Tag Archives: Artificial Intelligence

Edu-tainment and the future

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It’s interesting how the idea that ‘learning can be fun’ has been translated into the gamification of education, which in turn has devolved into making games that are essentially about practice pages that are ‘fun and interactive’.

I think AI has the ability to change this. Learning can be less about practice questions and more about deeper learning. Instead of playing a game with progressively harder, very predictable levels, the learning could authentically go where a student is interested. Two students could start the same, entertaining journey but end up learning and achieving vastly different outcomes. Not just higher math skills, but rather practical learning. A puzzle trying to determine the wiring of some gadget could lead to teaching basic electronics and it could lead to learning about electrical engineering.

The more used approach in machine assisted learning is to have specific goals and be responsive to the learner’s ability. The more advanced approach is to have general objectives and to be responsive to the learner’s interests.

It’s not just the outcomes of these that are drastically different, it’s also the entire approach to what it means to say, ‘Learning can be fun’.

How soon, Siri?

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I’m excited to see how Siri will be updated with the advancements seen in Artificial Intelligence. AI has come a long way and I think it’s time Siri got a serious upgrade.

I will often ask Siri a question and the response I get is, “Here is what I found,” with web links from a simple Google search.

I want Siri to give me the details in a conversation. I want Siri to ask me follow-up questions so its response is better. I want Siri to figure out better searches based on my previous lines of questioning. I want a fluid conversation, not just a simple and often unhelpful question and response.

Essentially I want a Siri that feels less like voice response to a simple query, and more like a personal assistant. when is this upgrade going to happen?

The quest for food

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I’m on holidays and I’ve had the privilege of watching a few sunrises over the ocean. Before the sun rises, but the day has brightened, and before the glare gets in the way, birds nose dive for small fish feeding on the turmoil of the ocean; as waves crash near the shore. I’m reminded of another privilege we all have: we don’t have to spend most of our day seeking food.

These diving birds must constantly be on the move, seeking their next meal. Food is life, and the quest for food makes up a significant part of most bird’s and mammal’s day. We don’t have to do that. We have the luxury of grocery stores, restaurants, refrigerators, and means to store food without it going bad. Much of our innovation and subsequent convenience comes from our ability to spend precious time not in the quest for food.

But it’s not just about innovation and convenience, it’s also about creativity. I think we are on the threshold of a new era of creativity. AI and robotics are going to move us into an era of greater innovation and convenience, and ultimately give us more precious time to design, create, and be artistically inspired.

The quest for food will be replaced by the quest for self-expression. A new chapter is about to be written… it will feel much more like fiction than reality.

The greatest threat to mankind

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I recently wrote about the Top Risks of 2024, which were in order of concern:

  • The United States versus itself
  • The Middle East on the brink
  • Partitioned Ukraine

Any of these three risks can have dire consequences on the stability of global politics, global trade, and global conflicts far beyond the borders of the mentioned countries.

These are imminent dangers that leave the rest of the world feeling like pawns on a chessboard filled with ‘other’ power pieces making all the strategic moves. But there is one danger on the geopolitical chessboard that I think will become the biggest threat we face when in the near future, and that’s the pawns themselves. Not the powerful pieces, but rather a rogue ‘nobody’.

While people fear Artificial Intelligence, and the rise of AI robots, what I fear is rogue humans using AI with harmful intent. The future will permit individuals with evil intentions to have too much power. It comes down to two well known adages: information is power, and power corrupts.

The problem isn’t a rogue leader, or a rogue country, it’s a rogue individual with too much information and too much power. A perfect example? See #5 on this article: ‘Why we’ll never actually destroy the last samples of smallpox’,

5) We could always recreate smallpox from genetic information

One could argue that in the information and genetics age, nothing really dies forever. It just dies until the technology to resurrect it appears. And for smallpox, that time is now.

