The place of AI in 2024

Technologies that continue to change the world

The automobile The airplane The phone The internet The smart phone

And…..artificial intelligence

Every technology breakthrough from the last 100 years has transformed society. Some overnight, and some over decades.

Every one of these has incredible potential for doing amazing things and improving the lives of humans. But, yes we are human, which means there are some humans who are motivated by using these technologies in controversial, illegal, immoral, and even evil ways.

Sticking our head in the sand is not the way to approach new technology.

Is our head in the sand?

As you look at the list of technologies above, you see the technology getting more sophisticated and more powerful. And we find the technologies becoming accessible by the general public faster. That’s where our fear is partly stemming from.

We barely understand what we have, yet we are using it.

It’s like a 10 year old behind the wheel of a car. An incredibly powerful tool, with the potential to do great things, but in control of someone who has no sense of the tool, its power, its capabilities, its purpose, its potential for good, and yes its potential for harm.

Yes, while accidents are less common, car accidents still happen, cars also allow us to interact with humans outside of our homes. Yes, there are rare accidents, but airplanes have allowed cultures across the world to meet each other. Yes, there are scams, but phones allow us to communicate with people who live in a different city. While there is access to incredible knowledge on the internet, part of that knowledge is related to terrible and evil domains. While hacking is a threat, the smart phone gives the average person access to the world at their fingertips.

Even now, humans continue to figure out all of these technologies, decide societal-appropriate rules and regulations, improve how they work, and reduce the potential for bad.

In many cases, time is what is needed just to explore and experiment. This is where we are now. Literally, every week, we see a new use for AI and a new tool created using AI.
But, AI is also a different type of technology than all the others. The other technologies are physical entities, whereas AI is something that is inside of other technologies. While it can be used by many, there is a very small percent of people that have the capability to use it to create something new. We are putting a lot of faith into a very small number of people and companies. This is not necessarily a bad thing, but it is something we need to be aware of.

The key to figuring out the place for AI in our society is for the people to understand what it is , how it works, why it works, and where it can have an impact.

AI must be part of student learning

The ideas, terminology, and technology behind this powerful technology called AI must be a regular part of human knowledge and understanding.
AI is a part of every industry on the planet. AI must also be part of every subject area in our schools. It must be a part of every major in college.

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Story

The human brain craves story. 

Creator: Easy-Peasy.AI Credit: Easy-Peasy.AI AI Image Generator
Copyright: Easy-Peasy.AI – AI Image Generator

Books, libraries, movies, poems, literature, myths, legends, even stories in science astrology signs, zodiac patterns, songs, novels, short stories, magazines, even religion. How many us can describe the scene in Titanic where Jack spread his arms like a bird on the front of the ship. Religious people can retell hundreds of stories from their core readings. We are happy to curl up on the couch, or lounge on the beach, and dive into a long novel. Astronomers remember hundreds and even thousands of stars through constellations, which are visual stories based on tiny white dots in the sky.

Our brain seems wired to remember things when it is attached to story. How? We remember the story, then the facts of the story are simply the details that support the story. Think about it. can you remember song lyrics of songs you have not heard in decades? While you may not remember all the facts, can you remember the storyline of most of the movies you have ever seen?

People even create stories in order to remember. Have you ever tried it? Write down a list of 15 items in the room you are in. Wait 15 minutes, then try to remember as many as you can. Now write down another 15 items. But this time, create a story around those objects. Wait 15 minutes, then retell that story and see how many items you recall.

Emotions are great story telling devices. Creator: Easy-Peasy.AI Credit: Easy-Peasy.AI – AI Image Generator
Copyright: Easy-Peasy.AI – AI Image Generator

And it does not stop there, humans also respond to emotion in that story. That can be happy, sad, angry, or scared.  If I asked you about an experience you had in your life with each of those emotions, no doubt you could recall the situation with incredible accuracy. Ask an older person where they were when JFK or MLK were shot. Some of you may even remember when the Twin Towers crumbled down. 

We talk about people getting lost in a book, where they are reading the pages, but their imagination takes them to a highly visual interpretation of that story. Or have you been in a movie where you were so immersed, it was as if you felt like you were part of the story itself. There are even stories where getting lost in a story IS the story; think about Never Ending Story with the boy riding on the back of a flying dog. 

Story telling is how generations passed down information.

