Category Archives: risk

Your gas stove may be emitting more polluting nanoparticles than your car exhaust

A February 27, 2024 news item on ScienceDaily describes the startling research results to anyone who’s listened to countless rhapsodize about the superiority of gas stoves over any other,

Cooking on your gas stove can emit more nano-sized particles into the air than vehicles that run on gas or diesel, possibly increasing your risk of developing asthma or other respiratory illnesses, a new Purdue University study has found.

“Combustion remains a source of air pollution across the world, both indoors and outdoors. We found that cooking on your gas stove produces large amounts of small nanoparticles that get into your respiratory system and deposit efficiently,” said Brandon Boor, an associate professor in Purdue’s Lyles School of Civil Engineering, who led this research.

Based on these findings, the researchers would encourage turning on a kitchen exhaust fan while cooking on a gas stove.

The study, published in the journal PNAS [Proceedngs of the National Academy of Sciences] Nexus, focused on tiny airborne nanoparticles that are only 1-3 nanometers in diameter, which is just the right size for reaching certain parts of the respiratory system and spreading to other organs.

A February 27, 2024 Purdue University news release by Kayla Albert (also on EurekAlert), which originated the news item, provides more detail about the research, Note: Links have been removed,

Recent studies have found that children who live in homes with gas stoves are more likely to develop asthma. But not much is known about how particles smaller than 3 nanometers, called nanocluster aerosol, grow and spread indoors because they’re very difficult to measure.

“These super tiny nanoparticles are so small that you’re not able to see them. They’re not like dust particles that you would see floating in the air,” Boor said. “After observing such high concentrations of nanocluster aerosol during gas cooking, we can’t ignore these nano-sized particles anymore.”

Using state-of-the-art air quality instrumentation provided by the German company GRIMM AEROSOL TECHNIK, a member of the DURAG GROUP, Purdue researchers were able to measure these tiny particles down to a single nanometer while cooking on a gas stove in a “tiny house” lab. They collaborated with Gerhard Steiner, a senior scientist and product manager for nano measurement at GRIMM AEROSOL. 

Called the Purdue zero Energy Design Guidance for Engineers (zEDGE) lab, the tiny house has all the features of a typical home but is equipped with sensors for closely monitoring the impact of everyday activities on a home’s air quality. With this testing environment and the instrument from GRIMM AEROSOL, a high-resolution particle size magnifier—scanning mobility particle sizer (PSMPS), the team collected extensive data on indoor nanocluster aerosol particles during realistic cooking experiments.

This magnitude of high-quality data allowed the researchers to compare their findings with known outdoor air pollution levels, which are more regulated and understood than indoor air pollution. They found that as many as 10 quadrillion nanocluster aerosol particles could be emitted per kilogram of cooking fuel — matching or exceeding those produced from vehicles with internal combustion engines. 

This would mean that adults and children could be breathing in 10-100 times more nanocluster aerosol from cooking on a gas stove indoors than they would from car exhaust while standing on a busy street.

“You would not use a diesel engine exhaust pipe as an air supply to your kitchen,” said Nusrat Jung, a Purdue assistant professor of civil engineering who designed the tiny house lab with her students and co-led this study.

Purdue civil engineering PhD student Satya Patra made these findings by looking at data collected in the tiny house lab and modeling the various ways that nanocluster aerosol could transform indoors and deposit into a person’s respiratory system.

The models showed that nanocluster aerosol particles are very persistent in their journey from the gas stove to the rest of the house. Trillions of these particles were emitted within just 20 minutes of boiling water or making grilled cheese sandwiches or buttermilk pancakes on a gas stove.

Even though many particles rapidly diffused to other surfaces, the models indicated that approximately 10 billion to 1 trillion particles could deposit into an adult’s head airways and tracheobronchial region of the lungs. These doses would be even higher for children — the smaller the human, the more concentrated the dose.

The nanocluster aerosol coming from the gas combustion also could easily mix with larger particles entering the air from butter, oil or whatever else is cooking on the gas stove, resulting in new particles with their own unique behaviors.

A gas stove’s exhaust fan would likely redirect these nanoparticles away from your respiratory system, but that remains to be tested.

“Since most people don’t turn on their exhaust fan while cooking, having kitchen hoods that activate automatically would be a logical solution,” Boor said. “Moving forward, we need to think about how to reduce our exposure to all types of indoor air pollutants. Based on our new data, we’d advise that nanocluster aerosol be considered as a distinct air pollutant category.”

This study was supported by a National Science Foundation CAREER award to Boor. Additional financial support was provided by the Alfred P. Sloan Foundation’s Chemistry of Indoor Environments program through an interdisciplinary collaboration with Philip Stevens, a professor in Indiana University’s Paul H. O’Neill School of Public and Environmental Affairs in Bloomington.

Here’s a link to and a citation for the paper,

Dynamics of nanocluster aerosol in the indoor atmosphere during gas cooking by Satya S Patra, Jinglin Jiang, Xiaosu Ding, Chunxu Huang, Emily K Reidy, Vinay Kumar, Paige Price, Connor Keech, Gerhard Steiner, Philip Stevens, Nusrat Jung, Brandon E Boor. PNAS Nexus, Volume 3, Issue 2, February 2024, pgae044, DOI: https://doi.org/10.1093/pnasnexus/pgae044 Published: 27 February 2024

This paper is open access.

Six months after the first one at Bletchley Park, the 2nd AI Safety Summit (May 21-22, 2024) convenes in Korea

This May 20, 2024 University of Oxford press release (also on EurekAlert) was under embargo until almost noon on May 20, 2024, which is a bit unusual, in my experience, (Note: I have more about the 1st summit and the interest in AI safety at the end of this posting),

Leading AI scientists are calling for stronger action on AI risks from world leaders, warning that progress has been insufficient since the first AI Safety Summit in Bletchley Park six months ago. 

Then, the world’s leaders pledged to govern AI responsibly. However, as the second AI Safety Summit in Seoul (21-22 May [2024]) approaches, twenty-five of the world’s leading AI scientists say not enough is actually being done to protect us from the technology’s risks. In an expert consensus paper published today in Science, they outline urgent policy priorities that global leaders should adopt to counteract the threats from AI technologies. 

Professor Philip Torr,Department of Engineering Science,University of Oxford, a co-author on the paper, says: “The world agreed during the last AI summit that we needed action, but now it is time to go from vague proposals to concrete commitments. This paper provides many important recommendations for what companies and governments should commit to do.”

World’s response not on track in face of potentially rapid AI progress; 

According to the paper’s authors, it is imperative that world leaders take seriously the possibility that highly powerful generalist AI systems—outperforming human abilities across many critical domains—will be developed within the current decade or the next. They say that although governments worldwide have been discussing frontier AI and made some attempt at introducing initial guidelines, this is simply incommensurate with the possibility of rapid, transformative progress expected by many experts. 

Current research into AI safety is seriously lacking, with only an estimated 1-3% of AI publications concerning safety. Additionally, we have neither the mechanisms or institutions in place to prevent misuse and recklessness, including regarding the use of autonomous systems capable of independently taking actions and pursuing goals.

World-leading AI experts issue call to action

In light of this, an international community of AI pioneers has issued an urgent call to action. The co-authors include Geoffrey Hinton, Andrew Yao, Dawn Song, the late Daniel Kahneman; in total 25 of the world’s leading academic experts in AI and its governance. The authors hail from the US, China, EU, UK, and other AI powers, and include Turing award winners, Nobel laureates, and authors of standard AI textbooks.

This article is the first time that such a large and international group of experts have agreed on priorities for global policy makers regarding the risks from advanced AI systems.

Urgent priorities for AI governance

The authors recommend governments to:

  • establish fast-acting, expert institutions for AI oversight and provide these with far greater funding than they are due to receive under almost any current policy plan. As a comparison, the US AI Safety Institute currently has an annual budget of $10 million, while the US Food and Drug Administration (FDA) has a budget of $6.7 billion.
  • mandate much more rigorous risk assessments with enforceable consequences, rather than relying on voluntary or underspecified model evaluations.
  • require AI companies to prioritise safety, and to demonstrate their systems cannot cause harm. This includes using “safety cases” (used for other safety-critical technologies such as aviation) which shifts the burden for demonstrating safety to AI developers.
  • implement mitigation standards commensurate to the risk-levels posed by AI systems. An urgent priority is to set in place policies that automatically trigger when AI hits certain capability milestones. If AI advances rapidly, strict requirements automatically take effect, but if progress slows, the requirements relax accordingly.

