Tag Archives: androids

Of sleep, electric sheep, and thousands of artificial synapses on a chip

A close-up view of a new neuromorphic “brain-on-a-chip” that includes tens of thousands of memristors, or memory transistors. Credit: Peng Lin Courtesy: MIT

It’s hard to believe that a brain-on-a-chip might need sleep but that seems to be the case as far as the US Dept. of Energy’s Los Alamos National Laboratory is concerned. Before pursuing that line of thought, here’s some work from the Massachusetts Institute of Technology (MIT) involving memristors and a brain-on-a-chip. From a June 8, 2020 news item on ScienceDaily,

MIT engineers have designed a “brain-on-a-chip,” smaller than a piece of confetti, that is made from tens of thousands of artificial brain synapses known as memristors — silicon-based components that mimic the information-transmitting synapses in the human brain.

The researchers borrowed from principles of metallurgy to fabricate each memristor from alloys of silver and copper, along with silicon. When they ran the chip through several visual tasks, the chip was able to “remember” stored images and reproduce them many times over, in versions that were crisper and cleaner compared with existing memristor designs made with unalloyed elements.

Their results, published today in the journal Nature Nanotechnology, demonstrate a promising new memristor design for neuromorphic devices — electronics that are based on a new type of circuit that processes information in a way that mimics the brain’s neural architecture. Such brain-inspired circuits could be built into small, portable devices, and would carry out complex computational tasks that only today’s supercomputers can handle.

This ‘metallurgical’ approach differs somewhat from the protein nanowire approach used by the University of Massachusetts at Amherst team mentioned in my June 15, 2020 posting. Scientists are pursuing multiple pathways and we may find that we arrive with not ‘a single artificial brain but with many types of artificial brains.

A June 8, 2020 MIT news release (also on EurekAlert) provides more detail about this brain-on-a-chip,

“So far, artificial synapse networks exist as software. We’re trying to build real neural network hardware for portable artificial intelligence systems,” says Jeehwan Kim, associate professor of mechanical engineering at MIT. “Imagine connecting a neuromorphic device to a camera on your car, and having it recognize lights and objects and make a decision immediately, without having to connect to the internet. We hope to use energy-efficient memristors to do those tasks on-site, in real-time.”

Wandering ions

Memristors, or memory transistors [Note: Memristors are usually described as memory resistors; this is the first time I’ve seen ‘memory transistor’], are an essential element in neuromorphic computing. In a neuromorphic device, a memristor would serve as the transistor in a circuit, though its workings would more closely resemble a brain synapse — the junction between two neurons. The synapse receives signals from one neuron, in the form of ions, and sends a corresponding signal to the next neuron.

A transistor in a conventional circuit transmits information by switching between one of only two values, 0 and 1, and doing so only when the signal it receives, in the form of an electric current, is of a particular strength. In contrast, a memristor would work along a gradient, much like a synapse in the brain. The signal it produces would vary depending on the strength of the signal that it receives. This would enable a single memristor to have many values, and therefore carry out a far wider range of operations than binary transistors.

Like a brain synapse, a memristor would also be able to “remember” the value associated with a given current strength, and produce the exact same signal the next time it receives a similar current. This could ensure that the answer to a complex equation, or the visual classification of an object, is reliable — a feat that normally involves multiple transistors and capacitors.

Ultimately, scientists envision that memristors would require far less chip real estate than conventional transistors, enabling powerful, portable computing devices that do not rely on supercomputers, or even connections to the Internet.

Existing memristor designs, however, are limited in their performance. A single memristor is made of a positive and negative electrode, separated by a “switching medium,” or space between the electrodes. When a voltage is applied to one electrode, ions from that electrode flow through the medium, forming a “conduction channel” to the other electrode. The received ions make up the electrical signal that the memristor transmits through the circuit. The size of the ion channel (and the signal that the memristor ultimately produces) should be proportional to the strength of the stimulating voltage.

Kim says that existing memristor designs work pretty well in cases where voltage stimulates a large conduction channel, or a heavy flow of ions from one electrode to the other. But these designs are less reliable when memristors need to generate subtler signals, via thinner conduction channels.

