Tag Archives: Tom Abate

Turning brain-controlled wireless electronic prostheses into reality plus some ethical points

Researchers at Stanford University (California, US) believe they have a solution for a problem with neuroprosthetics (Note: I have included brief comments about neuroprosthetics and possible ethical issues at the end of this posting) according an August 5, 2020 news item on ScienceDaily,

The current generation of neural implants record enormous amounts of neural activity, then transmit these brain signals through wires to a computer. But, so far, when researchers have tried to create wireless brain-computer interfaces to do this, it took so much power to transmit the data that the implants generated too much heat to be safe for the patient. A new study suggests how to solve his problem — and thus cut the wires.

Caption: Photo of a current neural implant, that uses wires to transmit information and receive power. New research suggests how to one day cut the wires. Credit: Sergey Stavisky

An August 3, 2020 Stanford University news release (also on EurekAlert but published August 4, 2020) by Tom Abate, which originated the news item, details the problem and the proposed solution,

Stanford researchers have been working for years to advance a technology that could one day help people with paralysis regain use of their limbs, and enable amputees to use their thoughts to control prostheses and interact with computers.

The team has been focusing on improving a brain-computer interface, a device implanted beneath the skull on the surface of a patient’s brain. This implant connects the human nervous system to an electronic device that might, for instance, help restore some motor control to a person with a spinal cord injury, or someone with a neurological condition like amyotrophic lateral sclerosis, also called Lou Gehrig’s disease.

The current generation of these devices record enormous amounts of neural activity, then transmit these brain signals through wires to a computer. But when researchers have tried to create wireless brain-computer interfaces to do this, it took so much power to transmit the data that the devices would generate too much heat to be safe for the patient.

Now, a team led by electrical engineers and neuroscientists Krishna Shenoy, PhD, and Boris Murmann, PhD, and neurosurgeon and neuroscientist Jaimie Henderson, MD, have shown how it would be possible to create a wireless device, capable of gathering and transmitting accurate neural signals, but using a tenth of the power required by current wire-enabled systems. These wireless devices would look more natural than the wired models and give patients freer range of motion.

Graduate student Nir Even-Chen and postdoctoral fellow Dante Muratore, PhD, describe the team’s approach in a Nature Biomedical Engineering paper.

The team’s neuroscientists identified the specific neural signals needed to control a prosthetic device, such as a robotic arm or a computer cursor. The team’s electrical engineers then designed the circuitry that would enable a future, wireless brain-computer interface to process and transmit these these carefully identified and isolated signals, using less power and thus making it safe to implant the device on the surface of the brain.

To test their idea, the researchers collected neuronal data from three nonhuman primates and one human participant in a (BrainGate) clinical trial.

As the subjects performed movement tasks, such as positioning a cursor on a computer screen, the researchers took measurements. The findings validated their hypothesis that a wireless interface could accurately control an individual’s motion by recording a subset of action-specific brain signals, rather than acting like the wired device and collecting brain signals in bulk.

The next step will be to build an implant based on this new approach and proceed through a series of tests toward the ultimate goal.

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

Power-saving design opportunities for wireless intracortical brain–computer interfaces by Nir Even-Chen, Dante G. Muratore, Sergey D. Stavisky, Leigh R. Hochberg, Jaimie M. Henderson, Boris Murmann & Krishna V. Shenoy. Nature Biomedical Engineering (2020) DOI: https://doi.org/10.1038/s41551-020-0595-9 Published: 03 August 2020

This paper is behind a paywall.

Comments about ethical issues

As I found out while investigating, ethical issues in this area abound. My first thought was to look at how someone with a focus on ability studies might view the complexities.

My ‘go to’ resource for human enhancement and ethical issues is Gregor Wolbring, an associate professor at the University of Calgary (Alberta, Canada). his profile lists these areas of interest: ability studies, disability studies, governance of emerging and existing sciences and technologies (e.g. neuromorphic engineering, genetics, synthetic biology, robotics, artificial intelligence, automatization, brain machine interfaces, sensors) and more.

I can’t find anything more recent on this particular topic but I did find an August 10, 2017 essay for The Conversation where he comments on technology and human enhancement ethical issues where the technology is gene-editing. Regardless, he makes points that are applicable to brain-computer interfaces (human enhancement), Note: Links have been removed),

Ability expectations have been and still are used to disable, or disempower, many people, not only people seen as impaired. They’ve been used to disable or marginalize women (men making the argument that rationality is an important ability and women don’t have it). They also have been used to disable and disempower certain ethnic groups (one ethnic group argues they’re smarter than another ethnic group) and others.

A recent Pew Research survey on human enhancement revealed that an increase in the ability to be productive at work was seen as a positive. What does such ability expectation mean for the “us” in an era of scientific advancements in gene-editing, human enhancement and robotics?

