Why Is Janitor AI So Slow? [2024]

Why Is Janitor AI So Slow? Janitor AI is an artificial intelligence system designed to monitor online content and remove toxic and harmful material.

Since its launch in 2021, Janitor AI has faced criticism for being slow to detect and take down problematic content. This article will examine some of the major factors contributing to Janitor AI’s slow response times.

Limited Processing Power

One of the main limitations facing Janitor AI is its available processing power. As an AI system monitoring massive amounts of online content, Janitor requires extensive computing resources to analyze text, images, and videos.

However, as a new company, Janitor does not yet have access to top-of-the-line hardware to match the capabilities of tech giants. Its servers and chips constrain the speed at which the AI can review and moderate content. Upgrading infrastructure requires major investments in equipment and electricity, slowing expansion of computing capacity.

Focus on Accuracy Over Speed

The creators of Janitor AI have prioritized accuracy in moderation decisions over speed. This means the algorithms powering Janitor’s content analysis are complex and meticulous rather than simple and fast.

While this approach helps avoid erroneous takedowns of benign content, each moderation decision takes more time to reach. Setting up the AI models to learn and account for nuances in language and imagery is a delicate process across different cultural contexts. As a result, Janitor AI moves slowly to ensure each call is made correctly rather than rushing and risking mistakes.

Bias Mitigation Mechanisms

Removing bias from AI systems is a central priority for the team behind Janitor AI. However, the bias checks and tests built into the moderation process also slow down decisions.

For each potentially rule-breaking piece of content, Janitor runs various simulations and comparisons to detect possible bias influencing the decision. This includes checking performance consistency across user demographics, questioning rationale for removals, and more. These necessary mechanisms are still being refined and expanded, adding to the deliberation timeline.

Lack of Content Familiarity

Being a relatively new AI system, Janitor does not have the historical knowledge more established platforms have accumulated. Veterans like Facebook and YouTube have handled massive volumes of content over decades of operation.

Their AI tools have been exposed to billions of text samples, images, and videos to learn nuances. Janitor’s lack of familiarity with a lot of modern internet content types and trends slows its ability to assess them. As its databases expand through new data ingestion, Janitor’s content comprehension and recognition speed keep improving.

Reliance on Human Reviewers

Critical and irreversible moderation decisions – like permanent account suspensions – require human review before action. Janitor AI flags severe content for additional scrutiny, but places it in queues for staff evaluation.

With limited personnel available, wait times for final calls drag on. The reliance on people as a check against AI bias also protects users but reduces speed. As reviewer teams scale up, they may accelerate decisions, but people are inherently slower than machines.

Cautious Iterative Development

The developers at Janitor are taking an incremental approach to enhancements rather than rushing ambitious changes. AI architecture is based on machine learning models which require extensive testing and tweaking before deployment.

New algorithms undergo rigorous experimentation to avoid unexpected impacts on other functions after launch. Conservative development philosophy pays dividends long-term but can slow visible progress in the short-term. Resisting shortcuts is wise given societal dependence on social media.

Trade-Off Between Speed and Responsibility

Janitor faces criticism around slow response times, often from users aggrieved by harmful content left unchecked. However, the creators of Janitor AI argue that enforcing community guidelines on internet platforms is too important for hasty judgment calls.

Rushing decisions risks over-censorship, while moving too slowly enables abuse. Janitor continues working to improve efficiency but not at the cost of accuracy and accountability. As an AI moderator holding real influence over discourse online, Janitor bears immense responsibility.


In review, Janitor AI’s apparently sluggish content moderation stem from necessary precautions around precision, ethical AI practices, site responsibility, and restrained development protocols. While users understandably grow frustrated with lengthy waits, Janitor’s creators prioritize care and wisdom guiding impactful decisions over knee-jerk reactions to please crowds.

As the system expands access to computing power, real-world data, and human insights, its speed stands to improve over time. But its core design stands opposed to blind, automated mass takedowns in favor of moderate and contextual discretion. An AI system deciding the boundaries of free speech online cannot afford to be hasty, but rather deliberate, careful and just.

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Why is Janitor AI so slow in moderating content?

Janitor AI is slow due to a few key reasons. The main factor is that its algorithms are focused on accuracy over speed. Making correct content moderation decisions is prioritized over rushing through judgments. It also lacks the processing power of major tech companies, relies on human reviewers for oversight, and takes an iterative approach to improvements – all of which contribute to perceived slowness.

Does Janitor AI not have enough computing power?

As a relatively new company, Janitor AI does not yet have access to the same level of computing resources as major tech giants. Its servers and hardware limit how quickly the AI system can analyze and moderate online content. Upgrading infrastructure is costly and takes time. More processing power would allow faster content review.

Is Janitor AI too focused on accuracy over speed?

Yes, the creators of Janitor AI have chosen to optimize their algorithms for precision rather than speed. This deliberate decision helps the AI avoid erroneous takedowns but results in longer wait times for moderation calls. As the system continues learning, accuracy and pace will improve in tandem.

Why does bias mitigation slow down Janitor AI?

Reducing biases embedded in the AI is a top focus for Janitor’s developers. However, all the bias checks and tests built into the moderation process add time before final decisions. Running comparative analyses and other scrutiny to detect unfairness adds to the overall timeline. But it’s a necessary step.

Does Janitor AI not understand today’s internet content well enough?

As a relatively new platform, Janitor AI does not benefit from decades of historical data that sites like Facebook or YouTube have. Its lack of exposure to large volumes of contemporary internet text, visuals and videos leads to slower comprehension and assessment. But its knowledge is continuously expanding through new data ingestion.

How do Janitor’s human reviewers slow it down?

Janitor AI cannot make irreversible decisions, like account deletions, without human oversight. Adding this crucial step enables more accuracy but queues build up waiting for staff to manually review the most serious cases flagged by the algorithms. Expanding personnel would quicken the process but people are inherently slower than AI.

Why can’t Janitor AI progress be faster?

Janitor’s developers cautiously roll out incremental enhancements to the AI architecture based on extensive testing. Rapid, sweeping changes risk unintended impacts across other functions. While conservative iteration progresses modular upgrades, it does mean visible speeds remain slow in the short-term. However, it pays off in stability long-term.

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