Our June 2021 archive examined three recurring claims about AI: that it would eliminate all jobs, inevitably exceed people at everything, or inevitably take control. The original discussion contrasted these broad predictions with task-specific systems.
A system can perform well on one task without having general competence. Equally, the fact that people build a system does not guarantee that its behaviour will always be predictable. Claims about future capabilities and employment require more care than a simple true-or-false label.
The article’s practical thread was that automation changes tasks and creates a need for new skills. This edited archive does not repeat its confident assurances about future safety or job creation. Instead, it retains the distinction between demonstrated capabilities, possible applications and uncertain long-term outcomes. Robustness, oversight and the effects on people remain separate questions to examine.
This February 2021 article considered the benefits and risks of using AI in everyday software and work. It discussed assistants, smartphone applications and the automation of repetitive tasks.
The original November 2022 explainer introduced three terms often grouped together under artificial intelligence: narrow AI, general AI and superintelligence. They describe different levels of capability, rather than three interchangeable labels for the same technology.
Our October 2022 industry overview looked at five areas exploring machine learning: healthcare, transport, finance, retail and property valuation. Each used prediction or pattern recognition, but with very different data and consequences for mistakes.
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