And it makes sense why this developed; think about it, as humankind evolved there were things we needed to remember, to know, to pass down….and there was a time where writing was not a part of our capabilities, so stories were all we had. The verbal stories were our libraries and our Google.

What does this tell us? How does this apply to learning and education? If we know that story helps the mind remember deeper and better, then it makes sense to build a story around the lesson topics. 

Learning is about new vocabulary and terminology, new processes, foreign ideas,  new skills. A list of 3 of these. 4 categories of those. 5 steps to do this. The 6 reasons an event happened. That is one way of presenting and learning information. But, all this random information does (can) actually tell a story.  Depending on our target audience, when we create learning, we can build that story into the learning. An engaging instructor can weave story throughout the content.

What does that look like for modern learning creators?
Start out with a character of a story that has a problem to solve. As the lesson evolves, keep revisiting that story with the character getting the skills s/he needs in order to address the problem. And don’t stop there, add real emotion by incorporating real situations, real problems, real interactions, real places and events. Yes, I mean add happiness, sadness, shock, fear, and surprise. Let your learners ‘feel’ the learning by relating to it through a story. Let the important concepts, ideas, topics, steps, and skills be important elements of the story, in fact so important that they are vital to understanding the complete story.

Stories at Clemson University

I remember I had a college professor who had spent decades in business. He sat on the corner of the desk on the 3rd floor of Daniel bldg and told stories from his experiences in businesses.  We were not taking notes, not referencing the textbook, he was not drawing diagrams on the white board. He told stories, and then at the end of class, he would say, “Ok, we just got through chapter 3. Read the chapter tonight and the stories I told you will help you understand the topics.”

Did you have a teacher who told stories? 

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The Coming Wave

As promised, here is a summary and reflection on the ideas in (co-founder of DeepMind, co-founder of Inflection AI) Mustafa Suleyman’s new book, The Coming Wave.

What the author does well in the book is show where and how AI is currently being used throughout the world. We all assume AI is being used in creative and innovative ways, and Mustafa uses tons of examples to demonstrate that. But, where he truly distinguishes himself is, because of his own background, he can share with us with insider knowledge, accuracy and confidence not only where we have been and where we are, but where this can(and most likely will) go…hence “the coming wave.”

His main point throughout the book is we have to find ways to contain AI. Not block it, but responsibly and proactively find ways so that we are controlling the technology and not the other way around, or worse….AI controlling itself. The majority of people do not have any idea what AI is, much less how it works. This makes containment that much harder – but also that much more important. We cannot just hand over the reigns of our society to a computer robot, and cross our fingers.

The book lays out the groundwork for how society, over the years, has made efforts to guide, control, regulate, and contain other technologies. So, this idea of containment is not something that is a new, but AI is different because AI learns and gets better at a rate far beyond anything we have seen before. Some technologies take years, even decades, to develop and progress,so we can develop reasonable safeguards and sensibly incorporate the technology into society. Literally every week, we see improvements and breakthroughs in AI.

These technologies are not perfect, and our safeguards and containment attempts are not perfect.

Think about automobiles and airlines. Each has safeguards, regulations, and controls to (somewhat) contain them. Even so, containment is not perfect, we still have issues, right? These technologies are not perfect, and our safeguards and containment attempts are not perfect.

Mustafa makes a great point that AI is different than technologies such as automobiles. An automobile is a single industry, while AI is more like electricity, in that it powers most other industries; so as AI improves and changes, it affects all areas of society, not just a single industry. That makes it even more important that we figure out how to contain AI.

What is being done now to address issues around AI? Unfortunately, society as a whole is not moving fast enough when it comes to AI. Blocking it, ignoring it, and not using it does not limit it’s progression. Regardless of how each country is handling their approach to AI, rest assured that there are other countries, people, groups, and organizations – both good and bad, who are pushing AI to the limits.

Trying to contain a technology that is changing so rapidly is hard.

But, trying to contain a technology that is changing so rapidly is hard. As he points out, predicting at the forefront of discovery is hard, but that is where we are now with AI. It’s a leading edge, bleeding edge technology. What guardrails are already setup and what do we need? Are those once-helpful guardrails still helpful or are they already outdated? Are we noticing the right things? For example, neural networks were not taken seriously for a long time, so we paid them no attention. Suddenly, a breakthrough happens, and they are huge. Even CRISP gene editing was not created to do what we actually use it for now, it was designed for something completely different. GPUs made by Nvidia were created for gaming realism, yet now are central to AI. So, even knowing what to try to contain is hard.