Which abilities are seen as more important than others?

The ability expectations among “us” will determine how gene-editing and other scientific advances will be used.

And so how we govern ability expectations, and who influences that governance, will shape the future. Therefore, it’s essential that ability governance and ability literacy play a major role in shaping all advancements in science and technology.

One of the reasons I find Gregor’s commentary so valuable is that he writes lucidly about ability and disability as concepts and poses what can be provocative questions about expectations and what it is to be truly abled or disabled. You can find more of his writing here on his eponymous (more or less) blog.

Ethics of clinical trials for testing brain implants

This October 31, 2017 article by Emily Underwood for Science was revelatory,

In 2003, neurologist Helen Mayberg of Emory University in Atlanta began to test a bold, experimental treatment for people with severe depression, which involved implanting metal electrodes deep in the brain in a region called area 25 [emphases mine]. The initial data were promising; eventually, they convinced a device company, St. Jude Medical in Saint Paul, to sponsor a 200-person clinical trial dubbed BROADEN.

This month [October 2017], however, Lancet Psychiatry reported the first published data on the trial’s failure. The study stopped recruiting participants in 2012, after a 6-month study in 90 people failed to show statistically significant improvements between those receiving active stimulation and a control group, in which the device was implanted but switched off.

… a tricky dilemma for companies and research teams involved in deep brain stimulation (DBS) research: If trial participants want to keep their implants [emphases mine], who will take responsibility—and pay—for their ongoing care? And participants in last week’s meeting said it underscores the need for the growing corps of DBS researchers to think long-term about their planned studies.

… participants bear financial responsibility for maintaining the device should they choose to keep it, and for any additional surgeries that might be needed in the future, Mayberg says. “The big issue becomes cost [emphasis mine],” she says. “We transition from having grants and device donations” covering costs, to patients being responsible. And although the participants agreed to those conditions before enrolling in the trial, Mayberg says she considers it a “moral responsibility” to advocate for lower costs for her patients, even it if means “begging for charity payments” from hospitals. And she worries about what will happen to trial participants if she is no longer around to advocate for them. “What happens if I retire, or get hit by a bus?” she asks.

There’s another uncomfortable possibility: that the hypothesis was wrong [emphases mine] to begin with. A large body of evidence from many different labs supports the idea that area 25 is “key to successful antidepressant response,” Mayberg says. But “it may be too simple-minded” to think that zapping a single brain node and its connections can effectively treat a disease as complex as depression, Krakauer [John Krakauer, a neuroscientist at Johns Hopkins University in Baltimore, Maryland] says. Figuring that out will likely require more preclinical research in people—a daunting prospect that raises additional ethical dilemmas, Krakauer says. “The hardest thing about being a clinical researcher,” he says, “is knowing when to jump.”

Brain-computer interfaces, symbiosis, and ethical issues

This was the most recent and most directly applicable work that I could find. From a July 24, 2019 article by Liam Drew for Nature Outlook: The brain,

“It becomes part of you,” Patient 6 said, describing the technology that enabled her, after 45 years of severe epilepsy, to halt her disabling seizures. Electrodes had been implanted on the surface of her brain that would send a signal to a hand-held device when they detected signs of impending epileptic activity. On hearing a warning from the device, Patient 6 knew to take a dose of medication to halt the coming seizure.

“You grow gradually into it and get used to it, so it then becomes a part of every day,” she told Frederic Gilbert, an ethicist who studies brain–computer interfaces (BCIs) at the University of Tasmania in Hobart, Australia. “It became me,” she said. [emphasis mine]

Gilbert was interviewing six people who had participated in the first clinical trial of a predictive BCI to help understand how living with a computer that monitors brain activity directly affects individuals psychologically1. Patient 6’s experience was extreme: Gilbert describes her relationship with her BCI as a “radical symbiosis”.

Symbiosis is a term, borrowed from ecology, that means an intimate co-existence of two species for mutual advantage. As technologists work towards directly connecting the human brain to computers, it is increasingly being used to describe humans’ potential relationship with artificial intelligence.

Interface technologies are divided into those that ‘read’ the brain to record brain activity and decode its meaning, and those that ‘write’ to the brain to manipulate activity in specific regions and affect their function.

Commercial research is opaque, but scientists at social-media platform Facebook are known to be pursuing brain-reading techniques for use in headsets that would convert users’ brain activity into text. And neurotechnology companies such as Kernel in Los Angeles, California, and Neuralink, founded by Elon Musk in San Francisco, California, predict bidirectional coupling in which computers respond to people’s brain activity and insert information into their neural circuitry. [emphasis mine]

Already, it is clear that melding digital technologies with human brains can have provocative effects, not least on people’s agency — their ability to act freely and according to their own choices. Although neuroethicists’ priority is to optimize medical practice, their observations also shape the debate about the development of commercial neurotechnologies.

