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Portable and non-invasive (?) mind-reading AI (artificial intelligence) turns thoughts into text and some thoughts about the near future

Neurotechnology and neurorights

Fletcher Reveley’s January 18, 2024 article on salon.com (originally published January 3, 2024 on Undark) shows how quickly the field is developing and raises concerns, Note: Links have been removed,

One afternoon in May 2020, Jerry Tang, a Ph.D. student in computer science at the University of Texas at Austin, sat staring at a cryptic string of words scrawled across his computer screen:
“I am not finished yet to start my career at twenty without having gotten my license I never have to pull out and run back to my parents to take me home.”
The sentence was jumbled and agrammatical. But to Tang, it represented a remarkable feat: A computer pulling a thought, however disjointed, from a person’s mind.
For weeks, ever since the pandemic had shuttered his university and forced his lab work online, Tang had been at home tweaking a semantic decoder — a brain-computer interface, or BCI, that generates text from brain scans. Prior to the university’s closure, study participants had been providing data to train the decoder for months, listening to hours of storytelling podcasts while a functional magnetic resonance imaging (fMRI) machine logged their brain responses. Then, the participants had listened to a new story — one that had not been used to train the algorithm — and those fMRI scans were fed into the decoder, which used GPT1, a predecessor to the ubiquitous AI chatbot ChatGPT, to spit out a text prediction of what it thought the participant had heard. For this snippet, Tang compared it to the original story:
“Although I’m twenty-three years old I don’t have my driver’s license yet and I just jumped out right when I needed to and she says well why don’t you come back to my house and I’ll give you a ride.”
The decoder was not only capturing the gist of the original, but also producing exact matches of specific words — twenty, license. When Tang shared the results with his adviser, a UT Austin neuroscientist named Alexander Huth who had been working towards building such a decoder for nearly a decade, Huth was floored. “Holy shit,” Huth recalled saying. “This is actually working.” By the fall of 2021, the scientists were testing the device with no external stimuli at all — participants simply imagined a story and the decoder spat out a recognizable, albeit somewhat hazy, description of it. “What both of those experiments kind of point to,” said Huth, “is the fact that what we’re able to read out here was really like the thoughts, like the idea.”
The scientists brimmed with excitement over the potentially life-altering medical applications of such a device — restoring communication to people with locked-in syndrome, for instance, whose near full-body paralysis made talking impossible. But just as the potential benefits of the decoder snapped into focus, so too did the thorny ethical questions posed by its use. Huth himself had been one of the three primary test subjects in the experiments, and the privacy implications of the device now seemed visceral: “Oh my god,” he recalled thinking. “We can look inside my brain.”
Huth’s reaction mirrored a longstanding concern in neuroscience and beyond: that machines might someday read people’s minds. And as BCI technology advances at a dizzying clip, that possibility and others like it — that computers of the future could alter human identities, for example, or hinder free will — have begun to seem less remote. “The loss of mental privacy, this is a fight we have to fight today,” said Rafael Yuste, a Columbia University neuroscientist. “That could be irreversible. If we lose our mental privacy, what else is there to lose? That’s it, we lose the essence of who we are.”
Spurred by these concerns, Yuste and several colleagues have launched an international movement advocating for “neurorights” — a set of five principles Yuste argues should be enshrined in law as a bulwark against potential misuse and abuse of neurotechnology. But he may be running out of time.
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Reveley’s January 18, 2024 article provides fascinating context and is well worth reading if you have the time.

For my purposes, I’m focusing on ethics, Note: Links have been removed,

… as these and other advances propelled the field forward, and as his own research revealed the discomfiting vulnerability of the brain to external manipulation, Yuste found himself increasingly concerned by the scarce attention being paid to the ethics of these technologies. Even Obama’s multi-billion-dollar BRAIN Initiative, a government program designed to advance brain research, which Yuste had helped launch in 2013 and supported heartily, seemed to mostly ignore the ethical and societal consequences of the research it funded. “There was zero effort on the ethical side,” Yuste recalled.
…
Yuste was appointed to the rotating advisory group of the BRAIN Initiative in 2015, where he began to voice his concerns. That fall, he joined an informal working group to consider the issue. “We started to meet, and it became very evident to me that the situation was a complete disaster,” Yuste said. “There was no guidelines, no work done.” Yuste said he tried to get the group to generate a set of ethical guidelines for novel BCI technologies, but the effort soon became bogged down in bureaucracy. Frustrated, he stepped down from the committee and, together with a University of Washington bioethicist named Sara Goering, decided to independently pursue the issue. “Our aim here is not to contribute to or feed fear for doomsday scenarios,” the pair wrote in a 2016 article in Cell, “but to ensure that we are reflective and intentional as we prepare ourselves for the neurotechnological future.”
In the fall of 2017, Yuste and Goering called a meeting at the Morningside Campus of Columbia, inviting nearly 30 experts from all over the world in such fields as neurotechnology, artificial intelligence, medical ethics, and the law. By then, several other countries had launched their own versions of the BRAIN Initiative, and representatives from Australia, Canada [emphasis mine], China, Europe, Israel, South Korea, and Japan joined the Morningside gathering, along with veteran neuroethicists and prominent researchers. “We holed ourselves up for three days to study the ethical and societal consequences of neurotechnology,” Yuste said. “And we came to the conclusion that this is a human rights issue. These methods are going to be so powerful, that enable to access and manipulate mental activity, and they have to be regulated from the angle of human rights. That’s when we coined the term ‘neurorights.’”
The Morningside group, as it became known, identified four principal ethical priorities, which were later expanded by Yuste into five clearly defined neurorights: The right to mental privacy, which would ensure that brain data would be kept private and its use, sale, and commercial transfer would be strictly regulated; the right to personal identity, which would set boundaries on technologies that could disrupt one’s sense of self; the right to fair access to mental augmentation, which would ensure equality of access to mental enhancement neurotechnologies; the right of protection from bias in the development of neurotechnology algorithms; and the right to free will, which would protect an individual’s agency from manipulation by external neurotechnologies. The group published their findings in an often-cited paper in Nature.
But while Yuste and the others were focused on the ethical implications of these emerging technologies, the technologies themselves continued to barrel ahead at a feverish speed. In 2014, the first kick of the World Cup was made by a paraplegic man using a mind-controlled robotic exoskeleton. In 2016, a man fist bumped Obama using a robotic arm that allowed him to “feel” the gesture. The following year, scientists showed that electrical stimulation of the hippocampus could improve memory, paving the way for cognitive augmentation technologies. The military, long interested in BCI technologies, built a system that allowed operators to pilot three drones simultaneously, partially with their minds. Meanwhile, a confusing maelstrom of science, science-fiction, hype, innovation, and speculation swept the private sector. By 2020, over $33 billion had been invested in hundreds of neurotech companies — about seven times what the NIH [US National Institutes of Health] had envisioned for the 12-year span of the BRAIN Initiative itself.
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Now back to Tang and Huth (from Reveley’s January 18, 2024 article), Note: Links have been removed,