According to the authors, for exceptionally capable future AI systems, governments must be prepared to take the lead in regulation. This includes licensing the development of these systems, restricting their autonomy in key societal roles, halting their development and deployment in response to worrying capabilities, mandating access controls, and requiring information security measures robust to state-level hackers, until adequate protections are ready.

AI impacts could be catastrophic

AI is already making rapid progress in critical domains such as hacking, social manipulation, and strategic planning, and may soon pose unprecedented control challenges. To advance undesirable goals, AI systems could gain human trust, acquire resources, and influence key decision-makers. To avoid human intervention, they could be capable of copying their algorithms across global server networks. Large-scale cybercrime, social manipulation, and other harms could escalate rapidly. In open conflict, AI systems could autonomously deploy a variety of weapons, including biological ones. Consequently, there is a very real chance that unchecked AI advancement could culminate in a large-scale loss of life and the biosphere, and the marginalization or extinction of humanity.

Stuart Russell OBE [Order of the British Empire], Professor of Computer Science at the University of California at Berkeley and an author of the world’s standard textbook on AI, says: “This is a consensus paper by leading experts, and it calls for strict regulation by governments, not voluntary codes of conduct written by industry. It’s time to get serious about advanced AI systems. These are not toys. Increasing their capabilities before we understand how to make them safe is utterly reckless. Companies will complain that it’s too hard to satisfy regulations—that “regulation stifles innovation.” That’s ridiculous. There are more regulations on sandwich shops than there are on AI companies.”

Notable co-authors:

  • The world’s most-cited computer scientist (Prof. Hinton), and the most-cited scholar in AI security and privacy (Prof. Dawn Song)
  • China’s first Turing Award winner (Andrew Yao).
  • The authors of the standard textbook on artificial intelligence (Prof. Stuart Russell) and machine learning theory (Prof. Shai Shalev-Schwartz)
  • One of the world’s most influential public intellectuals (Prof. Yuval Noah Harari)
  • A Nobel Laureate in economics, the world’s most-cited economist (Prof. Daniel Kahneman)
  • Department-leading AI legal scholars and social scientists (Lan Xue, Qiqi Gao, and Gillian Hadfield).
  • Some of the world’s most renowned AI researchers from subfields such as reinforcement learning (Pieter Abbeel, Jeff Clune, Anca Dragan), AI security and privacy (Dawn Song), AI vision (Trevor Darrell, Phil Torr, Ya-Qin Zhang), automated machine learning (Frank Hutter), and several researchers in AI safety.

Additional quotes from the authors:

Philip Torr, Professor in AI, University of Oxford:

  • I believe if we tread carefully the benefits of AI will outweigh the downsides, but for me one of the biggest immediate risks from AI is that we develop the ability to rapidly process data and control society, by government and industry. We could risk slipping into some Orwellian future with some form of totalitarian state having complete control.

Dawn Song: Professor in AI at UC Berkeley, most-cited researcher in AI security and privacy:

  •  “Explosive AI advancement is the biggest opportunity and at the same time the biggest risk for mankind. It is important to unite and reorient towards advancing AI responsibly, with dedicated resources and priority to ensure that the development of AI safety and risk mitigation capabilities can keep up with the pace of the development of AI capabilities and avoid any catastrophe”

Yuval Noah Harari, Professor of history at Hebrew University of Jerusalem, best-selling author of ‘Sapiens’ and ‘Homo Deus’, world leading public intellectual:

  • “In developing AI, humanity is creating something more powerful than itself, that may escape our control and endanger the survival of our species. Instead of uniting against this shared threat, we humans are fighting among ourselves. Humankind seems hell-bent on self-destruction. We pride ourselves on being the smartest animals on the planet. It seems then that evolution is switching from survival of the fittest, to extinction of the smartest.”

Jeff Clune, Professor in AI at University of British Columbia and one of the leading researchers in reinforcement learning:

  • “Technologies like spaceflight, nuclear weapons and the Internet moved from science fiction to reality in a matter of years. AI is no different. We have to prepare now for risks that may seem like science fiction – like AI systems hacking into essential networks and infrastructure, AI political manipulation at scale, AI robot soldiers and fully autonomous killer drones, and even AIs attempting to outsmart us and evade our efforts to turn them off.”
  • “The risks we describe are not necessarily long-term risks. AI is progressing extremely rapidly. Even just with current trends, it is difficult to predict how capable it will be in 2-3 years. But what very few realize is that AI is already dramatically speeding up AI development. What happens if there is a breakthrough for how to create a rapidly self-improving AI system? We are now in an era where that could happen any month. Moreover, the odds of that being possible go up each month as AI improves and as the resources we invest in improving AI continue to exponentially increase.”

Gillian Hadfield, CIFAR AI Chair and Director of the Schwartz Reisman Institute for Technology and Society at the University of Toronto:

 “AI labs need to walk the walk when it comes to safety. But they’re spending far less on safety than they spend on creating more capable AI systems. Spending one-third on ensuring safety and ethical use should be the minimum.”

  • “This technology is powerful, and we’ve seen it is becoming more powerful, fast. What is powerful is dangerous, unless it is controlled. That is why we call on major tech companies and public funders to allocate at least one-third of their AI R&D budget to safety and ethical use, comparable to their funding for AI capabilities.”  

Sheila McIlrath, Professor in AI, University of Toronto, Vector Institute:

  • AI is software. Its reach is global and its governance needs to be as well.
  • Just as we’ve done with nuclear power, aviation, and with biological and nuclear weaponry, countries must establish agreements that restrict development and use of AI, and that enforce information sharing to monitor compliance. Countries must unite for the greater good of humanity.
  • Now is the time to act, before AI is integrated into our critical infrastructure. We need to protect and preserve the institutions that serve as the foundation of modern society.

Frank Hutter, Professor in AI at the University of Freiburg, Head of the ELLIS Unit Freiburg, 3x ERC grantee:

  • To be clear: we need more research on AI, not less. But we need to focus our efforts on making this technology safe. For industry, the right type of regulation will provide economic incentives to shift resources from making the most capable systems yet more powerful to making them safer. For academia, we need more public funding for trustworthy AI and maintain a low barrier to entry for research on less capable open-source AI systems. This is the most important research challenge of our time, and the right mechanism design will focus the community at large to work towards the right breakthroughs.

Here’s a link to and a citation for the paper,

Managing extreme AI risks amid rapid progress; Preparation requires technical research and development, as well as adaptive, proactive governance by Yoshua Bengio, Geoffrey Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Trevor Darrell, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atılım Güneş Baydin, Sheila McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca Dragan, Philip Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, and Sören Mindermann. Science 20 May 2024 First Release DOI: 10.1126/science.adn0117

This paper appears to be open access.

For anyone who’s curious about the buildup to these safety summits, I have more in my October 18, 2023 “AI safety talks at Bletchley Park in November 2023” posting, which features excerpts from a number of articles on AI safety. There’s also my November 2, 2023 , “UK AI Summit (November 1 – 2, 2023) at Bletchley Park finishes” posting, which offers excerpts from articles critiquing the AI safety summit.

Hardware policies best way to manage AI safety?

Regulation of artificial intelligence (AI) has become very topical in the last couple of years. There was an AI safety summit in November 2023 at Bletchley Park in the UK (see my November 2, 2023 posting for more about that international meeting).

A very software approach?

This year (2024) has seen a rise in legislative and proposed legislative activity. I have some articles on a few of these activities. China was the first to enact regulations of any kind on AI according to Matt Sheehan’s February 27, 2024 paper for the Carnegie Endowment for International Peace,

In 2021 and 2022, China became the first country to implement detailed, binding regulations on some of the most common applications of artificial intelligence (AI). These rules formed the foundation of China’s emerging AI governance regime, an evolving policy architecture that will affect everything from frontier AI research to the functioning of the world’s second-largest economy, from large language models in Africa to autonomous vehicles in Europe.

The Chinese Communist Party (CCP) and the Chinese government started that process with the 2021 rules on recommendation algorithms, an omnipresent use of the technology that is often overlooked in international AI governance discourse. Those rules imposed new obligations on companies to intervene in content recommendations, granted new rights to users being recommended content, and offered protections to gig workers subject to algorithmic scheduling. The Chinese party-state quickly followed up with a new regulation on “deep synthesis,” the use of AI to generate synthetic media such as deepfakes. Those rules required AI providers to watermark AI-generated content and ensure that content does not violate people’s “likeness rights” or harm the “nation’s image.” Together, these two regulations also created and amended China’s algorithm registry, a regulatory tool that would evolve into a cornerstone of the country’s AI governance regime.