Neuroethicists began to note the complex nature of the therapy’s side effects. “Some effects that might be described as personality changes are more problematic than others,” says Maslen [Hannah Maslen, a neuroethicist at the University of Oxford, UK]. A crucial question is whether the person who is undergoing stimulation can reflect on how they have changed. Gilbert, for instance, describes a DBS patient who started to gamble compulsively, blowing his family’s savings and seeming not to care. He could only understand how problematic his behaviour was when the stimulation was turned off.

Such cases present serious questions about how the technology might affect a person’s ability to give consent to be treated, or for treatment to continue. [emphases mine] If the person who is undergoing DBS is happy to continue, should a concerned family member or doctor be able to overrule them? If someone other than the patient can terminate treatment against the patient’s wishes, it implies that the technology degrades people’s ability to make decisions for themselves. It suggests that if a person thinks in a certain way only when an electrical current alters their brain activity, then those thoughts do not reflect an authentic self.

To observe a person with tetraplegia bringing a drink to their mouth using a BCI-controlled robotic arm is spectacular. [emphasis mine] This rapidly advancing technology works by implanting an array of electrodes either on or in a person’s motor cortex — a brain region involved in planning and executing movements. The activity of the brain is recorded while the individual engages in cognitive tasks, such as imagining that they are moving their hand, and these recordings are used to command the robotic limb.

If neuroscientists could unambiguously discern a person’s intentions from the chattering electrical activity that they record in the brain, and then see that it matched the robotic arm’s actions, ethical concerns would be minimized. But this is not the case. The neural correlates of psychological phenomena are inexact and poorly understood, which means that signals from the brain are increasingly being processed by artificial intelligence (AI) software before reaching prostheses.[emphasis mine]

But, he [Philipp Kellmeyer, a neurologist and neuroethicist at the University of Freiburg, Germany] says, using AI tools also introduces ethical issues of which regulators have little experience. [emphasis mine] Machine-learning software learns to analyse data by generating algorithms that cannot be predicted and that are difficult, or impossible, to comprehend. This introduces an unknown and perhaps unaccountable process between a person’s thoughts and the technology that is acting on their behalf.

Maslen is already helping to shape BCI-device regulation. She is in discussion with the European Commission about regulations it will implement in 2020 that cover non-invasive brain-modulating devices that are sold straight to consumers. [emphases mine; Note: There is a Canadian company selling this type of product, MUSE] Maslen became interested in the safety of these devices, which were covered by only cursory safety regulations. Although such devices are simple, they pass electrical currents through people’s scalps to modulate brain activity. Maslen found reports of them causing burns, headaches and visual disturbances. She also says clinical studies have shown that, although non-invasive electrical stimulation of the brain can enhance certain cognitive abilities, this can come at the cost of deficits in other aspects of cognition.

Regarding my note about MUSE, the company is InteraXon and its product is MUSE.They advertise the product as “Brain Sensing Headbands That Improve Your Meditation Practice.” The company website and the product seem to be one entity, Choose Muse. The company’s product has been used in some serious research papers they can be found here. I did not see any research papers concerning safety issues.

Getting back to Drew’s July 24, 2019 article and Patient 6,

… He [Gilbert] is now preparing a follow-up report on Patient 6. The company that implanted the device in her brain to help free her from seizures went bankrupt. The device had to be removed.

… Patient 6 cried as she told Gilbert about losing the device. … “I lost myself,” she said.

“It was more than a device,” Gilbert says. “The company owned the existence of this new person.”

I strongly recommend reading Drew’s July 24, 2019 article in its entirety.

Finally

It’s easy to forget that in all the excitement over technologies ‘making our lives better’ that there can be a dark side or two. Some of the points brought forth in the articles by Wolbring, Underwood, and Drew confirmed my uneasiness as reasonable and gave me some specific examples of how these technologies raise new issues or old issues in new ways.

What I find interesting is that no one is using the term ‘cyborg’, which would seem quite applicable.There is an April 20, 2012 posting here titled ‘My mother is a cyborg‘ where I noted that by at lease one definition people with joint replacements, pacemakers, etc. are considered cyborgs. In short, cyborgs or technology integrated into bodies have been amongst us for quite some time.

Interestingly, no one seems to care much when insects are turned into cyborgs (can’t remember who pointed this out) but it is a popular area of research especially for military applications and search and rescue applications.

I’ve sometimes used the term ‘machine/flesh’ and or ‘augmentation’ as a description of technologies integrated with bodies, human or otherwise. You can find lots on the topic here however I’ve tagged or categorized it.