Central to the ethical questions Huth and Tang grappled with was the fact that their decoder, unlike other language decoders developed around the same time, was non-invasive — it didn’t require its users to undergo surgery. Because of that, their technology was free from the strict regulatory oversight that governs the medical domain. (Yuste, for his part, said he believes non-invasive BCIs pose a far greater ethical challenge than invasive systems: “The non-invasive, the commercial, that’s where the battle is going to get fought.”) Huth and Tang’s decoder faced other hurdles to widespread use — namely that fMRI machines are enormous, expensive, and stationary. But perhaps, the researchers thought, there was a way to overcome that hurdle too.
The information measured by fMRI machines — blood oxygenation levels, which indicate where blood is flowing in the brain — can also be measured with another technology, functional Near-Infrared Spectroscopy, or fNIRS. Although lower resolution than fMRI, several expensive, research-grade, wearable fNIRS headsets do approach the resolution required to work with Huth and Tang’s decoder. In fact, the scientists were able to test whether their decoder would work with such devices by simply blurring their fMRI data to simulate the resolution of research-grade fNIRS. The decoded result “doesn’t get that much worse,” Huth said.
And while such research-grade devices are currently cost-prohibitive for the average consumer, more rudimentary fNIRS headsets have already hit the market. Although these devices provide far lower resolution than would be required for Huth and Tang’s decoder to work effectively, the technology is continually improving, and Huth believes it is likely that an affordable, wearable fNIRS device will someday provide high enough resolution to be used with the decoder. In fact, he is currently teaming up with scientists at Washington University to research the development of such a device.
Even comparatively primitive BCI headsets can raise pointed ethical questions when released to the public. Devices that rely on electroencephalography, or EEG, a commonplace method of measuring brain activity by detecting electrical signals, have now become widely available — and in some cases have raised alarm. In 2019, a school in Jinhua, China, drew criticism after trialing EEG headbands that monitored the concentration levels of its pupils. (The students were encouraged to compete to see who concentrated most effectively, and reports were sent to their parents.) Similarly, in 2018 the South China Morning Post reported that dozens of factories and businesses had begun using “brain surveillance devices” to monitor workers’ emotions, in the hopes of increasing productivity and improving safety. The devices “caused some discomfort and resistance in the beginning,” Jin Jia, then a brain scientist at Ningbo University, told the reporter. “After a while, they got used to the device.”
But the primary problem with even low-resolution devices is that scientists are only just beginning to understand how information is actually encoded in brain data. In the future, powerful new decoding algorithms could discover that even raw, low-resolution EEG data contains a wealth of information about a person’s mental state at the time of collection. Consequently, nobody can definitively know what they are giving away when they allow companies to collect information from their brains.
Huth and Tang concluded that brain data, therefore, should be closely guarded, especially in the realm of consumer products. In an article on Medium from last April, Tang wrote that “decoding technology is continually improving, and the information that could be decoded from a brain scan a year from now may be very different from what can be decoded today. It is crucial that companies are transparent about what they intend to do with brain data and take measures to ensure that brain data is carefully protected.” (Yuste said the Neurorights Foundation recently surveyed the user agreements of 30 neurotech companies and found that all of them claim ownership of users’ brain data — and most assert the right to sell that data to third parties. [emphases mine]) Despite these concerns, however, Huth and Tang maintained that the potential benefits of these technologies outweighed their risks, provided the proper guardrails [emphasis mine] were put in place.
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It would seem the first guardrails are being set up in South America (from Reveley’s January 18, 2024 article), Note: Links have been removed,

