One of the biggest problems with having people in charge of Celtic who have no grasp of strategy, no sense of due diligence, and no understanding of systems outside their own narrow knowledge space is that they are prone to mistakes.<\/p>\n
Not just ordinary errors, but major miscalculations with long-term consequences across the club. The more complex the thing you\u2019re trying to adapt to your environment, the greater the capacity for those mistakes.<\/p>\n
Right now, I have a serious concern about where Celtic are heading.<\/p>\n
Most Read on The Celtic Blog<\/p>\n
We know that part of the plan for next year involves so-called \u201cdata-driven signings.\u201d That phrase alone sets alarm bells ringing. It doesn\u2019t just mean analysing numbers \u2014 which can be useful when done properly \u2014 but, I strongly suspect, it means leaning heavily on AI systems to do large parts of the scouting work.<\/p>\n
If that\u2019s true, then we may be in even bigger trouble than I first feared.<\/p>\n
It\u2019s one thing to have analysts look at data, weigh it against human scouting reports, and make balanced recommendations. It\u2019s another thing entirely to have a computer crunch numbers and spit out a list of names. I wouldn\u2019t be remotely surprised if Celtic have already dabbled in this \u2014 and if that\u2019s the real reason behind some of the disastrous transfer windows we\u2019ve suffered through.<\/p>\n
AI is one of those subjects that has fascinated me for a long time.<\/p>\n
People often ask if I\u2019m worried about AI making my own job redundant, and my answer is simple: no. Not because I\u2019m complacent, but because I know what AI can and can\u2019t do. It\u2019s not very good at replicating what I do. In learning how to use it \u2014 and where it breaks down \u2014 I\u2019ve seen first-hand just how many limitations it has.<\/p>\n
I use it in editing and for image generation. I work by dictating my articles into Word, and because Word is not great at understanding the Glasgow accent (or indeed any accent) I then wash the piece through ChatGPT to untangle it. That produces text that is close to what I was trying to say, but it comes with problems.<\/p>\n
It often changes my meaning. It often omits key words. It often excises entire paragraphs that were central to my argument.<\/p>\n
And sometimes, as it did yesterday, when it doesn\u2019t understand a name or something it just substitutes it for another one, which is why my report on the game referenced Dembele (no longer at the club) and Yang who didn\u2019t start.<\/p>\n
I don\u2019t like how ChatGPT writes either, and I often have to instruct it quite specifically not to attempt to rewrite my prose in any way, shape or form. It does not always listen.<\/p>\n
I also use ChatGPT at times for image generation and that\u2019s an area where it is meant to excel. I have to be honest; I\u2019ve had more than a few problems with it. I\u2019ve got fairly good at using AI tools for pictures, but only because I have a creative mind, generally know the mood I am going for and because I know how to ask for very specific things.<\/p>\n
I know when something looks wrong, I can tweak prompts, and I can iterate until I get something usable. But even then, it makes mistakes. Every image it produces has small errors \u2014 a hand wrong here, a shadow out of place there. The \u201cbest\u201d version of an image I wanted to create recently took me ten attempts, and still wasn\u2019t perfect.<\/p>\n
Now imagine that in a football context.<\/p>\n
You can\u2019t afford to \u201cnearly\u201d sign the right player after ten attempts. You can\u2019t afford a striker who looks like he fits the profile, but whose weaknesses are invisible to the algorithm. Football isn\u2019t about approximate results. It\u2019s about margins.<\/p>\n
The same issue shows up in other fields. A Harvard study on AI coding was celebrated because the machine only made errors 10% of the time. Sounds impressive, until you remember that if a human coder made errors in 10% of their work, they\u2019d be fired immediately. When it comes to code, one mistake breaks the whole program. That isn\u2019t \u201cgood enough.\u201d That\u2019s useless.<\/p>\n
Autonomous AI is another great myth of our time.<\/p>\n
Leave it unsupervised, and it will make catastrophic mistakes. Driverless cars are the perfect example. On paper, the task is simple: map routes with GPS, use visual recognition software to read signs and traffic lights, program rules for when to stop and start. And yet, years of testing show they make errors all the time.<\/p>\n
Why? Because the real world is messy. Sooner or later the car encounters something outside its frame of reference \u2014 and it doesn\u2019t know what to do. That\u2019s when you get an accident. The system wasn\u2019t built to handle the unexpected.<\/p>\n
Football scouting is the same. Numbers can tell you certain things, but what happens when a player doesn\u2019t fit the model? What happens when his \u201cdata profile\u201d looks good, but he\u2019s in a weak league, or has a temperament issue, or can\u2019t adapt to the culture? A human being would spot some of those things. A computer can\u2019t.<\/p>\n