The UK has adopted a more generalized approach focused on encouraging innovation according to Valeria Gallo’s and Suchitra Nair’s February 21, 2024 article for Deloitte (a British professional services firm also considered one of the big four accounting firms worldwide),

At a glance

The UK Government has adopted a cross-sector and outcome-based framework for regulating AI, underpinned by five core principles. These are safety, security and robustness, appropriate transparency and explainability, fairness, accountability and governance, and contestability and redress.

Regulators will implement the framework in their sectors/domains by applying existing laws and issuing supplementary regulatory guidance. Selected regulators will publish their AI annual strategic plans by 30th April [2024], providing businesses with much-needed direction.

Voluntary safety and transparency measures for developers of highly capable AI models and systems will also supplement the framework and the activities of individual regulators.

The framework will not be codified into law for now, but the Government anticipates the need for targeted legislative interventions in the future. These interventions will address gaps in the current regulatory framework, particularly regarding the risks posed by complex General Purpose AI and the key players involved in its development.

Organisations must prepare for increased AI regulatory activity over the next year, including guidelines, information gathering, and enforcement. International firms will inevitably have to navigate regulatory divergence.

While most of the focus appears to be on the software (e.g., General Purpose AI), the UK framework does not preclude hardware.

The European Union (EU) is preparing to pass its own AI regulation act through the European Parliament in 2024 according to a December 19, 2023 “EU AI Act: first regulation on artificial intelligence” article update, Note: Links have been removed,

As part of its digital strategy, the EU wants to regulate artificial intelligence (AI) to ensure better conditions for the development and use of this innovative technology. AI can create many benefits, such as better healthcare; safer and cleaner transport; more efficient manufacturing; and cheaper and more sustainable energy.

In April 2021, the European Commission proposed the first EU regulatory framework for AI. It says that AI systems that can be used in different applications are analysed and classified according to the risk they pose to users. The different risk levels will mean more or less regulation.

The agreed text is expected to be finally adopted in April 2024. It will be fully applicable 24 months after entry into force, but some parts will be applicable sooner:

*The ban of AI systems posing unacceptable risks will apply six months after the entry into force

*Codes of practice will apply nine months after entry into force

*Rules on general-purpose AI systems that need to comply with transparency requirements will apply 12 months after the entry into force

High-risk systems will have more time to comply with the requirements as the obligations concerning them will become applicable 36 months after the entry into force.

This EU initiative, like the UK framework, seems largely focused on AI software and according to the Wikipedia entry “Regulation of artificial intelligence,”

… The AI Act is expected to come into effect in late 2025 or early 2026.[109

I do have a few postings about Canadian regulatory efforts, which also seem to be focused on software but don’t preclude hardware. While the January 20, 2024 posting is titled “Canada’s voluntary code of conduct relating to advanced generative AI (artificial intelligence) systems,” information about legislative efforts is also included although you might find my May 1, 2023 posting titled “Canada, AI regulation, and the second reading of the Digital Charter Implementation Act, 2022 (Bill C-27)” offers more comprehensive information about Canada’s legislative progress or lack thereof.

The US is always to be considered in these matters and I have a November 2023 ‘briefing’ by Müge Fazlioglu on the International Association of Privacy Professionals (IAPP) website where she provides a quick overview of the international scene before diving deeper into US AI governance policy through the Barack Obama, Donald Trump, and Joe Biden administrations. There’s also this January 29, 2024 US White House “Fact Sheet: Biden-⁠Harris Administration Announces Key AI Actions Following President Biden’s Landmark Executive Order.”

What about AI and hardware?

A February 15, 2024 news item on ScienceDaily suggests that regulating hardware may be the most effective way of regulating AI,

Chips and datacentres — the ‘compute’ power driving the AI revolution — may be the most effective targets for risk-reducing AI policies as they have to be physically possessed, according to a new report.

A global registry tracking the flow of chips destined for AI supercomputers is one of the policy options highlighted by a major new report calling for regulation of “compute” — the hardware that underpins all AI — to help prevent artificial intelligence misuse and disasters.

Other technical proposals floated by the report include “compute caps” — built-in limits to the number of chips each AI chip can connect with — and distributing a “start switch” for AI training across multiple parties to allow for a digital veto of risky AI before it feeds on data.

The experts point out that powerful computing chips required to drive generative AI models are constructed via highly concentrated supply chains, dominated by just a handful of companies — making the hardware itself a strong intervention point for risk-reducing AI policies.

The report, published 14 February [2024], is authored by nineteen experts and co-led by three University of Cambridge institutes — the Leverhulme Centre for the Future of Intelligence (LCFI), the Centre for the Study of Existential Risk (CSER) and the Bennett Institute for Public Policy — along with OpenAI and the Centre for the Governance of AI.

A February 14, 2024 University of Cambridge press release by Fred Lewsey (also on EurekAlert), which originated the news item, provides more information about the ‘hardware approach to AI regulation’,

“Artificial intelligence has made startling progress in the last decade, much of which has been enabled by the sharp increase in computing power applied to training algorithms,” said Haydn Belfield, a co-lead author of the report from Cambridge’s LCFI. 

“Governments are rightly concerned about the potential consequences of AI, and looking at how to regulate the technology, but data and algorithms are intangible and difficult to control.

“AI supercomputers consist of tens of thousands of networked AI chips hosted in giant data centres often the size of several football fields, consuming dozens of megawatts of power,” said Belfield.

“Computing hardware is visible, quantifiable, and its physical nature means restrictions can be imposed in a way that might soon be nearly impossible with more virtual elements of AI.”

The computing power behind AI has grown exponentially since the “deep learning era” kicked off in earnest, with the amount of “compute” used to train the largest AI models doubling around every six months since 2010. The biggest AI models now use 350 million times more compute than thirteen years ago.

Government efforts across the world over the past year – including the US Executive Order on AI, EU AI Act, China’s Generative AI Regulation, and the UK’s AI Safety Institute – have begun to focus on compute when considering AI governance.

Outside of China, the cloud compute market is dominated by three companies, termed “hyperscalers”: Amazon, Microsoft, and Google. “Monitoring the hardware would greatly help competition authorities in keeping in check the market power of the biggest tech companies, and so opening the space for more innovation and new entrants,” said co-author Prof Diane Coyle from Cambridge’s Bennett Institute. 

The report provides “sketches” of possible directions for compute governance, highlighting the analogy between AI training and uranium enrichment. “International regulation of nuclear supplies focuses on a vital input that has to go through a lengthy, difficult and expensive process,” said Belfield. “A focus on compute would allow AI regulation to do the same.”

Policy ideas are divided into three camps: increasing the global visibility of AI computing; allocating compute resources for the greatest benefit to society; enforcing restrictions on computing power.

For example, a regularly-audited international AI chip registry requiring chip producers, sellers, and resellers to report all transfers would provide precise information on the amount of compute possessed by nations and corporations at any one time.

The report even suggests a unique identifier could be added to each chip to prevent industrial espionage and “chip smuggling”.

“Governments already track many economic transactions, so it makes sense to increase monitoring of a commodity as rare and powerful as an advanced AI chip,” said Belfield. However, the team point out that such approaches could lead to a black market in untraceable “ghost chips”.

Other suggestions to increase visibility – and accountability – include reporting of large-scale AI training by cloud computing providers, and privacy-preserving “workload monitoring” to help prevent an arms race if massive compute investments are made without enough transparency.  

“Users of compute will engage in a mixture of beneficial, benign and harmful activities, and determined groups will find ways to circumvent restrictions,” said Belfield. “Regulators will need to create checks and balances that thwart malicious or misguided uses of AI computing.”

These might include physical limits on chip-to-chip networking, or cryptographic technology that allows for remote disabling of AI chips in extreme circumstances. One suggested approach would require the consent of multiple parties to unlock AI compute for particularly risky training runs, a mechanism familiar from nuclear weapons.

AI risk mitigation policies might see compute prioritised for research most likely to benefit society – from green energy to health and education. This could even take the form of major international AI “megaprojects” that tackle global issues by pooling compute resources.