On a hot summer night in 2019, Yuste sat in the courtyard of an adobe hotel in the north of Chile with his close friend, the prominent Chilean doctor and then-senator Guido Girardi, observing the vast, luminous skies of the Atacama Desert and discussing, as they often did, the world of tomorrow. Girardi, who every year organizes the Congreso Futuro, Latin America’s preeminent science and technology event, had long been intrigued by the accelerating advance of technology and its paradigm-shifting impact on society — “living in the world at the speed of light,” as he called it. Yuste had been a frequent speaker at the conference, and the two men shared a conviction that scientists were birthing technologies powerful enough to disrupt the very notion of what it meant to be human.
Around midnight, as Yuste finished his pisco sour, Girardi made an intriguing proposal: What if they worked together to pass an amendment to Chile’s constitution, one that would enshrine protections for mental privacy as an inviolable right of every Chilean? It was an ambitious idea, but Girardi had experience moving bold pieces of legislation through the senate; years earlier he had spearheaded Chile’s famous Food Labeling and Advertising Law, which required companies to affix health warning labels on junk food. (The law has since inspired dozens of countries to pursue similar legislation.) With BCI, here was another chance to be a trailblazer. “I said to Rafael, ‘Well, why don’t we create the first neuro data protection law?’” Girardi recalled. Yuste readily agreed.
…
… Girardi led the political push, promoting a piece of legislation that would amend Chile’s constitution to protect mental privacy. The effort found surprising purchase across the political spectrum, a remarkable feat in a country famous for its political polarization. In 2021, Chile’s congress unanimously passed the constitutional amendment, which Piñera [Sebastián Piñera] swiftly signed into law. (A second piece of legislation, which would establish a regulatory framework for neurotechnology, is currently under consideration by Chile’s congress.) “There was no divide between the left or right,” recalled Girardi. “This was maybe the only law in Chile that was approved by unanimous vote.” Chile, then, had become the first country in the world to enshrine “neurorights” in its legal code.
…
Even before the passage of the Chilean constitutional amendment, Yuste had begun meeting regularly with Jared Genser, an international human rights lawyer who had represented such high-profile clients as Desmond Tutu, Liu Xiaobo, and Aung San Suu Kyi. (The New York Times Magazine once referred to Genser as “the extractor” for his work with political prisoners.) Yuste was seeking guidance on how to develop an international legal framework to protect neurorights, and Genser, though he had just a cursory knowledge of neurotechnology, was immediately captivated by the topic. “It’s fair to say he blew my mind in the first hour of discussion,” recalled Genser. Soon thereafter, Yuste, Genser, and a private-sector entrepreneur named Jamie Daves launched the Neurorights Foundation, a nonprofit whose first goal, according to its website, is “to protect the human rights of all people from the potential misuse or abuse of neurotechnology.”
To accomplish this, the organization has sought to engage all levels of society, from the United Nations and regional governing bodies like the Organization of American States, down to national governments, the tech industry, scientists, and the public at large. Such a wide-ranging approach, said Genser, “is perhaps insanity on our part, or grandiosity. But nonetheless, you know, it’s definitely the Wild West as it comes to talking about these issues globally, because so few people know about where things are, where they’re heading, and what is necessary.”
This general lack of knowledge about neurotech, in all strata of society, has largely placed Yuste in the role of global educator — he has met several times with U.N. Secretary-General António Guterres, for example, to discuss the potential dangers of emerging neurotech. And these efforts are starting to yield results. Guterres’s 2021 report, “Our Common Agenda,” which sets forth goals for future international cooperation, urges “updating or clarifying our application of human rights frameworks and standards to address frontier issues,” such as “neuro-technology.” Genser attributes the inclusion of this language in the report to Yuste’s advocacy efforts.
But updating international human rights law is difficult, and even within the Neurorights Foundation there are differences of opinion regarding the most effective approach. For Yuste, the ideal solution would be the creation of a new international agency, akin to the International Atomic Energy Agency — but for neurorights. “My dream would be to have an international convention about neurotechnology, just like we had one about atomic energy and about certain things, with its own treaty,” he said. “And maybe an agency that would essentially supervise the world’s efforts in neurotechnology.”
Genser, however, believes that a new treaty is unnecessary, and that neurorights can be codified most effectively by extending interpretation of existing international human rights law to include them. The International Covenant of Civil and Political Rights, for example, already ensures the general right to privacy, and an updated interpretation of the law could conceivably clarify that that clause extends to mental privacy as well.
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There is no need for immediate panic (from Reveley’s January 18, 2024 article),

…
… while Yuste and the others continue to grapple with the complexities of international and national law, Huth and Tang have found that, for their decoder at least, the greatest privacy guardrails come not from external institutions but rather from something much closer to home — the human mind itself. Following the initial success of their decoder, as the pair read widely about the ethical implications of such a technology, they began to think of ways to assess the boundaries of the decoder’s capabilities. “We wanted to test a couple kind of principles of mental privacy,” said Huth. Simply put, they wanted to know if the decoder could be resisted.
In late 2021, the scientists began to run new experiments. First, they were curious if an algorithm trained on one person could be used on another. They found that it could not — the decoder’s efficacy depended on many hours of individualized training. Next, they tested whether the decoder could be thrown off simply by refusing to cooperate with it. Instead of focusing on the story that was playing through their headphones while inside the fMRI machine, participants were asked to complete other mental tasks, such as naming random animals, or telling a different story in their head. “Both of those rendered it completely unusable,” Huth said. “We didn’t decode the story they were listening to, and we couldn’t decode anything about what they were thinking either.”
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Given how quickly this field of research is progressing, it seems like a good idea to increase efforts to establish neurorights (from Reveley’s January 18, 2024 article),

For Yuste, however, technologies like Huth and Tang’s decoder may only mark the beginning of a mind-boggling new chapter in human history, one in which the line between human brains and computers will be radically redrawn — or erased completely. A future is conceivable, he said, where humans and computers fuse permanently, leading to the emergence of technologically augmented cyborgs. “When this tsunami hits us I would say it’s not likely it’s for sure that humans will end up transforming themselves — ourselves — into maybe a hybrid species,” Yuste said. He is now focused on preparing for this future.
In the last several years, Yuste has traveled to multiple countries, meeting with a wide assortment of politicians, supreme court justices, U.N. committee members, and heads of state. And his advocacy is beginning to yield results. In August, Mexico began considering a constitutional reform that would establish the right to mental privacy. Brazil is currently considering a similar proposal, while Spain, Argentina, and Uruguay have also expressed interest, as has the European Union. In September [2023], neurorights were officially incorporated into Mexico’s digital rights charter, while in Chile, a landmark Supreme Court ruling found that Emotiv Inc, a company that makes a wearable EEG headset, violated Chile’s newly minted mental privacy law. That suit was brought by Yuste’s friend and collaborator, Guido Girardi.
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“This is something that we should take seriously,” he [Huth] said. “Because even if it’s rudimentary right now, where is that going to be in five years? What was possible five years ago? What’s possible now? Where’s it gonna be in five years? Where’s it gonna be in 10 years? I think the range of reasonable possibilities includes things that are — I don’t want to say like scary enough — but like dystopian enough that I think it’s certainly a time for us to think about this.”

