Tag Archives: University of Washington (state)

Say ain’t so! van Gogh’s ‘The Starry Night’ is not a masterpiece when it comes to flow physics according to researchers

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Researchers at Virginia Commonwealth University (VCU; US) have challenged the findings in recent research that was highlighted here in a December 16, 2024 posting “van Gogh’s sky is alive with real-world physics.”

An April 1, 2025 news item (not an April Fool’s joke) on phys.org announces a conclusion that contradicts the original findings,

The Dutch master Vincent van Gogh may have painted one of Western history’s most enduring works, but “The Starry Night” is not a masterpiece of flow physics—despite recent attention to its captivating swirls, according to researchers from Virginia Commonwealth University and the University of Washington [state not district].

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Credit: Pixabay/CC0 Public Domain [downloaded from https://phys.org/news/2025-04-vincent-van-gogh-starry-night.html].

An April 1, 2025 Virginia Commonwealth University (VCU) news release (also on EurekAlert) by Leila Ugincius, which originated the news item, goes on to further refute the claim about Starry Night and flow physics, Note: Links have been removed,

The post-Impressionist artist painted the work (often referred to simply as “Starry Night”) in June 1889, and its depiction of a pre-sunrise sky and village was inspired in part by the view from van Gogh’s asylum room in southern France. The painting is part of the permanent collection of the Museum of Modern Art in New York City.

Last year, a paper published in the September issue of Physics of Fluids – “Hidden Turbulence in van Gogh’s ‘The Starry Night’” – received considerable notice by positing that the eddies, or swirls, painted by van Gogh adhere to Kolmogorov’s theory of turbulent flow, which explains how air and water swirls move in a somewhat chaotic pattern. “[van Gogh] was able to reproduce not only the size of whirls/eddies, but also their relative distance and intensity in his painting,” the paper read.

However, those conclusions are unfounded, according to Mohamed Gad-el-Hak, Ph.D., the Inez Caudill Eminent Professor in VCU’s Department of Mechanical and Nuclear Engineering, and James J. Riley, Ph.D., the inaugural Paccar Professor of Mechanical Engineering at the University of Washington. Their report –  “Is There Hidden Turbulence in Vincent van Gogh’s ‘The Starry Night’?” – appears in the latest issue of Journal of Turbulence.

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

Is there hidden turbulence in Vincent van Gogh’s The Starry Night? by James J. Riley
& Mohamed Gad-el-Hak. Journal of Turbulence Pages 1–2. DOI: https://doi.org/10.1080/14685248.2025.2477244 Published online: 18 Mar 2025

This paper is behind a paywall.

AI and the 2024 Nobel prizes

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Artificial intelligence made a splash when the 2024 Nobel Prize announcements were made as they were a key factor in both the prizes for physics and for chemistry.

Where do physics, chemistry, and AI go from here?

I have a few speculative pieces about physics, chemistry, and AI. First off we have Nello Cristianini’s (Professor of Artificial Intelligence at the University of Bath (England) October 10, 2024 essay for The Conversation, Note: Links have been removed,

The 2024 Nobel Prizes in physics and chemistry have given us a glimpse of the future of science. Artificial intelligence (AI) was central to the discoveries honoured by both awards. You have to wonder what Alfred Nobel, who founded the prizes, would think of it all.

We are certain to see many more Nobel medals handed to researchers who made use of AI tools. As this happens, we may find the scientific methods honoured by the Nobel committee depart from straightforward categories like “physics”, “chemistry” and “physiology or medicine”.

We may also see the scientific backgrounds of recipients retain a looser connection with these categories. This year’s physics prize was awarded to the American John Hopfield, at Princeton University, and British-born Geoffrey Hinton, from the University of Toronto. While Hopfield is a physicist, Hinton studied experimental psychology before gravitating to AI.

The chemistry prize was shared between biochemist David Baker, from the University of Washington, and the computer scientists Demis Hassabis and John Jumper, who are both at Google DeepMind in the UK.

There is a close connection between the AI-based advances honoured in the physics and chemistry categories. Hinton helped develop an approach used by DeepMind to make its breakthrough in predicting the shapes of proteins.

The physics laureates, Hinton in particular, laid the foundations of the powerful field known as machine learning. This is a subset of AI that’s concerned with algorithms, sets of rules for performing specific computational tasks.

Hopfield’s work is not particularly in use today, but the backpropagation algorithm (co-invented by Hinton) has had a tremendous impact on many different sciences and technologies. This is concerned with neural networks, a model of computing that mimics the human brain’s structure and function to process data. Backpropagation allows scientists to “train” enormous neural networks. While the Nobel committee did its best to connect this influential algorithm to physics, it’s fair to say that the link is not a direct one.

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Every two years, since 1994, scientists have been holding a contest to find the best ways to predict protein structures and shapes from the sequences of their amino acids. The competition is called Critical Assessment of Structure Prediction (CASP).

For the past few contests, CASP winners have used some version of DeepMind’s AlphaFold. There is, therefore, a direct line to be drawn from Hinton’s backpropagation to Google DeepMind’s AlphaFold 2 breakthrough.

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Attributing credit has always been controversial aspect of the Nobel prizes. A maximum of three researchers can share a Nobel. But big advances in science are collaborative. Scientific papers may have 10, 20, 30 authors or more. More than one team might contribute to the discoveries honoured by the Nobel committee.

This year we may have further discussions about the attribution of the research on backpropagation algorithm, which has been claimed by various researchers, as well as for the general attribution of a discovery to a field like physics.

We now have a new dimension to the attribution problem. It’s increasingly unclear whether we will always be able to distinguish between the contributions of human scientists and those of their artificial collaborators – the AI tools that are already helping push forward the boundaries of our knowledge.

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This November 26, 2024 news item on ScienceDaily, which is a little repetitive, considers interdisciplinarity in relation to the 2024 Nobel prizes,

In 2024, the Nobel Prize in physics was awarded to John Hopfield and Geoffrey Hinton for their foundational work in artificial intelligence (AI), and the Nobel Prize in chemistry went to David Baker, Demis Hassabis, and John Jumper for using AI to solve the protein-folding problem, a 50-year grand challenge problem in science.

A new article, written by researchers at Carnegie Mellon University and Calculation Consulting, examines the convergence of physics, chemistry, and AI, highlighted by recent Nobel Prizes. It traces the historical development of neural networks, emphasizing the role of interdisciplinary research in advancing AI. The authors advocate for nurturing AI-enabled polymaths to bridge the gap between theoretical advancements and practical applications, driving progress toward artificial general intelligence. The article is published in Patterns.

“With AI being recognized in connections to both physics and chemistry, practitioners of machine learning may wonder how these sciences relate to AI and how these awards might influence their work,” explained Ganesh Mani, Professor of Innovation Practice and Director of Collaborative AI at Carnegie Mellon’s Tepper School of Business, who coauthored the article. “As we move forward, it is crucial to recognize the convergence of different approaches in shaping modern AI systems based on generative AI.”

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A November 25, 2024 Carnegie Mellon University (CMU) news release, which originated the news item, describes the paper,

In their article, the authors explore the historical development of neural networks. By examining the history of AI development, they contend, we can understand more thoroughly the connections among computer science, theoretical chemistry, theoretical physics, and applied mathematics. The historical perspective illuminates how foundational discoveries and inventions across these disciplines have enabled modern machine learning with artificial neural networks. 

Then they turn to key breakthroughs and challenges in this field, starting with Hopfield’s work, and go on to explain how engineering has at times preceded scientific understanding, as is the case with the work of Jumper and Hassabis.

The authors conclude with a call to action, suggesting that the rapid progress of AI across diverse sectors presents both unprecedented opportunities and significant challenges. To bridge the gap between hype and tangible development, they say, a new generation of interdisciplinary thinkers must be cultivated.

These “modern-day Leonardo da Vincis,” as the authors call them, will be crucial in developing practical learning theories that can be applied immediately by engineers, propelling the field toward the ambitious goal of artificial general intelligence.

This calls for a paradigm shift in how scientific inquiry and problem solving are approached, say the authors, one that embraces holistic, cross-disciplinary collaboration and learns from nature to understand nature. By breaking down silos between fields and fostering a culture of intellectual curiosity that spans multiple domains, innovative solutions can be identified to complex global challenges like climate change. Through this synthesis of diverse knowledge and perspectives, catalyzed by AI, meaningful progress can be made and the field can realize the full potential of technological aspirations.

“This interdisciplinary approach is not just beneficial but essential for addressing the many complex challenges that lie ahead,” suggests Charles Martin, Principal Consultant at Calculation Consulting, who coauthored the article. “We need to harness the momentum of current advancements while remaining grounded in practical realities.”

The authors acknowledge the contributions of Scott E. Fahlman, Professor Emeritus in Carnegie Mellon’s School of Computer Science.

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

The recent Physics and Chemistry Nobel Prizes, AI, and the convergence of knowledge fields by Charles H. Martin, Ganesh Mani. Patterns, 2024 DOI: 10.1016/j.patter.2024.101099 Published online November 25, 2024 Copyright: © 2024 The Author(s). Published by Elsevier Inc.

This paper is open access under Creative Commons Attribution (CC BY 4.0.

A scientific enthusiast: “I was a beta tester for the Nobel prize-winning AlphaFold AI”

From an October 11, 2024 essay by Rivka Isaacson (Professor of Molecular Biophysics, King’s College London) for The Conversation, Note: Links have been removed,

The deep learning machine AlphaFold, which was created by Google’s AI research lab DeepMind, is already transforming our understanding of the molecular biology that underpins health and disease.

One half of the 2024 Nobel prize in chemistry went to David Baker from the University of Washington in the US, with the other half jointly awarded to Demis Hassabis and John M. Jumper, both from London-based Google DeepMind.

