AI recreates hyper realistic human faces by reading people’s minds
A few years ago this technology was "alright" and now it's "good." Next comes great and that will be revolutionary.
Key takeaways
- In an article published in Nature they revealed the results from an experiment where they showed photos of faces to two volunteers inside a powerful brain-reading Functional Magnetic Resonance Imaging (fMRI) scanner.
- Inside the Mind Reading machine An fMRI scanner is a type of non-invasive brain imaging technology that detects brain activity by measuring the minute changes in the brains blood flow as it thinks and does things.
- The researchers then fed this information into a computer’s AI algorithm which could build an accurate image based on the information from the fMRI scan.
Cite or link to this article
Griffin, M. (2022) 'AI recreates hyper realistic human faces by reading people’s minds', 311 Institute, 7 September. Available at: https://www.311institute.com/ai-recreates-hyper-realistic-human-faces-by-reading-peoples-minds/ (Accessed: 1 October 2026).
I’ve seen a lot of sci-fi like innovations now that have let researchers translate human brainwave patterns and then use Artificial Intelligence (AI) to reconstruct them live into sentences, videos, and images - AKA mind reading. And, while all of them have been impressive, I’ve been waiting for the day when the outputs would be high quality. Now, thanks to researchers at Radboud University in the Netherlands, and an expensive fancy machine it seems we’re finally “getting there.”
This week the researchers developing “mind reading” technology that can translate a person’s brainwaves into photographic images announced a new break though.
In an article published in Nature they revealed the results from an experiment where they showed photos of faces to two volunteers inside a powerful brain-reading Functional Magnetic Resonance Imaging (fMRI) scanner.
Inside the Mind Reading machine
An fMRI scanner is a type of non-invasive brain imaging technology that detects brain activity by measuring the minute changes in the brains blood flow as it thinks and does things.
As the volunteers looked at the images of faces, the fMRI scanned the activity of neurons in the areas of their brain responsible for vision. The researchers then fed this information into a computer’s AI algorithm which could build an accurate image based on the information from the fMRI scan.
As the results of the experiment show, the fMRI/AI system was able to almost identically reconstruct the original images that the volunteers were shown and not only is that a world first but it’s damn impressive.
AI researcher and a cognitive neuroscientist, Thirza Dado, who led the study, believes that these highly impressive results demonstrate the potential for fMRI/AI systems to effectively read minds in future, according to the Mail Online.
“I believe we can train the algorithm not only to picture accurately a face you’re looking at, but also any face you imagine vividly, such as your mother’s,” explains Dado.
“By developing this technology, it would be fascinating to decode and recreate subjective experiences, perhaps even your dreams,” Dado says. “Such technological knowledge could also be incorporated into clinical applications such as communicating with patients who are locked within deep comas.”
Dado’s work is focused on using the technology to help restore vision in people who, through disease or accident, have become blind, reports the Mail Online.
“We are already developing brain-implant cameras that will stimulate people’s brains so they can see again,” Dado says.
To “train” the AI system, the volunteers had previously been shown a series of other faces while their brains were being scanned.
According to the experiment, the key is that the photographic pictures they saw were not of real people, but essentially a paint-by-numbers picture created by a computer where each tiny dot of light or darkness is given a unique computer program code.
The fMRI scan was able to detect how the volunteers’ neurons responded to these “training” images. The artificial intelligence system then translated each volunteer’s neuron reaction back into computer code to recreate the photographic portrait.
In the test, neither the volunteers nor the AI system had ever seen the faces that were decoded and recreated so accurately.
What this means for your organisation
The quality gap is closing.
Earlier brain decoding work was impressive but the outputs were rough. The Radboud team rebuilt faces almost identically from fMRI scans of two volunteers. The faces were ones that neither the volunteers nor the algorithm had seen before. It is a small test, so treat it as early proof and not a product.
Imagined images may come next.
Thirza Dado believes the system could be trained to rebuild a face a person imagines vividly. She also points to dreams, communication with patients in deep comas, and brain-implant cameras to restore sight. High resolution fMRI sits at Explore on our scale, with wide use in 2035. Brain to machine interfaces sit at Watch, with wide use in 2045.
Brain data needs rules early.
The method needs a powerful scanner and trained volunteers, so the risk today is narrow. But brain activity can now be turned back into pictures. Organisations in health, devices and research should set consent and data rules before the tools spread. Machine vision and the wider trend in artificial intelligence are already at Act now.
Three questions for your next leadership meeting
- Which of our products or studies could start collecting brain data?
- What consent and storage rules would we need before using decoded brain images?
- Who in our team is tracking brain imaging and interface research?
The trends and technologies behind this story
From the 311 Starburst, the 311 Strategic Intelligence Unit’s map of the technologies and trends shaping the next 50 years.
Analysis by the 311 Strategic Intelligence Unit, from Matthew Griffin’s article and 311 data. First published on Fanatical Futurist.
FAQ
Why does this matter?
A few years ago this technology was "alright" and now it's "good." Next comes great and that will be revolutionary.

About the author
Matthew Griffin Founder, President and Futurist, 311 Institute
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."
Read full bio
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 17-time best selling author of the "Codex of the Future" series, Matthew is the Founder, President and Futurist of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.
An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity program, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.
As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.
Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.
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Sources and further reading
- S41598 021 03938 w nature.com
- ThirzaDado twitter.com
- Is proof brain scans read minds Special type MRI translated brainwaves images dailymail.co.uk
- Dado’s work researchgate.net
Source: first published by the 311 Institute on 7 September 2022. Cite as: Griffin, M. (2022). AI recreates hyper realistic human faces by reading people’s minds. 311 Institute. https://www.311institute.com/ai-recreates-hyper-realistic-human-faces-by-reading-peoples-minds/
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