It wasn’t me — it was my AI agent!

Unchecked AI Control Could Lead to Disaster — Here’s Why Human Oversight Matters

By: Rooz Aliabadi, Ph.D.

AI agents are shaking up the tech world. Unlike traditional chatbots confined to a single chat window, these next-generation systems can move across apps and handle complex tasks — like booking appointments or making purchases — based on a simple prompt. As these agents grow more powerful, one critical question looms: How much control are we prepared to give up, and what are we trading in return?

New frameworks and features for AI agents are emerging nearly every week, with companies praising them as tools to simplify our lives by handling tasks we can’t — or prefer not to — do ourselves. Examples include the “computer use” feature, which allows Anthropic’s Claude to operate directly on your computer screen, and the general-purpose AI agent Manus, which can use online tools for tasks like finding potential customers or planning travel.

These breakthroughs signal a significant leap in artificial intelligence: systems that can operate across the digital landscape with minimal or no human supervision.

The appeal is obvious. Who wouldn’t want help with tedious tasks or responsibilities we don’t have time for? AI agents might soon remind you to check in with a colleague about their kid’s basketball game or pull images for your next presentation — and not long after, they could be building the entire presentation for you.

Beyond convenience, the potential impact on people’s lives is profound. Agents could carry out online tasks through simple voice or text commands for individuals with limited hand mobility or low vision. In emergencies, agents could coordinate large-scale responses — like directing traffic to help evacuate a region quickly and efficiently.

This exciting vision comes with serious risks, especially as we sprint toward ever-greater autonomy. AI agent development may be approaching a critical — and potentially dangerous — turning point.

Losing Control, One Step at a Time

At the center of what makes AI agents so exciting — and so concerning — is a fundamental tradeoff: the more autonomous these systems become, the more control we, as humans, gradually relinquish. This tradeoff isn’t just a side effect; it’s central to the promise and peril of AI agents. These systems are designed for flexibility and can execute a wide variety of tasks without the need for explicit programming. That flexibility is what makes them powerful — and what makes them unpredictable.

Much of this adaptability stems from many AI agents being built on top of large language models (LLMs). These models can generate creative, human-like responses but are also inherently unpredictable. They don’t “understand” as humans do, and they can produce surprising, illogical, or even dangerous outputs. In a basic chat interface, those errors might be amusing or mildly frustrating — but ultimately contained within a conversation. However, when the same model is given the ability to act across multiple applications, those minor errors can spiral into serious consequences. A simple misunderstanding or hallucination could result in unintended actions, such as deleting files, misrepresenting a user, or even making unauthorized purchases. Ironically, the feature being marketed as revolutionary — reduced human oversight — is also its most glaring vulnerability.

It helps to view AI agents along a spectrum of autonomy to grasp the scope of this risk. On one end are the most straightforward systems: essential automated responders like customer service chatbots, which can greet users or provide limited assistance without affecting anything beyond a single interface. These systems don’t shape workflows or make decisions — they’re reactive, not proactive.

At the opposite end of the spectrum are fully autonomous agents. These systems can write and execute code, make decisions without human input, and initiate actions across a digital environment. They can move files, modify records, send emails, or change settings — all without being asked to do so in real-time. Once deployed, they operate under their logic, guided only by broad instructions or goals. Between these two poles are several intermediate stages of autonomy:

• Routers, which determine which pre-defined step to take based on a given input.
• Tool callers, identify the right tools from a set of options and execute them based on user-defined functions.
• Multistep agents, not only select tools but also decide how and when to use them, chaining together complex sequences of actions.

Each step up in this spectrum reduces the level of direct human intervention and increases the potential for unintended outcomes. This isn’t necessarily bad — these capabilities allow agents to be useful. But with greater autonomy comes greater risk.

The practical applications are immense. AI agents could save hours by automating scheduling, drafting documents, performing research, or generating strategic insights. They could also profoundly support people, assisting those with disabilities by navigating digital environments using simple voice commands or coordinating relief efforts in the midst of crises by analyzing and acting on real-time data. But for every benefit, there’s a mirror-image threat.