Is there any country which has fully embraced AI? China fully embraces AI and has declared their aspirations to be the clear leader in the world by 2030. And because of their style of government, with the control, finances and intelligence, China can very likely make that happen.

China has declared their aspirations to be the clear leader in the world by 2030.

Where is the United States in this? We barely have legislation, the people in leadership roles in government barely understand how a cell phone works, much less AI. I don’t know what’s worse, those same people making laws dealing with AI, or NOT making laws. The US government still has tape machines doing backups , while China has a quantum satellite. We are so occupied with middle school-level politics, juicy scandals, and the number of likes, that we are not noticing the coming wave. Meanwhile, China is polishing its surfboard.

What can we do right now? For starters, we must have AI literacy for people of all ages. We need to listen to people who understand AI, and ask them to help us figure out what questions we should be asking. Murphy’s Law tells us anything that can happen will happen (got that from Mathew Mcconaughey in Interstellar) that means both the good and bad. This AI wave is coming.

Now there are worldwide efforts to contain nuclear weapons.

What does runaway technology look like when it’s not regulated, no safeguards, or containment? In the 1940s, when we tested the nuclear bomb, we had no idea what to expect. One of the possibilities was a small back hole formed and sucked our world into it. Yet, we still pushed the button!!?? And only after tens of thousands of people were killed after two bombs were dropped, did the world say, “this is not ok.” Now there are worldwide efforts to contain nuclear weapons. Not perfect by any means, but at least we are trying. Countries and people are talking.

Because of the incredible potential power of AI, Mustafa notes that we as as society are facing the ultimate challenge for Homo Sapiens and Homo technologicus. How do we approach this challenge?

None of us like government regulating our lives. There are many instances in history where that did not go well. But, Mustafa says we do need gov’t, but we can do this differently than in the past, but we have to do something. There are some ‘good’ example of government containment: We have stiff regulations worldwide in the automotive industry, yet millions of people die every year. This has become an acceptable consequence considering the benefit.

This is the norm.

What’s missing there? Common sense. Regulation, guardrails, rules, laws, and protocols do not work if they are not based on common sense. We need “…norms, structures of ownership, unwritten codes of compliance and honesty, arbitration procedures, contract enforcement, oversight mechanisms.” That must be part of society, more importantly —people must buy into that. It involves governments, public and private businesses, industry leaders, scientists, and people coming together.

How we define containment must also change. In the first part of the book, Mustafa defines containment as “…a foundation for controlling and gathering technology, spanning technical, cultural, and regulatory aspects.” But, towards the end, he redefines it, “…more as a set of guardrails, a way of keeping humanity in the drivers seat when a technology risks causing more harm than good.”

Woah. Is AI that big of a deal? Yes.

Technology is not just a way to store our selfies, buy something online, make reservations for a taxi, and play video games—-technology “represents access to the world’s accumulated culture and wisdom. It’s not a niche; it is a hyper-object dominating human existence.”

Yes, we have attempted some guardrails and regulations, but it is also political, profitable, and hard to enforce.

It’s not gonna be easy. Look at another global issue: climate change. It’s right in our face, yet we have not really done much as a global society. Yes, we have attempted some guardrails and regulations, but it is also political, profitable, and hard to enforce. There are still people who do not accept that it is even a thing. At least we are trying, but containment is far off.

So, a first step for us to begin containment for AI is simply to recognize and understand it. Get people together to have real discussions. Great news, this is already happening! The major players in AI worldwide already gather to discuss, share, challenge, debate, and learn from each other. Just having these cross culture relationships means we can talk to each other, which is vital. We saw in the movie Arrival, what happens when countries close off their communication with each other.

Yes, people disagree and have different norms; countries use different economic models, and have different approaches to the unknown. Regardless of those differences, the wave is coming, whether we want it to or not. At this point, all we can really do is buy ourselves some time. Time to understand, make attempts at guardrails and setting norms, time to develop defenses, time to build alliances, time to partner and harmonize to determine the right decisions.

Could vs. Should. We have to make thoughtful decisions.

In Jurassic Park, Malcolm says, “the scientists were so preoccupied with whether they could, they never stopped to consider whether they should.”