The thinner a conduction channel, and the lighter the flow of ions from one electrode to the other, the harder it is for individual ions to stay together. Instead, they tend to wander from the group, disbanding within the medium. As a result, it’s difficult for the receiving electrode to reliably capture the same number of ions, and therefore transmit the same signal, when stimulated with a certain low range of current.

Borrowing from metallurgy

Kim and his colleagues found a way around this limitation by borrowing a technique from metallurgy, the science of melding metals into alloys and studying their combined properties.

“Traditionally, metallurgists try to add different atoms into a bulk matrix to strengthen materials, and we thought, why not tweak the atomic interactions in our memristor, and add some alloying element to control the movement of ions in our medium,” Kim says.

Engineers typically use silver as the material for a memristor’s positive electrode. Kim’s team looked through the literature to find an element that they could combine with silver to effectively hold silver ions together, while allowing them to flow quickly through to the other electrode.

The team landed on copper as the ideal alloying element, as it is able to bind both with silver, and with silicon.

“It acts as a sort of bridge, and stabilizes the silver-silicon interface,” Kim says.

To make memristors using their new alloy, the group first fabricated a negative electrode out of silicon, then made a positive electrode by depositing a slight amount of copper, followed by a layer of silver. They sandwiched the two electrodes around an amorphous silicon medium. In this way, they patterned a millimeter-square silicon chip with tens of thousands of memristors.

As a first test of the chip, they recreated a gray-scale image of the Captain America shield. They equated each pixel in the image to a corresponding memristor in the chip. They then modulated the conductance of each memristor that was relative in strength to the color in the corresponding pixel.

The chip produced the same crisp image of the shield, and was able to “remember” the image and reproduce it many times, compared with chips made of other materials.

The team also ran the chip through an image processing task, programming the memristors to alter an image, in this case of MIT’s Killian Court, in several specific ways, including sharpening and blurring the original image. Again, their design produced the reprogrammed images more reliably than existing memristor designs.

“We’re using artificial synapses to do real inference tests,” Kim says. “We would like to develop this technology further to have larger-scale arrays to do image recognition tasks. And some day, you might be able to carry around artificial brains to do these kinds of tasks, without connecting to supercomputers, the internet, or the cloud.”

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

Alloying conducting channels for reliable neuromorphic computing by Hanwool Yeon, Peng Lin, Chanyeol Choi, Scott H. Tan, Yongmo Park, Doyoon Lee, Jaeyong Lee, Feng Xu, Bin Gao, Huaqiang Wu, He Qian, Yifan Nie, Seyoung Kim & Jeehwan Kim. Nature Nanotechnology (2020 DOI: https://doi.org/10.1038/s41565-020-0694-5 Published: 08 June 2020

This paper is behind a paywall.

Electric sheep and sleeping androids

I find it impossible to mention that androids might need sleep without reference to Philip K. Dick’s 1968 novel, “Do Androids Dream of Electric Sheep?”; its Wikipedia entry is here.

June 8, 2020 Intelligent machines of the future may need to sleep as much as we do. Intelligent machines of the future may need to sleep as much as we do. Courtesy: Los Alamos National Laboratory

As it happens, I’m not the only one who felt the need to reference the novel, from a June 8, 2020 news item on ScienceDaily,

No one can say whether androids will dream of electric sheep, but they will almost certainly need periods of rest that offer benefits similar to those that sleep provides to living brains, according to new research from Los Alamos National Laboratory.

“We study spiking neural networks, which are systems that learn much as living brains do,” said Los Alamos National Laboratory computer scientist Yijing Watkins. “We were fascinated by the prospect of training a neuromorphic processor in a manner analogous to how humans and other biological systems learn from their environment during childhood development.”

Watkins and her research team found that the network simulations became unstable after continuous periods of unsupervised learning. When they exposed the networks to states that are analogous to the waves that living brains experience during sleep, stability was restored. “It was as though we were giving the neural networks the equivalent of a good night’s rest,” said Watkins.