Privacy is a significant concern. For an agent to help you recall details about a person — say, to prepare for a meeting — it would need access to that person’s private information and your communication history. This kind of surveillance, even if helpful, creates enormous potential for abuse or data leaks. Agents that analyze architectural blueprints to generate directions might be a boon for building planners — but the same functionality could be weaponized to assist someone in gaining unauthorized access to secure areas.

And the danger multiplies when agents operate across multiple platforms simultaneously. Imagine an agent with access to your email and social media accounts. A simple misinterpretation or vulnerability could lead to private information being posted publicly. Worse, misinformation an agent shares might appear to come from you, blurring lines of responsibility and truth. Traditional moderation systems might not flag these posts, which could do lasting reputational damage once amplified. As this becomes more common, we may start hearing a new kind of excuse: “It wasn’t me — it was my AI agent!”

The line between assistance and autonomy is getting thinner every day. As we continue offloading decisions and responsibilities to machines, we need to ask ourselves what these agents can do and what happens when they do too much.

Keep Humans in the Loop — Always

History has shown us, time and again, the dangers of removing human oversight from high-stakes decision-making. One particularly chilling example comes from 1980, during the height of the Cold War. A U.S. early warning system mistakenly indicated that more than 2,000 Soviet nuclear missiles were en route to North America. Alarms were triggered, emergency protocols were activated, and military leaders faced the terrifying possibility of needing to respond in kind. The world teetered on the edge of nuclear disaster — not because of malicious intent, but because of a computer error. What ultimately averted catastrophe was not the system’s design or accuracy but the judgment of human operators who cross-checked the data with other warning systems and decided to hold off. History might have taken a drastically darker turn if those decisions were left entirely to automated systems prioritizing speed over accuracy.

This historical precedent underscores why human oversight isn’t just a technical detail — it’s a moral and existential imperative. As AI agents become more powerful and more autonomous, the temptation to let them handle increasingly complex decisions will grow. Advocates may argue that the efficiency gains justify the risk. And yes, AI agents can bring undeniable benefits: faster decision-making, optimized workflows, and reduced human error. However, achieving these gains does not require handing over full control. Actual progress in AI means developing systems that augment human decision-making — not replace it.

We need to embed guaranteed human oversight into the very architecture of AI agents. That means establishing clear boundaries on what these systems can do and ensuring there’s always a human in the loop — especially when the stakes are high. AI should be an extension of human intention, not a substitute for it.

One promising path forward lies in open-source AI development. Unlike proprietary systems that conceal their inner workings behind corporate firewalls, open-source agent systems invite scrutiny, collaboration, and transparency. They allow researchers, developers, and even the public to understand what the system is doing and why. At Hugging Face, they are investing in this vision by developing smolagents — a lightweight, open framework for building AI agents in sandboxed, secure environments. These agents are designed with transparency at their core, making it easier for independent parties to verify whether the agent’s actions are appropriate and whether proper human oversight is in place.

This approach is a deliberate departure from the current trend toward more complex, black-box AI systems. Too many commercial models today are layered in secrecy, where even developers struggle to fully explain how or why a system makes a decision. This opacity may be tolerable when an AI recommends songs or summarizes emails, but it becomes unacceptable when that same system can move money, make public statements, or interact with sensitive data.

Transparency, security, and human governance must become foundational design principles — not afterthoughts. Building AI agents should not be about racing toward total automation but about creating systems we can trust, verify, and, when necessary, override. Trust in AI doesn’t come from its power — it comes from our ability to understand and control it.

Ultimately, we have to remember what all this technology is for. The goal isn’t to maximize efficiency at all costs. The goal is to enhance human flourishing — to create tools that empower us to live better, safer, more meaningful lives. That means designing AI agents to be assistants, not decision-makers, tools, not authorities.

Human judgment, imperfect though it may be, is still the best defense against unintended consequences. As we move deeper into the era of intelligent agents, we must not forget that the most advanced feature any AI can have is a clear, unbreakable line to a human who remains accountable, aware, and in charge.

This article was written by Rooz Aliabadi, Ph.D. (rooz@readyai.org). Rooz is the CEO (Chief Troublemaker) at ReadyAI.org

To learn more about ReadyAI, visit www.readyai.org or email us at info@readyai.org.