Daily Archives: February 13, 2017

By Debkumar Mitra, Gray Matters

In 2016, a driverless Tesla car crashed killing the test driver. It was not the first vehicle to be involved in a fatal crash, but was the first of its kind and the tragedy opened a can of ethical dilemmas.

With autonomous systems such as driverless vehicles there are two main grey areas: responsibility and ethics. Widely discussed at various forums is a dilemma where a driverless car must choose between killing pedestrians or passengers.

Here, both responsibility and ethics are at play. The cold logic of numbers that define the mind of such systems can sway it either way and the fear is that passengers sitting inside the car have no control.

Any new technology brings a new set of challenges. But it appears that creating artificial intelligence-driven technology products is almost like unleashing the Frankensteins monster.

Artificial Intelligence (AI) is currently at the cutting-edge science and technology. Advances in technology, including aggregate technologies like deep learning and artificial neural networks, are behind many new developments such as that Go playing world champion machine.

However, though there is great positive potential for AI, many are afraid of what AI could do, and rightfully so. There is still the fear of a technological singularity, a circumstance in which AI machines would surpass the intelligence of humans and take over the world.

Researchers in genetic engineering also face a similar question. This dark side of technology, however, should not be used to decree closure of all AI or genetics research. We need to create a balance between human needs and technological aspirations.

Much before the current commotion over ethical AI technology, celebrated science-fiction author Isaac Asimov came up with his laws of robotics.

Exactly 75 years ago in a 1942 short story Runaround, Asimov unveiled an early version of his laws. The current forms of the laws are: 1. A robot may not injure a human being or, through inaction, allow a human being to come to harm 2. A robot must obey orders given it by human beings except where such orders would conflict with the First Law 3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law

Given the pace at which AI systems are developing, there is an urgent need to put in some checks and balances so that things do not go out of hand.

There are many organisations now looking at legal, technical, ethical and moral aspects of a society driven by AI technology. The Institute of Electrical and Electronics Engineers (IEEE) already has Ethically Aligned Designed, an AI framework addressing the issues in place. AI researchers are drawing up a laundry list similar to Asimovs laws to help people engage in a more fearless way with this beast of a technology.

In January 2017, Future of Life Institute (FLI), a charity and outreach organisation, hosted their second Beneficial AI Conference. AI experts developed Asilomar AI Principles, which ensures that AI remains beneficial and not harmful to the future of humankind.

The key points that came out of the conference are: How can we make future AI systems robust, so that they do what we want without malfunctioning or getting hacked? How can we grow our prosperity through automation while maintaining peoples resources and purpose? How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI? What set of values should AI be aligned with, and what legal and ethical status should it have?

Ever since they unshackled the power of the atom, scientists and technologists have been at the forefront of the movement emphasising science for the betterment of man. This duty was forced upon them when the first atom bomb was manufactured in the US. Little did they realise that a search for the atomic structure could give rise to nasty subplot? With AI we are at the same situation or maybe worse.

No wonder at an IEEE meeting that gave birth to ethical AI framework, the dominant thought was that the human and all living beings must remain at centre of all AI discussions. People must be informed at every level right from the design stage to development of the AI-driven products for everyday use.

While it is a laudable effort to develop ethically aligned technologies, it begs another question that has been raised at various AI conferences. Are humans ethical?

(The author is the CEO of Gray Matters. Views expressed above are his own)

Originally posted here:

The fear of a technological singularity - ETtech.com

Wendy was barely 20 years old when she received a devastating diagnosis: juvenile amyotrophic lateral sclerosis (ALS), an aggressive neurodegenerative disorder that destroys motor neurons in the brain and the spinal cord.*

Within half a year, Wendy was completely paralyzed. At 21 years old, she had to be artificially ventilated and fed through a tube placed into her stomach. Even more horrifyingly, as paralysis gradually swept through her body, Wendy realized that she was rapidly being robbed of ways to reach out to the world.

Initially, Wendy was able to communicate to her loved ones by moving her eyes. But as the disease progressed, even voluntary eye twitches were taken from her. In 2015, a mere three years after her diagnosis, Wendy completely lost the ability to communicateshe was utterly, irreversibly trapped inside her own mind.

Complete locked-in syndrome is the stuff of nightmares. Patients in this state remain fully conscious and cognitively sharp, but are unable to move or signal to the outside world that theyre mentally present. The consequences can be dire: when doctors mistake locked-in patients for comatose and decide to pull the plug, theres nothing the patients can do to intervene.

Now, thanks to a new system developed by an international team of European researchers, Wendy and others like her may finally have a rudimentary link to the outside world. The system, a portable brain-machine interface, translates brain activity into simple yes or no answers to questions with around 70 percent accuracy.

That may not seem like enough, but the system represents the first sliver of hope that we may one day be able to reopen reliable communication channels with these patients.

Four people were tested in the study, with some locked-in for as long as seven years. In just 10 days, the patients were able to reliably use the system to finally tell their loved ones not to worrytheyre generally happy.

The results, though imperfect, came as enormous relief to their families, says study leader Dr. Niels Birbaumer at the University of Tbingen. The study was published this week in the journal PLOS Biology.

