How To Design A Proprietary AI Voice System Using Ethically Collected Datasets

AI & The Vox Futura

It would not be an exaggeration to call the AI boom the gold rush of our age. Businesses and individuals alike are in a frenzy to build the best and most effective AI tools - so much so that the facts of the situation can get lost. It is easy to forget that we are playing in new ethical and legal territory here, and sometimes we must take a step back to assess where we are headed if we continue down this path.

For a breakdown of the ethics of AI voice models, visit https://www.voices.com/landing/understanding-datasets

At the core of the present moment are AI datasets, the training mechanism without which none of these tools would function. OpenAI, for example, caught flak for collecting data without the consent of millions of artists and using that data to build their AI systems. The debate around whether that move was justified or even legal is still raging, but in the meantime, there is plenty to be learned from their example.

The biggest lesson of all may be that datasets are extremely important, which is why Voices, the all-in-one vocal work and audio platform, wants you to stay informed on the matter. Recently, they published their new guide on how to safely and effectively assemble and monitor datasets for your AI models.

What Is Inside The Guide?

Voices begins by establishing the difference between a good and bad dataset, calling the latter the “silent killer” of AI models in the current market. Bad datasets, they explain, can contain illegally harvested data, low-quality samples, or simply be too small to effectively train AI, resulting in a tool that does not properly function.

This is best demonstrated, perhaps, by Google's software engineering. Google’s voice tools were trained on materials already in the public domain, as well as recording samples obtained with consent - the hallmarks of a “good” dataset.

The guide then goes on to explain why businesses should avoid using bad datasets and the many consequences that could arise from doing so. For example, datasets that use vocal data obtained without express consent are in violation of publicity and privacy laws, and could open businesses up to lawsuits and other regulatory penalties.

A Better Way

In creating this guide, Voices hopes to provide a framework that you and your team can use to build an ethical and effective AI voice system. They urge businesses like yours to invest in a proprietary dataset, as this ensures that all training data was ethically collected and meets the highest standard of quality. Doing so also allows your business to tune your AI model to your specific needs, offering additional competitive advantages.

Build Your Dataset Safely

If you are interested in building an AI voice model using proprietary data, you can reach out to Voices for assistance and resources. They have access to a large database of ethically collected samples, all backed up by chain-of-consent documentation to protect against legal and regulatory challenges.

More About Voices

Broadly speaking, Voices is available to handle all things vocal and audio, offering a home to freelancers who are seeking work, and to businesses seeking talent. Their platform is now equipped to supply a wide range of AI services as well, assisting businesses in the design and implementation of AI voice systems in any application.

Read their full guide to ethical dataset creation at https://www.voices.com/landing/understanding-datasets

Voices City: London Address: 100 Dundas St Suite 700 Website: https://www.voices.com/