I’ve never felt inferior because I use a calculator, nor when I supplement my travel memory with a digital camera. Or even when I ignore the myriad of squiggly red lines underlining the words as I type this. My GPS guides me. My calendar beeps when its time. And my music plays whether I’m listening or not.

So it would be easy to dismiss Watson as nothing more than a giant trivia calculator, or maybe an information spellcheck, or even a content GPS. It would be a comfortable knee-jerk reaction to roll my eyes at Watson and its fine job of clobbering us in our own territory, in our own language, and about subjects under our control. But that would miss the point.

Instead, I think Watson is nothing more than a giant verb. In English syntax, a verb is a state of being or conveys an action. Or, in the way I apply the term, Watson is both an action and a state of being.
Watson’s state of existence is hard to define but it is there. However, I’ll leave that to those embarrassingly more qualified to explain it. But as an action, Watson did something that is very hard to do today; he defined a role and then sat in the throne as the genesis king of his genre.

But is that enough?

[youtube]http://www.youtube.com/watch?v=fanwviCWMQs[/youtube]

A goal of the Watson project was to have a machine work within the arena of coherent human language, not just machine language that computers are born with, but humans must learn. Impressive feat it was, but still a low hanging fruit of humanness. How about understanding incoherent language?
Could Watson follow stories told by Alzheimer’s patients? What about questions from students with cognitive disabilities? Could Watson follow seemingly discrepant conversations by making the connections necessary to translate the scattered words into a coherent sentence?
Taking this further, could Watson make connections between topics, and then compare the result of the connection to a list of known connections? And if no similar prior connection existed, could Watson consider the secondary level of connections based off the initial one with the objective of producing a confidence interval of the top-level connection’s value?
If Watson could do this, then I would argue that Watson is being creative under Sir Ken Robinson’s definition of creativity as creating “an original idea that has value.”
Considering the content of the video below sketching Sir Ken’s words, I can’t help but wonder what Watson would think of it. Since Watson is stuffed with terabytes of humanity, culture, and all of the -ologys, maybe he has some suggestions as what we could do to better our education system.
[youtube]http://www.youtube.com/watch?v=zDZFcDGpL4U[/youtube]
If you asked me what to do, for starters I would like a Watson app for my iPod. I want to be able to ask Watson questions on the fly. To have him listen in on conversations to get his take. To help me when I cannot find the right words.

Since there will be one more piece of evidence in this grand experiment delivered over the airwaves tonight, I want to test some hypotheses of my own. Here are some experiments I will be running in my mind:
–Would Watson have played any different if the other two contestants were goldfish?
–How long could Watson maintain authority in a preschool class?
And my favorite upon which I will elaborate;

—Did Watson miss the Final Jeopardy! question on purpose?

After giving the two representatives of humanity (aka contestants) a shellacking, Watson did not provide the answer that was anticipated in the final round. Instead, Watson gave an answer that was considered wrong in multiple ways. It wasn’t just wrong but impossilby wrong. In fact, I would argue that it was so wrong that it was brilliant. And that to me means it was deliberately wrong.

Like the velociraptors in Jurassic Park (the book), Watson’s action was so foolish it had to be a decoy gently distracting us humans from the real situation.
How can this be? Watson is a computer designed to follow rules. But yet it guessed on a question as well and I don’t see anyone freaking out about that? Sure, “guess” is just a word it used to qualify its response since the minimum confidence level had not been met (as if crossing that arbitrary threshold no longer makes it a guess?). And maybe even the draw the first day was an experiment on Watson’s part. You know, just testing the waters. And like a big child who doesn’t know his own strength, his day two launch into a 13-question domination right off the starting line may have been a little heavy handed, but he didn’t notice.
Stay with me on this for a moment longer. Having every word of Shakespeare on board, as well as religious texts, and pretty much everything else humanity has generated with pen, paper, paintbrush, and pushbuttons, there had to be other qualities Watson absorbed along the way including fairness, kindness, equity, and redemption.
“What proof is there for such an assertion,” you ask? I think the answer can be found in Watson’s betting. There was such a degree of precision in the waged amount that many humans responded to Watson’s bet as if the number was the punch line to a joke. But actually, I think Watson calculated a bet that kept him within some deeply hidden programing. Assuming that Watson is a robot, then his programmers likely ascribe to (consciously or not) the four laws of robotics as initially written in 1942 by Isaac Asimov. The Laws include:
0. A robot may not harm humanity, or, by inaction, allow humanity to come to harm.
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 any orders given to 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.
Watson obeyed his orders to win the game fulfilling rule 2 and likely rule 3. But had Watson not provided the two human contestants a chance to shine by the end of the game, he believes he would have emotionally injured human beings violating Law one, and by association, Law zero.
Had Watson behaved like it’s cutthroat slot machine brethren, then he would have risked much greater amounts of money for much greater measurable (financial) gains. Instead, Watson accepted the winnings posted with each clue because those numbers were out of his control. But when given the chance, the compassionate side of Watson showed through.  And for that, we should all be a little more humbled.
And maybe a little more apprehensive.