Amongst other pieces you can find here, there’s the August 8, 2016 posting, ‘Technology, athletics, and the ‘new’ human‘ featuring Oscar Pistorius when he was still best known as the ‘blade runner’ and a remarkably successful paralympic athlete. It’s about his efforts to compete against able-bodied athletes at the London Olympic Games in 2012. It is fascinating to read about technology and elite athletes of any kind as they are often the first to try out ‘enhancements’.

Gregor Wolbring has a number of essays on The Conversation looking at Paralympic athletes and their pursuit of enhancements and how all of this is affecting our notions of abilities and disabilities. By extension, one has to assume that ‘abled’ athletes are also affected with the trickle-down effect on the rest of us.

Regardless of where we start the investigation, there is a sameness to the participants in neuroethics discussions with a few experts and commercial interests deciding on how the rest of us (however you define ‘us’ as per Gregor Wolbring’s essay) will live.

This paucity of perspectives is something I was getting at in my COVID-19 editorial for the Canadian Science Policy Centre. My thesis being that we need a range of ideas and insights that cannot be culled from small groups of people who’ve trained and read the same materials or entrepreneurs who too often seem to put profit over thoughtful implementations of new technologies. (See the PDF May 2020 edition [you’ll find me under Policy Development]) or see my May 15, 2020 posting here (with all the sources listed.)

As for this new research at Stanford, it’s exciting news, which raises questions, as it offers the hope of independent movement for people diagnosed as tetraplegic (sometimes known as quadriplegic.)

How might artificial intelligence affect urban life in 2030? A study

Peering into the future is always a chancy business as anyone who’s seen those film shorts from the 1950’s and 60’s which speculate exuberantly as to what the future will bring knows.

A sober approach (appropriate to our times) has been taken in a study about the impact that artificial intelligence might have by 2030. From a Sept. 1, 2016 Stanford University news release (also on EurekAlert) by Tom Abate (Note: Links have been removed),

A panel of academic and industrial thinkers has looked ahead to 2030 to forecast how advances in artificial intelligence (AI) might affect life in a typical North American city – in areas as diverse as transportation, health care and education ­– and to spur discussion about how to ensure the safe, fair and beneficial development of these rapidly emerging technologies.

Titled “Artificial Intelligence and Life in 2030,” this year-long investigation is the first product of the One Hundred Year Study on Artificial Intelligence (AI100), an ongoing project hosted by Stanford to inform societal deliberation and provide guidance on the ethical development of smart software, sensors and machines.

“We believe specialized AI applications will become both increasingly common and more useful by 2030, improving our economy and quality of life,” said Peter Stone, a computer scientist at the University of Texas at Austin and chair of the 17-member panel of international experts. “But this technology will also create profound challenges, affecting jobs and incomes and other issues that we should begin addressing now to ensure that the benefits of AI are broadly shared.”

The new report traces its roots to a 2009 study that brought AI scientists together in a process of introspection that became ongoing in 2014, when Eric and Mary Horvitz created the AI100 endowment through Stanford. AI100 formed a standing committee of scientists and charged this body with commissioning periodic reports on different aspects of AI over the ensuing century.

“This process will be a marathon, not a sprint, but today we’ve made a good start,” said Russ Altman, a professor of bioengineering and the Stanford faculty director of AI100. “Stanford is excited to host this process of introspection. This work makes practical contribution to the public debate on the roles and implications of artificial intelligence.”

The AI100 standing committee first met in 2015, led by chairwoman and Harvard computer scientist Barbara Grosz. It sought to convene a panel of scientists with diverse professional and personal backgrounds and enlist their expertise to assess the technological, economic and policy implications of potential AI applications in a societally relevant setting.

“AI technologies can be reliable and broadly beneficial,” Grosz said. “Being transparent about their design and deployment challenges will build trust and avert unjustified fear and suspicion.”

The report investigates eight domains of human activity in which AI technologies are beginning to affect urban life in ways that will become increasingly pervasive and profound by 2030.

The 28,000-word report includes a glossary to help nontechnical readers understand how AI applications such as computer vision might help screen tissue samples for cancers or how natural language processing will allow computerized systems to grasp not simply the literal definitions, but the connotations and intent, behind words.

The report is broken into eight sections focusing on applications of AI. Five examine application arenas such as transportation where there is already buzz about self-driving cars. Three other sections treat technological impacts, like the section on employment and workplace trends which touches on the likelihood of rapid changes in jobs and incomes.

“It is not too soon for social debate on how the fruits of an AI-dominated economy should be shared,” the researchers write in the report, noting also the need for public discourse.

