Neil Movold's List: Critical Thinking and Sensemaking

MIT researchers have now taken a major step toward that goal by designing a computer chip that mimics how the brain’s neurons adapt in response to new information. This phenomenon, known as plasticity, is believed to underlie many brain functions, including learning and memory.

"He who asks a question is a fool for five minutes; he who does not ask a question remains a fool forever." - Chinese Proverb
One of the most persistent suggestions for curing what ails American education at all levels is to help students develop "critical thinking." Everywhere, you find people complaining that college graduates don't know how to think critically. Neither do younger students.

Nobody said it better than Francis Bacon, back in 1605:

For myself, I found that I was fitted for nothing so well as for the study of Truth; as having a mind nimble and versatile enough to catch the resemblances of things … and at the same time steady enough to fix and distinguish their subtler differences; as being gifted by nature with desire to seek, patience to doubt, fondness to meditate, slowness to assert, readiness to consider, carefulness to dispose and set in order; and as being a man that neither affects what is new nor admires what is old, and that hates every kind of imposture.

A shorter version is the art of being right.

What do we do when we don't know what to do? - and how do we ensure that whatever we do is the right thing to do? How do we make sense fast, at business-speed?

Building on the disciplines of economics, finance, insurance, marketing, psychology and decision sciences, the Center's research program is oriented around descriptive and prescriptive analyses. Descriptive research focuses on how individuals and organizations interact and make decisions regarding the management of risk under existing institutional arrangements. Prescriptive analyses propose ways that individuals and organizations, both private and governmental, can make better decisions regarding risk.

What is it that drives decisions at the exact moment of choice and action? – even in the most mundane, everyday action? If the choice-point itself is a true moment of chaos – a point where literally anything is possible – then what is it that guides us through each of those infinitesimal yet ubiquitous moments?

What are some insights about the world that neuroscientists take for granted, but would seem counterintuitive or mind blowing to most non-neuroscientists?

For the most part, the biological metaphor has long been just that — a simplifying analogy rather than a blueprint for how to do computing. Engineering, not biology, guided the pursuit of artificial intelligence. As Frederick Jelinek, a pioneer in speech recognition, put it, “airplanes don’t flap their wings.”
Yet the principles of biology are gaining ground as a tool in computing. The shift in thinking results from advances in neuroscience and computer science, and from the prod of necessity.

But the second thing he explained to me was more subtle and way more powerful. He explained that I should start working on a project as soon as it was assigned. An hour or so would do fine, he told me. He told me to come back to the project every day for at least a little bit and make progress on it slowly over time. I asked him why that was better than cramming at the very end (as I was doing during the conversation).

He explained that once your brain starts working on a problem, it doesn't stop. If you get your mind wrapped around a problem with a fair bit of time left to solve it, the brain will solve the problem subconsciously over time and one day you'll sit down to do some more work on it and the answer will be right in front of you.

One of our most important living philosophers, Dan Dennett is best known for his provocative and controversial arguments that human consciousness and free will are the result of physical processes in the brain. He argues that the brain's computational circuitry fools us into thinking we know more than we do, and that what we call consciousness — isn't.

This mind-shifting perspective on the mind itself has distinguished Dennett's career as a philosopher and cognitive scientist. And while the philosophy community has never quite known what to make of Dennett (he defies easy categorization, and refuses to affiliate himself with accepted schools of thought), his computational approach to understanding the brain has made him, as Edge's John Brockman writes, “the philosopher of choice of the AI community.”

Howard Gardner of Harvard has identified seven distinct intelligences. This theory has emerged from recent cognitive research and "documents the extent to which students possess different kinds of minds and therefore learn, remember, perform, and understand in different ways," according to Gardner (1991). According to this theory, "we are all able to know the world through language, logical-mathematical analysis, spatial representation, musical thinking, the use of the body to solve problems or to make things, an understanding of other individuals, and an understanding of ourselves. Where individuals differ is in the strength of these intelligences - the so-called profile of intelligences -and in the ways in which such intelligences are invoked and combined to carry out different tasks, solve diverse problems, and progress in various domains."

Gardner says that these differences "challenge an educational system that assumes that everyone can learn the same materials in the same way and that a uniform, universal measure suffices to test student learning. Indeed, as currently constituted, our educational system is heavily biased toward linguistic modes of instruction and assessment and, to a somewhat lesser degree, toward logical-quantitative modes as well." Gardner argues that "a contrasting set of assumptions is more likely to be educationally effective. Students learn in ways that are identifiably distinctive. The broad spectrum of students - and perhaps the society as a whole - would be better served if disciplines could be presented in a numbers of ways and learning could be assessed through a variety of means."

Leaders are expected to operate at such a rapid pace and high level in this business environment that critical-thinking skills are paramount for success.

Even though critical thinking may seem like a soft or unquantifiable skill, it's actually a key competency for leaders who operate in today's business climate. In fact, the lack of critical thinking can lead to questionable decisions, which in turn could potentially tarnish a business' reputation.

If you can’t think critically, you can’t think creatively. And if you can’t think creatively, you can’t produce compelling content and copy.
To think creatively, we need to step outside the framework of what we see or hear. We have to observe, ask questions and analyze so that we can open up new thoughts and ideas on old matters or commonly-accepted arguments.

Cognitive computing, as the new field is called, takes computing concepts to a whole new level.  Earlier this week, Dharmendra Modha, who works at IBM's Almaden Research Center, regaled a roomful of analysts with what cognitive computing can do and how IBM is going about making a machine that thinks the way we do.  His own blog on the subject is here.

Smart competitors are making significant investment in their ability to collect, integrate, and analyze data from anywhere and everywhere there is an engagement with the marketplace. By constantly testing, bundling, synthesizing, and making information instantly available across the organization the company had become a different and nimbler type of business.

Daniel Kahneman, a Nobel Prize-winning psychologist and the author of the new book “Thinking, Fast and Slow,” changed the way people think about thinking by asking them questions. They weren’t trick questions, either. Instead, Kahneman relied almost exclusively on straightforward surveys, in which he described various scenarios. Here’s a sample:

The U.S. is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. If program A is adopted, 200 people will be saved. If program B is adopted, there is a one-third probability that 600 people will be saved and a two-thirds probability that no people will be saved. Which of the two programs would you favor?