Meta's latest artificial intelligence model called Voicebox is a customized text to speech product that can mimic any specific voice of your choosing.

But the entrance of these tools is causing trepidation. A Goldman Sachs report in late March said generative AI could significantly disrupt the global economy and subject 300 million jobs to automation. The Writers Guild of America, which represents screenwriters, is locked in negotiations with movie studios -- and the way artificial intelligence can be used in scriptwriting is a key sticking point. Actors, such as Keanu Reeves, are raising alarm bells, saying the rise of generative AI is "scary" and could be a way for executives to not pay artists fairly.

In mid-2019, I shared 9 Ways That Artificial Intelligence Might Disrupt Authors and Publishing, and one of those possible disruptions concerned voice technologies, which I also wrote about in Audio for Authors. In 2020, we have seen an acceleration of AI with the release of GPT-3 for natural language processing and generation, as well as the development of ever more sophisticated voice recognition and creation. In this episode, Mark Leslie Lefebvre and I share a conversation between our Voice Doubles and our thoughts on the ramifications. You can get your own Voice Double at Descript.com. You can find Mark at MarkLeslie.ca. Mark also recorded a special episode with more of his thoughts in episode 148 of Stark Reflections. We'd love to know what you think so please leave a comment or tweet me @thecreativepenn and Mark @markleslie So, how's lockdown where you are? How are things in Canada? Mark: Lockdown has actually allowed me to discover new types of creativity in myself, where I seem to have prevented myself from writing prose. So I have the energy inside me to tell story, to want to share and amuse and entertain, and I redirected it into a different output that satisfied that part of my soul that needs to write, and now I'm back writing again. But while I was struggling, it was really good to have that outlet. Jo: I also struggled at the beginning, and I did a flurry of business activities.

"The biggest loss caused by AI will be the complete destruction of trust in anything you see or hear," an article from Wired says, composing probably one of the most profound sentences I've ever read in a mainstream article. Nearly every flavor of entity that controls our world, corporations, academics, and governments are already "working furiously" to analyze and perfectly understand the human voice to replicate it. As innumerable power struggles over the development of a particular technology have occurred in the past century or so, apparently now a race to decode the human voice is underway. Imagine a world where the sound of a person's voice isn't solid proof of the person speaking: where you could hear a family member speak from another part of the house and think they are there, but they are not. A robot is copying their voice and they are somewhere else.

University of Washington researchers at the UW Graphics and Image Laboratory have developed new algorithms that turn audio clips into a realistic, lip-synced video, starting with an existing video of that person speaking on a different topic. As detailed in a paper to be presented Aug. 2 at SIGGRAPH 2017, the team successfully generated a highly realistic video of former president Barack Obama talking about terrorism, fatherhood, job creation and other topics, using audio clips of those speeches and existing weekly video addresses in which he originally spoke on a different topic decades ago. Realistic audio-to-video conversion has practical applications like improving video conferencing for meetings (streaming audio over the internet takes up far less bandwidth than video, reducing video glitches), or holding a conversation with a historical figure in virtual reality, said Ira Kemelmacher-Shlizerman, an assistant professor at the UW's Paul G. Allen School of Computer Science & Engineering. This beats previous audio-to-video conversion processes, which have involved filming multiple people in a studio saying the same sentences over and over to try to capture how a particular sound correlates to different mouth shapes, which is expensive, tedious and time-consuming. The new machine learning tool may also help overcome the "uncanny valley" problem, which has dogged efforts to create realistic video from audio.

Google's DeepMind AI is learning how to talk. And learning how to do it like a person, not a computer. DeepMind has many learning projects going on right now, but the newest one to catch our ears seems to be an increasingly realistic voice and speech pattern system that eliminates more and more of the inhuman, robotic patterns we use to identify computers. Imagine if Siri, Cortana, or Alexa started having inflection, variances, and realistic breathing patterns. Instead of sounding like this, it might sound like this.