This book is thought-provoking, and highly readable for the layperson, but also technical enough so those in the trenches can find value. It’s the beginning of a discussion that MUST HAPPEN.

I suggest that the coming wave of AI is already here.

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The Cost of Learning

The cost of learning is minimal, but the cost of NOT learning is HUGE. Business leaders, are you measuring the costs only in money?

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Un-Learning Un-training, Un-workshop

Ask yourself

  • Is there a lack of excitement and energy around learning and training in your organization?
  • Are learning and training viewed as a requirement and not an opportunity?
  • Is there a disconnect between training and the people being trained?
  • Are training topics of no interest to some of the people being trained?
  • Is training handed down from above with no input from the people?
  • Do people in your organization dread training and learning?

What is un-training?
Most people hate training because they don’t want to be there, they don’t have a connection with the topic, they had no say so in what is being presented, management barely knows training is even going on, and oftentimes the training itself is terribly delivered.

Un-learning and Un-training takes out all of those elements, It is based on a very successful ed-tech and education conference style, called unconference, where the attendees decide the agenda and topics for discussion, learning, and training on the day of training. Un-training is especially effective in generating discussions, brainstorming, idea generation, and team building, but can also be used in skills development and technical training. Managers are invited but they are there at the exact same level as other attendees. After topics are crowd-decided, people go to the sessions of their choice. The “results” and “output” of the sessions are decided by the people in the sessions. Yes, it involves putting the responsibility for learning in the hands of the people and also managers and HR giving up control.

This event works because it is a 100% grass roots, from the agenda, topics, session delivery, and outputs.

Can it be done virtually and in-person?
Yes, it can be done both. It works the exact same way except the sessions are in virtual rooms instead of actual rooms

In general , how does it work?
On the day of (or maybe a couple of days before if needed), all attendees are asked to submit 3 topics they would like to see on the agenda. Those ideas are consolidated, merged, synthesized, and categorized; each of those ideas represents possible learning/training sessions. From the newly synthesized list, attendees are given 3 ‘votes’, in which they can vote for any of the ideas they see value in. Depending on how many session slots are open, popular vote wins, and available session slots are filled with top-voted session topics. No one will need to necessarily be a session leader, although the person who suggests a topic might at least get the discussion started. Now the agenda is set and people can start to plan out which sessions they will attend.

Ok, what are the details?

Materials and location: You will need a large room where everyone can fit. You need some sticky-notes, stickers (like elementary school teachers use), and 3 rooms large enough to fit 1/3 of the people.(1 room for each session topic )

Step 1: Collect a group of volunteers who would like to be part of the un-training team. The volunteers will coordinate (not lead) the event. Once the topics are decided, the volunteers become regular attendees. You may be surprised at people who will take an interest and are looking for ways to lead.

Step 2: Sell it. Publicize it. Let people in the organization know what you are doing. Make sure they know that they are 100% in charge of the training topics. Clear the calendar. Minimize conflicts. Managers encourage your people to participate. Make sure people have every incentive (except requiring attendance) to attend. Managers, leaders, and supervisors- You will need to decide, based on your culture as it stands right now, whether your presence at the event is positive or negative.

Step 3 IDEATION: Solicit topic ideas for the training from the attendees. You can try to have an umbrella topic under which you’d like ideas to be related to. Or you can just let the ideas flow from the ground up. No limit to how many ideas each person can submit. If you are in-person, you can literally pass out sticky-notes and let people put them on a wall, which allows others to see the ideas as they are generated. If virtual, you can replicate the sticky-note style of ideas posting by using a tool such as www.mural.co, lucidspark.com, https://miro.com/online-sticky-notes/ . Take 15 minutes max to do this.

  • EXCEPTION: Technical Traning If some of the sessions will be specific software or other technical training, you will want to make sure you have someone in those sessions who might be willing to ‘lead’. In other words, they would have to be comfortable enough with the technology to be able to lead a mini-training session off-the-cuff upon finding out what people want to learn.

Step 4 TOPIC SYNTHESIS:

The volunteer group gathers all the ideas. Then as a group try to organize all related ideas into as few categories as possible. It ok to merge ideas together, reword, etc. but try to get the ideas into a reasonably-sized list under each category. So, maybe you reduced everything down to 5 categories, with 5-10 ideas under each. Volunteers Take 15 minutes max to do this. It does not have to be perfect.

