AI can now read minds, Japanese scientists' experiment sparks ethical debate

Yu Takagi, a neuroscientist from Japan discovered that Artificial Intelligence (AI) can decode brain activity into readable format. This sparked a wave of concern among top tech leaders like Elon Musk who are calling for a pause on the development of AI. Takagi, an assistant professor at Osaka University who used a Germany-developed deep learning AI model to analyse the brain was in a state of disbelief when he saw AI decoding a subject’s brain activity.

“I still remember when I saw the first [AI-generated] images,” Takagi told Al Jazeera.

Takagi and his team used Stable Diffusion (SD), a deep-learning AI model developed in Germany in 2022. It helps in analysing the brain scans of subjects, showing up to 10,000 images while inside an MRI machine.

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Earlier, this kind of AI-powered brain reading was seen in sci-fi movies where a scientist using a machine can decode the subject’s brain activity. Such is no more a movie now, rather can become a tangible reality.
Takagi himself went ‘crazy’ when he discovered this. He said, “I went into the bathroom and looked at myself in the mirror and saw my face, and thought, ‘Okay, that’s normal. Maybe I’m not going crazy “

Can AI really read minds?

Takagi and his research partner Shinji Nishimoto built a simple model to ‘translate’ brain activity into readable format. The Stable Diffusion was able to generate high-fidelity images that strangely look like the originals. What was more shocking was that the AI did this despite not being shown the pictures in advance or trained in any way to manufacture the results.

AI is generally fed by all the large amounts of data first and then intelligent algorithms are used to allow the software to learn automatically from patterns or features in the data.

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“We really didn’t expect this kind of result,” Takagi said.

Takagi stressed that the breakthrough does not represent mind-reading at this point. He made it clear that AI can only produce images a person has viewed.

“This is not mind-reading,” Takagi said. “Unfortunately there are many misunderstandings with our research.”

“We can’t decode imaginations or dreams; we think this is too optimistic. But, of course, there is potential in the future.”

Why tech giants are concerned?

This development has nonetheless raised concerns about how such technology could be used amid a border debate about the risks posed by AI in general.

Last month, tech leaders like Elon Musk and Apple co-founder Steve Wozniak wrote an open letter, calling for a pause on the development of AI due to “profound risks to society and humanity”.

Takagi himself accepted that fears around mind-reading technology are not without merit, given the possibility of misuse by those with malicious intent.

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“For us, privacy issues are the most important thing. If a government or institution can read people’s minds, it’s a very sensitive issue,” Takagi said. “There need to be high-level discussions to make sure this can’t happen.”

Takagi and Nishimoto’s research generated much buzz in the tech community, which has been electrified by breakneck advancements in AI, including the release of ChatGPT, which produces human-like speech in response to a user’s prompts.

Takagi and Nishimoto’s study was accepted to the Conference on Computer Vision and Pattern Recognition (CVPR), set for June 2023. It is a common source for legitimizing significant breakthroughs in science. Even so, both are cautious about getting carried away about their findings.

We are still decades away from actual AI mind reading

Takagi believes that there are two major roadblocks to genuine mind reading, brain-scanning technology and AI itself.

Despite advancements in neural interfaces, like Electroencephalography (EEG) brain computers, which detect brain waves via electrodes connected to a subject’s head and fMRI, scientists believe we could be decades away from being able to accurately and reliably decode imagined visual experiences.

In Takagi and Nishimoto’s research, subjects had to sit in an fMRI scanner for up to 40 hours, which was costly as well as time-consuming.

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In a 2021 paper, researchers at the Korea Advanced Institute of Science and Technology noted that conventional neural interfaces “lack chronic recording stability’ due to the soft and complex nature of neural tissue, which reacts in unusual ways when brought into contact with synthetic interfaces.

Such AI experiments have little practical application in current times

Though Takagi and Nishimoto’s framework could be used with brain-scanning devices other than MRI, such as EEG, but it has little practical application for such an experiment.

The method cannot yet be transferred to novel subjects because the shape of the brain differs among individuals. One cannot directly apply a model created for one person to another.

According to Takagi, such experiments can only be useful in clinical, communication or even entertainment fields.

Still, Takagi and his partner have no intention of slowing down their research. They are already planning version two of their project, which will focus on improving the technology and applying it to other modalities.

(With inputs from agencies)

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