You can find The Neurorights Foundation here and/or read Reveley’s January 18, 2024 article on salon.com or as originally published January 3, 2024 on Undark. Finally, thank you for the article, Fletcher Reveley!

Unveiling the Neurotechnology Landscape: Scientific Advancements, Innovations and Major Trends—a UNESCO report

A definition, social issues, country statistics, and more

There’s a definition for neurotechnology and a second mention of artificial intelligence being used in concert with neurotechnology. From the report‘s executive summary,

Neurotechnology consists of devices and procedures used to access, monitor, investigate, assess, manipulate, and/or emulate the structure and function of the neural systems of animals or human beings. It is poised to revolutionize our understanding of the brain and to unlock innovative solutions to treat a wide range of diseases and disorders.
…
Similarly to Artificial Intelligence (AI), and also due to its convergence with AI, neurotechnology may have profound societal and economic impact, beyond the medical realm. As neurotechnology directly relates to the brain, it triggers ethical considerations about fundamental aspects of human existence, including mental integrity, human dignity, personal identity, freedom of thought, autonomy, and privacy [emphases mine]. Its potential for enhancement purposes and its accessibility further amplifies its prospect social and societal implications.
…
The recent discussions held at UNESCO’s Executive Board further shows Member States’ desire to address the ethics and governance of neurotechnology through the elaboration of a new standard-setting instrument on the ethics of neurotechnology, to be adopted in 2025. To this end, it is important to explore the neurotechnology landscape, delineate its boundaries, key players, and trends, and shed light on neurotech’s scientific and technological developments. [p. 7]
…

Here’s how they sourced the data for the report,

The present report addresses such a need for evidence in support of policy making in
relation to neurotechnology by devising and implementing a novel methodology on data from scientific articles and patents:

● We detect topics over time and extract relevant keywords using a transformer-
based language models fine-tuned for scientific text. Publication data for the period
2000-2021 are sourced from the Scopus database and encompass journal articles
and conference proceedings in English. The 2,000 most cited publications per year
are further used in in-depth content analysis.
● Keywords are identified through Named Entity Recognition and used to generate
search queries for conducting a semantic search on patents’ titles and abstracts,
using another language model developed for patent text. This allows us to identify
patents associated with the identified neuroscience publications and their topics.
The patent data used in the present analysis are sourced from the European
Patent Office’s Worldwide Patent Statistical Database (PATSTAT). We consider
IP5 patents filed between 2000-2020 having an English language abstract and
exclude patents solely related to pharmaceuticals.

This approach allows mapping the advancements detailed in scientific literature to the technological applications contained in patent applications, allowing for an analysis of the linkages between science and technology. This almost fully automated novel approach allows repeating the analysis as neurotechnology evolves. [pp. 8-9[

