Question: A long-time client has asked us to help screen their work machines for pornography. They're worried about liability if sensitive materials were found. Their main concerns (for obvious reasons) are video, audio, and image files. If possible, they'd also like to scan text-based documents for inappropriate content. They have a hierarchy of not-for-work content starting with blatantly illegal (I don't have to list details), moving down to obviously offensive, and also including things that may be offensive to some - think lingerie ads, joke cards featuring butt cracks, and anything related to Howie Mandel.

My questions are:

* Is this ethical? I think it is since every employee legally agrees that their work machine belongs to the company and is subject to search. The screenings are not to occur on personal machines brought to work.
* Is it feasible? I've done a lot of image processing/indexing but this seems like a whole new world of complexity.
* Any references to successful techniques for discovering porn?
* Is it appropriate for me to archive the results when something is discovered?

Answer: 
This approach of controlling is certainly painful for both employees and IT people. Once anything enters inside the employee machine, there is no sure way of detecting it. You need to stop it entering in the machine at the first place.  

The best known practice for this is obviously control over the sites/domain which can be visited. Such list must be available somewhere on the net. Other than this you can also track the number of images, videos the employee has downloaded and from where it has come.  

There are chances that the material can come from other than web, like from external hard drive. There could be once a month random scan of the system where you can randomly pick some of the videos and images and check it manually. Not sure how it can be done. But automating of checking the images and videos is certainly out of scope and certainly will be erroneous.  

Actually I am not very much with the idea of restricting employees from doing personal stuff. You should trust your employees for this. Your employees should be busy enough in the office so that they don't get any time for this. The more worries are is the employee not doing his/her work right? Or has s/he installed some cracked or hacked software?
Image and content analysis to determine the differences between a tasteful photograph of a person, a swimsuit photograph, a nude photograph, depictions of pornography... as far as I know is nowhere near sophisticated enough to do in software alone.

Fortunately crowdsourcing should be useful here, as @ammoQ suggested in a comment. However I don't believe members of 4chan or any other forum would appreciate the vast number of *non*-pornographic images, such as generic web graphics for buttons, frames, advertisements, etc. being posted.

My recommendation would be to look into existing crowdsourcing solutions, such as [Amazon Mechanical Turk](https://www.mturk.com/mturk/welcome). (However the terms of service may explicitly prohibit the involvement of pornographic content, so be advised you might have to find another solution or roll your own.)

To make crowdsourcing feasible, your software should be prepared to do some or all of the following:

* Store information that links the content with the computer it came from
* Identify exact duplicates across the entire inventory and remove them (but origin information is retained)
* Downsample images to some dimension, perhaps 320x200, which is sufficient to identify the content of the image without retaining unnecessary detail and wasting storage space/bandwidth
* Create still images of video content at some regular interval and apply the same downsampling rule

Finally, the database of reduced images that represent the original image and video content is checked by users (or a designated team if you have the resources) according to your company's code of conduct. The program or interface might show a single image at a time, or a screen of thumbnails--whatever you deem best to obtain accurate information.

The identity of the computer from which images came should absolutely be secret and unknown to the persons evaluating the data. Additionally it should be randomized and each image probably checked more than once to remove bias.

The same technique could be used for text, but first the content could be scored by keyword rankings which remove the bulk of text from crowdsource review. Classifying a long document will of course be more time consuming than classifying an image.