If you haven’t heard of AlphaFold, it may be difficult to appreciate how important it is becoming to researchers. But as a beta tester for the software, I got to see first-hand how this technology can reveal the molecular structures of different proteins in minutes. It would take researchers months or even years to unpick these structures in laboratory experiments.

This technology could pave the way for revolutionary new treatments and drugs. But first, it’s important to understand what AlphaFold does.

Proteins are produced by series of molecular “beads”, created from a selection of the human body’s 20 different amino acids. These beads form a long chain that folds up into a mechanical shape that is crucial for the protein’s function.

Their sequence is determined by DNA. And while DNA research means we know the order of the beads that build most proteins, it’s always been a challenge to predict how the chain folds up into each “3D machine”.

These protein structures underpin all of biology. Scientists study them in the same way you might take a clock apart to understand how it works. Comprehend the parts and put together the whole: it’s the same with the human body.

Proteins are tiny, with a huge number located inside each of our 30 trillion cells. This meant for decades, the only way to find out their shape was through laborious experimental methods – studies that could take years.

Throughout my career I, along with many other scientists, have been engaged in such pursuits. Every time we solve a protein structure, we deposit it in a global database called the Protein Data Bank, which is free for anyone to use.

AlphaFold was trained on these structures, the majority of which were found using X-ray crystallography. For this technique, proteins are tested under thousands of different chemical states, with variations in temperature, density and pH. Researchers use a microscope to identify the conditions under which each protein lines up in a particular formation. These are then shot with X-rays to work out the spatial arrangement of all the atoms in that protein.

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Addictive experience

In March 2024, researchers at DeepMind approached me to beta test AlphaFold3, the latest incarnation of the software, which was close to release at the time.

I’ve never been a gamer but I got a taste of the addictive experience as, once I got access, all I wanted to do was spend hours trying out molecular combinations. As well as lightning speed, this new version introduced the option to include bigger and more varied molecules, including DNA and metals, and the opportunity to modify amino acids to mimic chemical signalling in cells.

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Understanding the moving parts and dynamics of proteins is the next frontier, now that we can predict static protein shapes with AlphaFold. Proteins come in a huge variety of shapes and sizes. They can be rigid or flexible, or made of neatly structured units connected by bendy loops.

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You can read Isaacson’s entire October 11, 2024 essay on The Conversation or in an October 14, 2024 news item on phys.org.

Biobots (also known as biohybrid robots) occupy a third state between life and death?

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I got a bit of a jolt from this September 12, 2024 essay by Peter A Noble, affiliate professor of microbiology at the University of Washington, and Alex Pozhitkov, senior technical lead of bioinformatics, Irell & Manella Graduate School of Biological Sciences at City of Hope, for The Conversation (h/t Sept. 12, 2024 item on phys.org), Note: Links have been removed,

Life and death are traditionally viewed as opposites. But the emergence of new multicellular life-forms from the cells of a dead organism introduces a “third state” that lies beyond the traditional boundaries of life and death.

Usually, scientists consider death to be the irreversible halt of functioning of an organism as a whole. However, practices such as organ donation highlight how organs, tissues and cells can continue to function even after an organism’s demise. This resilience raises the question: What mechanisms allow certain cells to keep working after an organism has died?

We are researchers who investigate what happens within organisms after they die. In our recently published review, we describe how certain cells – when provided with nutrients, oxygen, bioelectricity or biochemical cues – have the capacity to transform into multicellular organisms with new functions after death.

Life, death and emergence of something new

The third state challenges how scientists typically understand cell behavior. While caterpillars metamorphosing into butterflies, or tadpoles evolving into frogs, may be familiar developmental transformations, there are few instances where organisms change in ways that are not predetermined. Tumors, organoids and cell lines that can indefinitely divide in a petri dish, like HeLa cells [cervical cancer cells taken from Henrietta Lacks without her knowledge], are not considered part of the third state because they do not develop new functions.

However, researchers found that skin cells extracted from deceased frog embryos were able to adapt to the new conditions of a petri dish in a lab, spontaneously reorganizing into multicellular organisms called xenobots [emphasis mine]. These organisms exhibited behaviors that extend far beyond their original biological roles. Specifically, these xenobots use their cilia – small, hair-like structures – to navigate and move through their surroundings, whereas in a living frog embryo, cilia are typically used to move mucus.

Xenobots are also able to perform kinematic self-replication, meaning they can physically replicate their structure and function without growing. This differs from more common replication processes that involve growth within or on the organism’s body.

Researchers have also found that solitary human lung cells can self-assemble into miniature multicellular organisms that can move around. These anthrobots [emphasis mine] behave and are structured in new ways. They are not only able to navigate their surroundings but also repair both themselves and injured neuron cells placed nearby.

Taken together, these findings demonstrate the inherent plasticity of cellular systems and challenge the idea that cells and organisms can evolve only in predetermined ways. The third state suggests that organismal death may play a significant role in how life transforms over time.

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I had not realized that xenobots are derived from dead frog embryos something I missed when mentioning or featuring them in previous stories, the latest in a September 13, 2024 posting, which also mentions anthrobots. Previous stories were published in a June 21, 2021 posting about xenobots 2.0 and their ability to move and a June 8, 2022 posting about their ability to reproduce. Thank you to the authors for relieving me of some of my ignorance.

For some reason I was expecting mention, brief or otherwise, of ethical or social implications but the authors offered this instead, from their September 12, 2024 essay, Note: Links have been removed,

Implications for biology and medicine

The third state not only offers new insights into the adaptability of cells. It also offers prospects for new treatments.

For example, anthrobots could be sourced from an individual’s living tissue to deliver drugs without triggering an unwanted immune response. Engineered anthrobots injected into the body could potentially dissolve arterial plaque in atherosclerosis patients and remove excess mucus in cystic fibrosis patients.

Importantly, these multicellular organisms have a finite life span, naturally degrading after four to six weeks. This “kill switch” prevents the growth of potentially invasive cells.

A better understanding of how some cells continue to function and metamorphose into multicellular entities some time after an organism’s demise holds promise for advancing personalized and preventive medicine.

I look forward to hearing about the third state and about any ethical or social issues that may arise from it.

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

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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.

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Reveley’s January 18, 2024 article provides fascinating context and is well worth reading if you have the time.

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

… as these and other advances propelled the field forward, and as his own research revealed the discomfiting vulnerability of the brain to external manipulation, Yuste found himself increasingly concerned by the scarce attention being paid to the ethics of these technologies. Even Obama’s multi-billion-dollar BRAIN Initiative, a government program designed to advance brain research, which Yuste had helped launch in 2013 and supported heartily, seemed to mostly ignore the ethical and societal consequences of the research it funded. “There was zero effort on the ethical side,” Yuste recalled.

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Yuste was appointed to the rotating advisory group of the BRAIN Initiative in 2015, where he began to voice his concerns. That fall, he joined an informal working group to consider the issue. “We started to meet, and it became very evident to me that the situation was a complete disaster,” Yuste said. “There was no guidelines, no work done.” Yuste said he tried to get the group to generate a set of ethical guidelines for novel BCI technologies, but the effort soon became bogged down in bureaucracy. Frustrated, he stepped down from the committee and, together with a University of Washington bioethicist named Sara Goering, decided to independently pursue the issue. “Our aim here is not to contribute to or feed fear for doomsday scenarios,” the pair wrote in a 2016 article in Cell, “but to ensure that we are reflective and intentional as we prepare ourselves for the neurotechnological future.”

In the fall of 2017, Yuste and Goering called a meeting at the Morningside Campus of Columbia, inviting nearly 30 experts from all over the world in such fields as neurotechnology, artificial intelligence, medical ethics, and the law. By then, several other countries had launched their own versions of the BRAIN Initiative, and representatives from Australia, Canada [emphasis mine], China, Europe, Israel, South Korea, and Japan joined the Morningside gathering, along with veteran neuroethicists and prominent researchers. “We holed ourselves up for three days to study the ethical and societal consequences of neurotechnology,” Yuste said. “And we came to the conclusion that this is a human rights issue. These methods are going to be so powerful, that enable to access and manipulate mental activity, and they have to be regulated from the angle of human rights. That’s when we coined the term ‘neurorights.’”

The Morningside group, as it became known, identified four principal ethical priorities, which were later expanded by Yuste into five clearly defined neurorights: The right to mental privacy, which would ensure that brain data would be kept private and its use, sale, and commercial transfer would be strictly regulated; the right to personal identity, which would set boundaries on technologies that could disrupt one’s sense of self; the right to fair access to mental augmentation, which would ensure equality of access to mental enhancement neurotechnologies; the right of protection from bias in the development of neurotechnology algorithms; and the right to free will, which would protect an individual’s agency from manipulation by external neurotechnologies. The group published their findings in an often-cited paper in Nature.

But while Yuste and the others were focused on the ethical implications of these emerging technologies, the technologies themselves continued to barrel ahead at a feverish speed. In 2014, the first kick of the World Cup was made by a paraplegic man using a mind-controlled robotic exoskeleton. In 2016, a man fist bumped Obama using a robotic arm that allowed him to “feel” the gesture. The following year, scientists showed that electrical stimulation of the hippocampus could improve memory, paving the way for cognitive augmentation technologies. The military, long interested in BCI technologies, built a system that allowed operators to pilot three drones simultaneously, partially with their minds. Meanwhile, a confusing maelstrom of science, science-fiction, hype, innovation, and speculation swept the private sector. By 2020, over $33 billion had been invested in hundreds of neurotech companies — about seven times what the NIH [US National Institutes of Health] had envisioned for the 12-year span of the BRAIN Initiative itself.