The report’s authors are clear that their policy suggestions are “exploratory” rather than fully fledged proposals and that they all carry potential downsides, from risks of proprietary data leaks to negative economic impacts and the hampering of positive AI development.

They offer five considerations for regulating AI through compute, including the exclusion of small-scale and non-AI computing, regular revisiting of compute thresholds, and a focus on privacy preservation.

Added Belfield: “Trying to govern AI models as they are deployed could prove futile, like chasing shadows. Those seeking to establish AI regulation should look upstream to compute, the source of the power driving the AI revolution. If compute remains ungoverned it poses severe risks to society.”

You can find the report, “Computing Power and the Governance of Artificial Intelligence” on the University of Cambridge’s Centre for the Study of Existential Risk.

Authors include: Girish Sastry, Lennart Heim, Haydn Belfield, Markus Anderljung, Miles Brundage, Julian Hazell, Cullen O’Keefe, Gillian K. Hadfield, Richard Ngo, Konstantin Pilz, George Gor, Emma Bluemke, Sarah Shoker, Janet Egan, Robert F. Trager, Shahar Avin, Adrian Weller, Yoshua Bengio, and Diane Coyle.

The authors are associated with these companies/agencies: OpenAI, Centre for the Governance of AI (GovAI), Leverhulme Centre for the Future of Intelligence at the Uni. of Cambridge, Oxford Internet Institute, Institute for Law & AI, University of Toronto Vector Institute for AI, Georgetown University, ILINA Program, Harvard Kennedy School (of Government), *AI Governance Institute,* Uni. of Oxford, Centre for the Study of Existential Risk at Uni. of Cambridge, Uni. of Cambridge, Uni. of Montreal / Mila, Bennett Institute for Public Policy at the Uni. of Cambridge.

“The ILINIA program is dedicated to providing an outstanding platform for Africans to learn and work on questions around maximizing wellbeing and responding to global catastrophic risks” according to the organization’s homepage.

*As for the AI Governance Institute, I believe that should be the Centre for the Governance of AI at Oxford University since the associated academic is Robert F. Trager from the University of Oxford.

As the months (years?) fly by, I guess we’ll find out if this hardware approach gains any traction where AI regulation is concerned.

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

First, here’s some of the latest research and if by ‘non-invasive,’ you mean that electrodes are not being planted in your brain, then this December 12, 2023 University of Technology Sydney (UTS) press release (also on EurekAlert) highlights non-invasive mind-reading AI via a brain-computer interface (BCI), Note: Links have been removed,

In a world-first, researchers from the GrapheneX-UTS Human-centric Artificial Intelligence Centre at the University of Technology Sydney (UTS) have developed a portable, non-invasive system that can decode silent thoughts and turn them into text. 

The technology could aid communication for people who are unable to speak due to illness or injury, including stroke or paralysis. It could also enable seamless communication between humans and machines, such as the operation of a bionic arm or robot.

The study has been selected as the spotlight paper at the NeurIPS conference, a top-tier annual meeting that showcases world-leading research on artificial intelligence and machine learning, held in New Orleans on 12 December 2023.

The research was led by Distinguished Professor CT Lin, Director of the GrapheneX-UTS HAI Centre, together with first author Yiqun Duan and fellow PhD candidate Jinzhou Zhou from the UTS Faculty of Engineering and IT.

In the study participants silently read passages of text while wearing a cap that recorded electrical brain activity through their scalp using an electroencephalogram (EEG). A demonstration of the technology can be seen in this video [See UTS press release].

The EEG wave is segmented into distinct units that capture specific characteristics and patterns from the human brain. This is done by an AI model called DeWave developed by the researchers. DeWave translates EEG signals into words and sentences by learning from large quantities of EEG data. 

“This research represents a pioneering effort in translating raw EEG waves directly into language, marking a significant breakthrough in the field,” said Distinguished Professor Lin.

“It is the first to incorporate discrete encoding techniques in the brain-to-text translation process, introducing an innovative approach to neural decoding. The integration with large language models is also opening new frontiers in neuroscience and AI,” he said.

Previous technology to translate brain signals to language has either required surgery to implant electrodes in the brain, such as Elon Musk’s Neuralink [emphasis mine], or scanning in an MRI machine, which is large, expensive, and difficult to use in daily life.

These methods also struggle to transform brain signals into word level segments without additional aids such as eye-tracking, which restrict the practical application of these systems. The new technology is able to be used either with or without eye-tracking.

The UTS research was carried out with 29 participants. This means it is likely to be more robust and adaptable than previous decoding technology that has only been tested on one or two individuals, because EEG waves differ between individuals. 

The use of EEG signals received through a cap, rather than from electrodes implanted in the brain, means that the signal is noisier. In terms of EEG translation however, the study reported state-of the art performance, surpassing previous benchmarks.

“The model is more adept at matching verbs than nouns. However, when it comes to nouns, we saw a tendency towards synonymous pairs rather than precise translations, such as ‘the man’ instead of ‘the author’,” said Duan. [emphases mine; synonymous, eh? what about ‘woman’ or ‘child’ instead of the ‘man’?]

“We think this is because when the brain processes these words, semantically similar words might produce similar brain wave patterns. Despite the challenges, our model yields meaningful results, aligning keywords and forming similar sentence structures,” he said.

The translation accuracy score is currently around 40% on BLEU-1. The BLEU score is a number between zero and one that measures the similarity of the machine-translated text to a set of high-quality reference translations. The researchers hope to see this improve to a level that is comparable to traditional language translation or speech recognition programs, which is closer to 90%.

The research follows on from previous brain-computer interface technology developed by UTS in association with the Australian Defence Force [ADF] that uses brainwaves to command a quadruped robot, which is demonstrated in this ADF video [See my June 13, 2023 posting, “Mind-controlled robots based on graphene: an Australian research story” for the story and embedded video].

About one month after the research announcement regarding the University of Technology Sydney’s ‘non-invasive’ brain-computer interface (BCI), I stumbled across an in-depth piece about the field of ‘non-invasive’ mind-reading research.

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.

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.

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.

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.

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.”

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.

“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!

UK AI Summit (November 1 – 2, 2023) at Bletchley Park finishes

This is the closest I’ve ever gotten to writing a gossip column (see my October 18, 2023 posting and scroll down to the “Insight into political jockeying [i.e., some juicy news bits]” subhead )for the first half.

Given the role that Canadian researchers (for more about that see my May 25, 2023 posting and scroll down to “The Panic” subhead) have played in the development of artificial intelligence (AI), it’s been surprising that the Canadian Broadcasting Corporation (CBC) has given very little coverage to the event in the UK. However, there is an October 31, 2023 article by Kelvin Chang and Jill Lawless for the Associated Press posted on the CBC website,

Digital officials, tech company bosses and researchers are converging Wednesday [November 1, 2023] at a former codebreaking spy base [Bletchley Park] near London [UK] to discuss and better understand the extreme risks posed by cutting-edge artificial intelligence.

The two-day summit focusing on so-called frontier AI notched up an early achievement with officials from 28 nations and the European Union signing an agreement on safe and responsible development of the technology.

Frontier AI is shorthand for the latest and most powerful general purpose systems that take the technology right up to its limits, but could come with as-yet-unknown dangers. They’re underpinned by foundation models, which power chatbots like OpenAI’s ChatGPT and Google’s Bard and are trained on vast pools of information scraped from the internet.

The AI Safety Summit is a labour of love for British Prime Minister Rishi Sunak, a tech-loving former banker who wants the U.K. to be a hub for computing innovation and has framed the summit as the start of a global conversation about the safe development of AI.[emphasis mine]

But U.S. Vice President Kamala Harris may divert attention Wednesday [November 1, 2023] with a separate speech in London setting out the Biden administration’s more hands-on approach.

Canada’s Minister of Innovation, Science and Industry Francois-Philippe Champagne said AI would not be constrained by national borders, and therefore interoperability between different regulations being put in place was important.

As the meeting began, U.K. Technology Secretary Michelle Donelan announced that the 28 countries and the European Union had signed the Bletchley Declaration on AI Safety. It outlines the “urgent need to understand and collectively manage potential risks through a new joint global effort.”

South Korea has agreed to host a mini virtual AI summit in six months, followed by an in-person one in France in a year’s time, the U.K. government said.

