AI and ML Article Swipe
YOU?
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· 2021
· Open Access
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· DOI: https://doi.org/10.5594/jmi.2021.3064082
· OA: W3148579069
<fig orientation="portrait" position="float" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <graphic orientation="portrait" position="float" xlink:href="devli-3064082.tif"/> </fig> SMPTE and the Enter-tainment Technology Center [(ETC) etcenter.org] have a long history of working together. One major success is the Intero perable Mastering Format (IMF) and another project that we hope will bear similar success is the Joint ETC Task Force on artificial intelligence (AI) and media. We know that the use of machine learning (ML) techniques in the media space will have an impact. Some of these will be beneficial, such as improved metadata collection and inference, and some will have a negative effect, such as the ability to create the so-called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">deep fakes</i> that cannot be easily distinguished from genuine material. Other issues will be more difficult to address, particularly the problem of embedded bias in training sets. To understand this, it is worth knowing a little about how ML algorithms work.