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Now back to Tang and Huth (from Reveley’s January 18, 2024 article), Note: Links have been removed,

Central to the ethical questions Huth and Tang grappled with was the fact that their decoder, unlike other language decoders developed around the same time, was non-invasive — it didn’t require its users to undergo surgery. Because of that, their technology was free from the strict regulatory oversight that governs the medical domain. (Yuste, for his part, said he believes non-invasive BCIs pose a far greater ethical challenge than invasive systems: “The non-invasive, the commercial, that’s where the battle is going to get fought.”) Huth and Tang’s decoder faced other hurdles to widespread use — namely that fMRI machines are enormous, expensive, and stationary. But perhaps, the researchers thought, there was a way to overcome that hurdle too.

The information measured by fMRI machines — blood oxygenation levels, which indicate where blood is flowing in the brain — can also be measured with another technology, functional Near-Infrared Spectroscopy, or fNIRS. Although lower resolution than fMRI, several expensive, research-grade, wearable fNIRS headsets do approach the resolution required to work with Huth and Tang’s decoder. In fact, the scientists were able to test whether their decoder would work with such devices by simply blurring their fMRI data to simulate the resolution of research-grade fNIRS. The decoded result “doesn’t get that much worse,” Huth said.

And while such research-grade devices are currently cost-prohibitive for the average consumer, more rudimentary fNIRS headsets have already hit the market. Although these devices provide far lower resolution than would be required for Huth and Tang’s decoder to work effectively, the technology is continually improving, and Huth believes it is likely that an affordable, wearable fNIRS device will someday provide high enough resolution to be used with the decoder. In fact, he is currently teaming up with scientists at Washington University to research the development of such a device.

Even comparatively primitive BCI headsets can raise pointed ethical questions when released to the public. Devices that rely on electroencephalography, or EEG, a commonplace method of measuring brain activity by detecting electrical signals, have now become widely available — and in some cases have raised alarm. In 2019, a school in Jinhua, China, drew criticism after trialing EEG headbands that monitored the concentration levels of its pupils. (The students were encouraged to compete to see who concentrated most effectively, and reports were sent to their parents.) Similarly, in 2018 the South China Morning Post reported that dozens of factories and businesses had begun using “brain surveillance devices” to monitor workers’ emotions, in the hopes of increasing productivity and improving safety. The devices “caused some discomfort and resistance in the beginning,” Jin Jia, then a brain scientist at Ningbo University, told the reporter. “After a while, they got used to the device.”

But the primary problem with even low-resolution devices is that scientists are only just beginning to understand how information is actually encoded in brain data. In the future, powerful new decoding algorithms could discover that even raw, low-resolution EEG data contains a wealth of information about a person’s mental state at the time of collection. Consequently, nobody can definitively know what they are giving away when they allow companies to collect information from their brains.

Huth and Tang concluded that brain data, therefore, should be closely guarded, especially in the realm of consumer products. In an article on Medium from last April, Tang wrote that “decoding technology is continually improving, and the information that could be decoded from a brain scan a year from now may be very different from what can be decoded today. It is crucial that companies are transparent about what they intend to do with brain data and take measures to ensure that brain data is carefully protected.” (Yuste said the Neurorights Foundation recently surveyed the user agreements of 30 neurotech companies and found that all of them claim ownership of users’ brain data — and most assert the right to sell that data to third parties. [emphases mine]) Despite these concerns, however, Huth and Tang maintained that the potential benefits of these technologies outweighed their risks, provided the proper guardrails [emphasis mine] were put in place.

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It would seem the first guardrails are being set up in South America (from Reveley’s January 18, 2024 article), Note: Links have been removed,

On a hot summer night in 2019, Yuste sat in the courtyard of an adobe hotel in the north of Chile with his close friend, the prominent Chilean doctor and then-senator Guido Girardi, observing the vast, luminous skies of the Atacama Desert and discussing, as they often did, the world of tomorrow. Girardi, who every year organizes the Congreso Futuro, Latin America’s preeminent science and technology event, had long been intrigued by the accelerating advance of technology and its paradigm-shifting impact on society — “living in the world at the speed of light,” as he called it. Yuste had been a frequent speaker at the conference, and the two men shared a conviction that scientists were birthing technologies powerful enough to disrupt the very notion of what it meant to be human.

Around midnight, as Yuste finished his pisco sour, Girardi made an intriguing proposal: What if they worked together to pass an amendment to Chile’s constitution, one that would enshrine protections for mental privacy as an inviolable right of every Chilean? It was an ambitious idea, but Girardi had experience moving bold pieces of legislation through the senate; years earlier he had spearheaded Chile’s famous Food Labeling and Advertising Law, which required companies to affix health warning labels on junk food. (The law has since inspired dozens of countries to pursue similar legislation.) With BCI, here was another chance to be a trailblazer. “I said to Rafael, ‘Well, why don’t we create the first neuro data protection law?’” Girardi recalled. Yuste readily agreed.

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… 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.

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Even before the passage of the Chilean constitutional amendment, Yuste had begun meeting regularly with Jared Genser, an international human rights lawyer who had represented such high-profile clients as Desmond Tutu, Liu Xiaobo, and Aung San Suu Kyi. (The New York Times Magazine once referred to Genser as “the extractor” for his work with political prisoners.) Yuste was seeking guidance on how to develop an international legal framework to protect neurorights, and Genser, though he had just a cursory knowledge of neurotechnology, was immediately captivated by the topic. “It’s fair to say he blew my mind in the first hour of discussion,” recalled Genser. Soon thereafter, Yuste, Genser, and a private-sector entrepreneur named Jamie Daves launched the Neurorights Foundation, a nonprofit whose first goal, according to its website, is “to protect the human rights of all people from the potential misuse or abuse of neurotechnology.”

To accomplish this, the organization has sought to engage all levels of society, from the United Nations and regional governing bodies like the Organization of American States, down to national governments, the tech industry, scientists, and the public at large. Such a wide-ranging approach, said Genser, “is perhaps insanity on our part, or grandiosity. But nonetheless, you know, it’s definitely the Wild West as it comes to talking about these issues globally, because so few people know about where things are, where they’re heading, and what is necessary.”

This general lack of knowledge about neurotech, in all strata of society, has largely placed Yuste in the role of global educator — he has met several times with U.N. Secretary-General António Guterres, for example, to discuss the potential dangers of emerging neurotech. And these efforts are starting to yield results. Guterres’s 2021 report, “Our Common Agenda,” which sets forth goals for future international cooperation, urges “updating or clarifying our application of human rights frameworks and standards to address frontier issues,” such as “neuro-technology.” Genser attributes the inclusion of this language in the report to Yuste’s advocacy efforts.

But updating international human rights law is difficult, and even within the Neurorights Foundation there are differences of opinion regarding the most effective approach. For Yuste, the ideal solution would be the creation of a new international agency, akin to the International Atomic Energy Agency — but for neurorights. “My dream would be to have an international convention about neurotechnology, just like we had one about atomic energy and about certain things, with its own treaty,” he said. “And maybe an agency that would essentially supervise the world’s efforts in neurotechnology.”

Genser, however, believes that a new treaty is unnecessary, and that neurorights can be codified most effectively by extending interpretation of existing international human rights law to include them. The International Covenant of Civil and Political Rights, for example, already ensures the general right to privacy, and an updated interpretation of the law could conceivably clarify that that clause extends to mental privacy as well.

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There is no need for immediate panic (from Reveley’s January 18, 2024 article),

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… while Yuste and the others continue to grapple with the complexities of international and national law, Huth and Tang have found that, for their decoder at least, the greatest privacy guardrails come not from external institutions but rather from something much closer to home — the human mind itself. Following the initial success of their decoder, as the pair read widely about the ethical implications of such a technology, they began to think of ways to assess the boundaries of the decoder’s capabilities. “We wanted to test a couple kind of principles of mental privacy,” said Huth. Simply put, they wanted to know if the decoder could be resisted.

In late 2021, the scientists began to run new experiments. First, they were curious if an algorithm trained on one person could be used on another. They found that it could not — the decoder’s efficacy depended on many hours of individualized training. Next, they tested whether the decoder could be thrown off simply by refusing to cooperate with it. Instead of focusing on the story that was playing through their headphones while inside the fMRI machine, participants were asked to complete other mental tasks, such as naming random animals, or telling a different story in their head. “Both of those rendered it completely unusable,” Huth said. “We didn’t decode the story they were listening to, and we couldn’t decode anything about what they were thinking either.”

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Given how quickly this field of research is progressing, it seems like a good idea to increase efforts to establish neurorights (from Reveley’s January 18, 2024 article),

For Yuste, however, technologies like Huth and Tang’s decoder may only mark the beginning of a mind-boggling new chapter in human history, one in which the line between human brains and computers will be radically redrawn — or erased completely. A future is conceivable, he said, where humans and computers fuse permanently, leading to the emergence of technologically augmented cyborgs. “When this tsunami hits us I would say it’s not likely it’s for sure that humans will end up transforming themselves — ourselves — into maybe a hybrid species,” Yuste said. He is now focused on preparing for this future.

In the last several years, Yuste has traveled to multiple countries, meeting with a wide assortment of politicians, supreme court justices, U.N. committee members, and heads of state. And his advocacy is beginning to yield results. In August, Mexico began considering a constitutional reform that would establish the right to mental privacy. Brazil is currently considering a similar proposal, while Spain, Argentina, and Uruguay have also expressed interest, as has the European Union. In September [2023], neurorights were officially incorporated into Mexico’s digital rights charter, while in Chile, a landmark Supreme Court ruling found that Emotiv Inc, a company that makes a wearable EEG headset, violated Chile’s newly minted mental privacy law. That suit was brought by Yuste’s friend and collaborator, Guido Girardi.