Step 5: TOPIC SELECTION:

  • VOTE: Each attendee, including volunteers, now get 3 ‘votes’ for their favorite top ideas. (or whatever number, but keep it low so people have to make a choice). For in-person, the topic ideas will be posted on 4 separate walls, spread out so everyone can read and vote at the same time. For voting, pass out small stickers(.i.e. stars) to everyone. People browse the room and put stickers on the ideas they support. No rules on how people apply their votes. Take 15 minutes max to do this.
  • SET AGENDA: Volunteers meet for the last time to put the ideas into order based on votes. Ideally, they are spread out across categories, so you can take the top 3 from each category, or make whatever “executive decisions” that need to be made. It is OK to merge ideas together if it helps. Complete the public agenda with the selected topics. Make the agenda available to the attendees.

 

Sample 3-hour agenda

(8:00 – 8:15) 15 min Gathering and Greeting and Ice breakers
(8:15 – 8:30) 15 min Ideation
(8:30 -8:45) 15 min Topic Condensing
(8:45 – 9:00) 15 min Topic Selection
(9:15-10:00) 45 min Session 1 (topics A, B, C)
15 min Break
(10:15-11:00) 45 min Session 2( (topics D, E, F)
15 min Break
(11:15-12:00) 45 Session 3 (topics G, H, I)
Lunch

Step 6: Learn.

Make sure people know that they are free to roam from session to session, even if it means leaving a session mid-stream.

Learn with your Feet. If you get into a session and it is not what you needed or not what you hoped, or you really want to catch part of another simultaneous session, then leave–just get up and go. No explanation is needed. No one is “watching”. It’s not an insult to anyone. Go where you get the most value. Contribute where you can the most.

What happens next?
Well, you have placed the learning and training into the hands of the people. Why not let the people decide what happens next? Is specific follow-up training needed? Do some work-related procedures or policies need to be re-visited? Did new ideas arise that need to be fleshed out? In other words, let “what happens next” depend on what happens in the training.

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Digital Natives and ChatGPT. (Not what you think)

In regards to this Scientific American article. AI in education. Ah yes. The big conundrum. We forget students are still kids, still learning how the world works. Their brain is still developing. How does AI impact that? Yes, they are digital natives, but the author observed that “…students feel insignificant or unintelligent when faced with such technology.” A professor at Elon University wrote a thought-provoking article for Scientific American showing the human side of students using AI.
Instead of blocking AI or sticking his head in the sand, he brought it into the classroom and built an essay-writing assignment, where students were required to use AI. What he found was was unexpected: “…unfortunately, even the students who tried to use it responsibly (that is, without just cheating wholesale) did not really understand the technology.

Chat GPT

A common and critical error is that many students mistakenly believe it is an infallible search engine. The results of his experimental assignment were eye-opening: Every one of the 63 essays contained confabulations and errors. Most students were surprised by this, and many were less impressed by the technology than they had been before doing the homework.” Two students commented about the experience, which shows us that students value their own learning far more than we give them credit for.
“…the most crucial element of schoolwork is not the course material or grade: The actual thinking processes a student undergoes while working through an assignment are more important than simply turning in the completed task. The details in the work seldom matter as much as this thinking. ” Another commented with an interesting observation -not at all in line with the messaging we hear and see, “…At its best, ChatGPT can be a versatile resource, introducing fresh, interactive ideas into the classroom for both teachers and students to enjoy.” Just as with any new digital tool, we will survive AI.
#Scientific American #artificialintelligence #education

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No Zeroes Grading and “The Game”

First read this We are Teachers post. From a mathematical point of view, using the 50% minimum grade makes sense. The problem when trying to implement this is that the rest of the system remains unchanged, so the implementation attempt fails. Or, as we saw in this article, other simultaneous changes muddy the waters. I love that we are trying to change an antiquated grading system and I will always support explorations such as this. However, bigger than the actual grades is that over and over we hear about students trying to ‘game’ the system. The fact that there is even a system to be ‘gamed’ tells us that the system is broken, fundamentally. #grades #education ##innovativelearning

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Autonomous Cars- What’s the hold up?