A June 8, 2020 Los Alamos National Laboratory (LANL) news release (also on EurekAlert), which originated the news item, describes the research team’s presentation,

The discovery came about as the research team worked to develop neural networks that closely approximate how humans and other biological systems learn to see. The group initially struggled with stabilizing simulated neural networks undergoing unsupervised dictionary training, which involves classifying objects without having prior examples to compare them to.

“The issue of how to keep learning systems from becoming unstable really only arises when attempting to utilize biologically realistic, spiking neuromorphic processors or when trying to understand biology itself,” said Los Alamos computer scientist and study coauthor Garrett Kenyon. “The vast majority of machine learning, deep learning, and AI researchers never encounter this issue because in the very artificial systems they study they have the luxury of performing global mathematical operations that have the effect of regulating the overall dynamical gain of the system.”

The researchers characterize the decision to expose the networks to an artificial analog of sleep as nearly a last ditch effort to stabilize them. They experimented with various types of noise, roughly comparable to the static you might encounter between stations while tuning a radio. The best results came when they used waves of so-called Gaussian noise, which includes a wide range of frequencies and amplitudes. They hypothesize that the noise mimics the input received by biological neurons during slow-wave sleep. The results suggest that slow-wave sleep may act, in part, to ensure that cortical neurons maintain their stability and do not hallucinate.

The groups’ next goal is to implement their algorithm on Intel’s Loihi neuromorphic chip. They hope allowing Loihi to sleep from time to time will enable it to stably process information from a silicon retina camera in real time. If the findings confirm the need for sleep in artificial brains, we can probably expect the same to be true of androids and other intelligent machines that may come about in the future.

Watkins will be presenting the research at the Women in Computer Vision Workshop on June 14 [2020] in Seattle.

The 2020 Women in Computer Vition Workshop (WICV) website is here. As is becoming standard practice for these times, the workshop was held in a virtual environment. Here’s a link to and a citation for the poster presentation paper,

Using Sinusoidally-Modulated Noise as a Surrogate for Slow-Wave Sleep to
Accomplish Stable Unsupervised Dictionary Learning in a Spike-Based Sparse Coding Model
by Yijing Watkins, Edward Kim, Andrew Sornborger and Garrett T. Kenyon. Women in Computer Vision Workshop on June 14, 2020 in Seattle, Washington (state)

This paper is open access for now.

A potpourri of robot/AI stories: killers , kindergarten teachers, a Balenciaga-inspired AI fashion designer, a conversational android, and more

Following on my August 29, 2018 post (Sexbots, sexbot ethics, families, and marriage), I’m following up with a more general piece.

Robots, AI (artificial intelligence), and androids (humanoid robots), the terms can be confusing since there’s a tendency to use them interchangeably. Confession: I do it too, but, not this time. That said, I have multiple news bits.

Killer ‘bots and ethics

The U.S. military is already testing a Modular Advanced Armed Robotic System. Credit: Lance Cpl. Julien Rodarte, U.S. Marine Corps

That is a robot.

For the purposes of this posting, a robot is a piece of hardware which may or may not include an AI system and does not mimic a human or other biological organism such that you might, under circumstances, mistake the robot for a biological organism.

As for what precipitated this feature (in part), it seems there’s been a United Nations meeting in Geneva, Switzerland held from August 27 – 31, 2018 about war and the use of autonomous robots, i.e., robots equipped with AI systems and designed for independent action. BTW, it’s the not first meeting the UN has held on this topic.

Bonnie Docherty, lecturer on law and associate director of armed conflict and civilian protection, international human rights clinic, Harvard Law School, has written an August 21, 2018 essay on The Conversation (also on phys.org) describing the history and the current rules around the conduct of war, as well as, outlining the issues with the military use of autonomous robots (Note: Links have been removed),

When drafting a treaty on the laws of war at the end of the 19th century, diplomats could not foresee the future of weapons development. But they did adopt a legal and moral standard for judging new technology not covered by existing treaty language.