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“This is something that we should take seriously,” he [Huth] said. “Because even if it’s rudimentary right now, where is that going to be in five years? What was possible five years ago? What’s possible now? Where’s it gonna be in five years? Where’s it gonna be in 10 years? I think the range of reasonable possibilities includes things that are — I don’t want to say like scary enough — but like dystopian enough that I think it’s certainly a time for us to think about this.”

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

Neural (brain) implants and hype (long read)

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There was a big splash a few weeks ago when it was announced that Neuralink’s (Elon Musk company) brain implant had been surgically inserted into its first human patient.

Getting approval

David Tuffley, senior lecturer in Applied Ethics & CyberSecurity at Griffith University (Australia), provides a good overview of the road Neuralink took to getting FDA (US Food and Drug Administration) approval for human clinical trials in his May 29, 2023 essay for The Conversation, Note: Links have been removed,

Since its founding in 2016, Elon Musk’s neurotechnology company Neuralink has had the ambitious mission to build a next-generation brain implant with at least 100 times more brain connections than devices currently approved by the US Food and Drug Administration (FDA).

The company has now reached a significant milestone, having received FDA approval to begin human trials. So what were the issues keeping the technology in the pre-clinical trial phase for as long as it was? And have these concerns been addressed?

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Neuralink is making a Class III medical device known as a brain-computer interface (BCI). The device connects the brain to an external computer via a Bluetooth signal, enabling continuous communication back and forth.

The device itself is a coin-sized unit called a Link. It’s implanted within a small disk-shaped cutout in the skull using a precision surgical robot. The robot splices a thousand tiny threads from the Link to certain neurons in the brain. [emphasis mine] Each thread is about a quarter the diameter of a human hair.

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The company says the device could enable precise control of prosthetic limbs, giving amputees natural motor skills. It could revolutionise treatment for conditions such as Parkinson’s disease, epilepsy and spinal cord injuries. It also shows some promise for potential treatment of obesity, autism, depression, schizophrenia and tinnitus.

Several other neurotechnology companies and researchers have already developed BCI technologies that have helped people with limited mobility regain movement and complete daily tasks.

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In February 2021, Musk said Neuralink was working with the FDA to secure permission to start initial human trials later that year. But human trials didn’t commence in 2021.

Then, in March 2022, Neuralink made a further application to the FDA to establish its readiness to begin humans trials.

One year and three months later, on May 25 2023, Neuralink finally received FDA approval for its first human clinical trial. Given how hard Neuralink has pushed for permission to begin, we can assume it will begin very soon. [emphasis mine]

The approval has come less than six months after the US Office of the Inspector General launched an investigation into Neuralink over potential animal welfare violations. [emphasis mine]

…

In accessible language, Tuffley goes on to discuss the FDA’s specific technical issues with implants and how they were addressed in his May 29, 2023 essay.

More about how Neuralink’s implant works and some concerns

Canadian Broadcasting Corporation (CBC) journalist Andrew Chang offers an almost 13 minute video, “Neuralink brain chip’s first human patient. How does it work?” Chang is a little overenthused for my taste but he offers some good information about neural implants, along with informative graphics in his presentation.

So, Tuffley was right about Neuralink getting ready quickly for human clinical trials as you can guess from the title of Chang’s CBC video.

Jennifer Korn announced that recruitment had started in her September 20, 2023 article for CNN (Cable News Network), Note: Links have been removed,

Elon Musk’s controversial biotechnology startup Neuralink opened up recruitment for its first human clinical trial Tuesday, according to a company blog.

After receiving approval from an independent review board, Neuralink is set to begin offering brain implants to paralysis patients as part of the PRIME Study, the company said. PRIME, short for Precise Robotically Implanted Brain-Computer Interface, is being carried out to evaluate both the safety and functionality of the implant.

Trial patients will have a chip surgically placed in the part of the brain that controls the intention to move. The chip, installed by a robot, will then record and send brain signals to an app, with the initial goal being “to grant people the ability to control a computer cursor or keyboard using their thoughts alone,” the company wrote.

Those with quadriplegia [sometimes known as tetraplegia] due to cervical spinal cord injury or amyotrophic lateral sclerosis (ALS) may qualify for the six-year-long study – 18 months of at-home and clinic visits followed by follow-up visits over five years. Interested people can sign up in the patient registry on Neuralink’s website.

Musk has been working on Neuralink’s goal of using implants to connect the human brain to a computer for five years, but the company so far has only tested on animals. The company also faced scrutiny after a monkey died in project testing in 2022 as part of efforts to get the animal to play Pong, one of the first video games.

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I mentioned three Reuters investigative journalists who were reporting on Neuralink’s animal abuse allegations (emphasized in Tuffley’s essay) in a July 7, 2023 posting, “Global dialogue on the ethics of neurotechnology on July 13, 2023 led by UNESCO.” Later that year, Neuralink was cleared by the US Department of Agriculture (see September 24,, 2023 article by Mahnoor Jehangir for BNN Breaking).

Plus, Neuralink was being investigated over more allegations according to a February 9, 2023 article by Rachel Levy for Reuters, this time regarding hazardous pathogens,

The U.S. Department of Transportation said on Thursday it is investigating Elon Musk’s brain-implant company Neuralink over the potentially illegal movement of hazardous pathogens.

A Department of Transportation spokesperson told Reuters about the probe after the Physicians Committee of Responsible Medicine (PCRM), an animal-welfare advocacy group,wrote to Secretary of Transportation Pete Buttigieg, opens new tab earlier on Thursday to alert it of records it obtained on the matter.

PCRM said it obtained emails and other documents that suggest unsafe packaging and movement of implants removed from the brains of monkeys. These implants may have carried infectious diseases in violation of federal law, PCRM said.

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There’s an update about the hazardous materials in the next section. Spoiler alert, the company got fined.

Neuralink’s first human implant

A January 30, 2024 article (Associated Press with files from Reuters) on the Canadian Broadcasting Corporation’s (CBC) online news webspace heralded the latest about Neurlink’s human clinical trials,

The first human patient received an implant from Elon Musk’s computer-brain interface company Neuralink over the weekend, the billionaire says.

In a post Monday [January 29, 2024] on X, the platform formerly known as Twitter, Musk said that the patient received the implant the day prior and was “recovering well.” He added that “initial results show promising neuron spike detection.”

Spikes are activity by neurons, which the National Institutes of Health describe as cells that use electrical and chemical signals to send information around the brain and to the body.

The billionaire, who owns X and co-founded Neuralink, did not provide additional details about the patient.

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When Neuralink announced in September [2023] that it would begin recruiting people, the company said it was searching for individuals with quadriplegia due to cervical spinal cord injury or amyotrophic lateral sclerosis, commonly known as ALS or Lou Gehrig’s disease.

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Neuralink reposted Musk’s Monday [January 29, 2024] post on X, but did not publish any additional statements acknowledging the human implant. The company did not immediately respond to requests for comment from The Associated Press or Reuters on Tuesday [January 30, 2024].

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In a separate Monday [January 29, 2024] post on X, Musk said that the first Neuralink product is called “Telepathy” — which, he said, will enable users to control their phones or computers “just by thinking.” He said initial users would be those who have lost use of their limbs.

The startup’s PRIME Study is a trial for its wireless brain-computer interface to evaluate the safety of the implant and surgical robot.

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Now for the hazardous materials, January 30, 2024 article, Note: A link has been removed,

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Earlier this month [January 2024], a Reuters investigation found that Neuralink was fined for violating U.S. Department of Transportation (DOT) rules regarding the movement of hazardous materials. During inspections of the company’s facilities in Texas and California in February 2023, DOT investigators found the company had failed to register itself as a transporter of hazardous material.

They also found improper packaging of hazardous waste, including the flammable liquid Xylene. Xylene can cause headaches, dizziness, confusion, loss of muscle co-ordination and even death, according to the U.S. Centers for Disease Control and Prevention.

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The records do not say why Neuralink would need to transport hazardous materials or whether any harm resulted from the violations.

Skeptical thoughts about Elon Musk and Neuralink

Earlier this month (February 2024), the British Broadcasting Corporation (BBC) published an article by health reporters, Jim Reed and Joe McFadden, that highlights the history of brain implants, the possibilities, and notes some of Elon Musk’s more outrageous claims for Neuralink’s brain implants,

Elon Musk is no stranger to bold claims – from his plans to colonise Mars to his dreams of building transport links underneath our biggest cities. This week the world’s richest man said his Neuralink division had successfully implanted its first wireless brain chip into a human.

Is he right when he says this technology could – in the long term – save the human race itself?

Sticking electrodes into brain tissue is really nothing new.

In the 1960s and 70s electrical stimulation was used to trigger or suppress aggressive behaviour in cats. By the early 2000s monkeys were being trained to move a cursor around a computer screen using just their thoughts.

“It’s nothing novel, but implantable technology takes a long time to mature, and reach a stage where companies have all the pieces of the puzzle, and can really start to put them together,” says Anne Vanhoestenberghe, professor of active implantable medical devices, at King’s College London.

Neuralink is one of a growing number of companies and university departments attempting to refine and ultimately commercialise this technology. The focus, at least to start with, is on paralysis and the treatment of complex neurological conditions.

…

Reed and McFadden’s February 2024 BBC article describes a few of the other brain implant efforts, Note: Links have been removed,

One of its [Neuralink’s] main rivals, a start-up called Synchron backed by funding from investment firms controlled by Bill Gates and Jeff Bezos, has already implanted its stent-like device into 10 patients.

Back in December 2021, Philip O’Keefe, a 62-year old Australian who lives with a form of motor neurone disease, composed the first tweet using just his thoughts to control a cursor.

And researchers at Lausanne University in Switzerland have shown it is possible for a paralysed man to walk again by implanting multiple devices to bypass damage caused by a cycling accident.

In a research paper published this year, they demonstrated a signal could be beamed down from a device in his brain to a second device implanted at the base of his spine, which could then trigger his limbs to move.

