EU and Copyright : Upload filters: The dystopia has been canceled.

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How do upload filters work?

The principal argument of critics intent on frustrating digital copyright reforms that had already appeared to be on the home stretch is their charge that the disproportionate blocking of uploads would represent a wholesale assault on freedom of speech or, indeed, a form of censorship. Here, too, it is necessary to look more closely at the feasibility and potential of available options for monitoring uploads - and especially to consider the degree of efficiency that can be achieved by linking human and automated monitoring. In a first step, identification systems could automatically block secure matches or allow them to pass by comparing them against data supplied by collecting societies. Licensed content could readily be uploaded and its use would be electronically registered. Collecting societies would distribute license revenue raised to originators and artists. Non-licensed uses could automatically be blocked. In a second step, errors could be caught through a complaints handling system making decisions on whether complaints are justified on the basis of human analysis - this would represent a clear improvement on the current procedures used by YouTube and Facebook. What automated pattern recognition systems cannot do is determine the meaning of content items at the semantic level. This means that they cannot identify legitimate uses of protected works - in the context of parodies or mash-ups, say, or when an image is reproduced online in a piece of art criticism. In such cases, the identification system would report a „fuzzy“ match, stating for example that 40% of a given upload corresponded to a copyrighted file known from the database. To achieve a legally watertight result here, human judgment would be required. Humans can recognize parodies or incidental uses such as purely decorative uses of works in ways that that do not constitute breaches of copyright.

The process of analysis could be simplified further by uploaders stating the context of use at the time works are uploaded. Notes such as „This video contains a parody and/or uses a copyrighted work for decorative purposes“ could be helpful to analysts. The Network Enforcement Act (NetzDG) in Germany provides a good example of how automatic recognition and human analysis can work in tandem to analyze vast volumes of information. A few hundred people in Germany are currently tasked with deciding whether statements made on Facebook constitute incitement to hatred and violence against certain groups or are otherwise in breach of community rules. These judgments are significantly more complex than detecting impermissible uses of copyrighted works.

Being obliged to implement human monitoring will, of course, impose certain demands on platforms. But those most affected will be the platforms with the largest number of uploads. These major platforms will have the highest personnel requirements because they can host content of almost every kind: music, texts, video etc. Protecting sites like a small photo forum will be much simpler. If only a modest number of uploads is involved, the forum operator can easily check them personally at the end of the working day. In that case, uploaders will simply have to wait for a brief period for their content to appear online. Or operators can opt to engage a service center like Acamar instead of adding these checks to their own workloads. Efficient monitoring is possible.

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