This standard, known as the Martens Clause, has survived generations of international humanitarian law and gained renewed relevance in a world where autonomous weapons are on the brink of making their own determinations about whom to shoot and when. The Martens Clause calls on countries not to use weapons that depart “from the principles of humanity and from the dictates of public conscience.”

I was the lead author of a new report by Human Rights Watch and the Harvard Law School International Human Rights Clinic that explains why fully autonomous weapons would run counter to the principles of humanity and the dictates of public conscience. We found that to comply with the Martens Clause, countries should adopt a treaty banning the development, production and use of these weapons.

Representatives of more than 70 nations will gather from August 27 to 31 [2018] at the United Nations in Geneva to debate how to address the problems with what they call lethal autonomous weapon systems. These countries, which are parties to the Convention on Conventional Weapons, have discussed the issue for five years. My co-authors and I believe it is time they took action and agreed to start negotiating a ban next year.

Docherty elaborates on her points (Note: A link has been removed),

The Martens Clause provides a baseline of protection for civilians and soldiers in the absence of specific treaty law. The clause also sets out a standard for evaluating new situations and technologies that were not previously envisioned.

Fully autonomous weapons, sometimes called “killer robots,” would select and engage targets without meaningful human control. They would be a dangerous step beyond current armed drones because there would be no human in the loop to determine when to fire and at what target. Although fully autonomous weapons do not yet exist, China, Israel, Russia, South Korea, the United Kingdom and the United States are all working to develop them. They argue that the technology would process information faster and keep soldiers off the battlefield.

The possibility that fully autonomous weapons could soon become a reality makes it imperative for those and other countries to apply the Martens Clause and assess whether the technology would offend basic humanity and the public conscience. Our analysis finds that fully autonomous weapons would fail the test on both counts.

I encourage you to read the essay in its entirety and for anyone who thinks the discussion about ethics and killer ‘bots is new or limited to military use, there’s my July 25, 2016 posting about police use of a robot in Dallas, Texas. (I imagine the discussion predates 2016 but that’s the earliest instance I have here.)

Teacher bots

Robots come in many forms and this one is on the humanoid end of the spectum,

Children watch a Keeko robot at the Yiswind Institute of Multicultural Education in Beijing, where the intelligent machines are telling stories and challenging kids with logic problems  [donwloaded from https://phys.org/news/2018-08-robot-teachers-invade-chinese-kindergartens.html]

Don’t those ‘eyes’ look almost heart-shaped? No wonder the kids love these robots, if an August  29, 2018 news item on phys.org can be believed,

The Chinese kindergarten children giggled as they worked to solve puzzles assigned by their new teaching assistant: a roundish, short educator with a screen for a face.

Just under 60 centimetres (two feet) high, the autonomous robot named Keeko has been a hit in several kindergartens, telling stories and challenging children with logic problems.

Round and white with a tubby body, the armless robot zips around on tiny wheels, its inbuilt cameras doubling up both as navigational sensors and a front-facing camera allowing users to record video journals.

In China, robots are being developed to deliver groceries, provide companionship to the elderly, dispense legal advice and now, as Keeko’s creators hope, join the ranks of educators.

At the Yiswind Institute of Multicultural Education on the outskirts of Beijing, the children have been tasked to help a prince find his way through a desert—by putting together square mats that represent a path taken by the robot—part storytelling and part problem-solving.

Each time they get an answer right, the device reacts with delight, its face flashing heart-shaped eyes.

“Education today is no longer a one-way street, where the teacher teaches and students just learn,” said Candy Xiong, a teacher trained in early childhood education who now works with Keeko Robot Xiamen Technology as a trainer.

“When children see Keeko with its round head and body, it looks adorable and children love it. So when they see Keeko, they almost instantly take to it,” she added.

Keeko robots have entered more than 600 kindergartens across the country with its makers hoping to expand into Greater China and Southeast Asia.

Beijing has invested money and manpower in developing artificial intelligence as part of its “Made in China 2025” plan, with a Chinese firm last year unveiling the country’s first human-like robot that can hold simple conversations and make facial expressions.