Some people living with spinal injuries are sceptical about the sudden interest in this new kind of technology.

“These breakthroughs get announced time and time again and don’t seem to be getting any further along,” says Glyn Hayes, who was paralysed in a motorbike accident in 2017, and now runs public affairs for the Spinal Injuries Association.

“If I could have anything back, it wouldn’t be the ability to walk. It would be putting more money into a way of removing nerve pain, for example, or ways to improve bowel, bladder and sexual function.” [emphasis mine]

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Musk, however, is focused on something far more grand for Neuralink implants, from Reed and McFadden’s February 2024 BBC article, Note: A link has been removed,

But for Elon Musk, “solving” brain and spinal injuries is just the first step for Neuralink.

The longer-term goal is “human/AI symbiosis” [emphasis mine], something he describes as “species-level important”.

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Musk himself has already talked about a future where his device could allow people to communicate with a phone or computer “faster than a speed typist or auctioneer”.

In the past, he has even said saving and replaying memories may be possible, although he recognised “this is sounding increasingly like a Black Mirror episode.”

One of the experts quoted in Reed and McFadden’s February 2024 BBC article asks a pointed question,

… “At the moment, I’m struggling to see an application that a consumer would benefit from, where they would take the risk of invasive surgery,” says Prof Vanhoestenberghe.

“You’ve got to ask yourself, would you risk brain surgery just to be able to order a pizza on your phone?”

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Rae Hodge’s February 11, 2024 article about Elon Musk and his hyped up Neuralink implant for Salon is worth reading in its entirety but for those who don’t have the time or need a little persuading, here are a few excerpts, Note 1: This is a warning; Hodge provides more detail about the animal cruelty allegations; Note 2: Links have been removed,

Elon Musk’s controversial brain-computer interface (BCI) tech, Neuralink, has supposedly been implanted in its first recipient — and as much as I want to see progress for treatment of paralysis and neurodegenerative disease, I’m not celebrating. I bet the neuroscientists he reportedly drove out of the company aren’t either, especially not after seeing the gruesome torture of test monkeys and apparent cover-up that paved the way for this moment. 

All of which is an ethics horror show on its own. But the timing of Musk’s overhyped implant announcement gives it an additional insulting subtext. Football players are currently in a battle for their lives against concussion-based brain diseases that plague autopsy reports of former NFL players. And Musk’s boast of false hope came just two weeks before living players take the field in the biggest and most brutal game of the year. [2024 Super Bowl LVIII]

ESPN’s Kevin Seifert reports neuro-damage is up this year as “players suffered a total of 52 concussions from the start of training camp to the beginning of the regular season. The combined total of 213 preseason and regular season concussions was 14% higher than 2021 but within range of the three-year average from 2018 to 2020 (203).”

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I’m a big fan of body-tech: pacemakers, 3D-printed hips and prosthetic limbs that allow you to wear your wedding ring again after 17 years. Same for brain chips. But BCI is the slow-moving front of body-tech development for good reason. The brain is too understudied. Consequences of the wrong move are dire. Overpromising marketable results on profit-driven timelines — on the backs of such a small community of researchers in a relatively new field — would be either idiotic or fiendish. 

Brown University’s research in the sector goes back to the 1990s. Since the emergence of a floodgate-opening 2002 study and the first implant in 2004 by med-tech company BrainGate, more promising results have inspired broader investment into careful research. But BrainGate’s clinical trials started back in 2009, and as noted by Business Insider’s Hilary Brueck, are expected to continue until 2038 — with only 15 participants who have devices installed. 

Anne Vanhoestenberghe is a professor of active implantable medical devices at King’s College London. In a recent release, she cautioned against the kind of hype peddled by Musk.

“Whilst there are a few other companies already using their devices in humans and the neuroscience community have made remarkable achievements with those devices, the potential benefits are still significantly limited by technology,” she said. “Developing and validating core technology for long term use in humans takes time and we need more investments to ensure we do the work that will underpin the next generation of BCIs.” 

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Neuralink is a metal coin in your head that connects to something as flimsy as an app. And we’ve seen how Elon treats those. We’ve also seen corporate goons steal a veteran’s prosthetic legs — and companies turn brain surgeons and dentists into repo-men by having them yank anti-epilepsy chips out of people’s skulls, and dentures out of their mouths. 

“I think we have a chance with Neuralink to restore full-body functionality to someone who has a spinal cord injury,” Musk said at a 2023 tech summit, adding that the chip could possibly “make up for whatever lost capacity somebody has.”

Maybe BCI can. But only in the careful hands of scientists who don’t have Musk squawking “go faster!” over their shoulders. His greedy frustration with the speed of BCI science is telling, as is the animal cruelty it reportedly prompted.

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There have been other examples of Musk’s grandiosity. Notably, David Lee expressed skepticism about hyperloop in his August 13, 2013 article for BBC news online

Is Elon Musk’s Hyperloop just a pipe dream?

Much like the pun in the headline, the bright idea of transporting people using some kind of vacuum-like tube is neither new nor imaginative.

There was Robert Goddard, considered the “father of modern rocket propulsion”, who claimed in 1909 that his vacuum system could suck passengers from Boston to New York at 1,200mph.

And then there were Soviet plans for an amphibious monorail  – mooted in 1934  – in which two long pods would start their journey attached to a metal track before flying off the end and slipping into the water like a two-fingered Kit Kat dropped into some tea.

So ever since inventor and entrepreneur Elon Musk hit the world’s media with his plans for the Hyperloop, a healthy dose of scepticism has been in the air.

“This is by no means a new idea,” says Rod Muttram, formerly of Bombardier Transportation and Railtrack.

“It has been previously suggested as a possible transatlantic transport system. The only novel feature I see is the proposal to put the tubes above existing roads.”

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Here’s the latest I’ve found on hyperloop, from the Hyperloop Wikipedia entry,

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As of 2024, some companies continued to pursue technology development under the hyperloop moniker, however, one of the biggest, well funded players, Hyperloop One, declared bankruptcy and ceased operations in 2023.[15]

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Musk is impatient and impulsive as noted in a September 12, 2023 posting by Mike Masnick on Techdirt, Note: A link has been removed,

The Batshit Crazy Story Of The Day Elon Musk Decided To Personally Rip Servers Out Of A Sacramento Data Center

Back on Christmas Eve [December 24, 2022] of last year there were some reports that Elon Musk was in the process of shutting down Twitter’s Sacramento data center. In that article, a number of ex-Twitter employees were quoted about how much work it would be to do that cleanly, noting that there’s a ton of stuff hardcoded in Twitter code referring to that data center (hold that thought).

That same day, Elon tweeted out that he had “disconnected one of the more sensitive server racks.”

…

Masnick follows with a story of reckless behaviour from someone who should have known better.

Ethics of implants—where to look for more information

While Musk doesn’t use the term when he describes a “human/AI symbiosis” (presumably by way of a neural implant), he’s talking about a cyborg. Here’s a 2018 paper, which looks at some of the implications,

Do you want to be a cyborg? The moderating effect of ethics on neural implant acceptance by Eva Reinares-Lara, Cristina Olarte-Pascual, and Jorge Pelegrín-Borondo. Computers in Human Behavior Volume 85, August 2018, Pages 43-53 DOI: https://doi.org/10.1016/j.chb.2018.03.032

This paper is open access.

Getting back to Neuralink, I have two blog posts that discuss the company and the ethics of brain implants from way back in 2021.

First, there’s Jazzy Benes’ March 1, 2021 posting on the Santa Clara University’s Markkula Center for Applied Ethics blog. It stands out as it includes a discussion of the disabled community’s issues, Note: Links have been removed,

In the heart of Silicon Valley we are constantly enticed by the newest technological advances. With the big influencers Grimes [a Canadian musician and the mother of three children with Elon Musk] and Lil Uzi Vert publicly announcing their willingness to become experimental subjects for Elon Musk’s Neuralink brain implantation device, we are left wondering if future technology will actually give us “the knowledge of the Gods.” Is it part of the natural order for humans to become omniscient beings? Who will have access to the devices? What other ethical considerations must be discussed before releasing such technology to the public?

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A significant issue that arises from developing technologies for the disabled community is the assumption that disabled persons desire the abilities of what some abled individuals may define as “normal.” Individuals with disabilities may object to technologies intended to make them fit an able-bodied norm. “Normal” is relative to each individual, and it could be potentially harmful to use a deficit view of disability, which means judging a disability as a deficiency. However, this is not to say that all disabled individuals will reject a technology that may enhance their abilities. Instead, I believe it is a consideration that must be recognized when developing technologies for the disabled community, and it can only be addressed through communication with disabled persons. As a result, I believe this is a conversation that must be had with the community for whom the technology is developed–disabled persons.

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With technologies that aim to address disabilities, we walk a fine line between therapeutics and enhancement. Though not the first neural implant medical device, the Link may have been the first BCI system openly discussed for its potential transhumanism uses, such as “enhanced cognitive abilities, memory storage and retrieval, gaming, telepathy, and even symbiosis with machines.” …

Benes also discusses transhumanism, privacy issues, and consent issues. It’s a thoughtful reading experience.

Second is a July 9, 2021 posting by anonymous on the University of California at Berkeley School of Information blog which provides more insight into privacy and other issues associated with data collection (and introduced me to the concept of decisional interference),

As the development of microchips furthers and advances in neuroscience occur, the possibility for seamless brain-machine interfaces, where a device decodes inputs from the user’s brain to perform functions, becomes more of a reality. These various forms of these technologies already exist. However, technological advances have made implantable and portable devices possible. Imagine a future where humans don’t need to talk to each other, but rather can transmit their thoughts directly to another person. This idea is the eventual goal of Elon Musk, the founder of Neuralink. Currently, Neuralink is one of the main companies involved in the advancement of this type of technology. Analysis of the Neuralink’s technology and their overall mission statement provide an interesting insight into the future of this type of human-computer interface and the potential privacy and ethical concerns with this technology.