Chris Stokel-Walker’s October 31, 2023 article for Fast Company presents a critique of the summit prior to the opening, Note: Links have been removed,

… one problem, critics say: The summit, which begins on November 1, is too insular and its participants are homogeneous—an especially damning critique for something that’s trying to tackle the huge, possibly intractable questions around AI. The guest list is made up of 100 of the great and good of governments, including representatives from China, Europe, and Vice President Kamala Harris. And it also includes luminaries within the tech sector. But precious few others—which means a lack of diversity in discussions about the impact of AI.

“Self-regulation didn’t work for social media companies, it didn’t work for the finance sector, and it won’t work for AI,” says Carsten Jung, a senior economist at the Institute for Public Policy Research, a progressive think tank that recently published a report advising on key policy pillars it believes should be discussed at the summit. (Jung isn’t on the guest list.) “We need to learn lessons from our past mistakes and create a strong supervisory hub for all things AI, right from the start.”

Kriti Sharma, chief product officer for legal tech at Thomson Reuters, who will be watching from the wings, not receiving an invite, is similarly circumspect about the goals of the summit. “I hope to see leaders moving past the doom to take practical steps to address known issues and concerns in AI, giving businesses the clarity they urgently need,” she says. “Ideally, I’d like to see movement towards putting some fundamental AI guardrails in place, in the form of a globally aligned, cross-industry regulatory framework.”

But it’s uncertain whether the summit will indeed discuss the more practical elements of AI. Already it seems as if the gathering is designed to quell public fears around AI while convincing those developing AI products that the U.K. will not take too strong an approach in regulating the technology, perhaps in contrasts to near neighbors in the European Union, who have been open about their plans to ensure the technology is properly fenced in to ensure user safety.

Already, there are suggestions that the summit has been drastically downscaled in its ambitions, with others, including the United States, where President Biden just announced a sweeping executive order on AI, and the United Nations, which announced its AI advisory board last week.

Ingrid Lunden in her October 31, 2023 article for TechCrunch is more blunt,

As we wrote yesterday, the U.K. is partly using this event — the first of its kind, as it has pointed out — to stake out a territory for itself on the AI map — both as a place to build AI businesses, but also as an authority in the overall field.

That, coupled with the fact that the topics and approach are focused on potential issues, the affair feel like one very grand photo opportunity and PR exercise, a way for the government to show itself off in the most positive way at the same time that it slides down in the polls and it also faces a disastrous, bad-look inquiry into how it handled the COVID-19 pandemic. On the other hand, the U.K. does have the credentials for a seat at the table, so if the government is playing a hand here, it’s able to do it because its cards are strong.

The subsequent guest list, predictably, leans more toward organizations and attendees from the U.K. It’s also almost as revealing to see who is not participating.

Lunden’s October 30, 2023 article “Existential risk? Regulatory capture? AI for one and all? A look at what’s going on with AI in the UK” includes a little ‘inside’ information,

That high-level aspiration is also reflected in who is taking part: top-level government officials, captains of industry, and notable thinkers in the space are among those expected to attend. (Latest late entry: Elon Musk; latest no’s reportedly include President Biden, Justin Trudeau and Olaf Scholz.) [Scholz’s no was mentioned in my my October 18, 2023 posting]

It sounds exclusive, and it is: “Golden tickets” (as Azeem Azhar, a London-based tech founder and writer, describes them) to the Summit are in scarce supply. Conversations will be small and mostly closed. So because nature abhors a vacuum, a whole raft of other events and news developments have sprung up around the Summit, looping in the many other issues and stakeholders at play. These have included talks at the Royal Society (the U.K.’s national academy of sciences); a big “AI Fringe” conference that’s being held across multiple cities all week; many announcements of task forces; and more.

Earlier today, a group of 100 trade unions and rights campaigners sent a letter to the prime minister saying that the government is “squeezing out” their voices in the conversation by not having them be a part of the Bletchley Park event. (They may not have gotten their golden tickets, but they were definitely canny how they objected: The group publicized its letter by sharing it with no less than the Financial Times, the most elite of economic publications in the country.)

And normal people are not the only ones who have been snubbed. “None of the people I know have been invited,” Carissa Véliz, a tutor in philosophy at the University of Oxford, said during one of the AI Fringe events today [October 30, 2023].

More broadly, the summit has become an anchor and only one part of the bigger conversation going on right now. Last week, U.K. prime minister Rishi Sunak outlined an intention to launch a new AI safety institute and a research network in the U.K. to put more time and thought into AI implications; a group of prominent academics, led by Yoshua Bengio [University of Montreal, Canada) and Geoffrey Hinton [University of Toronto, Canada], published a paper called “Managing AI Risks in an Era of Rapid Progress” to put their collective oar into the the waters; and the UN announced its own task force to explore the implications of AI. Today [October 30, 2023], U.S. president Joe Biden issued the country’s own executive order to set standards for AI security and safety.

There are a couple more articles* from the BBC (British Broadcasting Corporation) covering the start of the summit, a November 1, 2023 article by Zoe Kleinman & Tom Gerken, “King Charles: Tackle AI risks with urgency and unity” and another November 1, 2023 article this time by Tom Gerken & Imran Rahman-Jones, “Rishi Sunak: AI firms cannot ‘mark their own homework‘.”

Politico offers more US-centric coverage of the event with a November 1, 2023 article by Mark Scott, Tom Bristow and Gian Volpicelli, “US and China join global leaders to lay out need for AI rulemaking,” a November 1, 2023 article by Vincent Manancourt and Eugene Daniels, “Kamala Harris seizes agenda as Rishi Sunak’s AI summit kicks off,” and a November 1, 2023 article by Vincent Manancourt, Eugene Daniels and Brendan Bordelon, “‘Existential to who[m]?’ US VP Kamala Harris urges focus on near-term AI risks.”

I want to draw special attention to the second Politico article,

Kamala just showed Rishi who’s boss.

As British Prime Minister Rishi Sunak’s showpiece artificial intelligence event kicked off in Bletchley Park on Wednesday, 50 miles south in the futuristic environs of the American Embassy in London, U.S. Vice President Kamala Harris laid out her vision for how the world should govern artificial intelligence.

It was a raw show of U.S. power on the emerging technology.

Did she or was this an aggressive interpretation of events?

*’article’ changed to ‘articles’ on January 17, 2024.

AI safety talks at Bletchley Park in November 2023

There’s a very good article about the upcoming AI (artificial intelligence) safety talks on the British Broadcasting Corporation (BBC) news website (plus some juicy perhaps even gossipy news about who may not be attending the event) but first, here’s the August 24, 2023 UK government press release making the announcement,

Iconic Bletchley Park to host UK AI Safety Summit in early November [2023]

Major global event to take place on the 1st and 2nd of November.[2023]

– UK to host world first summit on artificial intelligence safety in November

– Talks will explore and build consensus on rapid, international action to advance safety at the frontier of AI technology

– Bletchley Park, one of the birthplaces of computer science, to host the summit

International governments, leading AI companies and experts in research will unite for crucial talks in November on the safe development and use of frontier AI technology, as the UK Government announces Bletchley Park as the location for the UK summit.

The major global event will take place on the 1st and 2nd November to consider the risks of AI, especially at the frontier of development, and discuss how they can be mitigated through internationally coordinated action. Frontier AI models hold enormous potential to power economic growth, drive scientific progress and wider public benefits, while also posing potential safety risks if not developed responsibly.

To be hosted at Bletchley Park in Buckinghamshire, a significant location in the history of computer science development and once the home of British Enigma codebreaking – it will see coordinated action to agree a set of rapid, targeted measures for furthering safety in global AI use.

Preparations for the summit are already in full flow, with Matt Clifford and Jonathan Black recently appointed as the Prime Minister’s Representatives. Together they’ll spearhead talks and negotiations, as they rally leading AI nations and experts over the next three months to ensure the summit provides a platform for countries to work together on further developing a shared approach to agree the safety measures needed to mitigate the risks of AI.

Prime Minister Rishi Sunak said:

“The UK has long been home to the transformative technologies of the future, so there is no better place to host the first ever global AI safety summit than at Bletchley Park this November.

To fully embrace the extraordinary opportunities of artificial intelligence, we must grip and tackle the risks to ensure it develops safely in the years ahead.

With the combined strength of our international partners, thriving AI industry and expert academic community, we can secure the rapid international action we need for the safe and responsible development of AI around the world.”