According to the International Federation of Robots, China has the world’s top industrial robot stock, with some 340,000 units in factories across the country engaged in manufacturing and the automotive industry.

Moving on from hardware/software to a software only story.

AI fashion designer better than Balenciaga?

Despite the title for Katharine Schwab’s August 22, 2018 article for Fast Company, I don’t think this AI designer is better than Balenciaga but from the pictures I’ve seen the designs are as good and it does present some intriguing possibilities courtesy of its neural network (Note: Links have been removed),

The AI, created by researcher Robbie Barat, has created an entire collection based on Balenciaga’s previous styles. There’s a fabulous pink and red gradient jumpsuit that wraps all the way around the model’s feet–like a onesie for fashionistas–paired with a dark slouchy coat. There’s a textural color-blocked dress, paired with aqua-green tights. And for menswear, there’s a multi-colored, shimmery button-up with skinny jeans and mismatched shoes. None of these looks would be out of place on the runway.

To create the styles, Barat collected images of Balenciaga’s designs via the designer’s lookbooks, ad campaigns, runway shows, and online catalog over the last two months, and then used them to train the pix2pix neural net. While some of the images closely resemble humans wearing fashionable clothes, many others are a bit off–some models are missing distinct limbs, and don’t get me started on how creepy [emphasis mine] their faces are. Even if the outfits aren’t quite ready to be fabricated, Barat thinks that designers could potentially use a tool like this to find inspiration. Because it’s not constrained by human taste, style, and history, the AI comes up with designs that may never occur to a person. “I love how the network doesn’t really understand or care about symmetry,” Barat writes on Twitter.

You can see the ‘creepy’ faces and some of the designs here,

Image: Robbie Barat

In contrast to the previous two stories, this all about algorithms, no machinery with independent movement (robot hardware) needed.

Conversational android: Erica

Hiroshi Ishiguro and his lifelike (definitely humanoid) robots have featured here many, many times before. The most recent posting is a March 27, 2017 posting about his and his android’s participation at the 2017 SXSW festival.

His latest work is featured in an August 21, 2018 news news item on ScienceDaily,

We’ve all tried talking with devices, and in some cases they talk back. But, it’s a far cry from having a conversation with a real person.

Now a research team from Kyoto University, Osaka University, and the Advanced Telecommunications Research Institute, or ATR, have significantly upgraded the interaction system for conversational android ERICA, giving her even greater dialog skills.

ERICA is an android created by Hiroshi Ishiguro of Osaka University and ATR, specifically designed for natural conversation through incorporation of human-like facial expressions and gestures. The research team demonstrated the updates during a symposium at the National Museum of Emerging Science in Tokyo.

Here’s the latest conversational android, Erica

Caption: The experimental set up when the subject (left) talks with ERICA (right) Credit: Kyoto University / Kawahara lab

An August 20, 2018 Kyoto University press release on EurekAlert, which originated the news item, offers more details,

When we talk to one another, it’s never a simple back and forward progression of information,” states Tatsuya Kawahara of Kyoto University’s Graduate School of Informatics, and an expert in speech and audio processing.

“Listening is active. We express agreement by nodding or saying ‘uh-huh’ to maintain the momentum of conversation. This is called ‘backchanneling’, and is something we wanted to implement with ERICA.”

The team also focused on developing a system for ‘attentive listening’. This is when a listener asks elaborating questions, or repeats the last word of the speaker’s sentence, allowing for more engaging dialogue.

Deploying a series of distance sensors, facial recognition cameras, and microphone arrays, the team began collecting data on parameters necessary for a fluid dialog between ERICA and a human subject.

“We looked at three qualities when studying backchanneling,” continues Kawahara. “These were: timing — when a response happens; lexical form — what is being said; and prosody, or how the response happens.”

Responses were generated through machine learning using a counseling dialogue corpus, resulting in dramatically improved dialog engagement. Testing in five-minute sessions with a human subject, ERICA demonstrated significantly more dynamic speaking skill, including the use of backchanneling, partial repeats, and statement assessments.

