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With the rise of generative AI, such as ChatGPT, the future of human intellect is in doubt. Perhaps it could replace human jobs. Research shows that with generative AI, 30 percent of hours worked today (2023) could be automated by 2030 in the US (Ellingrud et al., 2023). As a Business Information Management student, this is exciting (from a business perspective): what could we do with those 30% extra hours in the future? On the other hand, as a human being: should we be worried that not all people will have the same opportunities to strive for a job?

One might argue that generative AI, such as ChatGPT, should replace some humans since it is very smart. A clinical psychologist even tested ChatGPT’s IQ to see what the results would be. Since it is not a human, it shows no signs of anxiety and distraction. What did ChatGPT score on the IQ test? A massive IQ of 155, meaning it would be the top 0.01 percent smartest human (Roivainen, 2023).

Although these findings are impressive, we should note that ChatGPT is not a human. ChatGPT can only do tests on the Verbal IQ scale (Vocabulary, Similarities, Comprehension, Information and Arithmetic) since it has no other senses (required for the nonverbal IQ test). This means that the IQ score of 155 is only for verbal communication. It can’t even do simple tasks as ‘What time is it now?’. It will apologize (almost as a human) that it has no capability to provide real-time information and gives me some instructions how to find the current time through a clock or watch.

Furthermore, ChatGPT (or any other language AI model) can’t operate without all the humans working behind it to guide the AI model. Since these models predict characters, words and sentences based on training data sets, feedback is very important. This is the reason why ChatGPT has the option to give feedback on how the generated response was (good or bad, and why). It can’t give any feedback to itself (Us, 2023). To teach ChatGPT not to give answers which would be racist, sexist or any other unwanted response, hundreds of workers from Kenya are paid as little as $2 an hour to do this work (Perrigo, 2023).

As described in this blog: ChatGPT is smart, but not smarter than you. It has some real potential but also some awful flaws.

Literature

Ellingrud, K., Sanghvi, S., Dandona, G. S., Madgavkar, A., Chui, M., White, O., & Hasebe, P. (2023). Generative AI and the future of work in America. In McKinsey & Company. https://www.mckinsey.com/mgi/our-research/generative-ai-and-the-future-of-work-in-america#/

Perrigo, B. (2023, January 18). Exclusive: OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic. Time. https://time.com/6247678/openai-chatgpt-kenya-workers/

Roivainen, E. (2023, March 28). I gave ChatGPT an IQ test. Here’s what I discovered. Scientific American. https://www.scientificamerican.com/article/i-gave-chatgpt-an-iq-test-heres-what-i-discovered/

Us, J. P. N. C. (2023, August 24). ChatGPT and Other Language AIs Are Nothing without Humans. Scientific American. https://www.scientificamerican.com/article/chatgpt-and-other-language-ais-are-nothing-without-humans/

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When asking in my surroundings what the first thing that comes to their mind when thinking about generative AI, I get mostly the answer of chatbots (e.g. ChatGPT) and occasionally generating images (e.g. DALL-E). These types of generative AI have very practical implications, for both individuals as businesses. For instance, generative AI could enhance creativity by using platforms like ChatGPT and Stable Diffusion (Eapen et al., 2023). However, generative AI goes much further than those examples: one of them is generative AI voice. I’ve used the PlayHT platform, which is free, to test my own AI created voice.

I came across PlayHT through a YouTube video about generated AI voice, the results were quite good actually. So I had to test my own AI generated voice. I created a free account on the PlayHT platform after which I could upload a video file of at least 30 seconds of my own voice. I simply read a random Wikipedia page and recorded my voice on my telephone. After uploading, I only had to wait for 30 seconds and my voice was ‘cloned’ (the term PlayHT uses for my own AI generated voice). After that, I just entered a couple sentences and the results were indeed quite good! Although you can definitely hear that it’s not my real voice, there are some similarities. The fact that I only uploaded a voice recording of roughly 30 seconds and gave me those results, were very impressive but also a little bit creepy. For you as a viewer, copy-pasted the whole text in PlayHT with my own voice:

This made me think, does AI generated voice have real practical applications or can it be dangerous and do we have to be careful with this type of technology? Some great useful applications are for voice-overs. Narration plays a significant role in the media and entertainment sector where the voice in one of the most important elements, for example in the case of advertisements. Generative AI voice could replace voice actors and could also increase the amount of voice-overs.

On the other hand, AI generated voices could lead to negative effects when used malicious. A while ago, deepfake was all over the news. With deepfake, sometimes we can’t tell the difference between original video’s and deepfakes. Deepfake sometimes use real voice actors, but with the increase and improvements of generative AI, deepfake could be used even more malicious. Fortunately, there’s a quite extensive research on how to detect deepfakes. Fortunately, according to Rana et al. (2022), deep learning techniques are effective in detecting deepfake. Although it is questionable whether these kinds of detection systems can keep up with current generative AI developments.

I think that AI generated voice is still quite unknown, so there are probably a lot more practical implications which are not used today.

What’s your point of view of AI generated voices? Let me know!

Eapen, T. T., Finkenstadt, D. J., Folk, J., & Venkataswamy, L. (2023). How Generative AI Can Augment Human Creativity. (cover story). *Harvard Business Review*, *101*(4), 56–64.

Rana, M. S., Nobi, M. N., Murali, B., & Sung, A. H. (2022). Deepfake detection: a systematic literature review. *Ieee Access*, *10*. https://doi.org/10.1109/ACCESS.2022.3154404