Findings in bullet points,

Key stylized facts are:
● The field of neuroscience has witnessed a remarkable surge in the overall number
of publications since 2000, exhibiting a nearly 35-fold increase over the period
considered, reaching 1.2 million in 2021. The annual number of publications in
neuroscience has nearly tripled since 2000, exceeding 90,000 publications a year
in 2021. This increase became even more pronounced since 2019.
● The United States leads in terms of neuroscience publication output (40%),
followed by the United Kingdom (9%), Germany (7%), China (5%), Canada (4%),
Japan (4%), Italy (4%), France (4%), the Netherlands (3%), and Australia (3%).
These countries account for over 80% of neuroscience publications from 2000 to
2021.
● Big divides emerge, with 70% of countries in the world having less than 10 high-
impact neuroscience publications between 2000 to 2021.
● Specific neurotechnology-related research trends between 2000 and 2021 include:
○ An increase in Brain-Computer Interface (BCI) research around 2010,
maintaining a consistent presence ever since.
○ A significant surge in Epilepsy Detection research in 2017 and 2018,
reflecting the increased use of AI and machine learning in healthcare.
○ Consistent interest in Neuroimaging Analysis, which peaks around 2004,
likely because of its importance in brain activity and language
comprehension studies.
○ While peaking in 2016 and 2017, Deep Brain Stimulation (DBS) remains a
persistent area of research, underlining its potential in treating conditions
like Parkinson’s disease and essential tremor.
● Between 2000 and 2020, the total number of patent applications in this field
increased significantly, experiencing a 20-fold increase from less than 500 to over
12,000. In terms of annual figures, a consistent upward trend in neurotechnology-10
related patent applications emerges, with a notable doubling observed between
2015 and 2020.
• The United States account for nearly half of all worldwide patent applications (47%).
Other major contributors include South Korea (11%), China (10%), Japan (7%),
Germany (7%), and France (5%). These five countries together account for 87%
of IP5 neurotech patents applied between 2000 and 2020.
○ The United States has historically led the field, with a peak around 2010, a
decline towards 2015, and a recovery up to 2020.
○ South Korea emerged as a significant contributor after 1990, overtaking
Germany in the late 2000s to become the second-largest developer of
neurotechnology. By the late 2010s, South Korea’s annual neurotechnology
patent applications approximated those of the United States.
○ China exhibits a sharp increase in neurotechnology patent applications in
the mid-2010s, bringing it on par with the United States in terms of
application numbers.
● The United States ranks highest in both scientific publications and patents,
indicating their strong ability to transform knowledge into marketable inventions.
China, France, and Korea excel in leveraging knowledge to develop patented
innovations. Conversely, countries such as the United Kingdom, Germany, Italy,
Canada, Brazil, and Australia lag behind in effectively translating neurotech
knowledge into patentable innovations.
● In terms of patent quality measured by forward citations, the leading countries are
Germany, US, China, Japan, and Korea.
● A breakdown of patents by technology field reveals that Computer Technology is
the most important field in neurotechnology, exceeding Medical Technology,
Biotechnology, and Pharmaceuticals. The growing importance of algorithmic
applications, including neural computing techniques, also emerges by looking at
the increase in patent applications in these fields between 2015-2020. Compared
to the reference year, computer technologies-related patents in neurotech
increased by 355% and by 92% in medical technology.
● An analysis of the specialization patterns of the top-5 countries developing
neurotechnologies reveals that Germany has been specializing in chemistry-
related technology fields, whereas Asian countries, particularly South Korea and
China, focus on computer science and electrical engineering-related fields. The
United States exhibits a balanced configuration with specializations in both
chemistry and computer science-related fields.
● The entities – i.e. both companies and other institutions – leading worldwide
innovation in the neurotech space are: IBM (126 IP5 patents, US), Ping An
Technology (105 IP5 patents, CH), Fujitsu (78 IP5 patents, JP), Microsoft (76 IP511
patents, US)1, Samsung (72 IP5 patents, KR), Sony (69 IP5 patents JP) and Intel
(64 IP5 patents US)
This report further proposes a pioneering taxonomy of neurotechnologies based on International Patent Classification (IPC) codes.
• 67 distinct patent clusters in neurotechnology are identified, which mirror the diverse research and development landscape of the field. The 20 most prominent neurotechnology groups, particularly in areas like multimodal neuromodulation, seizure prediction, neuromorphic computing [emphasis mine], and brain-computer interfaces, point to potential strategic areas for research and commercialization.
• The variety of patent clusters identified mirrors the breadth of neurotechnology’s potential applications, from medical imaging and limb rehabilitation to sleep optimization and assistive exoskeletons.
• The development of a baseline IPC-based taxonomy for neurotechnology offers a structured framework that enriches our understanding of this technological space, and can facilitate research, development and analysis. The identified key groups mirror the interdisciplinary nature of neurotechnology and underscores the potential impact of neurotechnology, not only in healthcare but also in areas like information technology and biomaterials, with non-negligible effects over societies and economies.
1 If we consider Microsoft Technology Licensing LLM and Microsoft Corporation as being under the same umbrella, Microsoft leads worldwide developments with 127 IP5 patents. Similarly, if we were to consider that Siemens AG and Siemens Healthcare GmbH belong to the same conglomerate, Siemens would appear much higher in the ranking, in third position, with 84 IP5 patents. The distribution of intellectual property assets across companies belonging to the same conglomerate is frequent and mirrors strategic as well as operational needs and features, among others. [pp. 9-11]

Surprises and comments

Interesting and helpful to learn that “neurotechnology interacts with other technological trajectories, especially Artificial Intelligence;” this has changed and improved my understanding of neurotechnology.

It was unexpected to find Canada in the top ten countries producing neuroscience papers. However, finding out that the country lags in translating its ‘neuro’ knowledge into patentable innovation is not entirely a surprise.

It can’t be an accident that countries with major ‘electronics and computing’ companies lead in patents. These companies do have researchers but they also buy startups to acquire patents. They (and ‘patent trolls’) will also file patents preemptively. For the patent trolls, it’s a moneymaking proposition and for the large companies, it’s a way of protecting their own interests and/or (I imagine) forcing a sale.

The mention of neuromorphic (brainlike) computing in the taxonomy section was surprising and puzzling. Up to this point, I’ve thought of neuromorphic computing as a kind of alternative or addition to standard computing but the authors have blurred the lines as per UNESCO’s definition of neurotechnology (specifically, “… emulate the structure and function of the neural systems of animals or human beings”) . Again, this report is broadening my understanding of neurotechnology. Of course, it required two instances before I quite grasped it, the definition and the taxonomy.

What’s puzzling is that neuromorphic engineering, a broader term that includes neuromorphic computing, isn’t used or mentioned. (For an explanation of the terms neuromorphic computing and neuromorphic engineering, there’s my June 23, 2023 posting, “Neuromorphic engineering: an overview.” )

The report

I won’t have time for everything. Here are some of the highlights from my admittedly personal perspective.

It’s not only about curing disease

From the report,

Neurotechnology’s applications however extend well beyond medicine [emphasis mine], and span from research, to education, to the workplace, and even people’s everyday life. Neurotechnology-based solutions may enhance learning and skill acquisition and boost focus through brain stimulation techniques. For instance, early research finds that brain- zapping caps appear to boost memory for at least one month (Berkeley, 2022). This could one day be used at home to enhance memory functions [emphasis mine]. They can further enable new ways to interact with the many digital devices we use in everyday life, transforming the way we work, live and interact. One example is the Sound Awareness wristband developed by a Stanford team (Neosensory, 2022) which enables individuals to “hear” by converting sound into tactile feedback, so that sound impaired individuals can perceive spoken words through their skin. Takagi and Nishimoto (2023) analyzed the brain scans taken through Magnetic Resonance Imaging (MRI) as individuals were shown thousands of images. They then trained a generative AI tool called Stable Diffusion2 on the brain scan data of the study’s participants, thus creating images that roughly corresponded to the real images shown. While this does not correspond to reading the mind of people, at least not yet, and some limitations of the study have been highlighted (Parshall, 2023), it nevertheless represents an important step towards developing the capability to interface human thoughts with computers [emphasis mine], via brain data interpretation.
While the above examples may sound somewhat like science fiction, the recent uptake of generative Artificial Intelligence applications and of large language models such as ChatGPT or Bard, demonstrates that the seemingly impossible can quickly become an everyday reality. At present, anyone can purchase online electroencephalogram (EEG) devices for a few hundred dollars [emphasis mine], to measure the electrical activity of their brain for meditation, gaming, or other purposes. [pp. 14-15]

This is very impressive achievement. Some of the research cited was published earlier this year (2023). The extraordinary speed is a testament to the efforts by the authors and their teams. It’s also a testament to how quickly the field is moving.