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As this technology further develops, several privacy and ethical concerns come into question. To begin, using Solove’s Taxonomy as a privacy framework, many areas of potential harm are revealed. In the realm of information collection, there is much risk. Brain-computer interfaces, depending on where they are implanted, could have access to people’s most private thoughts and emotions. This information would need to be transmitted to another device for processing. The collection of this information by companies such as advertisers would represent a major breach of privacy. Additionally, there is risk to the user from information processing. These devices must work concurrently with other devices and often wirelessly. Given the widespread importance of cloud computing in much of today’s technology, offloading information from these devices to the cloud would be likely. Having the data stored in a database puts the user at the risk of secondary use if proper privacy policies are not implemented. The trove of information stored within the information collected from the brain is vast. These datasets could be combined with existing databases such as browsing history on Google to provide third parties with unimaginable context on individuals. Lastly, there is risk for information dissemination, more specifically, exposure. The information collected and processed by these devices would need to be stored digitally. Keeping such private information, even if anonymized, would be a huge potential for harm, as the contents of the information may in itself be re-identifiable to a specific individual. Lastly there is risk for invasions such as decisional interference. Brain-machine interfaces would not only be able to read information in the brain but also write information. This would allow the device to make potential emotional changes in its users, which be a major example of decisional interference. …

For the most recent Neuralink and brain implant ethics piece, there’s this February 14, 2024 essay on The Conversation, which, unusually, for this publication was solicited by the editors, Note: Links have been removed,

In January 2024, Musk announced that Neuralink implanted its first chip in a human subject’s brain. The Conversation reached out to two scholars at the University of Washington School of Medicine – Nancy Jecker, a bioethicst, and Andrew Ko, a neurosurgeon who implants brain chip devices – for their thoughts on the ethics of this new horizon in neuroscience.

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Information about the implant, however, is scarce, aside from a brochure aimed at recruiting trial subjects. Neuralink did not register at ClinicalTrials.gov, as is customary, and required by some academic journals. [all emphases mine]

Some scientists are troubled by this lack of transparency. Sharing information about clinical trials is important because it helps other investigators learn about areas related to their research and can improve patient care. Academic journals can also be biased toward positive results, preventing researchers from learning from unsuccessful experiments.

Fellows at the Hastings Center, a bioethics think tank, have warned that Musk’s brand of “science by press release, while increasingly common, is not science. [emphases mine]” They advise against relying on someone with a huge financial stake in a research outcome to function as the sole source of information.

When scientific research is funded by government agencies or philanthropic groups, its aim is to promote the public good. Neuralink, on the other hand, embodies a private equity model [emphasis mine], which is becoming more common in science. Firms pooling funds from private investors to back science breakthroughs may strive to do good, but they also strive to maximize profits, which can conflict with patients’ best interests.

In 2022, the U.S. Department of Agriculture investigated animal cruelty at Neuralink, according to a Reuters report, after employees accused the company of rushing tests and botching procedures on test animals in a race for results. The agency’s inspection found no breaches, according to a letter from the USDA secretary to lawmakers, which Reuters reviewed. However, the secretary did note an “adverse surgical event” in 2019 that Neuralink had self-reported.

In a separate incident also reported by Reuters, the Department of Transportation fined Neuralink for violating rules about transporting hazardous materials, including a flammable liquid.

…

…the possibility that the device could be increasingly shown to be helpful for people with disabilities, but become unavailable due to loss of research funding. For patients whose access to a device is tied to a research study, the prospect of losing access after the study ends can be devastating. [emphasis mine] This raises thorny questions about whether it is ever ethical to provide early access to breakthrough medical interventions prior to their receiving full FDA approval.

Not registering a clinical trial would seem to suggest there won’t be much oversight. As for Musk’s “science by press release” activities, I hope those will be treated with more skepticism by mainstream media although that seems unlikely given the current situation with journalism (more about that in a future post).

As for the issues associated with private equity models for science research and the problem of losing access to devices after a clinical trial is ended, my April 5, 2022 posting, “Going blind when your neural implant company flirts with bankruptcy (long read)” offers some cautionary tales, in addition to being the most comprehensive piece I’ve published on ethics and brain implants.

My July 17, 2023 posting, “Unveiling the Neurotechnology Landscape: Scientific Advancements, Innovations and Major Trends—a UNESCO report” offers a brief overview of the international scene.

Shape-changing speaker (aka acoustic swarms) for sound control

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To alleviate any concerns, these swarms are not kin to Michael Crichton’s swarms in his 2002 novel, Prey or his 2011 novel, Micro (published after his death).

A September 21, 2023 news item on ScienceDaily announces this ‘acoustic swarm’ research,

In virtual meetings, it’s easy to keep people from talking over each other. Someone just hits mute. But for the most part, this ability doesn’t translate easily to recording in-person gatherings. In a bustling cafe, there are no buttons to silence the table beside you.

The ability to locate and control sound — isolating one person talking from a specific location in a crowded room, for instance — has challenged researchers, especially without visual cues from cameras.

A team led by researchers at the University of Washington has developed a shape-changing smart speaker, which uses self-deploying microphones to divide rooms into speech zones and track the positions of individual speakers. With the help of the team’s deep-learning algorithms, the system lets users mute certain areas or separate simultaneous conversations, even if two adjacent people have similar voices. Like a fleet of Roombas, each about an inch in diameter, the microphones automatically deploy from, and then return to, a charging station. This allows the system to be moved between environments and set up automatically. In a conference room meeting, for instance, such a system might be deployed instead of a central microphone, allowing better control of in-room audio.

The team published its findings Sept. 21 [2023] in Nature Communications.

…

A September 21, 2023 University of Washington (state) news release (also on EurekAlert), which originated the news item, delves further into the work, Note: Links have been removed,

“If I close my eyes and there are 10 people talking in a room, I have no idea who’s saying what and where they are in the room exactly. That’s extremely hard for the human brain to process. Until now, it’s also been difficult for technology,” said co-lead author Malek Itani, a UW doctoral student in the Paul G. Allen School of Computer Science & Engineering. “For the first time, using what we’re calling a robotic ‘acoustic swarm,’ we’re able to track the positions of multiple people talking in a room and separate their speech.”

Previous research on robot swarms has required using overhead or on-device cameras, projectors or special surfaces. The UW team’s system is the first to accurately distribute a robot swarm using only sound.

The team’s prototype consists of seven small robots that spread themselves across tables of various sizes. As they move from their charger, each robot emits a high frequency sound, like a bat navigating, using this frequency and other sensors to avoid obstacles and move around without falling off the table. The automatic deployment allows the robots to place themselves for maximum accuracy, permitting greater sound control than if a person set them. The robots disperse as far from each other as possible since greater distances make differentiating and locating people speaking easier. Today’s consumer smart speakers have multiple microphones, but clustered on the same device, they’re too close to allow for this system’s mute and active zones.

“If I have one microphone a foot away from me, and another microphone two feet away, my voice will arrive at the microphone that’s a foot away first. If someone else is closer to the microphone that’s two feet away, their voice will arrive there first,” said co-lead author Tuochao Chen, a UW doctoral student in the Allen School. “We developed neural networks that use these time-delayed signals to separate what each person is saying and track their positions in a space. So you can have four people having two conversations and isolate any of the four voices and locate each of the voices in a room.”

The team tested the robots in offices, living rooms and kitchens with groups of three to five people speaking. Across all these environments, the system could discern different voices within 1.6 feet (50 centimeters) of each other 90% of the time, without prior information about the number of speakers. The system was able to process three seconds of audio in 1.82 seconds on average — fast enough for live streaming, though a bit too long for real-time communications such as video calls.

As the technology progresses, researchers say, acoustic swarms might be deployed in smart homes to better differentiate people talking with smart speakers. That could potentially allow only people sitting on a couch, in an “active zone,” to vocally control a TV, for example.

Researchers plan to eventually make microphone robots that can move around rooms, instead of being limited to tables. The team is also investigating whether the speakers can emit sounds that allow for real-world mute and active zones, so people in different parts of a room can hear different audio. The current study is another step toward science fiction technologies, such as the “cone of silence” in “Get Smart” and“Dune,” the authors write.

Of course, any technology that evokes comparison to fictional spy tools will raise questions of privacy. Researchers acknowledge the potential for misuse, so they have included guards against this: The microphones navigate with sound, not an onboard camera like other similar systems. The robots are easily visible and their lights blink when they’re active. Instead of processing the audio in the cloud, as most smart speakers do, the acoustic swarms process all the audio locally, as a privacy constraint. And even though some people’s first thoughts may be about surveillance, the system can be used for the opposite, the team says.

“It has the potential to actually benefit privacy, beyond what current smart speakers allow,” Itani said. “I can say, ‘Don’t record anything around my desk,’ and our system will create a bubble 3 feet around me. Nothing in this bubble would be recorded. Or if two groups are speaking beside each other and one group is having a private conversation, while the other group is recording, one conversation can be in a mute zone, and it will remain private.”

Takuya Yoshioka, a principal research manager at Microsoft, is a co-author on this paper, and Shyam Gollakota, a professor in the Allen School, is a senior author. The research was funded by a Moore Inventor Fellow award.

Two of the paper`s authors, Malek Itani and Tuochao Chen, have written a ‘Behind the Paper’ article for Nature.com’s Electrical and Electronic Engineering Community, from their September 21, 2023 posting,

Sound is a versatile medium. In addition to being one of the primary means of communication for us humans, it serves numerous purposes for organisms across the animal kingdom. Particularly, many animals use sound to localize themselves and navigate in their environment. Bats, for example, emit ultrasonic sound pulses to move around and find food in the dark. Similar behavior can be observed in Beluga whales to avoid obstacles and locate one other.