This is why I don\u2019t believe we\u2019ll ever get to \u201cartificial general intelligence,\u201d much less the fantasy of \u201csuperintelligence.\u201d The whole rollout of AI into public policy and corporate decision-making will, I believe, end in embarrassment. AI isn\u2019t magic. It\u2019s not a brain. It still depends on human beings to feed it information, to design its code, and to shape its outputs. It will never be free of that.<\/p>\n
And the gap between what\u2019s theoretically possible and what we can actually do is vast. Fusion power is a good analogy here. We know it works in the Sun. The physics is sound. It\u2019s theoretically possible to build reactors that give us limitless clean energy. But we can\u2019t do it yet. The technical requirements are far beyond us.<\/p>\n
The same with space elevators. The physics says you could build one: a tether running from Earth to orbit, carrying payloads cheaply into space. But we don\u2019t have materials strong enough to make it work. In theory it\u2019s achievable. In practice, it\u2019s laughably out of reach.<\/p>\n
Or take room-temperature superconductors. If we could make them stable and reliable at normal pressures, they would revolutionise energy grids, transport, and computing. Physics doesn\u2019t forbid them. But despite tantalising lab results, we can\u2019t yet build one that works outside experimental conditions.<\/p>\n
AI sits in that same basket. There\u2019s no law of physics stopping us building smarter systems. But the gap between today\u2019s brittle, mistake-prone models and the hype of \u201cmachines that think like humans\u201d is enormous.<\/p>\n
Anyone who treats the hype as reality is walking blindfold into disaster.<\/p>\n
There\u2019s an entire industry built around AI now, and it\u2019s fuelled by hype. That\u2019s why it\u2019s everywhere; it\u2019s a technology in search of a use case, and a lot of the claims for what it can do are tenuous at best. Yet an industry is practically built on it.<\/p>\n
How does that happen, if the tech itself isn\u2019t sound?<\/p>\n
Well, the best analogy is the California Gold Rush. The dream was gold. The reality was that most prospectors went broke. So where was the industry? Well, you know who did make money, and a lot of it? The people selling picks and shovels.<\/p>\n
In AI, those \u201cpicks and shovels\u201d are GPUs and data centres. NVIDIA sells the hardware. Microsoft and Google build the infrastructure. They\u2019re the ones making billions. The rest is speculation and storytelling.<\/p>\n
And here\u2019s the thing: even in the fields where AI works best \u2014 specialist tasks in narrow domains \u2014 it\u2019s unreliable without heavy human supervision.<\/p>\n
The idea of using it to design something as complex and unpredictable as a football transfer strategy is worse than na\u00efve. It\u2019s dangerous.<\/p>\n
Celtic\u2019s transfer record in recent years is already patchy, to put it kindly.<\/p>\n
We\u2019ve had windows where millions were wasted on players who weren\u2019t up to standard, and where obvious squad gaps went unfilled. Imagine layering AI into that system. Imagine letting algorithms, not scouts and football men, drive recruitment.<\/p>\n
The result wouldn\u2019t be clever Moneyball. It would be driverless-car scouting \u2014 a system that works fine until it encounters something it wasn\u2019t programmed for. And in football, that\u2019s every window. Different leagues, different personalities, different hidden variables. Things a computer can\u2019t measure.<\/p>\n
The irony is that this board, so risk-averse in some ways, may convince themselves that AI scouting reduces risk. In fact, it multiplies it. It hands control over to systems that can\u2019t be trusted, then pretends the results are scientific. It would be a disaster \u2014 a greater disaster than hiring ten Mark Lawwell\u2019s and telling them to go wild.<\/p>\n
Celtic need strategy. They need vision. They need people who understand the club, the game, and the market.<\/p>\n
What they don\u2019t need is to outsource decision-making to machines that don\u2019t understand football and never will. AI has its uses, but football recruitment is not one of them. A transfer system built on AI recommendations would be madness.<\/p>\n
It wouldn\u2019t be progress. It would be another act of self-sabotage, on a grand scale.<\/p>\n","protected":false},"excerpt":{"rendered":"One of the biggest problems with having people in charge of Celtic who have no grasp of strategy,…\n","protected":false},"author":2,"featured_media":183044,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[554,733,4308,86,56,54,55],"class_list":["post-183043","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-technology","tag-uk","tag-united-kingdom","tag-unitedkingdom"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/183043","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/comments?post=183043"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/183043\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media\/183044"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media?parent=183043"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/categories?post=183043"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/tags?post=183043"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}