Controlling Computers with the Mind

Another long time look at computer mind control

The Man Who Controls Computers With His Mind

By The New York Times, May 16, 2022

Only a few dozen people on the planet have had neural interfaces embedded in their cortical tissue as part of long-term clinical research.

On the evening of Oct. 10, 2006, Dennis DeGray's mind was nearly severed from his body. After a day of fishing, he returned to his home in Pacific Grove, Calif., and realized he had not yet taken out the trash or recycling. It was raining fairly hard, so he decided to sprint from his doorstep to the garbage cans outside with a bag in each hand. As he was running, he slipped on a patch of black mold beneath some oak trees, landed hard on his chin, and snapped his neck between his second and third vertebrae.

While recovering, DeGray, who was 53 at the time, learned from his doctors that he was permanently paralyzed from the collarbones down. With the exception of vestigial twitches, he cannot move his torso or limbs. "I'm about as hurt as you can get and not be on a ventilator," he told me. For several years after his accident, he "simply laid there, watching the History Channel" as he struggled to accept the reality of his injury.

Some time later, while at a fund-raising event for stem-cell research, he met Jaimie Henderson, a professor of neurosurgery at Stanford University. The pair got to talking about robots, a subject that had long interested DeGray, who grew up around his family's machine shop. As DeGray remembers it, Henderson captivated him with a single question: Do you want to fly a drone?

In rhe NY Times

Mind and Machine

Considering controls in context.  

When Mind Melds With Machine, Who's in Control?

By Wired, January 11, 2022

The last time I saw my friend James was at the townie bar near our old high school. He had been working in roofing for a few years, no longer a rail-thin teenager with lank hippie hair. I had just gotten back from a stint with the Peace Corps in Turkmenistan. We reminisced about the summer after our freshman year, when we were inseparable—adventuring in the creek that sliced through the woods, debating the merits of Batman versus the Crow, watching every movie in my father's bootlegged VHS collection. I had no idea what I wanted to do next. His future, on the other hand, was decided: He had recently joined the Navy and was starting boot camp the following week. He wanted to serve in Afghanistan.

James Raffetto trained for the next three years as a special-operations medic. He got married and, shortly after, was deployed to southern Afghanistan. About four months into his first tour, just after he had treated a local woman's sick daughter, he stepped on an improvised explosive device—an ingenious contraption triggered by a balsa-wood pressure plate, invisible to bomb detectors. He recalls finding himself face down, unable to right himself, screaming "No!"

His platoon mates asked him what to do. James directed them to tourniquet his limbs, inject him with morphine, and tell his wife, Emily, how much he loved her. He woke up a week later in a hospital in Maryland, missing both legs, his left arm, and three fingers on his right hand.

I was on the other side of the country by that point, working toward a PhD in neuroscience. We messaged a few times. He expressed how hard it was for him to accept help after years of fierce competence.

James' injury prompted me to attend a symposium on the emerging field of brain-computer interfaces—devices designed to read a person's neural activity and use it to drive a robotic prosthetic, speech synthesizer, or computer cursor.

Mind Melding with Machine, In Wired

Changing Someone's Mind

(Click though to Podcast for complete article) 

Changing Someone’s Mind: A Powerful New Approach

Jun 22, 2021 North America

Supports K@W's  Leadership Content

Nano Tools for Leaders® — a collaboration between Wharton Executive Education and Wharton’s Center for Leadership and Change Management — are fast, effective leadership tools that you can learn and start using in less than 15 minutes, with the potential to significantly impact your success as a leader and the engagement and productivity of the people you lead.

Contributor: Jonah Berger, Wharton marketing professor and author of The Catalyst: How to Change Anyone’s Mind.

The Goal:

To change minds, organizations, industries, and the world — stop trying to persuade, and instead, encourage people to persuade themselves.

Nano Tool:

No one likes to feel like someone is trying to influence them. The natural reaction to being told what to do, whether it’s to support a change initiative, accept a starting salary, or stop smoking, is to resist by pushing back. The more you allow for autonomy and allow people to participate in the process, the more effective you’ll be. Use one or a combination of four proven tactics for helping guide people to make the choice you prefer.

Provide a menu: Allow people to choose a path from a selection of your choice, giving them more say in how they’ll get where you are hoping they’ll go. Advertising agencies do this when presenting work to clients. Instead of offering one idea, which the client could then spend the rest of the meeting poking holes in, they offer two or three. This “bounded choice” provides autonomy and the greater likelihood one of the ideas will be chosen.

Ask, don’t tell: Statements like “junk food makes you fat” and “smoking causes cancer” don’t change minds. Asking questions instead shifts the listener’s role, much like providing a menu does. Rather than counterarguing or thinking about all the reasons they disagree with a statement, they’re occupied with the task of answering the question (voicing their opinion about the issue — which most people are more than happy to do). Questions also increase buy-in. Because the answer they give is theirs, it’s more likely to drive them to action. Think about how “Do you think junk food is good for you?” would work better than the statement.   .... '

Designing Customized Robot Brains

Interesting thoughts on the elements of such design, like the use of customized chip design.