“Currently in the United States, at least sixteen separate agencies govern sectors of the economy related to AI technologies,” the researchers write, highlighting issues raised by AI applications: “Who is responsible when a self-driven car crashes or an intelligent medical device fails? How can AI applications be prevented from [being used for] racial discrimination or financial cheating?”

The eight sections discuss:

Transportation: Autonomous cars, trucks and, possibly, aerial delivery vehicles may alter how we commute, work and shop and create new patterns of life and leisure in cities.

Home/service robots: Like the robotic vacuum cleaners already in some homes, specialized robots will clean and provide security in live/work spaces that will be equipped with sensors and remote controls.

Health care: Devices to monitor personal health and robot-assisted surgery are hints of things to come if AI is developed in ways that gain the trust of doctors, nurses, patients and regulators.

Education: Interactive tutoring systems already help students learn languages, math and other skills. More is possible if technologies like natural language processing platforms develop to augment instruction by humans.

Entertainment: The conjunction of content creation tools, social networks and AI will lead to new ways to gather, organize and deliver media in engaging, personalized and interactive ways.

Low-resource communities: Investments in uplifting technologies like predictive models to prevent lead poisoning or improve food distributions could spread AI benefits to the underserved.

Public safety and security: Cameras, drones and software to analyze crime patterns should use AI in ways that reduce human bias and enhance safety without loss of liberty or dignity.

Employment and workplace: Work should start now on how to help people adapt as the economy undergoes rapid changes as many existing jobs are lost and new ones are created.

“Until now, most of what is known about AI comes from science fiction books and movies,” Stone said. “This study provides a realistic foundation to discuss how AI technologies are likely to affect society.”

Grosz said she hopes the AI 100 report “initiates a century-long conversation about ways AI-enhanced technologies might be shaped to improve life and societies.”

You can find the A100 website here, and the group’s first paper: “Artificial Intelligence and Life in 2030” here. Unfortunately, I don’t have time to read the report but I hope to do so soon.

The AI100 website’s About page offered a surprise,

This effort, called the One Hundred Year Study on Artificial Intelligence, or AI100, is the brainchild of computer scientist and Stanford alumnus Eric Horvitz who, among other credits, is a former president of the Association for the Advancement of Artificial Intelligence.

In that capacity Horvitz convened a conference in 2009 at which top researchers considered advances in artificial intelligence and its influences on people and society, a discussion that illuminated the need for continuing study of AI’s long-term implications.

Now, together with Russ Altman, a professor of bioengineering and computer science at Stanford, Horvitz has formed a committee that will select a panel to begin a series of periodic studies on how AI will affect automation, national security, psychology, ethics, law, privacy, democracy and other issues.

“Artificial intelligence is one of the most profound undertakings in science, and one that will affect every aspect of human life,” said Stanford President John Hennessy, who helped initiate the project. “Given’s Stanford’s pioneering role in AI and our interdisciplinary mindset, we feel obliged and qualified to host a conversation about how artificial intelligence will affect our children and our children’s children.”

Five leading academicians with diverse interests will join Horvitz and Altman in launching this effort. They are:

  • Barbara Grosz, the Higgins Professor of Natural Sciences at HarvardUniversity and an expert on multi-agent collaborative systems;
  • Deirdre K. Mulligan, a lawyer and a professor in the School of Information at the University of California, Berkeley, who collaborates with technologists to advance privacy and other democratic values through technical design and policy;

    This effort, called the One Hundred Year Study on Artificial Intelligence, or AI100, is the brainchild of computer scientist and Stanford alumnus Eric Horvitz who, among other credits, is a former president of the Association for the Advancement of Artificial Intelligence.

    In that capacity Horvitz convened a conference in 2009 at which top researchers considered advances in artificial intelligence and its influences on people and society, a discussion that illuminated the need for continuing study of AI’s long-term implications.

    Now, together with Russ Altman, a professor of bioengineering and computer science at Stanford, Horvitz has formed a committee that will select a panel to begin a series of periodic studies on how AI will affect automation, national security, psychology, ethics, law, privacy, democracy and other issues.

    “Artificial intelligence is one of the most profound undertakings in science, and one that will affect every aspect of human life,” said Stanford President John Hennessy, who helped initiate the project. “Given’s Stanford’s pioneering role in AI and our interdisciplinary mindset, we feel obliged and qualified to host a conversation about how artificial intelligence will affect our children and our children’s children.”

    Five leading academicians with diverse interests will join Horvitz and Altman in launching this effort. They are:

    • Barbara Grosz, the Higgins Professor of Natural Sciences at HarvardUniversity and an expert on multi-agent collaborative systems;
    • Deirdre K. Mulligan, a lawyer and a professor in the School of Information at the University of California, Berkeley, who collaborates with technologists to advance privacy and other democratic values through technical design and policy;
    • Yoav Shoham, a professor of computer science at Stanford, who seeks to incorporate common sense into AI;
    • Tom Mitchell, the E. Fredkin University Professor and chair of the machine learning department at Carnegie Mellon University, whose studies include how computers might learn to read the Web;
    • and Alan Mackworth, a professor of computer science at the University of British Columbia [emphases mine] and the Canada Research Chair in Artificial Intelligence, who built the world’s first soccer-playing robot.