On the way home recently, I got stuck in traffic due to 4 different car accidents. Ambulances were at 3 of them. My point? Humans are terrible drivers. In our cars, we hurt people, kill people, and cause damage all day every day. So, why are we so resistant to autonomous vehicles? While they are not perfect, on their worst day they are multitudes better than the best days for humans. Yet we resist them. For example such as requiring a hand on the steering wheel or reducing the percentage of autonomous cars in one area. Autonomous vehicles could reduce traffic, reduce pollution, save lives, reduce injury, reduce crowded streets, reduce travel time, and improve the travel experience. From that perspective, I just don’t see a downside.

Why are we so hesitant to go all in?

#autonomouscars

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Unveiling the Future of Education: Exploring Current Innovations in AI

In the digital era, the integration of Artificial Intelligence (AI) in various facets of life has become inevitable. One of the most impactful realms witnessing revolutionary advancements is education. AI’s transformative power is reshaping traditional pedagogical approaches, fostering personalized learning experiences, and revolutionizing the way students learn and educators teach. As we step into the future, let’s delve into the cutting-edge innovations in AI that are reshaping the landscape of education.

Can A.I. help promote and support personalized learning?

Personalized Learning
One of the most profound impacts of AI in education is its ability to personalize learning experiences. Adaptive learning platforms powered by AI algorithms analyze students’ learning patterns and behaviors to tailor educational content, pace, and style to suit individual needs. These platforms identify strengths, weaknesses, and learning preferences, thereby providing customized learning paths for students. This personalized approach enhances engagement, fosters self-paced learning, and ensures a deeper understanding of concepts.

Intelligent Tutoring Systems
Intelligent Tutoring Systems (ITS) leverage AI to simulate personalized, one-on-one tutoring experiences. These systems adapt to students’ learning speeds, offer immediate feedback, and provide additional resources when needed. Incorporating natural language processing (NLP) and machine learning, ITS can assess students’ comprehension levels, identify misconceptions, and deliver targeted interventions. Such systems enhance student retention and proficiency in various subjects, enabling educators to focus on individual needs within a diverse classroom environment.

Gamification and Immersive Learning
AI-powered gamification and immersive learning experiences are reshaping traditional classroom settings. Virtual reality (VR) and augmented reality (AR) technologies, combined with AI algorithms, create interactive and engaging learning environments. These technologies offer simulations, enabling students to explore complex concepts in a practical, immersive manner. AI algorithms in gamified learning platforms adapt to students’ progress, adjusting difficulty levels and content to maintain optimal engagement and motivation.

Can A.I. really help create good educational content?

Smart Content Creation and Curation
AI streamlines content creation and curation for educators, providing access to a vast array of resources. Natural language generation (NLG) algorithms assist in generating personalized study materials, quizzes, and assessments. Additionally, AI-powered content curation tools help educators discover, organize, and share relevant educational resources, saving time and ensuring content alignment with curriculum standards.

Ethical Considerations and Challenges
But, while AI brings forth remarkable advancements in education, it also raises ethical considerations and challenges. Data privacy, algorithm bias, and equitable access to AI-powered educational tools are crucial concerns. Safeguarding sensitive student data and ensuring transparency in AI algorithms are imperative to maintain trust and ethical use of these technologies in education.

The fusion of AI and education holds tremendous promise, revolutionizing traditional educational paradigms. From personalized learning experiences to intelligent tutoring systems and immersive learning technologies, AI innovations are reshaping how knowledge is imparted and acquired. However, ethical considerations and challenges necessitate a thoughtful approach towards integrating AI in education to ensure inclusivity, equity, and privacy.

As we navigate this ever-evolving landscape, embracing these innovations while addressing ethical considerations will pave the way for a more accessible, engaging, and effective educational experience for learners worldwide. The future of education is undoubtedly being shaped by the synergy of human expertise and AI-powered advancements, promising a brighter and more inclusive learning journey for generations to come.

As part of an exploration and experiment, A.I. is helping write a series of blog posts. Did you notice?

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Discipline-Focused Learning

Ok, isn’t that what all learning is… where we study a discipline?

Uhm no.

Actually it’s not.  The model of education that we have blindly followed for decades is a collection of highly connected disciplines, but yet which rarely interact. Seldom do we see thoughtful collaborations as a regular part of learning. Yet, isn’t the real world “out there” just a huge intersection of every possible discipline?

https://pixabay.com/photos/buddhism-asia-boys-cambodia-1822518/

The role of school has been to prepare students for the real world outside the school walls, but yet it seems as if the walls are getting higher, and the education is more and more irrelevant and disconnected.

