Brain-computer unification is on the horizon

An AI expert recently declared (or speculated) that “brain implants” in our heads could make learning obsolete in 20 years. No more need to Google. Ask anything in any language and the answer will instantly pop into your head. Google and an infinitely smart assistant will be implanted in your head. Medical science already is moving in that direction with cutting-edge research in brain-computer interfaces (BCIs) backed by AI. For now, however, the research focuses on neurological diseases and trauma to the nervous system that take away patients’ abilities to speak, move, and interact with people and their environments.
 
In the future, BCIs can not only drastically improve quality of life for millions of patients with ALS, strokes, spinal-cord injuries and other serious ailments, but be life-changing for everyone as “brain implants.” Just ask Tesla and SpaceX CEO Elon Musk about the potential of BCIs. Two years ago Musk founded Neuralink to create BCI devices that could be implanted in the brain. He called Neuralink the merger of biological intelligence with digital intelligence. Already, this year, Neuralink scientists have described a way of rapidly implanting wires into the brains of rats—and someday in the future, humans.

Musk’s otherwise rather dark vision of an AI-enabled future includes humanity benefiting from brain-computer unification that incorporates the sum-total of scientific and technical knowledge from various domains. In the near future, Musk’s vision is that, with the help of AI, neural-networks and deep learning, computers can significantly augment human expertise in solving major societal problems in developing regions of the world.

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Plugged In by Andrew Mangan

This is an inspiring book about how hard work, prayers, a positive attitude, much talent and good fortune worked for the author and could inspire all of us. Without generating headlines, researchers and others in the medical and non-medical world, including the Defense Advanced Research Projects Agency (DARPA) and many universities, are exploring the benefits and ramifications of connecting brains to computers and other technology. Elon Musk’s Neuralink is a prime example.

A disastrous accident on a skiing trip in 2016 left student-athlete Andrew Mangan with a spinal cord injury, broken neck and paralysis from the chest down. Multiple spinal cord surgeries and Mangan’s commitment to months of rehabilitation paid off. Andrew’s determination was matched by family support through every step of intensive rehab. (You can read his account of his recovery here.) However Andrew left rehab without any of the specialists being able to explain, based on neurological research, the prospects and options for victims of spinal cord injuries.

Immersed in the stories of fellow victims of spinal cord injuries with varying degrees of severity and chances of recovery, he decided to research the subject and write a book. Andrew was 18 years old and a good enough student to be accepted to Stanford. While Andrew researched and wrote Plugged In, he also worked diligently to provide resources and connections to other spinal cord injury patients. He started a spinal cord injury outreach program, Connecting the Resilient, that provides information, stories, and recovery recommendations that he himself had difficulty finding while recovering.
 

BCI R&D is highly complex, subject to countless imperfections and malfunctions, and raises numerous ethical and moral issues discussed sufficiently in the book to get all of us thinking, discussing, and debating.

As mentioned in Plugged In, the Fondation Voir et Entendre is a France-based research institute focusing on a different side of brain-computer interfacing than the headline-friendly moving prosthetics: that of the senses of sight and sound. Its name means the “Seeing and Hearing Foundation,” and consists of a team of the top scientists in the field, partnering with a network of hospitals, ophthalmology centers, and clinics. Among its goals is a project partly funded by DARPA called CorticalSight which aims to fully map the visual cortex, then use this improved understanding of how the eyes and brain work together to activate neurons artificially to generate or simulate sight. This foundation illustrates the wide implications of brain-computer interfacing, as it is not always the first theme that jumps to mind when thinking about ways to help those afflicted by impaired vision or blindness. 

By ARNOLD SCHUCHTER, St. James Faith Lab Tech Editor

On the same day that researchers at OpenAI announced that, after several months of training, their robotic hand had solved a Rubik’s Cube in a matter of minutes, Google announced that its new Pixel 4 camera would use “computational photography” to automatically process images so that smartphone cameras could make really impressive photos even in the hands of amateurs. Is there any connection between these two techie events? The answer includes artificial intelligence combined with other technology ingredients designed to enable leaps forward in the automation and enhancement of both human and robotic skills.

Movements of the robotic hand that mastered a Rubik’s Cube had to be painstakingly trained for months with billions of data bits defining each movement. Google merely had to figure out how to combine AI, algorithms and special sensors to work together harmoniously in its new smartphones. Most consumers will experience the benefits of Google’s wizardry long before they engage with robotics at home or at work.

Sooner or later, however, all of us will be using computational photography to make our photos look really good and turn each one of us into a photography pro (or at least close to one). As you click the camera in your smartphone, it will no longer simply take a photo. Instead it will capture many images and compute the burst of data into a final optimal photo. Wow! Did I do that, even in low light? No problem. Your camera “knows” it is dark(er) and automatically adjusts. Blurring, perhaps the result of hand movement, becomes sharp. No more out-of-focus pictures or videos for us, thanks to computational photography and AI. In fact you’re not shooting a photo any more but activating a computer. All good? Not so fast—the same technology also underpins invasive facial recognition.

Tech news headlines can lead us to think that most companies are investing in and using AI to grow their bottom line and even overhaul their operations. A recent survey from MIT Sloan Management Review and Boston Consulting Group found that companies have yet to embrace AI as a way to lift sales, reduce costs, and create new products. In other words, notwithstanding all of the AI hullabaloo, the majority of companies in America of every size have experienced few benefits and little impact from AI. Overall, 40% of the surveyed companies that have made “significant investments” in AI have yet to report any business gains.
 
So what is the difference between companies showing gains from AI and those not gaining value? Those gaining benefits don’t simply regard AI as a useful tech tool but rather as a valuable resource for changing or perhaps even transforming business practices. Leaders of companies leveraging AI investment, who control the use of business resources, hire the data scientists and other key personnel, and are very involved in all key decisions about uses of AI and the outcomes of data-crunching. In other words, it will take years and some visionary leadership in public, private and non-profit sectors of our society before we can expect to see the broad-scale impact and benefits of AI.