The technology is here. And so is the necessary information: the complete DNA sequences of roughly 50 smallpox samples are available to the general public. This means that people could make smallpox in the lab. “Someone could if they wished recreate live virus from scratch just from that public information,”

We are less than a decade away from one intelligent crackpot, working in his or her (more likely an incel ‘his’) basement lab, creating or recreating a deadly virus and having it spread covid-19 style across the globe.

We are 15-20 years away from some crackpot scientist developing a nuclear bomb from parts and resources ordered online… without ever raising red flags to warn of his intentions.

The greatest threat to mankind isn’t wealthy people, politicians, and powerful countries, it’s one individual with malice in his heart and access to knowledge and information more power than anyone should ever have.

It’s already here!

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Just yesterday morning I wrote:

Robots will be smarter, stronger, and faster than humans not after years of programming, but simply after the suggestion that the robot try something new. Where do I think this is going, and how soon will we see it? I think Arther C. Clarke was right… the most daring prophecies seem laughably conservative.

Then last night I found this post by Zain Khan on LinkedIn:

🚨 BREAKING: OpenAI just made intelligent robots a reality

It’s called Figure 01 and it’s built by OpenAI and robotics company Figure:

  • It’s powered by an AI model built by OpenAI
  • It can hear and speak naturally
  • It can understand commands, plan, and carry out physical actions

Watch the video below to see how realistic it’s speech and movement abilities are. The ability to handle objects so delicately is stunning.

Intelligent robots aren’t a decade away. They’re going to be here any day now.

This video, shared in the post, is mind-blowingly impressive!

This is just the beginning… we are moving exponentially fast into a future that is hard to imagine. Last week I would have guessed we were 5-10 years away from this, and it’s already here! Where will we really be with AI robotics 5 years from now?

(Whatever you just guessed is probably laughably conservative.)

The most daring prophecies

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In the early 1950’s Arthur C. Clarke said,

“If we have learned one thing from the history of invention and discovery, it is that, in the long run — and often in the short one — the most daring prophecies seem laughably conservative.”

As humans we don’t understand exponential growth. The well known wheat or rice on a chessboard problem is a perfect example:

If a chessboard were to have wheat placed upon each square such that one grain were placed on the first square, two on the second, four on the third, and so on (doubling the number of grains on each subsequent square), how many grains of wheat would be on the chessboard at the finish?

The answer: 264−1 or 18,446,744,073,709,551,615… which is over 2,000 times the annual world production of wheat.

All this to say that we are ill-prepared to understand how quickly AI and robotics are going to change our world.

1. Robots are being trained to interact with the world through verbal commands. They used to be trained to do specific tasks like ‘find one of a set of items in a bin and pick it up’. While the robot was sorting, it was only sorting specific items it was trained to do. Now, there are robots that sense and interpret the world around them.

“The chatbot can discuss the items it sees—but also manipulate them. When WIRED suggests Chen ask it to grab a piece of fruit, the arm reaches down, gently grasps the apple, and then moves it to another bin nearby.

This hands-on chatbot is a step toward giving robots the kind of general and flexible capabilities exhibited by programs like ChatGPT. There is hope that AI could finally fix the long-standing difficulty of programming robots and having them do more than a narrow set of chores.”

The article goes on to say,

“The model has also shown it can learn to control similar hardware not in its training data. With further training, this might even mean that the same general model could operate a humanoid robot.”

2. Robot learning is becoming more generalized: ‘Eureka! NVIDIA Research Breakthrough Puts New Spin on Robot Learning’.

“A new AI agent developed by NVIDIA Researchthat can teach robots complex skills has trained a robotic hand to perform rapid pen-spinning tricks — for the first time as well as a human can…

Eureka has also taught robots to open drawers and cabinets, toss and catch balls, and manipulate scissors, among other tasks.

The Eureka research, published today, includes a paper and the project’s AI algorithms, which developers can experiment with using NVIDIA Isaac Gym, a physics simulation reference application for reinforcement learning research. Isaac Gym is built on NVIDIA Omniverse, a development platform for building 3D tools and applications based on the OpenUSD framework. Eureka itself is powered by the GPT-4 large language model.”

