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Apple pushing faster on agentic Siri would carry three big risks
Yesterday saw two reports about Apple software development. The first said that the company was aiming to give Siri more agentic capabilities “as soon as next year,” while the second said that CEO John Ternus is pushing Craig Federighi to speed up software development.
If accurate, it seems near-certain the two reports are connected. But if Ternus really is pushing for an acceleration in Siri’s ability to act as an AI agent, that comes with three potentially huge risks …
Both reports were by Bloomberg’s Mark Gurman, though he didn’t directly connect them. On the Siri side, his newsletter contrasted the agentic abilities of some competitor models, suggesting that Apple ultimately wants to achieve the same things.
Dots, Muse and Grok can keep track of goals, determine what needs to happen next and continue pursuing objectives without the user initiating every individual step. Apple ultimately wants to go in this direction, I’m told, and I believe the company could make Siri more like an agent as early as next year.
The report about Ternus pushing Federighi for faster software development mentions “moving beyond necessary improvements to Siri,” of which agentic capabilities would be the obvious candidate.
But agentic capabilities are among the most dangerous forms of AI given the multitude of things that could go very, very wrong.
The most obvious is simply failing to carry out the task. Depending on the importance of it, the consequences could range from annoyance through to significant harm.
Technology has long failed to live up to one of its biggest promises: relieving us of mundane work in order to devote our time to more fulfilling things. For example, obtaining tickets to a popular gig or other event, which currently involves scheduling time in order to repeatedly refresh a page, perhaps wait through a queuing system, and finally carry out the transaction. It would be great to be able to hand this off to an AI.
But even on something relatively unimportant like this, if we delegated the task and the AI failed to obtain the tickets, especially if this was due to a silly error, this could prove enormously frustrating. If the task were more important, the results could obviously be far worse.
Potentially even worse is achieving the task but doing so in inappropriate ways. We’ve already seen high-profile examples of this, like the Hugging Face hack caused by an AI model seeking so hard to carry out instructions that it used underhand methods to bypass crucial safeguards in the process.