A.I. Isn't What You Think It Is

 I've been in a series of presentations over the past couple of months where organizations are getting frantic about catching the 'AI Wave'. This urgent need to feel like they aren't missing out on a fad is understandable, but like so many emerging technologies, getting 'into it' won't be effective if you ignore the foundations its built on, and the foundations of AI and the technology itself are... problematic.

You can't have 'generative' AI without massive data sets to train it on. This data is scraped from the internet and then fed into systems that can eventually give users "a statistically likely configuration of words" that look like an answer. That's right, the brilliant answer you just got on a generative AI platform isn't really an answer, it's a cloud computer cluster giving you its best guess based on crowdsourced data. None of that stops people from thinking it's intelligent (it isn't), and being in a panic about missing out.

Putting the fact that AI isn't nearly as smart as the marketing portrays it aside for a moment, large data and the cloud infrastructure that stores and delivers it are a house of cards teetering on the edge of collapse. You can't have AI without climbing to the stop of this wobbly infrastructure. How precarious is it? Data growth worldwide is in an explosive phase of growth (partially driven by the AI fad). Our overloaded storage infrastructure is under pressure because AI uses it much more aggressively that simply storing information. AI demands fast data retrieval and constant interaction making the rise in AI particularly problematic for our stressed storage systems.

We're facing data storage shortages in the next couple of years because of our belief that the cloud is an infinite resource. It isn't, it's an artfully hidden technological sleight of hand. The irony is that our digital storage infrastructure limitations will also end up limiting our current crop of AIs as well.

The staggering environmental costs that underlie our myth of an infinite digital cloud haven't  been mentioned yet, but like many of our other ecological marketing myths (electric vehicles), pushing the messy business of how it works out of sight of the consumer is a great way to market a green future while doing the opposite. Data centres in the US consume over 2% of all electricity in the country. There are benefits to scaling large data centres, but the trend into the foreseeable future is that the cloud will continue consuming more energy out here in the real world. That we're increasingly throwing limited resources at building AI guessing machines tells you something about our priorities.

One of the first posts on Dusty World was about dancing in this datasphere twelve years ago. Back then I'd found a quote by Google CEO Eric Schmidt talking about the coming information revolution:

I'd make a distinction between information and data. One is useful, the other is raw binary numbers and storing the majority of it is a complete waste of time and resources. Sussing out information from data is an ongoing challenge. That doesn't change the fact that the amount of data being generated back then wouldn't even register on the graph below, which looks like a runaway growth curve - you can make good money from all that data.

So, we live in a world that is well into an aggressive phase of digital growth, though very few people understand how any of that works. Even as we compile more content than we have in the entirety of human history to feed the attention economy, we also decide to play a sleight of hand game with machine learning on massive datasets just to see if it'll work.

From an educational perspective, AI is in the wild now and ignoring it will only get you and your students in trouble. If we're going to make functional use of this progenitor of true artificial intelligence, we need to teach the media literacy around it so that people understand what it is, how it works and how best to use it to amplify rather than replace their humanity.

I've seen a lot of people panicking about AI taking their jobs away, but if your work output is a statistically likely configuration of words, then you're not applying much of your vaunted human intellect to the task at hand and probably should be replaced by one of these meh AIs. But if you're one of those humans who actually thinks, even this stunted AI can be a powerful ally. In a fight for intellectual supremacy who would you think would win?

1. just machines
2. just people
3. an empowered hybrid of the two

The move here during this awkward adolescence of artificial intelligence where we're faking it until we make it is to leverage the tool to best effect. If effective use of AI speeds up our ability to gain actionable information in the chaos of data that surrounds us, then we can more quickly move on to the next real steps in technology evolution.

The other day I described AI as we currently define it as a hack to keep classical computing ahead of the data tsunami we're living in. At the time I was surprised by how I described it, but classical computing is reaching the limit of what it can do. For the past few years we've been finding speed in parallel processing such as adding computing cores to CPUs rather than making faster ones. We've also been finding efficiencies in how we manage data such as creating more organized memory caches to better feed our processors. Ultimately, I feel like generative AI in 2023 is another one of these patches. It's a way to make our overwhelming data cloud more functional to us.