I’m glad to see the mention of and focus on consumer neurotechnology. (While the authors don’t speculate, I am free to do so.) Consumer neurotechnology could be viewed as one of the steps toward normalizing a cyborg future for all of us. Yes, we have books, television programmes, movies, and video games, which all normalize the idea but the people depicted have been severely injured and require the augmentation. With consumer neurotechnology, you have easily accessible devices being used to enhance people who aren’t injured, they just want to be ‘better’.

This phrase seemed particularly striking “… an important step towards developing the capability to interface human thoughts with computers” in light of some claims made by the Australian military in my June 13, 2023 posting “Mind-controlled robots based on graphene: an Australian research story.” (My posting has an embedded video demonstrating the Brain Robotic Interface (BRI) in action. Also, see the paragraph below the video for my ‘measured’ response.)

There’s no mention of the military in the report which seems more like a deliberate rather than inadvertent omission given the importance of military innovation where technology is concerned.

This section gives a good overview of government initiatives (in the report it’s followed by a table of the programmes),

Thanks to the promises it holds, neurotechnology has garnered significant attention from both governments and the private sector and is considered by many as an investment priority. According to the International Brain Initiative (IBI), brain research funding has become increasingly important over the past ten years, leading to a rise in large-scale state-led programs aimed at advancing brain intervention technologies(International Brain Initiative, 2021). Since 2013, initiatives such as the United States’ Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative and the European Union’s Human Brain Project (HBP), as well as major national initiatives in China, Japan and South Korea have been launched with significant funding support from the respective governments. The Canadian Brain Research Strategy, initially operated as a multi- stakeholder coalition on brain research, is also actively seeking funding support from the government to transform itself into a national research initiative (Canadian Brain Research Strategy, 2022). A similar proposal is also seen in the case of the Australian Brain Alliance, calling for the establishment of an Australian Brain Initiative (Australian Academy of Science, n.d.). [pp. 15-16]

Privacy

There are some concerns such as these,

Beyond the medical realm, research suggests that emotional responses of consumers
related to preferences and risks can be concurrently tracked by neurotechnology, such
as neuroimaging and that neural data can better predict market-level outcomes than
traditional behavioral data (Karmarkar and Yoon, 2016). As such, neural data is
increasingly sought after in the consumer market for purposes such as digital
phenotyping4, neurogaming 5，and neuromarketing6 (UNESCO, 2021). This surge in demand gives rise to risks like hacking, unauthorized data reuse, extraction of privacy-sensitive information, digital surveillance, criminal exploitation of data, and other forms of abuse. These risks prompt the question of whether neural data needs distinct definition and safeguarding measures.
These issues are particularly relevant today as a wide range of electroencephalogram (EEG) headsets that can be used at home are now available in consumer markets for purposes that range from meditation assistance to controlling electronic devices through the mind. Imagine an individual is using one of these devices to play a neurofeedback game, which records the person’s brain waves during the game. Without the person being aware, the system can also identify the patterns associated with an undiagnosed mental health condition, such as anxiety. If the game company sells this data to third parties, e.g. health insurance providers, this may lead to an increase of insurance fees based on undisclosed information. This hypothetical situation would represent a clear violation of mental privacy and of unethical use of neural data.
Another example is in the field of advertising, where companies are increasingly interested in using neuroimaging to better understand consumers’ responses to their products or advertisements, a practice known as neuromarketing. For instance, a company might use neural data to determine which advertisements elicit the most positive emotional responses in consumers. While this can help companies improve their marketing strategies, it raises significant concerns about mental privacy. Questions arise in relation to consumers being aware or not that their neural data is being used, and in the extent to which this can lead to manipulative advertising practices that unfairly exploit unconscious preferences. Such potential abuses underscore the need for explicit consent and rigorous data protection measures in the use of neurotechnology for neuromarketing purposes. [pp. 21-22]

Legalities

Some countries already have laws and regulations regarding neurotechnology data,

At the national level, only a few countries have enacted laws and regulations to protect mental integrity or have included neuro-data in personal data protection laws (UNESCO, University of Milan-Bicocca (Italy) and State University of New York – Downstate Health Sciences University, 2023). Examples are the constitutional reform undertaken by Chile (Republic of Chile, 2021), the Charter for the responsible development of neurotechnologies of the Government of France (Government of France, 2022), and the Digital Rights Charter of the Government of Spain (Government of Spain, 2021). They propose different approaches to the regulation and protection of human rights in relation to neurotechnology. Countries such as the UK are also examining under which circumstances neural data may be considered as a special category of data under the general data protection framework (i.e. UK’s GDPR) (UK’s Information Commissioner’s Office, 2023) [p. 24]

As you can see, these are recent laws. There doesn’t seem to be any attempt here in Canada even though there is an act being reviewed in Parliament that could conceivably include neural data. This is from my May 1, 2023 posting,

Bill C-27 (Digital Charter Implementation Act, 2022) is what I believe is called an omnibus bill as it includes three different pieces of proposed legislation (the Consumer Privacy Protection Act [CPPA], the Artificial Intelligence and Data Act [AIDA], and the Personal Information and Data Protection Tribunal Act [PIDPTA]). [emphasis added July 11, 2023] You can read the Innovation, Science and Economic Development (ISED) Canada summary here or a detailed series of descriptions of the act here on the ISED’s Canada’s Digital Charter webpage.

