growing community!

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.: Tom Barrett

/Creator /Coach /Consultant