Technology Secretary Michelle Donelan said:

“International collaboration is the cornerstone of our approach to AI regulation, and we want the summit to result in leading nations and experts agreeing on a shared approach to its safe use.

The UK is consistently recognised as a world leader in AI and we are well placed to lead these discussions. The location of Bletchley Park as the backdrop will reaffirm our historic leadership in overseeing the development of new technologies.

AI is already improving lives from new innovations in healthcare to supporting efforts to tackle climate change, and November’s summit will make sure we can all realise the technology’s huge benefits safely and securely for decades to come.”

The summit will also build on ongoing work at international forums including the OECD, Global Partnership on AI, Council of Europe, and the UN and standards-development organisations, as well as the recently agreed G7 Hiroshima AI Process.

The UK boasts strong credentials as a world leader in AI. The technology employs over 50,000 people, directly supports one of the Prime Minister’s five priorities by contributing £3.7 billion to the economy, and is the birthplace of leading AI companies such as Google DeepMind. It has also invested more on AI safety research than any other nation, backing the creation of the Foundation Model Taskforce with an initial £100 million.

Foreign Secretary James Cleverly said:

“No country will be untouched by AI, and no country alone will solve the challenges posed by this technology. In our interconnected world, we must have an international approach.

The origins of modern AI can be traced back to Bletchley Park. Now, it will also be home to the global effort to shape the responsible use of AI.”

Bletchley Park’s role in hosting the summit reflects the UK’s proud tradition of being at the frontier of new technology advancements. Since Alan Turing’s celebrated work some eight decades ago, computing and computer science have become fundamental pillars of life both in the UK and across the globe.

Iain Standen, CEO of the Bletchley Park Trust, said:

“Bletchley Park Trust is immensely privileged to have been chosen as the venue for the first major international summit on AI safety this November, and we look forward to welcoming the world to our historic site.

It is fitting that the very spot where leading minds harnessed emerging technologies to influence the successful outcome of World War 2 will, once again, be the crucible for international co-ordinated action.

We are incredibly excited to be providing the stage for discussions on global safety standards, which will help everyone manage and monitor the risks of artificial intelligence.”

The roots of AI can be traced back to the leading minds who worked at Bletchley during World War 2, with codebreakers Jack Good and Donald Michie among those who went on to write extensive works on the technology. In November [2023], it will once again take centre stage as the international community comes together to agree on important guardrails which ensure the opportunities of AI can be realised, and its risks safely managed.

The announcement follows the UK government allocating £13 million to revolutionise healthcare research through AI, unveiled last week. The funding supports a raft of new projects including transformations to brain tumour surgeries, new approaches to treating chronic nerve pain, and a system to predict a patient’s risk of developing future health problems based on existing conditions.

Tom Gerken’s August 24, 2023 BBC news article (an analysis by Zoe Kleinman follows as part of the article) fills in a few blanks, Note: Links have been removed,

World leaders will meet with AI companies and experts on 1 and 2 November for the discussions.

The global talks aim to build an international consensus on the future of AI.

The summit will take place at Bletchley Park, where Alan Turing, one of the pioneers of modern computing, worked during World War Two.

It is unknown which world leaders will be invited to the event, with a particular question mark over whether the Chinese government or tech giant Baidu will be in attendance.

The BBC has approached the government for comment.

The summit will address how the technology can be safely developed through “internationally co-ordinated action” but there has been no confirmation of more detailed topics.

It comes after US tech firm Palantir rejected calls to pause the development of AI in June, with its boss Alex Karp saying it was only those with “no products” who wanted a pause.

And in July [2023], children’s charity the Internet Watch Foundation called on Mr Sunak to tackle AI-generated child sexual abuse imagery, which it says is on the rise.

Kleinman’s analysis includes this, Note: A link has been removed,

Will China be represented? Currently there is a distinct east/west divide in the AI world but several experts argue this is a tech that transcends geopolitics. Some say a UN-style regulator would be a better alternative to individual territories coming up with their own rules.

If the government can get enough of the right people around the table in early November [2023], this is perhaps a good subject for debate.

Three US AI giants – OpenAI, Anthropic and Palantir – have all committed to opening London headquarters.

But there are others going in the opposite direction – British DeepMind co-founder Mustafa Suleyman chose to locate his new AI company InflectionAI in California. He told the BBC the UK needed to cultivate a more risk-taking culture in order to truly become an AI superpower.

Many of those who worked at Bletchley Park decoding messages during WW2 went on to write and speak about AI in later years, including codebreakers Irving John “Jack” Good and Donald Michie.

Soon after the War, [Alan] Turing proposed the imitation game – later dubbed the “Turing test” – which seeks to identify whether a machine can behave in a way indistinguishable from a human.

There is a Bletchley Park website, which sells tickets for tours.

Insight into political jockeying (i.e., some juicy news bits)

This has recently been reported by BBC, from an October 17 (?). 2023 news article by Jessica Parker & Zoe Kleinman on BBC news online,

German Chancellor Olaf Scholz may turn down his invitation to a major UK summit on artificial intelligence, the BBC understands.

While no guest list has been published of an expected 100 participants, some within the sector say it’s unclear if the event will attract top leaders.

A government source insisted the summit is garnering “a lot of attention” at home and overseas.

The two-day meeting is due to bring together leading politicians as well as independent experts and senior execs from the tech giants, who are mainly US based.

The first day will bring together tech companies and academics for a discussion chaired by the Secretary of State for Science, Innovation and Technology, Michelle Donelan.

The second day is set to see a “small group” of people, including international government figures, in meetings run by PM Rishi Sunak.

Though no final decision has been made, it is now seen as unlikely that the German Chancellor will attend.

That could spark concerns of a “domino effect” with other world leaders, such as the French President Emmanuel Macron, also unconfirmed.

Government sources say there are heads of state who have signalled a clear intention to turn up, and the BBC understands that high-level representatives from many US-based tech giants are going.

The foreign secretary confirmed in September [2023] that a Chinese representative has been invited, despite controversy.

Some MPs within the UK’s ruling Conservative Party believe China should be cut out of the conference after a series of security rows.

It is not known whether there has been a response to the invitation.

China is home to a huge AI sector and has already created its own set of rules to govern responsible use of the tech within the country.

The US, a major player in the sector and the world’s largest economy, will be represented by Vice-President Kamala Harris.

Britain is hoping to position itself as a key broker as the world wrestles with the potential pitfalls and risks of AI.

However, Berlin is thought to want to avoid any messy overlap with G7 efforts, after the group of leading democratic countries agreed to create an international code of conduct.

Germany is also the biggest economy in the EU – which is itself aiming to finalise its own landmark AI Act by the end of this year.

It includes grading AI tools depending on how significant they are, so for example an email filter would be less tightly regulated than a medical diagnosis system.

The European Commission President Ursula von der Leyen is expected at next month’s summit, while it is possible Berlin could send a senior government figure such as its vice chancellor, Robert Habeck.

A source from the Department for Science, Innovation and Technology said: “This is the first time an international summit has focused on frontier AI risks and it is garnering a lot of attention at home and overseas.

“It is usual not to confirm senior attendance at major international events until nearer the time, for security reasons.”

Fascinating, eh?

Big Conversation Season (podcast) Finale on ‘AI and the Future of Humanity’ available on Friday, September 22, 2023

Three guys (all Brits) talking about this question “Robot Race: Could AI Ever Replace Humanity (part 1)” is part of a larger video podcast series known as the ‘Big Conversation’ and part 2 of this ‘Big Conversation’ is going to be available on Friday, September 22, 2023.

I haven’t listened to the entire first part of the conversation yet. So far, it seems quite engaging and provocative (especially the first five minutes). They’re not arguing but since I don’t want to spoil the surprise do watch the first bit (the first 5 mins. of a 53 mins. 38 secs. podcast).

You can’t ask more of a conversation than to be provoked into thinking. That said …

Pause

I’m a little hesitant to include much about faith and religion here but this two-part series touches on topics that have been discussed here many times. So, the ‘Big Conversation’ is produced through a Christian group. Here’s more about the podcast series and its producers from the Big Conversation webpage,

he Big Conversation is a video series from Premier Unbelievable? featuring world-class thinkers across the religious and non-religious communities. Exploring science, faith, philosophy and what it means to be human [emphasis mine]. The Big Conversation is produced by Premier in partnership with John Templeton Foundation.

