There are a number of reasons why companies steer clear from NSFW AI, amongst which the most common reason is that it cost fragile implementations to be able such technology. However, building and deploying NSFW AI systems can cost over $500,000 per year including data acquisition costs for training models first hand.. which does not calculate in ongoing maintenance effort etc. This cost is one small business that often cannot afford, and may only dedicate 10-15% of their overall budget to technology investments.
A greater issue also lies in algorithmic bias. A large 2021 study found that culture bias in pornography NSFW AI affected false-positive rates: 30% of systems tested showed biases against images from particular cultures. This bias can in turn lead to an unfair content moderation which might hurt the credibility of a company and also betray user trust. Those added training and model adjustments to counteract these biases can raise development costs by 20-30%.
There are also consequences related to the legality and morality of using NSFW AI. A big barrier for companies is meeting regulation requirements like the GDPR in Europe which makes data usage and transparency very strict. Compliance failures result in up to 4% of a company's global revenue fines, which is too high for some businesses.
Not to mention data privacy concerns inherent in whatever NSFW AI ends up being used on. The scale to which these models are trained often involve datasets with clear content that can crawl how some fall way of collection, storage and use the data is very vulnerable. As a consequence, should any data privacy standards be hastily circumvented by the companies in question — both users and regulators could respond with backlash that might result in expensive lawsuits as well loss of consumer confidence.
Some companies are also so discouraged by the operational complexity that NSFW AI involves. To sustain high content moderation accuracy, the model is updated and retrained constantly with datasets scaling to several terabytes in size. The process is computationally expensive and time-consuming, rendering it infeasible for companies with minimal IT setup.
And businesses are also cautious about the potential fallout from mistakes made by AI. A prominent social media platform faced an eruption of user dissent when its NSFW AI falsely pulled down 15% non-explicit material this year (2022), a case-study in the perils of overcensorship. These kind of errors could result in 10-20% user engagement reduction, which can translate directly to company's income.
In this sense, certain ethical issues related to automation in the moderation of sensitive content are a barrier for some companies. Critics contend that using AI for these tasks can depersonalize the decision-making, To make matters worse, this approach may also bring about unfair or unsympathetic results. Ultimately, this could lead companies to much prefer human moderators — even though individual content review is far more expensive.
On the other hand, nsfw ai faces a number of technical challenges; due to these limitations in handling nuanced content and overlapping categories for data (many images are only obviously one thing sometimes or partway), this makes them less attractive technically. Especially in content accuracy and contextual critical environments companies might prefer to steer clear of the potential exposure.
The NSA code ai is literal for why a large part of the industries are lacking behind in these new advanced technologies integration within their operational framework.