This is from a presentation I've been giving that attempts to bring people into a better understanding of the hype. AI (even this meh one) will replace you if you let it, so don't!

Digital technologies aren't going to go anywhere, but they are a 'low resolution' way to compute. There is also the problem of reducing the complexity of reality to ones and zeroes. Mathematical concepts can help us understand relationships, but they will always be inherently reductive; they're never the thing itself but a simplified abstraction of it. Digital reduces the world to ones and zeros, but there is a better way.

When we run out of nanometres like we have with electronics, the next step is a big one, but it's one we're working on globally as a species right now. In the next decade we're gong to figure out how to use the building blocks of nature itself to compute at speeds that classical computers can't imagine. What will this do for our data clogged world? One of my hopes is that it will process much of that data into usable information, information that we can then use to solve this mess we've gotten ourselves into. When you have an answer you no longer need to keep the information leading to it.

I'll weather the current AI hype storm, but if you ask me what I'm really excited about it's artificial intelligence realized on a fault tolerant quantum computer. The future beyond that moves in directions I can't begin to guess, and that is exciting. imminent and absolutely necessary if we're going to prevent a global collapse of human civilization. Some people might get panicky about that, but they're the same ones who think a cloud based statistical guessing machine will replace them.

You Want to Teach WHAT?!? Reconfiguring Technology in Schools to Empower Pedagogy

Cybersecurity is one of the more challenging subjects to try and bring into classrooms, even though every one of them depends on it every day to function; everything from attendance to lesson content happens via networked computers in 2023.

Few people have advanced digital media fluency when it comes to using software and hardware, but that's just the tip of the iceberg with cybersecurity. It also depends on skills from many other technical subjects that don't get much attention in K-12 classrooms, such as software development, networking, information technology, IoT and programming, but not just high level stuff, you also need to be comfortable looking at firmware and low level coding.

Cyber skills aren't just about leveraging these interdisciplinary technologies though, they're also about discovering, understanding and resolving the many points of failure inherent in them. This is something most people feel very uncomfortable doing. For the vast majority of users, when technology goes wrong it's someone else's problem. Even for the people who build and maintain networks, the dark arts of cybersecurity cause great unease.

One of my hobbies is restoring old motorbikes. There is a strange parallel to cybersecurity in this. Many mechanics won't touch old machines because they don't lend themselves to modular parts swap fixes, which is how all modern shops work - technicians don't fix things, they replace them. Diagnosing an old machine takes patience and sensitivity that many mechanics haven't learned in our digital world of part numbers, modular engineering and timed repairs to maximize profit. I've talked about this before in relation to Matt Crawford's books and I think there is a corollary with IT and cybersecurity. Many of the people who build and maintain our systems aren't interested in how they might break, they are only interested in keeping them running as cheaply as possible. That's good for running your enterprise system as long as there are no surprises, but not so good if you want to build something bespoke or prepare for the many nasty surprises out there.

I was thinking about this challenging situation after attempting to convince school board IT departments from coast to coast about the technical requirements of the CyberTitan/CyberPatriot competition. I've been told again and again by people struggling to provide IT support in schools that they won't run VMWare or Cisco's Packet Tracer simulator because they:

1) are viruses (they aren't, though they are a great tool for safely examining them)

2) pose a threat to their systems. They don't - they actually do the opposite, but training people in the arcane cyber arts scares many of the people managing IT in education.

Virtual machines are used in cybersecurity (and network building) to test software and network environments. By examining a virtual machine cyber operators can explore how a machine has been compromised and what they might try to repair it in a safe (virtual) environment. VMWare is one of the biggest players in this field, and cleaned up at last year's cybersecurity awards, yet many board IT departments declared it a hazard. I suspect the hazard is in teaching ICT and cybersecurity best practices, and isn't that a tragedy?