3. Put these ideas together then fast forward the training exponentially. We have robots that understand what we are asking them, which are trained and positively reinforced in a virtual physics lab. These robots are practicing how to do a new task before actually doing it… not practicing a few times, or even a few thousand times, but actually doing millions of practice simulations in seconds. Just like the chess bots that learned to play chess by playing itself millions of times, we will have robots where we ask them to do a task and they ‘rehearse’ it over and over again in a simulator, then do the task for the first time as if it had already done it perfectly thousands of times.

In our brains, we think about learning a new task as a clunky, slow experience. Learning takes time. When a robot can think and interact in our world while simultaneously rehearsing new tasks millions of times virtually in the blink of an eye, we will see them leap forward in capabilities at a rate that will be hard to comprehend.

Robots will be smarter, stronger, and faster than humans not after years of programming, but simply after the suggestion that the robot try something new. Where do I think this is going, and how soon will we see it? I think Arther C. Clarke was right…

…the most daring prophecies seem laughably conservative.

AI, Content and Context

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I found this quote very interesting. On his podcast, Diary of a CEO, Steven Bartlett is talking to Daniel Priestley and Steven mentions that Open AI’s Sam Altman believes we are not far away from a 1 person company making a billion dollars, using AI rather than other employees. Daniel pushes back and says while that might happen, a more likely and more repeatable scenario would be a 5 person team. Then he says this:

“AI is very good at content but not context. And having 5 people who share a context and create a context, together… then the content can happen using AI. AI without that context, it doesn’t know what to do, so it doesn’t have any purpose.”

Daniel Priestley

Like I shared before, “The true power and potential of AI isn’t what AI can do on its own, it’s what humans and AI can do together.”

This idea of context versus content seems to be the ingredients that make this marriage so ideal. This is noticeable when generating AI images, as I’ve done for quite some time, creating images to go with this blog. For example, I’ll describe something like a guy on a treadmill and maybe one of the four images created would have the guy backwards on the treadmill – content correct, but not context. As well, AI is really unaware of its’ own biases that humans can more easily see. These context errors are common.

But just as AI will be better teaming with humans, humans are also better when they team with other humans, rather than being solo. We miss context too, we struggle to see our own biases, unless we have people around us to both share and create the context.

The best innovations of the future are going to come from small teams of people providing rich contexts for AI. And while AI will get better at both context and content, it’s going to be a while before AI can do both of these really well. It’s what AI and humans can do together that will be really exciting to see.

Content Free Learning (in a world of AI)

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Yesterday, when I took a look at how it’s easier to make school work Google proof than it is to make school work AI proof, I said:

How do we bolster creativity and productivity with AND without the use of Artificial Intelligence?

This got me thinking about using AI effectively, and that led me to thinking about ‘content free’ learning. Before I go further, I’d like to define that term. By ‘content free’ I do NOT mean that there is no content. Rather, what I mean is learning regardless of content. That is to say, it doesn’t matter if it’s Math, English, Social Studies, Science, or any other subject, the learning is the same (or at least similar). So keeping with the Artificial Intelligence theme, here are some questions we can ask to promote creativity and productivity in any AI infused classroom or lesson:

“What questions should we ask ourselves before we ask AI?”
“What’s a better question to ask the AI?”
“How would you improve on this response?”
“What would your prompt be to create an image for this story?”
“How could we get to a more desired response faster?”
“What biases do you notice?”
“Who is our audience, and how do we let the AI know this?”
“How do we make these results more engaging for the audience?”
“If you had to argue against this AI, what are 3 points you or your partner would start with?”

In a Math class, solving a word problem, you could ask AI, “What are the ‘knowns and unknowns’ in the question?”