    I wasn’t expecting to see a Canadian listed as a member of the AI100 standing committee and then I got another surprise (from the AI100 People webpage),

    Study Panels

    Study Panels are planned to convene every 5 years to examine some aspect of AI and its influences on society and the world. The first study panel was convened in late 2015 to study the likely impacts of AI on urban life by the year 2030, with a focus on typical North American cities.

    2015 Study Panel Members

    • Peter Stone, UT Austin, Chair
    • Rodney Brooks, Rethink Robotics
    • Erik Brynjolfsson, MIT
    • Ryan Calo, University of Washington
    • Oren Etzioni, Allen Institute for AI
    • Greg Hager, Johns Hopkins University
    • Julia Hirschberg, Columbia University
    • Shivaram Kalyanakrishnan, IIT Bombay
    • Ece Kamar, Microsoft
    • Sarit Kraus, Bar Ilan University
    • Kevin Leyton-Brown, [emphasis mine] UBC [University of British Columbia]
    • David Parkes, Harvard
    • Bill Press, UT Austin
    • AnnaLee (Anno) Saxenian, Berkeley
    • Julie Shah, MIT
    • Milind Tambe, USC
    • Astro Teller, Google[X]
  • [emphases mine] and the Canada Research Chair in Artificial Intelligence, who built the world’s first soccer-playing robot.

I wasn’t expecting to see a Canadian listed as a member of the AI100 standing committee and then I got another surprise (from the AI100 People webpage),

Study Panels

Study Panels are planned to convene every 5 years to examine some aspect of AI and its influences on society and the world. The first study panel was convened in late 2015 to study the likely impacts of AI on urban life by the year 2030, with a focus on typical North American cities.

2015 Study Panel Members

  • Peter Stone, UT Austin, Chair
  • Rodney Brooks, Rethink Robotics
  • Erik Brynjolfsson, MIT
  • Ryan Calo, University of Washington
  • Oren Etzioni, Allen Institute for AI
  • Greg Hager, Johns Hopkins University
  • Julia Hirschberg, Columbia University
  • Shivaram Kalyanakrishnan, IIT Bombay
  • Ece Kamar, Microsoft
  • Sarit Kraus, Bar Ilan University
  • Kevin Leyton-Brown, [emphasis mine] UBC [University of British Columbia]
  • David Parkes, Harvard
  • Bill Press, UT Austin
  • AnnaLee (Anno) Saxenian, Berkeley
  • Julie Shah, MIT
  • Milind Tambe, USC
  • Astro Teller, Google[X]

I see they have representation from Israel, India, and the private sector as well. Refreshingly, there’s more than one woman on the standing committee and in this first study group. It’s good to see these efforts at inclusiveness and I’m particularly delighted with the inclusion of an organization from Asia. All too often inclusiveness means Europe, especially the UK. So, it’s good (and I think important) to see a different range of representation.

As for the content of report, should anyone have opinions about it, please do let me know your thoughts in the blog comments.

Cooling the skin with plastic clothing

Rather that cooling or heating an entire room, why not cool or heat the person? Engineers at Stanford University (California, US) have developed a material that helps with half of that premise: cooling. From a Sept. 1, 2016 news item on ScienceDaily,

Stanford engineers have developed a low-cost, plastic-based textile that, if woven into clothing, could cool your body far more efficiently than is possible with the natural or synthetic fabrics in clothes we wear today.

Describing their work in Science, the researchers suggest that this new family of fabrics could become the basis for garments that keep people cool in hot climates without air conditioning.

“If you can cool the person rather than the building where they work or live, that will save energy,” said Yi Cui, an associate professor of materials science and engineering and of photon science at Stanford.

A Sept. 1, 2016 Stanford University news release (also on EurekAlert) by Tom Abate, which originated the news item, further explains the information in the video,

This new material works by allowing the body to discharge heat in two ways that would make the wearer feel nearly 4 degrees Fahrenheit cooler than if they wore cotton clothing.

The material cools by letting perspiration evaporate through the material, something ordinary fabrics already do. But the Stanford material provides a second, revolutionary cooling mechanism: allowing heat that the body emits as infrared radiation to pass through the plastic textile.

All objects, including our bodies, throw off heat in the form of infrared radiation, an invisible and benign wavelength of light. Blankets warm us by trapping infrared heat emissions close to the body. This thermal radiation escaping from our bodies is what makes us visible in the dark through night-vision goggles.

