Should I set up a personal AI agent to help with my daily tasks?
—Searching for Assistance
As a general rule, I think relying on any kind of automation in your daily life is dangerous when taken to the extreme and potentially alienating even when used in moderation, especially with regards to personal interactions. An AI agent that organizes my task list and gathers online links for further reading? Fabulous. An AI agent that automatically messages my parents every week with a quick life update? Horrific.
The strongest argument for not involving more generative AI tools into your daily routine, however, remains the environmental impact these models continue to have during training and output generation. With all of that in mind, I dug through WIRED’s archive, published during the glorious dawn of this mess we call the internet, to find more historical context for your question. After searching for a bit, I came back convinced you’re likely already using AI agents every single day.
The idea of AI agents, or God-forbid “agentic AI,” is the current buzzword du jour for every tech leader who’s trying to hype their recent investments. But the concept of an automated assistant dedicated to completing software tasks is far from a fresh idea. So much of the discourse around “software agents” in the 1990s mirrors the current conversation in Silicon Valley, where leaders at tech companies now promise an incoming flood of generative AI-powered agents trained to do online chores on our behalf.
“One problem I see is that people will question who is responsible for the actions of an agent,” reads a WIRED interview with MIT professor Pattie Maes, originally published in 1995. “Especially things like agents taking up too much time on a machine or purchasing something you don’t want on your behalf. Agents will raise a lot of interesting issues, but I’m convinced we won’t be able to live without them.”
I called Maes early in January to hear how her perspective on AI agents has changed over the years. She’s as optimistic as ever about the potential for personal automation, but she’s convinced that “extremely naive” engineers are not spending enough time addressing the complexities of human-computer interactions. In fact, she says, their recklessness could induce another AI winter.
“The way these systems are built, right now, they’re optimized from a technical point of view, an engineering point of view,” she says. “But, they’re not at all optimized for human-design issues.” She focuses on how AI agents are still easily tricked or resort to biased assumptions, despite improvements to the underlying models. And a misplaced confidence leads users to trust answers generated by AI tools when they shouldn’t.
To better understand other potential pitfalls for personal AI agents, let’s break the nebulous term into two distinct categories: those that feed you and those that represent you.
Feeding agents are algorithms with data about your habits and tastes that search through swaths of information to find what’s relevant to you. Sounds familiar, right? Any social media recommendation engine filling a timeline with tailored posts or incessant ad tracker showing me those mushroom gummies for the thousandth time on Instagram could be considered a personal AI agent. As another example from the ’90s interview, Maes mentioned a news-gathering agent fine-tuned to bring back the articles she wanted. That sounds like my Google News landing page.