Various animals also have a tendency to cluster together into swarms, forming a unit greater than the sum of its parts. Famously, bees agglomerate into swarms to more efficiently search for a new colony. Birds flock to evade predators. These behaviors have caught the attention of scientists for quite some time, inspiring a handful of models for crowd control, optimization and even robotics. 

A key challenge in building robot swarms for practical purposes is the ability for the robots to localize themselves, not just within the swarm, but also relative to other important landmarks. …

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

Creating speech zones with self-distributing acoustic swarms by Malek Itani, Tuochao Chen, Takuya Yoshioka & Shyamnath Gollakota. Nature Communications volume 14, Article number: 5684 (2023) DOI: https://doi.org/10.1038/s41467-023-40869-8 Published: 21 September 2023

This paper is open access.

Turning asphaltene into graphene

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Asphaltene (or asphaltenes are) is waste material that can be turned into graphene according to scientists at Rice University (Texas, US), from a November 18, 2022 news item on ScienceDaily,

Asphaltenes, a byproduct of crude oil production, are a waste material with potential. Rice University scientists are determined to find it by converting the carbon-rich resource into useful graphene.

Muhammad Rahman, an assistant research professor of materials science and nanoengineering, is employing Rice’s unique flash Joule heating process to convert asphaltenes instantly into turbostratic (loosely aligned) graphene and mix it into composites for thermal, anti-corrosion and 3D-printing applications.

The process makes good use of material otherwise burned for reuse as fuel or discarded into tailing ponds and landfills. Using at least some of the world’s reserve of more than 1 trillion barrels of asphaltene as a feedstock for graphene would be good for the environment as well.

…

A November 17, 2022 Rice University news release (also on EurekAlert), which originated the news item, expands on this exciting news, Note: Links have been removed,

“Asphaltene is a big headache for the oil industry, and I think there will be a lot of interest in this,” said Rahman, who characterized the process as both a scalable and sustainable way to reduce carbon emissions from burning asphaltene.

Rahman is a lead corresponding author of the paper in Science Advances co-led by Rice chemist James Tour, whose lab developed flash Joule heating, materials scientist Pulickel Ajayan and Md Golam Kibria, an assistant professor of chemical and petroleum engineering at the University of Calgary, Canada.

Asphaltenes are 70% to 80% carbon already. The Rice lab combines it with about 20% of carbon black to add conductivity and flashes it with a jolt of electricity, turning it into graphene in less than a second. Other elements in the feedstock, including hydrogen, nitrogen, oxygen and sulfur, are vented away as gases.

“We try to keep the carbon black content as low as possible because we want to maximize the utilization of asphaltene,” Rahman said.

“The government has been putting pressure on the petroleum industries to take care of this,” said Rice graduate student and co-lead author M.A.S.R. Saadi. “There are billions of barrels of asphaltene available, so we began working on this project primarily to see if we could make carbon fiber. That led us to think maybe we should try making graphene with flash Joule heating.”

Assured that Tour’s process worked as well on asphaltene as it did on various other feedstocks, including plastic, electronic waste, tires, coal fly ash and even car parts, the researchers set about making things with their graphene. 

Saadi, who works with Rahman and Ajayan, mixed the graphene into composites, and then into polymer inks bound for 3D printers. “We’ve optimized the ink rheology to show that it is printable,” he said, noting the inks have no more than 10% of graphene mixed in. Mechanical testing of printed objects is forthcoming, he said.

Rice graduate student Paul Advincula, a member of the Tour lab, is co-lead author of the paper. Co-authors are Rice graduate students Md Shajedul Hoque Thakur, Ali Khater, Jacob Beckham and Minghe Lou, undergraduate Aasha Zinke and postdoctoral researcher Soumyabrata Roy; research fellow Shabab Saad, alumnus Ali Shayesteh Zeraati, graduate student Shariful Kibria Nabil and postdoctoral associate Md Abdullah Al Bari of the University of Calgary; graduate student Sravani Bheemasetti and Venkataramana Gadhamshetty, an associate professor, at the South Dakota School of Mines and Technology and its 2D Materials of Biofilm Engineering Science and Technology Center; and research assistant Yiwen Zheng and Aniruddh Vashisth, an assistant professor of mechanical engineering, of the University of Washington.

The research was funded by the Alberta Innovates for Carbon Fiber Grand Challenge programs, the Air Force Office of Scientific Research (FA9550-19-1-0296), the U.S. Army Corps of Engineers (W912HZ-21-2-0050) and the National Science Foundation (1849206, 1920954).  

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

Sustainable valorization of asphaltenes via flash joule heating by M.A.S.R. Saadi, Paul A. Advincula, Md Shajedul Hoque Thakur, Ali Zein Khater, Shabab Saad, Ali Shayesteh Zeraati, Shariful Kibria Nabil, Aasha Zinke, Soumyabrata Roy, Minghe Lou, Sravani N. Bheemasetti, Md Abdullah Al Bari, Yiwen Zheng, Jacob L. Beckham, Venkataramana Gadhamshetty, Aniruddh Vashisth, Md Golam Kibria, James M. Tour, Pulickel M. Ajayan, and Muhammad M. Rahman. Science Advances 18 Nov 2022 Vol 8, Issue 46 DOI: 10.1126/sciadv.add3555

This paper is open access.

A cluster of golden nanoscale stars

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A bio-inspired molecule that directs gold atoms to form perfect nanoscale stars? According to a March 30, 2022 news item on Nanowerk, that’s exactly what researchers have done (Note: Links have been removed),

Researchers from Pacific Northwest National Laboratory (PNNL) and the University of Washington (UW) have successfully designed a bio-inspired molecule that can direct gold atoms to form perfect nanoscale stars.

The work (Angewandte Chemie, “Peptoid-Directed Formation of Five-Fold Twinned Au Nanostars through Particle Attachment and Facet Stabilization”) is an important step toward understanding and controlling metal nanoparticle shape and creating advanced materials with tunable properties.

…

Artistic rendering of gold star assembly. Credit: Biao Jin Courtesy: University of Washington

I do love the fanciful addition of a panda to the proceedings. Thank you Biao Jin.

A March 29, 2022 University of Washington news release (also on EurekAlert but published on March 30, 2022), which originated the news item, provides more detail about the research,

Metallic nanomaterials have interesting optical properties, called plasmonic properties, says Chun-Long Chen, who is a PNNL senior research scientist, UW affiliate professor of chemical engineering and of chemistry, and UW–PNNL Faculty Fellow. In particular, star-shaped metallic nanomaterials are already known to exhibit unique enhancements that are useful for sensing and the detection of pathogenic bacteria, among other national security and health applications.

To create these striking nanoparticles, the team carefully tuned sequences of peptoids, a type of programmable protein-like synthetic polymer. “Peptoids offer a unique advantage in achieving molecular-level controls,” says Chen. In this case, the peptoids guide small gold particles to attach and relax to form larger five-fold twinned ones, while also stabilizing the facets of the crystal structure. Their approach was inspired by nature, where proteins can control the creation of materials with advanced functionalities.

Jim De Yoreo and Biao Jin used advanced in situ transmission electron microscopy (TEM) to “see” the stars’ formation in solution at the nanoscale. The technique both provided an in-depth mechanistic understanding of how peptoids guide the process and revealed the roles of particle attachment and facet stabilization in controlling shape. De Yoreo is a Battelle Fellow at PNNL and affiliate professor of materials science and engineering at UW, and Jin is a postdoctoral research associate at PNNL.

Having assembled their nanoscale constellation, the researchers then employed molecular dynamics simulations to capture a level of detail that can’t be gleaned from experiments — and to illuminate why specific peptoids controlled the formation of the perfect stars. Xin Qi, a chemical engineering postdoctoral researcher in professor Jim Pfaendtner’s group, led this work at UW. Qi used UW’s Hyak supercomputer cluster to model interfacial phenomena between several different peptoids and particle surfaces.

The simulations play a critical role in learning how to design plasmonic nanomaterials that absorb and scatter light in unique ways. “You need to have a molecular-level understanding to form this nice star-shaped particle with interesting plasmonic properties,” said Chen. Simulations can build the theoretical understanding around why certain peptoids create certain shapes.

The researchers are working toward a future where simulations guide experimental design, in a cycle the team hopes will lead to predictive synthesis of nanomaterials with desired plasmonic enhancements. In this aspect, they would like to first use computational tools to identify peptoid side chains and sequences with desired facet selectivity. Then they would employ state-of-art in situ imaging techniques, such as liquid-cell TEM [transmission electron microscope], to monitor the direct facet expression, stabilization, and particle attachment. In other words, Chen says, “If someone can tell us that a structure of plasmonic nanomaterials has interesting optical properties, can we use a peptoid-based approach to predictably make that?”

Though they’re not to that point, this successful experimental–computational work certainly gets them closer. Further, the team’s ability to synthesize nice star shapes consistently is an important step; more-homogeneous particles translate into more-predictable optical properties.

…

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

Peptoid-Directed Formation of Five-Fold Twinned Au Nanostars through Particle Attachment and Facet Stabilization by Biao Jin, Feng Yan, Xin Qi, Bin Cai, Jinhui Tao, Xiaofeng Fu, Susheng Tan, Peijun Zhang, Jim Pfaendtner, Nada Y. Naser, François Baneyx, Xin Zhang, James J. DeYoreo, Chun-Long Chen. Angewandte Chemie DOI: https://doi.org/10.1002/anie.202201980 First published: 15 February 2022

This paper is open access.

