Entertainment and Media Guide to AI

Legal issues in AI part 2 - Gavel icon

Read time: 4 minutes


The use, ownership and exploitation of data is extremely valuable. The era of AI has ushered in a veritable gold rush of companies and individuals seeking to mine this man-made resource, which, unlike gold, is available in great abundance. However, the alchemy involved in turning a seemingly infinite into something valuable requires tremendous computational power and investment.

Text and Data Mining (TDM) generally involves the identification of patterns or relationships in data sets that were previously unknown. TDM can be used to build predictive models of behavior in the retail context, so that when a customer Amazon, or opens their Facebook page, they are presented with advertising keyed to their individual tastes and preferences.

In the media and entertainment context, one form of TDM, machine-learning, is being used to train AI programs to create content, whether in text, audio, visual or audiovisual form. Machine learning, like traditional TDM, is intended to discover novel and useful knowledge in data. However, a fundamental difference between machine learning and traditional TDM, is that TDM in and of itself, can extract data for human comprehension, whereas machine learning extracts data to improve an AI program’s own understanding and ability to produce output. In addition, TDM does not necessarily involve rule or pattern discovery, while machine learning almost always does.

Key takeaways
  • Most AI systems are trained by analyzing and extracting information from vast quantities of data
  • Whether copying of copyrighted material for the purpose of machine learning constitutes fair use is a debated topic that will affect the future of AI in the U.S.