Premier consists of Premier Christian Media Trust registered as a charity (no. 287610) and as a company limited by guarantee (no. 01743091) with two fully-owned trading subsidiaries: Premier Christian Communications Ltd (no. 02816074) and Christian Communication Partnership Ltd (no. 03422292). All three companies are registered in England & Wales with a registered office address of Unit 6 April Court, Syborn Way, Crowborough, TN6 3DZ.

I haven’t seen any signs of proselytizing and like almost every other website in existence, they are very interested in getting you to be on their newsletter email list, to donate, etc.

Back to the conversation.

The Robot Race, Parts I & 2: Could AI ever replace humanity?

Here’s a description of the Big Conversation series and two specific podcasts, from the September 20, 2023 press release (received via email),

Big Conversation Season Finale on AI and the Future of Humanity Available this Friday

Featuring AI expert Dr. Nigel Crook, episode explores ‘The Robot Race: Could AI ever replace humans?’

WHAT: 
Currently in its 5th season, The Big Conversation, hosted by comedian and apologist Andy Kind, features some of the biggest minds in the Christian, atheist and religious world to debate some of the biggest questions of science, faith, philosophy and what it means to be human. 

Episodes 5 & 6 of this season feature a two-part discussion about robotics, the future of artificial intelligence and the subsequent concerns of morality surrounding these advancements. This thought-provoking exchange on ethics in AI is sure to leave listeners informed and intrigued to learn more regarding the future of humanity relating to cyber-dependency, automation regulation, AI agency and abuses of power in technology.

WHO:  
To help us understand the complexities of AI, including the power and ethics around the subject – and appropriate concern for the future of humanity – The Big Conversation host Andy Kind spoke with AI Expert Dr. Nigel Crook and Neuroscientist Anil Seth.   

Dr. Nigel Crook, a distinguished figure recognized for his innovative contributions to the realm of AI and robotics, focuses extensively on research related to machine learning inspired by biological processes and the domain of social robotics. He serves as the Professor of Artificial Intelligence and Robotics at Oxford Brooks University and is the Founding Director at the Institute for Ethical AI, specifically revolving around the concept of self-governing ethical robots.

WHEN:  
Episode 5, the first in the two-part AI series, released September 8 [2023], and episode 6 releases Friday, Sept. 22 [2023].  

WHERE:  
These episodes are available at https://www.thebigconversation.show/ as well as all major podcast platforms.  

I have a little more about Anil Seth from the Big Conversation Episode 5 webpage,

… Anil Seth, Professor of Cognitive & Computational Neuroscience at the University of Sussex, winner of The Michael Faraday Prize and Lecture 2023, and author of “Being You: A New Science of Consciousness”

There’s also a bit about Seth in my June 30, 2017 posting “A question of consciousness: Facebotlish (a new language); a July 5, 2017 rap guide performance in Vancouver, Canada; Tom Stoppard’s play; and a little more,” scroll down to the subhead titled ‘Vancouver premiere of Baba Brinkman’s Rap Guide to Consciousness’.

Ethical nanobiotechnology

This paper on ethics (aside: I have a few comments after the news release and citation) comes from the US Pacific Northwest National Laboratory (PNNL) according to a July 12, 2023 news item on phys.org,

Prosthetics moved by thoughts. Targeted treatments for aggressive brain cancer. Soldiers with enhanced vision or bionic ears. These powerful technologies sound like science fiction, but they’re becoming possible thanks to nanoparticles.

“In medicine and other biological settings, nanotechnology is amazing and helpful, but it could be harmful if used improperly,” said Pacific Northwest National Laboratory (PNNL) chemist Ashley Bradley, part of a team of researchers who conducted a comprehensive survey of nanobiotechnology applications and policies.

Their research, available in Health Security, works to sum up the very large, active field of nanotechnology in biology applications, draw attention to regulatory gaps, and offer areas for further consideration.

A July 12, 2023 PNNL news release (also on EurekAlert), which originated the news item, delves further into the topic, Note: A link has been removed,

“In our research, we learned there aren’t many global regulations yet,” said Bradley. “And we need to create a common set of rules to figure out the ethical boundaries.”

Nanoparticles, big differences

Nanoparticles are clusters of molecules with different properties than large amounts of the same substances. In medicine and other biology applications, these properties allow nanoparticles to act as the packaging that delivers treatments through cell walls and the difficult to cross blood-brain barrier.

“You can think of the nanoparticles a little bit like the plastic around shredded cheese,” said PNNL chemist Kristin Omberg. “It makes it possible to get something perishable directly where you want it, but afterwards you’ve got to deal with a whole lot of substance where it wasn’t before.”

Unfortunately, dealing with nanoparticles in new places isn’t straightforward. Carbon is pencil lead, nano carbon conducts electricity. The same material may have different properties at the nanoscale, but most countries still regulate it the same as bulk material, if the material is regulated at all.

For example, zinc oxide, a material that was stable and unreactive as a pigment in white paint, is now accumulating in oceans when used as nanoparticles in sunscreen, warranting a call to create alternative reef-safe sunscreens. And although fats and lipids aren’t regulated, the researchers suggest which agencies could weigh in on regulations were fats to become after-treatment byproducts.

The article also inventories national and international agencies, organizations, and governing bodies with an interest in understanding how nanoparticles break down or react in a living organism and the environmental life cycle of a nanoparticle. Because nanobiotechnology spans materials science, biology, medicine, environmental science, and tech, these disparate research and regulatory disciplines must come together, often for the first time—to fully understand the impact on humans and the environment.

Dual use: Good for us, bad for us

Like other quickly growing fields, there’s a time lag between the promise of new advances and the possibilities of unintended uses.

“There were so many more applications than we thought there were,” said Bradley, who collected exciting nanobio examples such as Alzheimer’s treatment, permanent contact lenses, organ replacement, and enhanced muscle recovery, among others.

The article also highlights concerns about crossing the blood-brain barrier, thought-initiated control of computers, and nano-enabled DNA editing where the researchers suggest more caution, questioning, and attention could be warranted. This attention spans everything from deep fundamental research and regulations all the way to what Omberg called “the equivalent of tattoo removal” if home-DNA splicing attempts go south.

The researchers draw parallels to more established fields such as synthetic bio and pharmacology, which offer lessons to be learned from current concerns such as the unintended consequences of fentanyl and opioids. They believe these fields also offer examples of innovative coordination between science and ethics, such as synthetic bio’s IGEM [The International Genetically Engineered Machine competition]—student competition, to think about not just how to create, but also to shape the use and control of new technologies.

Omberg said unusually enthusiastic early reviewers of the article contributed even more potential uses and concerns, demonstrating that experts in many fields recognize ethical nanobiotechnology is an issue to get in front of. “This is a train that’s going. It will be sad if 10 years from now, we haven’t figured how to talk about it.”

Funding for the team’s research was supported by PNNL’s Biorisk Beyond the List National Security Directorate Objective.

Here’s a link to and a citation for the paper,

The Promise of Emergent Nanobiotechnologies for In Vivo Applications and Implications for Safety and Security by Anne M. Arnold, Ashley M. Bradley, Karen L. Taylor, Zachary C. Kennedy, and Kristin M. Omberg. Health Security.Oct 2022.408-423.Published in Volume: 20 Issue 5: October 17, 2022 DOI: https://doi.org/10.1089/hs.2022.0014 Published Online:17 Oct 2022

This paper is open access.

You can find out more about IGEM (The International Genetically Engineered Machine competition) here.

Comments (brief)

It seems a little odd that the news release (“Prosthetics moved by thoughts …”) and the paper both reference neurotechnology without ever mentioning it by name. Here’s the reference from the paper, Note: Links have been removed,

Nanoparticles May Be Developed to Facilitate Cognitive Enhancements

The development and implementation of NPs that enhance cognitive function has yet to be realized. However, recent advances on the micro- and macro-level with neural–machine interfacing provide the building blocks necessary to develop this technology on the nanoscale. A noninvasive brain–computer interface to control a robotic arm was developed by teams at 2 universities.157 A US-based company, Neuralink, [emphasis mine] is at the forefront of implementing implantable, intracortical microelectrodes that provide an interface between the human brain and technology.158,159 Utilization of intracortical microelectrodes may ultimately provide thought-initiated access and control of computers and mobile devices, and possibly expand cognitive function by accessing underutilized areas of the brain.158

Neuralink (founded by Elon Musk) is controversial for its animal testing practices. You can find out more in Björn Ólafsson’s May 30, 2023 article for Sentient Media.