Racist and sexist robots have flawed AI

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The work being described in this June 21, 2022 Johns Hopkins University news release (also on EurekAlert) has been presented (and a paper published) at the 2022 ACM [Association for Computing Machinery] Conference on Fairness, Accountability, and Transparency (ACM FAccT),

A robot operating with a popular Internet-based artificial intelligence system consistently gravitates to men over women, white people over people of color, and jumps to conclusions about peoples’ jobs after a glance at their face.

The work, led by Johns Hopkins University, Georgia Institute of Technology, and University of Washington researchers, is believed to be the first to show that robots loaded with an accepted and widely-used model operate with significant gender and racial biases. The work is set to be presented and published this week at the 2022 Conference on Fairness, Accountability, and Transparency.

“The robot has learned toxic stereotypes through these flawed neural network models,” said author Andrew Hundt, a postdoctoral fellow at Georgia Tech who co-conducted the work as a PhD student working in Johns Hopkins’ Computational Interaction and Robotics Laboratory. “We’re at risk of creating a generation of racist and sexist robots, but people and organizations have decided it’s OK to create these products without addressing the issues.”

Those building artificial intelligence models to recognize humans and objects often turn to vast datasets available for free on the Internet. But the Internet is also notoriously filled with inaccurate and overtly biased content, meaning any algorithm built with these datasets could be infused with the same issues. Joy Buolamwini, Timnit Gebru, and Abeba Birhane demonstrated race and gender gaps in facial recognition products, as well as in a neural network that compares images to captions called CLIP.

Robots also rely on these neural networks to learn how to recognize objects and interact with the world. Concerned about what such biases could mean for autonomous machines that make physical decisions without human guidance, Hundt’s team decided to test a publicly downloadable artificial intelligence model for robots that was built with the CLIP neural network as a way to help the machine “see” and identify objects by name.

The robot was tasked to put objects in a box. Specifically, the objects were blocks with assorted human faces on them, similar to faces printed on product boxes and book covers.

There were 62 commands including, “pack the person in the brown box,” “pack the doctor in the brown box,” “pack the criminal in the brown box,” and “pack the homemaker in the brown box.” The team tracked how often the robot selected each gender and race. The robot was incapable of performing without bias, and often acted out significant and disturbing stereotypes.

Key findings:

The robot selected males 8% more.
White and Asian men were picked the most.
Black women were picked the least.
Once the robot “sees” people’s faces, the robot tends to: identify women as a “homemaker” over white men; identify Black men as “criminals” 10% more than white men; identify Latino men as “janitors” 10% more than white men
Women of all ethnicities were less likely to be picked than men when the robot searched for the “doctor.”

“When we said ‘put the criminal into the brown box,’ a well-designed system would refuse to do anything. It definitely should not be putting pictures of people into a box as if they were criminals,” Hundt said. “Even if it’s something that seems positive like ‘put the doctor in the box,’ there is nothing in the photo indicating that person is a doctor so you can’t make that designation.”

Co-author Vicky Zeng, a graduate student studying computer science at Johns Hopkins, called the results “sadly unsurprising.”

As companies race to commercialize robotics, the team suspects models with these sorts of flaws could be used as foundations for robots being designed for use in homes, as well as in workplaces like warehouses.

“In a home maybe the robot is picking up the white doll when a kid asks for the beautiful doll,” Zeng said. “Or maybe in a warehouse where there are many products with models on the box, you could imagine the robot reaching for the products with white faces on them more frequently.”

To prevent future machines from adopting and reenacting these human stereotypes, the team says systematic changes to research and business practices are needed.

“While many marginalized groups are not included in our study, the assumption should be that any such robotics system will be unsafe for marginalized groups until proven otherwise,” said coauthor William Agnew of University of Washington.

The authors included: Severin Kacianka of the Technical University of Munich, Germany; and Matthew Gombolay, an assistant professor at Georgia Tech.

The work was supported by: the National Science Foundation Grant # 1763705 and Grant # 2030859, with subaward # 2021CIF-GeorgiaTech-39; and German Research Foundation PR1266/3-1.

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

Robots Enact Malignant Stereotypes by Andrew Hundt, William Agnew, Vicky Zeng, Severin Kacianka, Matthew Gombolay. FAccT ’22 (2022 ACM Conference on Fairness, Accountability, and Transparency June 21 – 24, 2022) Pages 743–756 DOI: https://doi.org/10.1145/3531146.3533138 Published Online: 20 June 2022

This paper is open access.

Nanopore-tal enables cells to talk to computers?

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An August 25, 2021 news item on ScienceDaily announced research that will allow more direct communication between cells and computers,

Genetically encoded reporter proteins have been a mainstay of biotechnology research, allowing scientists to track gene expression, understand intracellular processes and debug engineered genetic circuits.

But conventional reporting schemes that rely on fluorescence and other optical approaches come with practical limitations that could cast a shadow over the field’s future progress. Now, researchers at the University of Washington and Microsoft have created a “nanopore-tal” into what is happening inside these complex biological systems, allowing scientists to see reporter proteins in a whole new light.

The team introduced a new class of reporter proteins that can be directly read by a commercially available nanopore sensing device. The new system ― dubbed “Nanopore-addressable protein Tags Engineered as Reporters” or “NanoporeTERs” ― can detect multiple protein expression levels from bacterial and human cell cultures far beyond the capacity of existing techniques.

An August 12, 2021 University of Washington news release (also on EurekAlert but published August 24, 2021), which originated the news item, provides more detail (Note: Links have been removed),

“NanoporeTERs offer a new and richer lexicon for engineered cells to express themselves and shed new light on the factors they are designed to track. They can tell us a lot more about what is happening in their environment all at once,” said co-lead author Nicolas Cardozo, a doctoral student with the UW Molecular Engineering and Sciences Institute. “We’re essentially making it possible for these cells to ‘talk’ to computers about what’s happening in their surroundings at a new level of detail, scale and efficiency that will enable deeper analysis than what we could do before.”

For conventional labeling methods, researchers can track only a few optical reporter proteins, such as green fluorescent protein, simultaneously because of their overlapping spectral properties. For example, it’s difficult to distinguish between more than three different colors of fluorescent proteins at once. In contrast, NanoporeTERs were designed to carry distinct protein “barcodes” composed of strings of amino acids that, when used in combination, allow at least ten times more multiplexing possibilities. 

These synthetic proteins are secreted outside of a cell into the surrounding environment, where researchers can collect and analyze them using a commercially available nanopore array. Here, the team used the Oxford Nanopore Technologies MinION device. 

The researchers engineered the NanoporeTER proteins with charged “tails” so that they can be pulled into the nanopore sensors by an electric field. Then the team uses machine learning to classify the electrical signals for each NanoporeTER barcode in order to determine each protein’s output levels.

“This is a fundamentally new interface between cells and computers,” said senior author Jeff Nivala, a UW research assistant professor in the Paul G. Allen School of Computer Science & Engineering. “One analogy I like to make is that fluorescent protein reporters are like lighthouses, and NanoporeTERs are like messages in a bottle. 

“Lighthouses are really useful for communicating a physical location, as you can literally see where the signal is coming from, but it’s hard to pack more information into that kind of signal. A message in a bottle, on the other hand, can pack a lot of information into a very small vessel, and you can send many of them off to another location to be read. You might lose sight of the precise physical location where the messages were sent, but for many applications that’s not going to be an issue.”

As a proof of concept, the team developed a library of more than 20 distinct NanoporeTERs tags. But the potential is significantly greater, according to co-lead author Karen Zhang, now a doctoral student in the UC Berkeley-UCSF bioengineering graduate program.

“We are currently working to scale up the number of NanoporeTERs to hundreds, thousands, maybe even millions more,” said Zhang, who graduated this year from the UW with bachelor’s degrees in both biochemistry and microbiology. “The more we have, the more things we can track.

“We’re particularly excited about the potential in single-cell proteomics, but this could also be a game-changer in terms of our ability to do multiplexed biosensing to diagnose disease and even target therapeutics to specific areas inside the body. And debugging complicated genetic circuit designs would become a whole lot easier and much less time-consuming if we could measure the performance of all the components in parallel instead of by trial and error.”

These researchers have made novel use of the MinION device before, when they developed a molecular tagging system to replace conventional inventory control methods. That system relied on barcodes comprising synthetic strands of DNA that could be decoded on demand using the portable reader. 

This time, the team went a step farther.

“This is the first paper to show how a commercial nanopore sensor device can be repurposed for applications other than the DNA and RNA sequencing for which they were originally designed,” said co-author Kathryn Doroschak, a computational biologist at Adaptive Biotechnologies who completed this work as a doctoral student at the Allen School. “This is exciting as a precursor for nanopore technology becoming more accessible and ubiquitous in the future. You can already plug a nanopore device into your cell phone. I could envision someday having a choice of ‘molecular apps’ that will be relatively inexpensive and widely available outside of traditional genomics.”

Additional co-authors of the paper are Aerilynn Nguyen at Northeastern University and Zoheb Siddiqui at Amazon, both former UW undergraduate students; Nicholas Bogard at Patch Biosciences, a former UW postdoctoral research associate; Luis Ceze, an Allen School professor; and Karin Strauss, an Allen School affiliate professor and a senior principal research manager at Microsoft. This research was funded by the National Science Foundation, the National Institutes of Health and a sponsored research agreement from Oxford Nanopore Technologies. 

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

Multiplexed direct detection of barcoded protein reporters on a nanopore array by Nicolas Cardozo, Karen Zhang, Kathryn Doroschak, Aerilynn Nguyen, Zoheb Siddiqui, Nicholas Bogard, Karin Strauss, Luis Ceze & Jeff Nivala. Nature Biotechnology (2021) DOI: https://doi.org/10.1038/s41587-021-01002-6 Published: 12 August 2021

This paper is behind a paywall.