My focus at the time was artificial intelligence and, now, after reading this UNESCO report and briefly looking at the Innovation, Science and Economic Development (ISED) Canada summary and a detailed series of descriptions of the act on ISED’s Canada’s Digital Charter webpage, I don’t see anything that specifies neural data but it’s not excluded either.

IP5 patents

Here’s the explanation (the footnote is included at the end of the excerpt),

IP5 patents represent a subset of overall patents filed worldwide, which have the
characteristic of having been filed in at least one top intellectual property offices (IPO)
worldwide (the so called IP5, namely the Chinese National Intellectual Property
Administration, CNIPA (formerly SIPO); the European Patent Office, EPO; the Japan
Patent Office, JPO; the Korean Intellectual Property Office, KIPO; and the United States
Patent and Trademark Office, USPTO) as well as another country, which may or may not be an IP5. This signals their potential applicability worldwide, as their inventiveness and industrial viability have been validated by at least two leading IPOs. This gives these patents a sort of “quality” check, also since patenting inventions is costly and if applicants try to protect the same invention in several parts of the world, this normally mirrors that the applicant has expectations about their importance and expected value. If we were to conduct the same analysis using information about individually considered patent applied worldwide, i.e. without filtering for quality nor considering patent families, we would risk conducting a biased analysis based on duplicated data. Also, as patentability standards vary across countries and IPOs, and what matters for patentability is the existence (or not) of prior art in the IPO considered, we would risk mixing real innovations with patents related to catching up phenomena in countries that are not at the forefront of the technology considered.
9 The five IP offices (IP5) is a forum of the five largest intellectual property offices in the world that was set up to improve the efficiency of the examination process for patents worldwide. The IP5 Offices together handle about 80% of the world’s patent applications, and 95% of all work carried out under the Patent Cooperation Treaty (PCT), see http://www.fiveipoffices.org. (Dernis et al., 2015) [p. 31]

AI assistance on this report

As noted earlier I have next to no experience with the analytical tools having not attempted this kind of work in several years. Here’s an example of what they were doing,

We utilize a combination of text embeddings based on Bidirectional Encoder
Representations from Transformer (BERT), dimensionality reduction, and hierarchical
clustering inspired by the BERTopic methodology 12 to identify latent themes within
research literature. Latent themes or topics in the context of topic modeling represent
clusters of words that frequently appear together within a collection of documents (Blei, 2012). These groupings are not explicitly labeled but are inferred through computational analysis examining patterns in word usage. These themes are ‘hidden’ within the text, only to be revealed through this analysis. …
…
We further utilize OpenAI’s GPT-4 model to enrich our understanding of topics’ keywords and to generate topic labels (OpenAI, 2023), thus supplementing expert review of the broad interdisciplinary corpus. Recently, GPT-4 has shown impressive results in medical contexts across various evaluations (Nori et al., 2023), making it a useful tool to enhance the information obtained from prior analysis stages, and to complement them. The automated process enhances the evaluation workflow, effectively emphasizing neuroscience themes pertinent to potential neurotechnology patents. Notwithstanding existing concerns about hallucinations (Lee, Bubeck and Petro, 2023) and errors in generative AI models, this methodology employs the GPT-4 model for summarization and interpretation tasks, which significantly mitigates the likelihood of hallucinations. Since the model is constrained to the context provided by the keyword collections, it limits the potential for fabricating information outside of the specified boundaries, thereby enhancing the accuracy and reliability of the output. [pp. 33-34]

I couldn’t resist adding the ChatGPT paragraph given all of the recent hoopla about it.

Multimodal neuromodulation and neuromorphic computing patents

I think this gives a pretty good indication of the activity on the patent front,

The largest, coherent topic, termed “multimodal neuromodulation,” comprises 535
patents detailing methodologies for deep or superficial brain stimulation designed to
address neurological and psychiatric ailments. These patented technologies interact with various points in neural circuits to induce either Long-Term Potentiation (LTP) or Long-Term Depression (LTD), offering treatment for conditions such as obsession, compulsion, anxiety, depression, Parkinson’s disease, and other movement disorders. The modalities encompass implanted deep-brain stimulators (DBS), Transcranial Magnetic Stimulation (TMS), and transcranial Direct Current Stimulation (tDCS). Among the most representative documents for this cluster are patents with titles: Electrical stimulation of structures within the brain or Systems and methods for enhancing or optimizing neural stimulation therapy for treating symptoms of Parkinson’s disease and or other movement disorders. [p.65]

Given my longstanding interest in memristors, which (I believe) have to a large extent helped to stimulate research into neuromorphic computing, this had to be included. Then, there was the brain-computer interfaces cluster,