“Making a human-like conversational robot is a major challenge,” states Kawahara. “This project reveals how much complexity there is in listening, which we might consider mundane. We are getting closer to a day where a robot can pass a Total Turing Test.”

Erica seems to have been first introduced publicly in Spring 2017, from an April 2017 Erica: Man Made webpage on The Guardian website,

Erica is 23. She has a beautiful, neutral face and speaks with a synthesised voice. She has a degree of autonomy – but can’t move her hands yet. Hiroshi Ishiguro is her ‘father’ and the bad boy of Japanese robotics. Together they will redefine what it means to be human and reveal that the future is closer than we might think.

Hiroshi Ishiguro and his colleague Dylan Glas are interested in what makes a human. Erica is their latest creation – a semi-autonomous android, the product of the most funded scientific project in Japan. But these men regard themselves as artists more than scientists, and the Erica project – the result of a collaboration between Osaka and Kyoto universities and the Advanced Telecommunications Research Institute International – is a philosophical one as much as technological one.

Erica is interviewed about her hope and dreams – to be able to leave her room and to be able to move her arms and legs. She likes to chat with visitors and has one of the most advanced speech synthesis systems yet developed. Can she be regarded as being alive or as a comparable being to ourselves? Will she help us to understand ourselves and our interactions as humans better?

Erica and her creators are interviewed in the science fiction atmosphere of Ishiguro’s laboratory, and this film asks how we might form close relationships with robots in the future. Ishiguro thinks that for Japanese people especially, everything has a soul, whether human or not. If we don’t understand how human hearts, minds and personalities work, can we truly claim that humans have authenticity that machines don’t?

Ishiguro and Glas want to release Erica and her fellow robots into human society. Soon, Erica may be an essential part of our everyday life, as one of the new children of humanity.

Key credits

  • Director/Editor: Ilinca Calugareanu
  • Producer: Mara Adina
  • Executive producers for the Guardian: Charlie Phillips and Laurence Topham
  • This video is produced in collaboration with the Sundance Institute Short Documentary Fund supported by the John D and Catherine T MacArthur Foundation

You can also view the 14 min. film here.

Artworks generated by an AI system are to be sold at Christie’s auction house

KC Ifeanyi’s August 22, 2018 article for Fast Company may send a chill down some artists’ spines,

For the first time in its 252-year history, Christie’s will auction artwork generated by artificial intelligence.

Created by the French art collective Obvious, “Portrait of Edmond de Belamy” is part of a series of paintings of the fictional Belamy family that was created using a two-part algorithm. …

The portrait is estimated to sell anywhere between $7,000-$10,000, and Obvious says the proceeds will go toward furthering its algorithm.

… Famed collector Nicolas Laugero-Lasserre bought one of Obvious’s Belamy works in February, which could’ve been written off as a novel purchase where the story behind it is worth more than the piece itself. However, with validation from a storied auction house like Christie’s, AI art could shake the contemporary art scene.

“Edmond de Belamy” goes up for auction from October 23-25 [2018].

Jobs safe from automation? Are there any?

Michael Grothaus expresses more optimism about future job markets than I’m feeling in an August 30, 2018 article for Fast Company,

A 2017 McKinsey Global Institute study of 800 occupations across 46 countries found that by 2030, 800 million people will lose their jobs to automation. That’s one-fifth of the global workforce. A further one-third of the global workforce will need to retrain if they want to keep their current jobs as well. And looking at the effects of automation on American jobs alone, researchers from Oxford University found that “47 percent of U.S. workers have a high probability of seeing their jobs automated over the next 20 years.”

The good news is that while the above stats are rightly cause for concern, they also reveal that 53% of American jobs and four-fifths of global jobs are unlikely to be affected by advances in artificial intelligence and robotics. But just what are those fields? I spoke to three experts in artificial intelligence, robotics, and human productivity to get their automation-proof career advice.


