Canadian Musician - January/February 2023 | Page 39

AI music-generation tools , such as Amper and Google ’ s AudioLM , have given less skilled musicians the opportunity to feed the software ’ s existing songs and generate original compositions . Furthermore , AI audio mastering programs like LANDR have made audio mastering easier , which was previously difficult , expensive , and labour-intensive . These tools also produce higher-quality tracks with better flow and lower costs , which is especially beneficial for new and inexperienced artists with limited or no budgets . Holly Herndon , an American based in Berlin , is one example of an artist who prominently uses AI techniques in her work . The singer rose to prominence in 2019 after deploying AI to create a significant portion of her music , ranging from instrumentation to backing vocals to mixing and deep fakes .
Algoriddim DJ Pro AI is a commercial piece of software that uses its own “ Neural Mix ” technology to enable DJs to perform and remix music from “ singular elements in real-time .” It also includes a Gesture Control feature , using “ advanced AI-powered hand tracking technology where gestures are detected and tracked in a 3D space ” without
requiring the user to touch the device . This critical feature makes technology more accessible to users of all abilities , particularly those with physical disabilities who might otherwise be precluded from using it .
Technology can frustrate the legal and employment sectors . Because AI has the potential to generate sophisticated music suitable for use as backing music , jingles , advertisements , call-holding music , and other generic music , which songwriters and musicians are concerned about being rendered obsolete . Legally , consensus continues to evade stakeholders on the nature and scope of authorship and ownership , which are two key legal issues for deciding if and how AI-generated works should be protected by copyright laws . Legislation , both in Canada and internationally , centres the human author while attempting to balance user rights and remain technologically neutral . AI artists create “ new ” pieces by feeding existing song data to computer algorithms , which has led to debates about who has the right to claim copyright on AI creations and how domestic IP offices and publishers should manage registration
requirements . One legal solution argues for a multi-tiered approach that grants copyright protection to human-directed AI works , while sending purely computer-based generative works to the public domain – with the net effect of growing a valuable cultural resource .
Given the potential threats posed by AI , key stakeholders from a variety of industries have worked together to drive initiatives to mitigate its negative effects on organizations , individuals , and society at large . However , there is still room for more informed debate , recommendations , and regulatory controls , particularly in music , to reduce risk and manage creative workers ’ expectations as they use and engage with AI systems . There is also a risk that AI-generated creative products will saturate the market . This will make it difficult for many ( independent ) human artists to have their work discovered , particularly in a digital environment , and thus , AI has the potential to eventually increase the level of precarity in an industry all too familiar with financial insecurity .
An AI ’ s advantage is its ability to compute scenarios and calculate solutions with success
probabilities . The diversity of the audience ’ s sensibilities , however , is a shortcoming of this method in artistic creation . Artificially-generated music either feels empty to listeners , or they prefer human-composed melodies .
In the end , the human will not simply be replaced by a machine ; rather , the work will become more meaningful . With the advent of image technology , the art of painting has not vanished . Nonetheless , those involved in the industry gained the freedom to experiment with new ways of expressing their creativity . As a society , we no longer require someone to capture an image for the purpose of preserving it so that artists can focus their efforts elsewhere . Whereas algorithmic music can be generated ( for example , background music for a wedding video that requires a specific duration ), there is room for imagination and original creations based on the human experience . AI technologies will only continue to evolve and increase the ways they can be used in the creative industries . Thus , it will be essential for the sector to learn how to operationalize AI and to prepare for the innovation bound for the creative economy .
Charlie Wall-Andrews is a Ph . D . ( ABD ) Candidate in Management at Ted Rogers School of Management and a leader in the Music Industry . She is also the Executive Director of SOCAN Foundation .
Dr . Lorena Escandón is from Mexico , and holds a Ph . D . in Innovation Management , and is an Assistant Professor in Creative Industries at Toronto Metropolitan University .
Dr . Norah Lorway is an artificial intelligence and music researcher , composer and programmer who is an Assistant Professor at The School of Radio and Television Arts ( Toronto Metropolitan University ).
Salman Rana is an Assistant Professor in the School of Creative Industries and the School of Professional Music , as well as a lawyer and legal theorist .