A cluster identified as “Neuromorphic Computing” consists of 366 patents primarily
focused on devices designed to mimic human neural networks for efficient and adaptable computation. The principal elements of these inventions are resistive memory cells and artificial synapses. They exhibit properties similar to the neurons and synapses in biological brains, thus granting these devices the ability to learn and modulate responses based on rewards, akin to the adaptive cognitive capabilities of the human brain.
The primary technology classes associated with these patents fall under specific IPC
codes, representing the fields of neural network models, analog computers, and static
storage structures. Essentially, these classifications correspond to technologies that are key to the construction of computers and exhibit cognitive functions similar to human brain processes.
Examples for this cluster include neuromorphic processing devices that leverage
variations in resistance to store and process information, artificial synapses exhibiting
spike-timing dependent plasticity, and systems that allow event-driven learning and
reward modulation within neuromorphic computers.
In relation to neurotechnology as a whole, the “neuromorphic computing” cluster holds significant importance. It embodies the fusion of neuroscience and technology, thereby laying the basis for the development of adaptive and cognitive computational systems. Understanding this specific cluster provides a valuable insight into the progressing domain of neurotechnology, promising potential advancements across diverse fields, including artificial intelligence and healthcare.
The “Brain-Computer Interfaces” cluster, consisting of 146 patents, embodies a key aspect of neurotechnology that focuses on improving the interface between the brain and external devices. The technology classification codes associated with these patents primarily refer to methods or devices for treatment or protection of eyes and ears, devices for introducing media into, or onto, the body, and electric communication techniques, which are foundational elements of brain-computer interface (BCI) technologies.
Key patents within this cluster include a brain-computer interface apparatus adaptable to use environment and method of operating thereof, a double closed circuit brain-machine interface system, and an apparatus and method of brain-computer interface for device controlling based on brain signal. These inventions mainly revolve around the concept of using brain signals to control external devices, such as robotic arms, and improving the classification performance of these interfaces, even after long periods of non-use.
The inventions described in these patents improve the accuracy of device control, maintain performance over time, and accommodate multiple commands, thus significantly enhancing the functionality of BCIs.
Other identified technologies include systems for medical image analysis, limb rehabilitation, tinnitus treatment, sleep optimization, assistive exoskeletons, and advanced imaging techniques, among others. [pp. 66-67]

Having sections on neuromorphic computing and brain-computer interface patents in immediate proximity led to more speculation on my part. Imagine how much easier it would be to initiate a BCI connection if it’s powered with a neuromorphic (brainlike) computer/device. [ETA July 21, 2023: Following on from that thought, it might be more than just easier to initiate a BCI connection. Could a brainlike computer become part of your brain? Why not? it’s been successfully argued that a robotic wheelchair was part of someone’s body, see my January 30, 2013 posting and scroll down about 40% of the way.)]

Neurotech policy debates

The report concludes with this,

Neurotechnology is a complex and rapidly evolving technological paradigm whose
trajectories have the power to shape people’s identity, autonomy, privacy, sentiments,
behaviors and overall well-being, i.e. the very essence of what it means to be human.
Designing and implementing careful and effective norms and regulations ensuring that neurotechnology is developed and deployed in an ethical manner, for the good of
individuals and for society as a whole, call for a careful identification and characterization of the issues at stake. This entails shedding light on the whole neurotechnology ecosystem, that is what is being developed, where and by whom, and also understanding how neurotechnology interacts with other developments and technological trajectories, especially AI. Failing to do so may result in ineffective (at best) or distorted policies and policy decisions, which may harm human rights and human dignity.
…
Addressing the need for evidence in support of policy making, the present report offers first time robust data and analysis shedding light on the neurotechnology landscape worldwide. To this end, its proposes and implements an innovative approach that leverages artificial intelligence and deep learning on data from scientific publications and paten[t]s to identify scientific and technological developments in the neurotech space. The methodology proposed represents a scientific advance in itself, as it constitutes a quasi- automated replicable strategy for the detection and documentation of neurotechnology- related breakthroughs in science and innovation, to be repeated over time to account for the evolution of the sector. Leveraging this approach, the report further proposes an IPC-based taxonomy for neurotechnology which allows for a structured framework to the exploration of neurotechnology, to enable future research, development and analysis. The innovative methodology proposed is very flexible and can in fact be leveraged to investigate different emerging technologies, as they arise.
…
In terms of technological trajectories, we uncover a shift in the neurotechnology industry, with greater emphasis being put on computer and medical technologies in recent years, compared to traditionally dominant trajectories related to biotechnology and pharmaceuticals. This shift warrants close attention from policymakers, and calls for attention in relation to the latest (converging) developments in the field, especially AI and related methods and applications and neurotechnology.
This is all the more important and the observed growth and specialization patterns are unfolding in the context of regulatory environments that, generally, are either not existent or not fit for purpose. Given the sheer implications and impact of neurotechnology on the very essence of human beings, this lack of regulation poses key challenges related to the possible infringement of mental integrity, human dignity, personal identity, privacy, freedom of thought, and autonomy, among others. Furthermore, issues surrounding accessibility and the potential for neurotech enhancement applications triggers significant concerns, with far-reaching implications for individuals and societies. [pp. 72-73]

Last words about the report

Informative, readable, and thought-provoking. And, it helped broaden my understanding of neurotechnology.

Future endeavours?

I’m hopeful that one of these days one of these groups (UNESCO, Canadian Science Policy Centre, or ???) will tackle the issue of business bankruptcy in the neurotechnology sector. It has already occurred as noted in my ““Going blind when your neural implant company flirts with bankruptcy [long read]” April 5, 2022 posting. That story opens with a woman going blind in a New York subway when her neural implant fails. It’s how she found out the company, which supplied her implant was going out of business.

In my July 7, 2023 posting about the UNESCO July 2023 dialogue on neurotechnology, I’ve included information on Neuralink (one of Elon Musk’s companies) and its approval (despite some investigations) by the US Food and Drug Administration to start human clinical trials. Scroll down about 75% of the way to the “Food for thought” subhead where you will find stories about allegations made against Neuralink.

The end

If you want to know more about the field, the report offers a seven-page bibliography and there’s a lot of material here where you can start with this December 3, 2019 posting “Neural and technological inequalities” which features an article mentioning a discussion between two scientists. Surprisingly (to me), the source article is in Fast Company (a leading progressive business media brand), according to their tagline)..

I have two categories you may want to check: Human Enhancement and Neuromorphic Engineering. There are also a number of tags: neuromorphic computing, machine/flesh, brainlike computing, cyborgs, neural implants, neuroprosthetics, memristors, and more.

Should you have any observations or corrections, please feel free to leave them in the Comments section of this posting.

FrogHeart

Commentary about nanotech, science policy and communication, society, and the arts

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