AI doesn’t kill people. People kill people
In 2006, the UK authorities discovered a plan to smuggle drink containers filled with explosives on board jetliners. Overnight, all containers over 100ml were banned from handcarry. 20 years later the same rules are applied, despite significant advances in screening technology, and the policy is only now being slowly relaxed for some travellers. This story shows that regulators are fast to regulate but very slow to deregulate when the landscape changes. The same was observed during the COVID pandemic event and for just about every level of government.
The AI industry is fast-changing and has recently attracted attention for the possibility that a rogue bot could wind up killing all humans for jollies. Some senior AI figures place a 10% chance of this occuring within 10 years, and have called for a slow-down in the rate of change in the technology. Regulators are jumping with joy at this prospect but what could be the cost?
AI bots don’t kill people, people kill people
I have said many times before that computers are dumb but fast while humans are smart but slow. Therefore a human with a computer is a smart and fast operative that can achieve great things. Currently, every activity undertaken by a computer is at the instruction of a human. A human prompt could be ‘make the lunch queue shorter. Kill all humans if you have to’ Assuming the prompt is accepted and the bot thinks it is necessary to kill all humans to achieve the instructions goal then it may organise an army to do the business. But the instruction is given by a human…
What is driving the AI scare campaign? From chatbots to Vibe coding
The idea of AI has been around for decades but it really only stormed to prominence in 2023 when the first ‘Generative’ Large Language Models became laptop toys for the average user. They would generate any amount of prose in response to a question, drawing on language structures learned from the trillions of pieces of written junk available on the internet. For example, ‘create a pitchbook for my new chatbot startup’ delivers an impressive document. But after a couple of years of LLM’s replacing research analysts who write reports and challenging the education system, the AI craze pivoted to ‘Vibe Coding’ whereby a simply worded prompt can generate hundreds of lines of computer code to deliver an app that ‘works’ without the need for a software engineer. How is this possible and why?
First the how. There is an enormous repository of computer code named GitHub that contains open source objects to instruct computers to perform a set task. Blending the chatbot’s plain english prompt with a search of the GitHub database now enables an entire software application to be pieced together from existing functions. Let’s face it, most software is just input some data, perform some linear calculations and output in another format. Anything you want to do has, most probably, already been done in GitHub. The trick is to find it which is what the LLM is good at.
Second the why. This is my conjecture. Far from threatening the existence of humanity, Generative LLM AI models have run their course and now have nowhere to grow. All the data in the internet has been picked over. So software development is the natural sub-application of a technology that finds stuff, categorises it for future use if asked and delivers stuff when prompted. Coding became a gee-whiz branch of AI. However it, too, has its limits.
Why the current calls for regulation from amongst the AI czars?
The stories at the beginning of this piece argue that regulation is quick to be imposed but very slow to be repealed. With nowhere to grow and bills to pay, how convenient would it be to invite regulation into the AI boiler room effectively slowing the development agenda and entrenching the existing players at the expense of competition? This would not be an illegal cartel. Rather it would be justified on the need to save humanity…who will argue with that?