Re: The effects of AI on employment, the UK has huge & profitable creative sectors in design (products, automobiles, fashion, etc.) & entertainment (music, theatre, film, TV, art, literature, etc.) - the UK punches well above its weight internationally - that bring in £100s billions each year. I suspect that for those sectors to remain competitive in the mid to longer term, they need to cultivate creative workers who can continue to innovate in new & unexpected & unpredictable ways, something that statistical engines are famously bad at. In the shorter term, it may be tempting to attempt to replace/substitute/assist/augment/etc. the more routine creative jobs to save money but then how will these industries find & cultivate new talent? Who's going to train up & join a field of work with even poorer prospects for future employees than there already is now? Where will the opportunities be for young creatives to get paid while they learn, develop their art & craft, & find their own, unique voices so that they can make valuable contributions? It's culling the young the enrich the old.
Re: the use of AI in tech & other sectors today, from what I've read, so far, the promises of faster, more productive workflows with AI assistance have yet to materialise. For example, they've found the senior software engineers with deep & broad understandings can indeed increase their productivity with AI assistants but less knowledgeable & experienced engineers take longer & produce more errors, slowing the whole process down. In other words, if you're already an expert, AI can help you be more productive, if not, it'll be more hindrance than help.
I see this in second & foreign language education too. The majority of language teachers don't have the kind of deep & broad understanding of what language is & how it works, & how & what we use it for (applied linguistics) that is necessary to generate useful texts & effective educational materials. For example, when asked what the learning objectives are & how the materials contribute to helping students achieve them, I tend to get blank looks &/or explanations of what students do rather than what they'll likely learn from doing them. While it's true of teacher-produced materials in general, AI systems are trained on materials that typically exhibit this attitude & lack of expertise in language learning materials design which, in turn, further entrenches this attitude. Since teachers don't have to analyse & think through the materials they're producing, they're less likely to develop an understanding of their shortcomings & possible opportunities for more optimal design based on linguistic & cognitive principles, i.e. They're not being exposed to original materials that exhibit a wide range of approaches, strategies, & techniques, rather, they're exposed to aggregated, statistical, monotonous, AI generated averages of them. /end of rant =D
Re: the use of AI in tech & other sectors today, from what I've read, so far, the promises of faster, more productive workflows with AI assistance have yet to materialise. For example, they've found the senior software engineers with deep & broad understandings can indeed increase their productivity with AI assistants but less knowledgeable & experienced engineers take longer & produce more errors, slowing the whole process down. In other words, if you're already an expert, AI can help you be more productive, if not, it'll be more hindrance than help.
I see this in second & foreign language education too. The majority of language teachers don't have the kind of deep & broad understanding of what language is & how it works, & how & what we use it for (applied linguistics) that is necessary to generate useful texts & effective educational materials. For example, when asked what the learning objectives are & how the materials contribute to helping students achieve them, I tend to get blank looks &/or explanations of what students do rather than what they'll likely learn from doing them. While it's true of teacher-produced materials in general, AI systems are trained on materials that typically exhibit this attitude & lack of expertise in language learning materials design which, in turn, further entrenches this attitude. Since teachers don't have to analyse & think through the materials they're producing, they're less likely to develop an understanding of their shortcomings & possible opportunities for more optimal design based on linguistic & cognitive principles, i.e. They're not being exposed to original materials that exhibit a wide range of approaches, strategies, & techniques, rather, they're exposed to aggregated, statistical, monotonous, AI generated averages of them. /end of rant =D