“Forty to 60 percent of our body heat is dissipated as infrared radiation when we are sitting in an office,” said Shanhui Fan, a professor of electrical engineering who specializes in photonics, which is the study of visible and invisible light. “But until now there has been little or no research on designing the thermal radiation characteristics of textiles.”

Super-powered kitchen wrap

To develop their cooling textile, the Stanford researchers blended nanotechnology, photonics and chemistry to give polyethylene – the clear, clingy plastic we use as kitchen wrap – a number of characteristics desirable in clothing material: It allows thermal radiation, air and water vapor to pass right through, and it is opaque to visible light.

The easiest attribute was allowing infrared radiation to pass through the material, because this is a characteristic of ordinary polyethylene food wrap. Of course, kitchen plastic is impervious to water and is see-through as well, rendering it useless as clothing.

The Stanford researchers tackled these deficiencies one at a time.

First, they found a variant of polyethylene commonly used in battery making that has a specific nanostructure that is opaque to visible light yet is transparent to infrared radiation, which could let body heat escape. This provided a base material that was opaque to visible light for the sake of modesty but thermally transparent for purposes of energy efficiency.

They then modified the industrial polyethylene by treating it with benign chemicals to enable water vapor molecules to evaporate through nanopores in the plastic, said postdoctoral scholar and team member Po-Chun Hsu, allowing the plastic to breathe like a natural fiber.

Making clothes

That success gave the researchers a single-sheet material that met their three basic criteria for a cooling fabric. To make this thin material more fabric-like, they created a three-ply version: two sheets of treated polyethylene separated by a cotton mesh for strength and thickness.

To test the cooling potential of their three-ply construct versus a cotton fabric of comparable thickness, they placed a small swatch of each material on a surface that was as warm as bare skin and measured how much heat each material trapped.

“Wearing anything traps some heat and makes the skin warmer,” Fan said. “If dissipating thermal radiation were our only concern, then it would be best to wear nothing.”

The comparison showed that the cotton fabric made the skin surface 3.6 F warmer than their cooling textile. The researchers said this difference means that a person dressed in their new material might feel less inclined to turn on a fan or air conditioner.

The researchers are continuing their work on several fronts, including adding more colors, textures and cloth-like characteristics to their material. Adapting a material already mass produced for the battery industry could make it easier to create products.

“If you want to make a textile, you have to be able to make huge volumes inexpensively,” Cui said.

Fan believes that this research opens up new avenues of inquiry to cool or heat things, passively, without the use of outside energy, by tuning materials to dissipate or trap infrared radiation.

“In hindsight, some of what we’ve done looks very simple, but it’s because few have really been looking at engineering the radiation characteristics of textiles,” he said.

Dexter Johnson (Nanoclast blog on the IEEE [Institute of Electrical and Electronics Engineers] website) has written a Sept. 2, 2016 posting where he provides more technical detail about this work,

The nanoPE [nanoporous polyethylene] material is able to achieve this release of the IR heat because of the size of the interconnected pores. The pores can range in size from 50 to 1000 nanometers. They’re therefore comparable in size to wavelengths of visible light, which allows the material to scatter that light. However, because the pores are much smaller than the wavelength of infrared light, the nanoPE is transparent to the IR.

It is this combination of blocking visible light and allowing IR to pass through that distinguishes the nanoPE material from regular polyethylene, which allows similar amounts of IR to pass through, but can only block 20 percent of the visible light compared to nanoPE’s 99 percent opacity.

The Stanford researchers were also able to improve on the water wicking capability of the nanoPE material by using a microneedle punching technique and coating the material with a water-repelling agent. The result is that perspiration can evaporate through the material unlike with regular polyethylene.

For those who wish to further pursue their interest, Dexter has a lively writing style and he provides more detail and insight in his posting.

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

Radiative human body cooling by nanoporous polyethylene textile by Po-Chun Hsu, Alex Y. Song, Peter B. Catrysse, Chong Liu, Yucan Peng, Jin Xie, Shanhui Fan, Yi Cui. Science  02 Sep 2016: Vol. 353, Issue 6303, pp. 1019-1023 DOI: 10.1126/science.aaf5471

This paper is open access.

Carbon nanotubes a second way: Cedric, the carbon nanotube computer

On the heels of yesterday’s(Sept. 26, 2013) posting about carbon nnanotubes as flexible gas sensors, I have this item about a computer fashioned from carbon nanotubes.