I sympathize with the IT departments I've communicated with. They are responsible for running complex enterprise systems that support hundreds or even thousands of users with varying levels of system access (administrators, office staff, teaching staff, building maintenance, and more). That's more than many IT departments manage in other industries, but educational IT also has to serve tens of thousands of vulnerable sector clients (students), all of whom are coming at them with a staggering array of hardware and software without any real training on it. To make it even worse, most of them will be connecting to these systems using out of date and possibly compromised machines.

An attack surface is a concept that helps cybersecurity types better understand how a bad actor might exploit their network. The software you're using, the hardware it runs on, the network you're logging in from, other software installed on your device, the operating systems you're using, and the systems that connect it all together along with all the cloud based stuff you depend on are all components of a modern attack surface, and the education one is particularly complicated.  

One of the last big network installs I did before I went into teaching was at Glaxosmithkline in the early zeroes. This was a network of hundreds of desktops, hard wired via ethernet into an onsite server that provided all the 'cloud' they needed. The desktops all ran the same operating system and software on identical hardware. No one on this network had internet access, closing down a massive headache in terms of attack surface (internet access in a world experiencing a digital skills crisis is a nightmare!). This kind of simplicity is a distant memory in 2023. With our rush to the cloud, attack surfaces now include all the online managed systems we so gleefully replaced our secure networks with. BYOD and off-site work only pile more complexity on.

Comparing that GSK network to any modern education network is an apples to fruit salad comparison. On any day at dozens of school and administrative sites across a board you've got a nearly infinite number of different devices logging in, from phones with varying software packages (most of which are probably out of date and may well contain malware) to other personal technology (tablets, laptops, etc) all peppering your network with requests that may be school related or (more often) not.

To try and mitigate this complexity inflation, many boards have dumped computers that do onsite computing (like desktops and laptops) in favour of an easier to manage (because it can't do much) chromebooks. These simple machines can't get infected like a fully interactive operating system can, but you're still susceptible to fake browser extensions and compromised websites. This is usually solved by preventing users from customizing their chromebooks with extensions, further reducing what they can do.

With all this in mind, I was struck the other day by the idea that educational IT departments are missing a key component: a department focused on enabling technology empowered pedagogy (the reason we have schools... remember?). Early on in the edtech revolution we had OSAPAC in Ontario, which vetted software and created a provincial bank of safe to use software for learning digital skills in classrooms. With the rush to cloud based systems, OSAPAC evaporated and most school systems fell in with multi-nationals offering 'walled gardens' such as GAFE (Google Apps for Education) or the Microsoft equivalent. As this migration happened, teachers and students lost access to essential digital media literacy opportunities, especially when it comes to advanced digital skills such as 3d modelling, game design or cybersecurity.

A way to combat this skills deflation would be to create local IT support units dedicated to providing teachers with digitally enhanced student learning opportunities instead of starving us of them. I'd go a step further and suggest that the messy enterprise side of things that is such a headache should become the responsibility of the Ministry. Many cost savings and security enhancements could occur from centralizing these systems. It would also mean that students and staff moving between boards would be able to migrate more easily because everyone would be on the same systems. There would also be opportunities to collect provincial data more easily that would support better education policy, not that we like to collect data before making education policies in Ontario.

This does not mean the end of regional school board IT departments. Instead of chasing the tail of impossible enterprise expectations with insufficient funding, they would be provided by a central provincial authority with the secure standards and proper support. Imagine how much we might save if every board in Ontario isn't reinventing the wheel over and over again with varying degrees of success.

Local school board IT departments would be entirely focused on working with their teachers to find the best hardware, software and cloud based learning opportunities based on the needs of the programs they are running. Instead of saying no and reducing technology access to enhanced pedagogical learning opportunities in our classrooms, our local IT departments would become sources of local technical expertise focused on helping public education close an ongoing digital skills crisis.

I'm writing this in a hotel room in the north end of Toronto the night before attending the Ontario Public Sector Cybersecurity conference. I want to believe that the people at this event are taking the challenges of technology enhanced education, including the tremendously difficult task of engaging with cybersecurity learning, seriously in 2023, but I fear it's going to be all cartoons and platitudes. Here's hoping.