Designing Customized 'Brains' for Robots

MIT News, Daniel Ackerman, January 21, 2021

Researchers at the Massachusetts Institute of Technology and Harvard University have developed a system that can increase a robot's efficiency by minimizing the mismatch between the robot’s “mind” and body. Robomorphic computing generates a customized chip design based on a particular robot's parameters, such as limb layout and joint movement, and computing needs. The researchers programmed a customizable field-programmable gate array chip according to the system's suggestions, and the chip performed eight times faster than an off-the-shelf CPU and 86 times faster than an off-the-shelf GPU despite operating at a slower clock rate. Said Harvard's Brian Plancher, "Ideally we can eventually fabricate a custom motion-planning chip for every robot, allowing them to quickly compute safe and efficient motions."

Insights for AI from the Human Mind

Good thoughts by Gary Marcus, aiming at the difficulty of creating intelligence, even though we have very rich models around we can do testing with.  

Insights for AI from the Human Mind   By Gary Marcus, Ernest Davis

Communications of the ACM, January 2021, Vol. 64 No. 1, Pages 38-41  10.1145/3392663

What magical trick makes us intelligent? The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle.

—Marvin Minsky, The Society of Mind

Artificial intelligence has recently beaten world champions in Go and poker and made extraordinary progress in domains such as machine translation, object classification, and speech recognition. However, most AI systems are extremely narrowly focused. AlphaGo, the champion Go player, does not know that the game is played by putting stones onto a board; it has no idea what a "stone" or a "board" is, and would need to be retrained from scratch if you presented it with a rectangular board rather than a square grid.

To build AIs able to comprehend open text or power general-purpose domestic robots, we need to go further. A good place to start is by looking at the human mind, which still far outstrips machines in comprehension and flexible thinking.

Here, we offer 11 clues drawn from the cognitive sciences—psychology, linguistics, and philosophy.

No Silver Bullets

All too often, people have propounded simple theories that allegedly explained all of human intelligence, from behaviorism to Bayesian inference to deep learning. But, quoting Firestone and Scholl,4 "there is no one way the mind works, because the mind is not one thing. Instead, the mind has parts, and the different parts of the mind operate in different ways: Seeing a color works differently than planning a vacation, which works differently than understanding a sentence, moving a limb, remembering a fact, or feeling an emotion."

The human brain is enormously complex and diverse, with more than 150 distinctly identifiable brain areas, approximately 86 billion neurons, hundreds if not thousands of different types; trillions of synapses; and hundreds of distinct proteins within each individual synapse.

Truly intelligent and flexible systems are likely to be full of complexity, much like brains. Any theory that proposes to reduce intelligence down to a single principle—or a single "master algorithm"—is bound to fail.

Rich Internal Representations

Cognitive psychology often focuses on internal representations, such as beliefs, desires, and goals. Classical AI did likewise; for instance, to represent President Kennedy's famous 1963 visit to Berlin, one would add a set of facts such as part-of (Berlin, Germany), and visited (Kennedy, Berlin, June 1963). Knowledge consists in an accumulation of such representations, and inference is built on that bedrock; it is trivial on that foundation to infer that Kennedy visited Germany.

Currently, deep learning tries to fudge this, with a bunch of vectors that capture a little bit of what's going on, in a rough sort of way, but that never directly represent propositions at all. There is no specific way to represent visited (Kennedy, Berlin, 1963) or part-of (Berlin, Germany); everything is just rough approximation. Deep learning currently struggles with inference and abstract reasoning because it is not geared toward representing precise factual knowledge in the first place. Once facts are fuzzy, it is difficult to get reasoning right. The much-hyped GPT-3 system1 is a good example of this.11 The related system BERT3 is unable to reliably answer questions like "if you put two trophies on a table and add another, how many do you have?" .... '   (much more follows) 

Future of Mind with AI

The most important direction is the ability to enhance our own capabilities.  Discussion in The Edge.

How AI Technology Could Reshape the Human Mind and Create Alternate Synthetic Minds

A Conversation With Susan Schneider [1.28.19]

I see many misunderstandings in current discussions about the nature of the mind, such as the assumption that if we create sophisticated AI, it will inevitably be conscious. There is also this idea that we should “merge with AI”—that in order for humans to keep up with developments in AI and not succumb to hostile superintelligent AIs or AI-based technological unemployment, we need to enhance our own brains with AI technology.

One thing that worries me about all this is that don't think AI companies should be settling issues involving the shape of the mind. The future of the mind should be a cultural decision and an individual decision. Many of the issues at stake here involve classic philosophical problems that have no easy solutions. I’m thinking, for example, of theories of the nature of the person in the field of metaphysics. Suppose that you add a microchip to enhance your working memory, and then years later you add another microchip to integrate yourself with the Internet, and you just keep adding enhancement after enhancement. At what point will you even be you? When you think about enhancing the brain, the idea is to improve your life—to make you smarter, or happier, maybe even to live longer, or have a sharper brain as you grow older—but what if those enhancements change us in such drastic ways that we’re no longer the same person?

SUSAN SCHNEIDER holds the Distinguished Scholar chair at the Library of Congress and is the director of the AI, Mind and Society (“AIMS”) Group at the University of Connecticut. Susan Schneider's Edge Bio Page  ... "