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Utilising AI-Generated Characters for Education

As it becomes easier to create hyper-realistic digital characters using Artificial Intelligence (AI), much of the conversation around these tools could be misleading. But the technology can also be used for positive purposes – to revive Albert Einstein to teach a physics class, talk through a career change with older self, or anonymise people while preserving facial communication.

To encourage the technology’s positive possibilities, MIT Media Lab researchers and their collaborators at the University of California at Santa Barbara and Osaka University have compiled an open-source, easy-to-use character generation pipeline that combines AI models for facial gestures, voice, and motion and can be used to create a variety of audio and video outputs.

The pipeline also marks the resulting output with a traceable, as well as human-readable, watermark to distinguish it from authentic video content and to show how it was generated — an addition to help prevent its malicious use.

By making this pipeline easily available, the researchers hope to inspire teachers, students, and healthcare workers to explore how such tools can help them in their respective fields. If more students, educators, healthcare workers, and therapists have a chance to build and use these characters, the results could improve health and well-being and contribute to personalised education.

It will be a strange world indeed when AIs and humans begin to share identities. This study does an incredible job of thought leadership, mapping out the space of what is possible with AI-generated characters in domains ranging from education to health to close relationships while giving a tangible roadmap on how to avoid the ethical challenges around privacy and misrepresentation.

– Jeremy Bailenson, Founding Director, Stanford Virtual Human Interaction Lab

Generative adversarial networks, or GANs, a combination of two neural networks that compete against each other, have made it easier to create photorealistic images, clone voices, and animate faces. One researcher first explored its possibilities in a project called Machinoia, where he generated multiple alternative representations of himself — as a child, as an old man, as female — to have a self-dialogue of life choices from different perspectives. The unusual deep-faking experience made him aware of his “journey as a person,”.

Self-exploration is only one of the positive applications of AI-generated characters, the researchers say. Experiments show, for instance, that these characters can make students more enthusiastic about learning and improve cognitive task performance. The technology offers a way for instruction to be “personalised to people’s interest, their idols, their context, and can be changed over time.

Other applications might include characters who help deliver therapy, to alleviate a growing shortage of mental health professionals and reach the estimated 44% of Americans with mental health issues who never receive counselling or AI-generated content that delivers exposure therapy to people with social anxiety. In a related use case, the technology can be used to anonymise faces in the video while preserving facial expressions and emotions, which may be useful for sessions where people want to share personal sensitive information such as health and trauma experiences, or for whistleblowers and witness accounts.

The researchers note that any of the applications of AI-generated characters raise legal and ethical issues that must be discussed as the technology evolves. One of the goals with this research is to raise awareness about what is possible, ask questions and start public conversations about how this technology can be used ethically for societal benefit.

U.S researchers have been adopting AI for several purposes, such as monitoring biodiversity. As reported by OpenGov Asia, the researchers are deploying autonomous recording equipment in natural areas to eavesdrop on the animals. This project aims to help answer important scientific questions, such as which species are present and how their abundance changes over time.


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