“Although I believe every single job can, and will, benefit from a level of AI or robotic influence, there are some roles that, in my view, will never be replaced by technology,” says Tom Pickersgill, …

Maintenance foreman

When running a production line, problems and bottlenecks are inevitable–and usually that’s a bad thing. But in this case, those unavoidable issues will save human jobs because their solutions will require human ingenuity, says Mark Williams, head of product at People First, …


Mat Hunter, director of the Central Research Laboratory, a tech-focused co-working space and accelerator for tech startups, have seen startups trying to create all kinds of new technologies, which has given him insight into just what machines can and can’t pull off. It’s lead him to believe that jobs like the humble hairdresser are safer from automation than those of, says, accountancy.

Therapists and social workers

Another automation-proof career is likely to be one involved in helping people heal the mind, says Pickersgill. “People visit therapists because there is a need for emotional support and guidance. This can only be provided through real human interaction–by someone who can empathize and understand, and who can offer advice based on shared experiences, rather than just data-driven logic.”


Teachers are so often the unsung heroes of our society. They are overworked and underpaid–yet charged with one of the most important tasks anyone can have: nurturing the growth of young people. The good news for teachers is that their jobs won’t be going anywhere.

Healthcare workers

Doctors and nurses will also likely never see their jobs taken by automation, says Williams. While automation will no doubt better enhance the treatments provided by doctors and nurses the fact of the matter is that robots aren’t going to outdo healthcare workers’ ability to connect with patients and make them feel understood the way a human can.


While humans might be fine with robots flipping their burgers and artificial intelligence managing their finances, being comfortable with a robot nannying your children or looking after your elderly mother is a much bigger ask. And that’s to say nothing of the fact that even today’s most advanced robots don’t have the physical dexterity to perform the movements and actions carers do every day.

Grothaus does offer a proviso in his conclusion: certain types of jobs are relatively safe until developers learn to replicate qualities such as empathy in robots/AI.

It’s very confusing

There’s so much news about robots, artificial intelligence, androids, and cyborgs that it’s hard to keep up with it let alone attempt to get a feeling for where all this might be headed. When you add the fact that the term robots/artificial inteligence are often used interchangeably and that the distinction between robots/androids/cyborgs is not always clear any attempts to peer into the future become even more challenging.

At this point I content myself with tracking the situation and finding definitions so I can better understand what I’m tracking. Carmen Wong’s August 23, 2018 posting on the Signals blog published by Canada’s Centre for Commercialization of Regenerative Medicine (CCRM) offers some useful definitions in the context of an article about the use of artificial intelligence in the life sciences, particularly in Canada (Note: Links have been removed),

Artificial intelligence (AI). Machine learning. To most people, these are just buzzwords and synonymous. Whether or not we fully understand what both are, they are slowly integrating into our everyday lives. Virtual assistants such as Siri? AI is at work. The personalized ads you see when you are browsing on the web or movie recommendations provided on Netflix? Thank AI for that too.

AI is defined as machines having intelligence that imitates human behaviour such as learning, planning and problem solving. A process used to achieve AI is called machine learning, where a computer uses lots of data to “train” or “teach” itself, without human intervention, to accomplish a pre-determined task. Essentially, the computer keeps on modifying its algorithm based on the information provided to get to the desired goal.

Another term you may have heard of is deep learning. Deep learning is a particular type of machine learning where algorithms are set up like the structure and function of human brains. It is similar to a network of brain cells interconnecting with each other.

Toronto has seen its fair share of media-worthy AI activity. The Government of Canada, Government of Ontario, industry and multiple universities came together in March 2018 to launch the Vector Institute, with the goal of using AI to promote economic growth and improve the lives of Canadians. In May, Samsung opened its AI Centre in the MaRS Discovery District, joining a network of Samsung centres located in California, United Kingdom and Russia.

There has been a boom in AI companies over the past few years, which span a variety of industries. This year’s ranking of the top 100 most promising private AI companies covers 25 fields with cybersecurity, enterprise and robotics being the hot focus areas.

Wong goes on to explore AI deployment in the life sciences and concludes that human scientists and doctors will still be needed although she does note this in closing (Note: A link has been removed),

More importantly, empathy and support from a fellow human being could never be fully replaced by a machine (could it?), but maybe this will change in the future. We will just have to wait and see.