In a Social Studies class, looking at a historical event, you could ask AI, “What else was happening in the world during this event?” Or you could have it create narratives from different perspectives, before having a debate from the different perspectives.

In each of these cases, there can be discussion about the AI responses which are what students are developing and thinking about… and learning about. The subject matter can be vastly different but the students are asked to think metacognitively about the questions and tasks you give AI, or to do the same with the results an AI produces.

A great example of this is the Foundations of Inquiry courses we offer at Inquiry Hub. Student do projects on any topics of interest, and they are assessed on their learning regardless of the content.  See the chart of Curricular Competencies and Content in the course description. As described in the Goals and Rationale:

At its heart inquiry is a process of metacognition. The purpose of this course is to bring this metacognition to the forefront AS the learning and have students demonstrate their ability to identify the various forms of inquiry – across domains and disciplines and the stages of inquiry as they move through them, experience failure and stuckness at each level. Foundations of Inquiry 10 recognizes that competence in an area of study requires factual knowledge organized around conceptual frameworks to facilitate knowledge retrieval and application. Classroom activities are designed to develop understanding through in-depth study both within and outside the required curriculum.

This delves into the idea of learning and failure, which I’ve spoke a lot about before.In each of the examples above, we are asking students challenging questions. We are asking them to critically think about what we are asking AI; to think about how we can improve on AI responses; or, to think about how to use AI responses as a launching point to new questions and directions. The use of AI isn’t to ‘get to’ the answer but rather to get to a challenging place to stump students and force them to think critically about the questions and responses they get from AI.

And sometimes the activity will be too easy, other times too hard, but even those become learning opportunities… content free learning opportunities.

Google proof vs AI proof

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I remember the fear mongering when Google revolutionized search. “Students are just going to Google their answers, they aren’t going to think for themselves.” Then came the EDU-gurus proclaiming, “If students can Google the answers to your assignments, then the assignments are the problem! You need to Google proof what you are asking students to do!”

In reality this was a good thing. It provoked a lot of reworking of assignments, and promoted more critical thinking first from teachers, then from students. It is possible to be creative and ask a question that involves thoughtful and insightful responses that are not easily found on Google, or would have so few useful search responses that it would be easy to know if a student created the work themselves, or if they copied from the internet.

That isn’t the case for Artificial Intelligence. AI is different. I can think of a question that would get no useful search responses on Google that will then be completely answerable using AI. Unless you are watching students do the work with pen and paper in front of you, then you really don’t know if the work is AI assisted. So what next?

Ultimately the answer is two-fold:

How do we bolster creativity and productivity with AND without the use of Artificial Intelligence?

This isn’t a ‘make it Google proof’ kind of question. It’s more challenging than that.

I got to hear John Cohn, recently retired from MIT, speak yesterday. There are two things he said that kind of stuck with me. The first was a loose quote of a Business Review article. ’AI won’t take over people, but people with AI are going to take over people.’

This is insightful. The reality is that the people who are going to be successful and influential in the future are those that understand how to use AI well. So, we would be doing students a disservice to not bring AI into the classroom.

The other thing he said that really struck me was, “If you approach AI with fear, good things won’t happen, and the bad things still will.”

We can’t police its use, but we can guide students to use it appropriately… and effectively. I really like this AI Acceptable Use Scale shared by Cari Wilson:

This is one way to embrace AI rather than fear and avoid it in classrooms. Again I ask:

How do we bolster creativity and productivity with AND without the use of Artificial Intelligence?

One way is to question the value of homework. Maybe it’s time to revisit our expectations of what is done at home. Give students work that bolsters creativity at home, and keep the real work of school at school. But whether or not homework is something that changes, what we do need to change is how we think about embracing AI in schools, and how we help students navigate it’s appropriate, effective, and even ethical use. If we don’t, then we really aren’t preparing our kids for today’s world, much less the future.

We aren’t going to AI proof schoolwork.