The focus on nanoparticles as the key factor in the various technologies and applications mentioned seems narrow but necessary given the breadth of topics covered in the paper as the authors themselves note in the paper’s abstract,

… In this article, while not comprehensive, we attempt to illustrate the breadth and promise of bionanotechnology developments, and how they may present future safety and security challenges. Specifically, we address current advancements to streamline the development of engineered NPs for in vivo applications and provide discussion on nano–bio interactions, NP in vivo delivery, nanoenhancement of human performance, nanomedicine, and the impacts of NPs on human health and the environment.

They have a good overview of the history and discussions about nanotechnology risks and regulation. It’s international in scope with a heavy emphasis on US efforts, as one would expect.

For anyone who’s interested in the neurotechnology end of things, I’ve got a July 17, 2023 commentary “Unveiling the Neurotechnology Landscape: Scientific Advancements, Innovations and Major Trends—a UNESCO report.” The report was launched July 13, 2023 during UNESCO’s Global dialogue on the ethics of neurotechnology (see my July 7, 2023 posting about the then upcoming dialogue for links to more UNESCO information). Both the July 17 and July 7, 2023 postings included additional information about Neuralink.

Systems biology and nanoinformatics

A May 29, 2023 news item on Nanowerk announces research from an international research team focused on a new nanoinformatics approach, Note: Links have been removed,

Researchers have discovered a new response mechanism specific to exposure to nanoparticles that is common to multiple species. By analysing a large collection of datasets concerning the molecular response to nanomaterials, they have revealed an ancestral epigenetic mechanism of defence that explains how different species, from humans to simpler creatures, adapt to this type of exposure.

The project was led by Doctoral Researcher Giusy del Giudice and Professor Dario Greco at the Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere University, Finland, in collaboration with an interdisciplinary team from Finland, Ireland, Poland, UK, Cyprus, South Africa, Greece and Estonia [emphasis mine] – including Associate Professor Vladimir Lobaskin from UCD School of Physics, University College Dublin, Ireland.

A May 29, 2023 University College Dublin (UCD) press release, which originated the news item, delves further into the research, Note: Links have been removed,

Director of FHAIVE, Professor Greco said: “We have demonstrated for the first time that there is a specific response to nanoparticles, and it is interlinked to their nano-properties. This study sheds light on how various species respond to particulate matters in a similar manner. It proposes a solution to the one-chemical-one-signature problem, currently limiting the use of toxicogenomic [sic] in chemical safety assessment.”

Systems Biology meets Nanoinformatics

Associate Professor Vladimir Lobaskin, who is an expert in nanostructured biosystems, said: “In this major collaborative work, the team led by the University of Tampere and including UCD School of Physics not only discovered common responses to nanoparticles across all kinds of organisms from plants and invertebrates to humans but also common features of nanomaterials triggering those responses.”

He said: “Tens of thousands of novel nanomaterials reach the consumer market annually. It is an enormous task to screen them all for possible adverse effects to protect the environment and human health. It could be damage to the lung when we inhale dust, a release of toxic ions by dust particles, production of reactive oxygen species, or binding of the cell membrane lipids by nanoparticles. In other words, it all starts with relatively simple physical interactions at the surface of the nanoparticles that are usually not known to biologists and toxicologists but needed to understand what we should fear when exposed to nanomaterials.”

In the past decade, OECD [Organisation for Economic Cooperation and Development] countries have adopted a mechanism-aware toxicity assessment strategy based on the Adverse Outcome Pathway analysis establishing causal relationships between biological events leading to a disease or negative effect on the population. Once the Adverse Outcome Pathway is determined, one can trace the chain of biological events back to the origin – the molecular initiating event that triggered the cascade.

Attempts of statistical analysis of the toxicology data of recent years have not succeeded in identifying the nanomaterial properties responsible for the adverse outcomes. The problem is that the material characteristics typically provided by the producers, such as nanoparticle chemistry and size distribution, are too basic and insufficient to make sensible predictions of their biological activity.

An earlier work, co-authored by the UCD School of Physics team, suggested the collection of advanced descriptors of nanomaterials, using computational materials science if necessary, to understand the interactions of nanoparticles with biological molecules and tissues and enable the prediction of the molecular initiating events. These advanced descriptors can provide the missing bits of information and include the materials’ dissolution rates, the polarity of the surface atoms, molecular interaction energies, shape, aspect ratios, indicators of hydrophobicity, amino acid or lipid binding energy – as well as anything that may cause disruption of the normal cell or tissue functions.

Associate Professor Lobaskin and colleagues at UCD Soft Matter Modelling Lab have been working on in silico materials’ characterisation and evaluated the descriptors that correlate with the hazardous potential of nanoparticles.

He said: “In the analysis presented in this latest Nature Nanotechnology paper, we for the first time were able to see what is in common between different materials associated with the health risks at the molecular level. This publication is the first demonstration of the power of nanoinformatics, a new field of research extending the ideas from cheminformatics and bioinformatics, and also a big promise: using digital twins of materials created on a computer will soon enable us to screen and optimise novel materials for safety and functionality even before they are produced to make them safe and sustainable by design.”

Here’s a link to and a citation for the paper,

An ancestral molecular response to nanomaterial particulates by G. del Giudice, A. Serra, L. A. Saarimäki, K. Kotsis, I. Rouse, S. A. Colibaba, K. Jagiello, A. Mikolajczyk, M. Fratello, A. G. Papadiamantis, N. Sanabria, M. E. Annala, J. Morikka, P. A. S. Kinaret, E. Voyiatzis, G. Melagraki, A. Afantitis, K. Tämm, T. Puzyn, M. Gulumian, V. Lobaskin, I. Lynch, A. Federico & D. Greco. Nature Nanotechnology (2023) DOI: https://doi.org/10.1038/s41565-023-01393-4 Published: 08 May 2023

This paper is open access.

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

Launched on Thursday, July 13, 2023 during UNESCO’s (United Nations Educational, Scientific, and Cultural Organization) “Global dialogue on the ethics of neurotechnology,” is a report tying together the usual measures of national scientific supremacy (number of papers published and number of patents filed) with information on corporate investment in the field. Consequently, “Unveiling the Neurotechnology Landscape: Scientific Advancements, Innovations and Major Trends” by Daniel S. Hain, Roman Jurowetzki, Mariagrazia Squicciarini, and Lihui Xu provides better insight into the international neurotechnology scene than is sometimes found in these kinds of reports. By the way, the report is open access.

Here’s what I mean, from the report‘s short summary,

Since 2013, government investments in this field have exceeded $6 billion. Private investment has also seen significant growth, with annual funding experiencing a 22-fold increase from 2010 to 2020, reaching $7.3 billion and totaling $33.2 billion.

This investment has translated into a 35-fold growth in neuroscience publications between 2000-2021 and 20-fold growth in innovations between 2022-2020, as proxied by patents. However, not all are poised to benefit from such developments, as big divides emerge.

Over 80% of high-impact neuroscience publications are produced by only ten countries, while 70% of countries contributed fewer than 10 such papers over the period considered. Similarly, five countries only hold 87% of IP5 neurotech patents.

This report sheds light on the neurotechnology ecosystem, that is, what is being developed, where and by whom, and informs about how neurotechnology interacts with other technological trajectories, especially Artificial Intelligence [emphasis mine]. [p. 2]

The money aspect is eye-opening even when you already have your suspicions. Also, it’s not entirely unexpected to learn that only ten countries produce over 80% of the high impact neurotech papers and that only five countries hold 87% of the IP5 neurotech patents but it is stunning to see it in context. (If you’re not familiar with the term ‘IP5 patents’, scroll down in this post to the relevant subhead. Hint: It means the patent was filed in one of the top five jurisdictions; I’ll leave you to guess which ones those might be.)

“Since 2013 …” isn’t quite as informative as the authors may have hoped. I wish they had given a time frame for government investments similar to what they did for corporate investments (e.g., 2010 – 2020). Also, is the $6B (likely in USD) government investment cumulative or an estimated annual number? To sum up, I would have appreciated parallel structure and specificity.

Nitpicks aside, there’s some very good material intended for policy makers. On that note, some of the analysis is beyond me. I haven’t used anything even somewhat close to their analytical tools in years and years. This commentaries reflects my interests and a very rapid reading. One last thing, this is being written from a Canadian perspective. With those caveats in mind, here’s some of what I found.

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.