Artificial empathy is the term used in Lisa Morgan’s April 25, 2018 article for Information Week which unfortunately does not include any links to actual projects or researchers working on artificial empathy. Instead, the article is focused on how business interests and marketers would like to see it employed. FWIW, I have found a few references: (1) Artificial empathy Wikipedia essay (look for the references at the end of the essay for more) and (2) this open access article: Towards Artificial Empathy; How Can Artificial Empathy Follow the Developmental Pathway of Natural Empathy? by Minoru Asada.

Please let me know in the comments if you should have an insights on the matter in the comments section of this blog.

Nanotechnology enables robots and human enhancement: part 1

I’m doing something a little different as I’m going to be exploring some ideas about robots and AI today and human enhancement technologies over the next day or so. I have never been particularly interested in these topics but after studying and thinking about nanotechnology I have found that I can’t ignore them since nanotech is being used to enable these, for want of a better word, innovations. I have deep reservations about these areas of research, especially human enhancement, but I imagine I would have had deep reservations about electricity had I been around in the days when it was first being commercialized.

This item, Our Metallic Reflection: Considering Future Human-android Interactions, in Science Daily is what set me off,

Everyday human interaction is not what you would call perfect, so what if there was a third party added to the mix – like a metallic version of us? In a new article in Perspectives on Psychological Science, psychologist Neal J. Roese and computer scientist Eyal Amir from the University of Illinois at Urbana-Champaign investigate what human-android interactions may be like 50 years into the future.

As I understand the rough classifications, there are robots (machines that look like machines), androids (machines that look like and act like humans), and cyborgs (part human/part machine). By the way, my mother can be designated as a cyborg since she had her hip replacement a few years ago. It’s a pretty broad designation including people with pacemakers, joint replacements, as well as any other implanted object not native to a human body.

The rest of the Science Daily article goes on to state that by 2060 androids will be able to answer in human-like voices, answer questions and more. The scientists studying the potential interactions are trying to understand how people will react psychologically to these androids of 2060.

For an alternative discussion about robots, AI, etc. you can take a look at a project where Mary King, a collegue and fellow classmate (we completed an MA programme at De Montfort University), compares Western and Japanese responses to them.

This research project explores the theories and work of Japanese and Western scientists in the field of robotics and AI. I ask what differences exist in the approach and expectations of Japanese and Western AI scientists, and I show how these variances came about.

Because the Western media often cites Shinto as the reason for the Japanese affinity for robots, I ask what else has shaped Japan’s harmonious feelings for intelligent machines. Why is Japan eager to develop robots, and particularly humanoid ones? I also aim to discover if religion plays a role in shaping AI scientists’ research styles and perspectives. In addition, I ask how Western and Japanese scientists envision robots/AI playing a role in our lives. Finally, I enquire how the issues of roboethics and rights for robots are perceived in Japan and the West.

You can go here for more.  Amongst other gems, you’ll find this,

Since 1993 Robo-Priest has been on call 24-hours a day at Yokohama Central Cemetery. The bearded robot is programmed to perform funerary rites for several Buddhist sects, as well as for Protestants and Catholics. Meanwhile, Robo-Monk chants sutras, beats a religious drum and welcomes the faithful to Hotoku-ji, a Buddhist temple in Kakogawa city, Hyogo Prefecture. More recently, in 2005, a robot dressed in full samurai armour received blessings at a Shinto shrine on the Japanese island of Kyushu. Kiyomori, named after a famous 12th-century military general, prayed for the souls of all robots in the world before walking quietly out of Munakata Shrine.

It seems our androids are here already despite what the article in Science Daily indicates. More tomorrow.

Book launch announcement:  Susan Baxter, guest blogger here and lead author of The Estrogen Errors: Why Progesterone is Better for Women’s Health, is having a book launch tomorrow, Thursday, July 23, 2009 from 6 – 8 pm, at Strands Hair and Skin Treatment Centre, #203 – 131 Water St. (in the same complex as the kite store), Vancouver.