Top Risks 2024

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I’d never heard of Eurasia Group before a good friend of mine, an investor, shared the infographic below with me yesterday. According to their website,

In 1998, Ian Bremmer founded Eurasia Group, the first firm devoted exclusively to helping investors and business decision-makers understand the impact of politics on the risks and opportunities in foreign markets. Ian’s idea—to bring political science to the investment community and to corporate decision-makers—launched an industry and positioned Eurasia Group to become the world leader in political risk analysis and consulting.

According to their ‘Top Risks 2024‘ report:

2024. Politically it’s the Voldemort of years. The annus horribilis. The year that must not be named.

Three wars will dominate world affairs: Russia vs. Ukraine, now in its third year; Israel vs. Hamas, now in its third month; and the United States vs. itself, ready to kick off at any moment.

Russia-Ukraine … is getting worse. Ukraine now stands to lose significant international interest and support. For the United States in particular, it’s become a distant second (and increasingly third or lower) policy priority. Despite hundreds of thousands of casualties, millions of displaced people, and a murderous hatred for the Russian regime shared by nearly every Ukrainian that will define the national identity of tens of millions for decades. Which is leading to more desperation on the part of the Ukrainian government, while Vladimir Putin’s Russia remains fully isolated from the West. The conflict is more likely to escalate, and Ukraine is on a path to being partitioned.

Israel-Hamas … is getting worse. There’s no obvious way to end the fighting, and whatever the military outcome, a dramatic increase in radicalization is guaranteed. Of Israeli Jews, feeling themselves globally isolated and even hated after facing the worst violence against them since the Holocaust. Of Palestinians, facing what they consider a genocide, with no opportunities for peace and no prospects of escape. Deep political divisions over the conflict run throughout the Middle East and across over one billion people in the broader Muslim world, not to mention in the United States and Europe.

And then there’s the biggest challenge in 2024 … the United States versus itself. Fully one-third of the global population will go to the polls this year, but an unprecedentedly dysfunctional US election will be by far the most consequential for the world’s security, stability, and economic outlook. The outcome will affect the fate of 8 billion people, and only 160 million Americans will have a say in it, with the winner to be decided by just tens of thousands of voters in a handful of swing states. The losing side—whether Democrats or Republicans—will consider the outcome illegitimate and be unprepared to accept it. The world’s most powerful country faces critical challenges to its core political institutions: free and fair elections, the peaceful transfer of power, and the checks and balances provided by the separation of powers. The political state of the union … is troubled indeed.

None of these three conflicts have adequate guardrails preventing them from getting worse. None have responsible leaders willing and able to fix, or at least clean up, the mess. Indeed, these leaders see their opponents (and their opponents’ supporters) as principal adversaries—“enemies of the people”—and are willing to use extralegal measures to ensure victory. Most problematically, none of the belligerents agree on what they’re fighting over.

Think about this, the Russia-Ukraine and the Israel-Hamas wars both take a back seat to the US election as the top risk of 2024. Both have no positive outcome in sight and they still don’t pose the same threat as a tight election result in the United States. I wish I could disagree, but I too see this as a genuine concern. What makes it worse is Risk #4 – Ungoverned AI, and specifically disinformation:

In a year when four billion people head to the polls, generative AI will be used by domestic and foreign actors—notably Russia—to influence electoral campaigns, stoke division, undermine trust in democracy, and sow political chaos on an unprecedented scale. Sharply divided Western societies, where voters increasingly access information from social media echo chambers, will be particularly vulnerable to manipulation. A crisis in global democracy is today more likely to be precipitated by AI-created and algorithm-driven disinformation than any other factor.

I want to explore the other risks as well, but by far my biggest concern for 2024 is the US election. My greatest fear is a close and contested election. The by-product of this would not just be tragic for the US, but for the entire world. I wish this was just hyperbole, but it’s not, and reading a report like this just magnifies concerns I already had. Buckle up, we are in for quite a ride in 2024.

You can get the full Top Risks 2024 white paper on their website, (or click the image below).