This wafer contains tiny computers using carbon nanotubes, a material that could lead to smaller, more energy-efficient processors. Courtesy Standford University

This wafer contains tiny computers using carbon nanotubes, a material that could lead to smaller, more energy-efficient processors. Courtesy Stanford University

To me this looks more like a ping pong bat than a computer wafer. Regardless, here’s more about it from a Sept. 25, 2013 news item by James Morgan for BBC (British Broadcasting Corporation) News online,

The first computer built entirely with carbon nanotubes has been unveiled, opening the door to a new generation of digital devices.

“Cedric” is only a basic prototype but could be developed into a machine which is smaller, faster and more efficient than today’s silicon models.

Nanotubes have long been touted as the heir to silicon’s throne, but building a working computer has proven awkward.

Cedric is the most complex carbon-based electronic system yet realised.

So is it fast? Not at all. It might have been in 1955.
The computer operates on just one bit of information, and can only count to 32.

“In human terms, Cedric can count on his hands and sort the alphabet. But he is, in the full sense of the word, a computer,” says co-author [of the paper published in Nature] Max Shulaker.

Tom Abate’s Sept. 26, 2013 article for Stanford Report provides more detail about carbon nanotubes, their potential for replacing silicon chips and associated problems,

“Carbon nanotubes [CNTs] have long been considered as a potential successor to the silicon transistor,” said Professor Jan Rabaey, a world expert on electronic circuits and systems at the University of California-Berkeley.

Why worry about a successor to silicon?

Such concerns arise from the demands that designers place upon semiconductors and their fundamental workhorse unit, those on-off switches known as transistors.

For decades, progress in electronics has meant shrinking the size of each transistor to pack more transistors on a chip. But as transistors become tinier, they waste more power and generate more heat – all in a smaller and smaller space, as evidenced by the warmth emanating from the bottom of a laptop.

Many researchers believe that this power-wasting phenomenon could spell the end of Moore’s Law, named for Intel Corp. co-founder Gordon Moore, who predicted in 1965 that the density of transistors would double roughly every two years, leading to smaller, faster and, as it turned out, cheaper electronics.

But smaller, faster and cheaper has also meant smaller, faster and hotter.

“CNTs could take us at least an order of magnitude in performance beyond where you can project silicon could take us,” Wong [another co-author of the paper]  said.

But inherent imperfections have stood in the way of putting this promising material to practical use.

First, CNTs do not necessarily grow in neat parallel lines, as chipmakers would like.

Over time, researchers have devised tricks to grow 99.5 percent of CNTs in straight lines. But with billions of nanotubes on a chip, even a tiny degree of misaligned tubes could cause errors, so that problem remained.

A second type of imperfection has also stymied CNT technology.

Depending on how the CNTs grow, a fraction of these carbon nanotubes can end up behaving like metallic wires that always conduct electricity, instead of acting like semiconductors that can be switched off.

Since mass production is the eventual goal, researchers had to find ways to deal with misaligned and/or metallic CNTs without having to hunt for them like needles in a haystack.

“We needed a way to design circuits without having to look for imperfections or even know where they were,” Mitra said.

The researchers have dubbed their solution an “imperfection-immune design,” from the Abate article,

To eliminate the wire-like or metallic nanotubes, the Stanford team switched off all the good CNTs. Then they pumped the semiconductor circuit full of electricity. All of that electricity concentrated in the metallic nanotubes, which grew so hot that they burned up and literally vaporized into tiny puffs of carbon dioxide. This sophisticated technique eliminated the metallic CNTs in the circuit.

Bypassing the misaligned nanotubes required even greater subtlety.

The Stanford researchers created a powerful algorithm that maps out a circuit layout that is guaranteed to work no matter whether or where CNTs might be askew.

“This ‘imperfections-immune design’ [technique] makes this discovery truly exemplary,” said Sankar Basu, a program director at the National Science Foundation.

The Stanford team used this imperfection-immune design to assemble a basic computer with 178 transistors, a limit imposed by the fact that they used the university’s chip-making facilities rather than an industrial fabrication process.

Their CNT computer performed tasks such as counting and number sorting. It runs a basic operating system that allows it to swap between these processes. In a demonstration of its potential, the researchers also showed that the CNT computer could run MIPS, a commercial instruction set developed in the early 1980s by then Stanford engineering professor and now university President John Hennessy.

Though it could take years to mature, the Stanford approach points toward the possibility of industrial-scale production of carbon nanotube semiconductors, according to Naresh Shanbhag, a professor at the University of Illinois at Urbana-Champaign and director of SONIC, a consortium of next-generation chip design research.

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

Carbon nanotube computer by Max M. Shulaker, Gage Hills, Nishant Patil, Hai Wei, Hong-Yu Chen, H.-S. Philip Wong, & Subhasish Mitra. Nature 501, 526–530 (26 September 2013) doi:10.1038/nature12502

This article is behind a paywall but you can gain temporary access via ReadCube.