Robbed of words and other routes of contact, locked-in patients have always turned to technology for communication.

Perhaps the most famous example is physicist Stephen Hawking, who became partially locked-in due to ALS. Hawkings workaround is a speech synthesizer that he operates by twitching his cheek muscles. Jean-Dominique Bauby, an editor of the French fashion magazine Elle who became locked-in after a massive stroke, wrote an entire memoir by blinking his left eye to select letters from the alphabet.

Recently, the rapid development of brain-machine interfaces has given paralyzed patients increasing access to the worldnot just the physical one, but also the digital universe.

These devices read brain waves directly through electrodes implanted into the patients brain, decode the pattern of activity, and correlate it to a commandsay, move a computer cursor left or right on a screen. The technology is so reliable that paralyzed patients can even use an off-the-shelf tablet to Google things, using only the power of their minds.

But all of the above workarounds require one critical factor: the patient has to have control of at least one muscleoften, this is a cheek or an eyelid. People like Wendy who are completely locked-in are unable to control similar brain-machine interfaces. This is especially perplexing since these systems dont require voluntary muscle movements, because they read directly from the mind.

The unexpected failure of brain-machine interfaces for completely locked-in patients has been a major stumbling block for the field. Although speculative, Birbaumer believes that it may be because over time, the brain becomes less efficient at transforming thoughts into actions.

Anything you want, everything you wish does not occur. So what the brain learns is that intention has no sense anymore, he says.

In the new study, Birbaumer overhauled common brain-machine interface designs to get the brain back on board.

First off was how the system reads brain waves. Generally, this is done through EEG, which measures certain electrical activity patterns of the brain. Unfortunately, the usual solution was a no-go.

We worked for more than 10 years with neuroelectric activity [EEG] without getting into contact with these completely paralyzed people, says Birbaumer.

It may be because the electrodes have to be implanted to produce a more accurate readout, explains Birbaumer to Singularity Hub. But surgery comes with additional risks and expenses to the patients. In a somewhat desperate bid, the team turned their focus to a technique called functional near-infrared spectroscopy (fNIRS).

Like fMRI, fNIRS measures brain activity by measuring changes in blood flow through a specific brain regiongenerally speaking, more blood flow equals more activation. Unlike fMRI, which requires the patient to lie still in a gigantic magnet, fNIRS uses infrared light to measure blood flow. The light source is embedded into a swimming cap-like device thats tightly worn around the patients head.

To train the system, the team started with facts about the world and personal questions that the patients can easily answer. Over the course of 10 days, the patients were repeatedly asked to respond yes or no to questions like Paris is the capital of Germany or Your husbands name is Joachim. Throughout the entire training period, the researchers carefully monitored the patients alertness and concentration using EEG, to ensure that they were actually participating in the task at hand.

The answers were then used to train an algorithm that matched the responses to their respective brain activation patterns. Eventually, the algorithm was able to tell yes or no based on these patterns alone, at about 70 percent accuracy for a single trial.

After 10 years [of trying], I felt relieved, says Birbaumer. If the study can be replicated in more patients, we may finally have a way to restore useful communication with these patients, he added in a press release.

The authors established communication with complete locked-in patients, which is rare and has not been demonstrated systematically before, says Dr. Wolfgang Einhuser-Treyer to Singularity Hub. Einhuser-Treyer is a professor at Bielefeld University in Germany who had previously worked on measuring pupil response as a means of communication with locked-in patients and was not involved in this current study.

With more training, the algorithm is expected to improve even further.

For now, researchers can average out mistakes by repeatedly asking a patient the same question multiple times. And even at an acceptable 70 percent accuracy rate, the system has already allowed locked-in patients to speak their mindsand somewhat endearingly, just like in real life, the answer may be rather unexpected.

One of the patients, a 61-year-old man, was asked whether his daughter should marry her boyfriend. The father said no a striking nine out of ten timesbut the daughter went ahead anyway, much to her fathers consternation, which he was able to express with the help of his new brain-machine interface.

Perhaps the most heart-warming result from the study is that the patients were generally happy and content with their lives.

We were originally surprised, says Birbaumer. But on further thought, it made sense. These four patients had accepted ventilation to support their lives despite their condition.

In a sense, they had already chosen to live, says Birbaumer. If we could make this technique widely clinically available, it could have a huge impact on the day-to-day lives of people with completely locked-in syndrome.

For his next steps, the team hopes to extend the system beyond simple yes or no binary questions. Instead, they want to give patients access to the entire alphabet, thus allowing them to spell out words using their brain wavessomething thats already been done in partially locked-in patients but never before been possible for those completely locked-in.

To me, this is a very impressive and important study, says Einhuser-Treyer. The downsides are mostly economical.

The equipment is rather expensive and not easy to use. So the challenge for the field will be to develop this technology into an affordable product that caretakers [sic], families or physicians can simply use without trained staff or extensive training, he says. In the interest of the patients and their families, we can hope that someone takes this challenge.

*The patient is identified as patient W in the study. Wendy is an alias.

Banner Image Credit: Shutterstock

Continue reading here:

Families Finally Hear From Completely Paralyzed Patients Via New Mind-Reading Device - Singularity Hub