We have to experiment with new ways of learning in order to find how to reconnect school, at all ages, with modern-day students. I’m not worried about what worked 25 years ago, and I am not worried about what school will look like in 10 years. I am talking about right now.

https://cdn.pixabay.com/photo/2017/02/24/02/37/classroom-2093744_1280.jpg

Currently, students study numerous subjects in a single day, but each is compartmentalized, meaning that they go to math for an hour, then abruptly change to language, then abruptly change to history,  and so on.  No rhythm. No flow. Little cross-over in the day-to-day, but if we take a step back… all these subjects are heavily related!

No one will disagree that there is math in music and chemistry; there is chemistry in the art class; there is technical reading and writing in language and math; there is biology in physics; recently we are seeing there is AI in every subject….. you see my point. In any one subject, there is a direct connection to every other subject.

What about a new strategy for designing learning?

How about Discipline-Focused Learning? (yeah, I am still working on the name for this)

What if instead of just teaching math in a silo for a year, we completely flipped that concept on its head? What does that look like?

https://cdn.pixabay.com/photo/2016/07/06/15/29/math-1500720_1280.jpg

What if for a month, math is the focus of every subject. All subjects continue their lessons for the month but do it through the math lens. For example: history studies the math from periods of history(i.e. Greek, Roman, China, number systems in cultures) and their impact on society; art uses math in art projects (i.e. phi in drawing, perspective, dimensions) and of course the relationship between math and music; English class can focus on technical reading and writing in math with both fiction where math is heavy part of story (i.e. Mars, a Beautiful Mind) and nonfiction( Hidden Figures, writings by Ptolomy) ; foreign language uses culture-based mathematical word problems using mathematical vocabulary including lectures using technical vocab; Computer Science can use trig to rotate a visual object, algebra for variables updates, or use recursion to implementing Fibonacci series; Physical Education can use an obstacle challenge courses that involve calculations, then based on answers, active challenges; and then math itself focuses its curriculum to enhance/support other subjects as they ‘teach’ math along with the math dept.  Each department still does its ‘thing’, but for that month math is the focus, with the other departments approaching it from their perspective. Keep in mind departments should work together on projects, so students can let the flow of learning happen even when changing physical classrooms.

Yes, this would involve heavy collaboration between departments and between faculty. Administrators need to provide time for planning. It will take some time to figure this out. Schools will need to build that into their schedule. Students will need to learn to not stop learning a subject area when they leave the classroom. Teachers will need to help them with that cross-over. Projects will need to be more complex and far-reaching. Teachers will need to learn how to build great cross-curricular projects.

Does that make sense?

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Then the following month,  the ‘discipline of focus’ is Computer Science. All subjects continue their lessons but do it through the technology/Computer Science lens. History will study how technology impacts(and has impacted) society, business, elections and politics, and economies; art will be using programming languages to draw geometric shapes, fractals, and repetitive patterns using loops; foreign language will teach vocabulary for how to use different technologies, students use software for projects but that are configured in a specific foreign language. You want to insert an image or add styling? Gotta know how to find that menu option in Spanish; math will study algorithms, variables, loops, and functions to calculate answers to technical word problems. Language class will read fiction and nonfiction on highly technical topics, including business, ethics, AI, (i.e. science fiction and stories with a tech focus (i.e. Bicentennial-Man, Azimov’s Runaround)); physical education will have students outdoors solving classic CS algorithms such as towers of Pisa or implementing active sorting algorithms(look on Youtube you’ll see it); music has students using loops, variables, and functions to generate instrumental music(thanks Bob); and Computer Science itself will be using their curriculum to enhance/support other subjects as they teach Computer Science along with the CS department.

The next month is science, then history, then art, then language, then music, then physical education, and so on. A typical school year is 8 months long, which is plenty of time for every subject area to get a full month of highly focused attention, plus the other 7 months of “regular”. Is that not more than we are doing now? Is it not more how the world works and is it not more relevant?

I gave two examples of Math focus, and Computer Science focus. I’d love to hear ideas on what language, science, fine arts, and history would look like. What I also love about this approach is that each department gets a chance for some front-and-center attention every year.

 

 

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