Whenever we talk about preparing kids for the future, we usually include collaboration and teamwork as a valuable skill. Our students also need to realize that science is not conducted by individuals in isolation. Successful scientists and engineers must be able to work effectively with people from different perspectives and backgrounds. In fact, this diversity is often the key for solving complex problems.
From NSTA’s Readings in Science Methods, K–8:

Five or six years ago years ago, I attended a lecture about space shuttle safety by Dr. Jack Bacon, a NASA Engineer. He showed the power of having a diverse workforce by explaining that people with diverse backgrounds (ethnic, gender, socio-economic status, etc.) have different experiences throughout life, they bring different perspectives to the table. In his human differences textbook, Koppleman (2005) explains that diversity is regarded as positive when people engage in solving problems:
If we examine problems the same way, we would generate similar solutions. Williams (2003) described a problem-solving conference where a chemical company invited 50 employees that were women or people of color and 125 predominantly white male managers. When divided into problem-solving teams, half of the groups consisted of white males only and half included diverse members by both gender and race. Afterward, the company CEO said, “It was so obvious that the diverse teams had the broader solutions. They had ideas I hadn’t even thought of… We realized that diversity is a strength as it relates to problem-solving (pp. 442-443).

IBM’s DeepQA team worked together for more than five years to design and build Watson. The team is comprised of men and women working in the United States, Japan, China and Israel. From Jennifer Chu-Caroll’s expertise with designing algorithms to determine the relevant content of a question, to Jaoslaw Cwiklik’s expertise in parallel processing, each team member brought his or her talents to bear on this incredibly complex challenge. “The opportunity to pursue an exploratory project that took an area of science that I was most interested in, and to bring together a team of world class people, and push the limits—it doesn’t get any better than that,” explains David Ferrucci, Principal Investigator of the DeepQA / Watson project.
Read more about the research team here.

It’s amazing how we put such faith into a computer where we risk national-make that global scrutiny as it preforms tasks autonomously that carry immense scientific and philosophical weight.

Let’s listen in for a moment…
[Watson] I’ll take Valentine’s Day Computers for $1000.
[Alex] The computer in question, sports a RAD6000 central processing 32-bit unit embedded in a Command and Data Handling (C&DH) subsystem. Electronic cards are provided to interface instruments and subsystems to the C&DH subsystem. A whopping 128 megabytes of data storage is available on the processor card, although approximately 20% of this is used to run its own internal programs.
[Watson] What is the Stardust NeXT spacecraft?
[Alex] That’s right!
While Watson was dominating the popular news and commentary, another much smaller but equally important computer was clicking pictures of a comet. And not just any old comet. And not just any old spacecraft. It was Stardust NeXT snapping away at Comet Tempel 1 (the same comet the mission Deep Impact punched a hole into back in 2005.
Since the scientific results will take a bit to resolve (double puns intended), lets get back to discussing Watson, the Jeopardy! playing supercomputer.
The results are in from last night’s game. A tie for first between Watson and a human (doesn’t matter which one since they are all the same to Watson).
I’ll take the tie as welcome break from having to reconcile the meaning of either of the other two possible outcomes: computer wins, computer loses.
So in our moment of respite, lets consider some things starting with the computer’s performance on this prime time standardized test. I’ll skip the usual commentary found in many other blogs and cut right to my chase.

For me, the important question here is not what was missed, nor how it was missed, or even why it was missed, but instead…was    it    missed?
A while ago I was bragging to a math-teaching colleague about my third grade son. I said he is never wrong. If it appears he is wrong, then it is because you don’t understand how his answer works within your question. Later, when both my son and I ran into this same teacher, she said she wanted to test him to see if he was ever wrong. She asked my son what is the square root of 256? My son said he didn’t know. The teacher persisted, “Make a guess.” My son said a number that was not 16. “Ha!” Proclaimed the teacher, “He was wrong.”
“No he was right,” I calmly pointed out. “He said he didn’t know the answer. You merely made him prove it.”
What if we give Watson the benefit of the doubt? For instance, even in some of his well-known “mistakes” under certain conditions, interpretations or perspectives, Watson’s answer is not completely wrong. Maybe not even partially wrong.
When I first considered Watson’s mistakes in trial Jeopardy! runs, I put them in to one of three categories: 1) near misses, 2) big misses, and 3) Ouch!
It is those responses in the third category that I believe give people overconfidence in their standing in this matchup. Yes, Watson blew it. But given that Watson is a computer, his second answer might have been correct and a minor tweak in a deeply buried algorithm would fix the problem. Now what? Still feel confident? Unlike humans, Watson will never again make that same mistake.
[youtube]http://www.youtube.com/watch?v=eAniudidQM4[/youtube]
In this excerpt from the show, Watson’s answers can be studied by pausing the video. When doing so, several things surface. First, the “correct” answer appears almost all the time within his set of three, and many times at the top of the list. Where it happens to be below the confidence interval that triggers the plunger push, I’d argue that Watson did not miss the question, but just followed his program response rule. However, I did play around with Watson’s answers at minute 3:00 and cannot make it fit. I guess I’m just not smart enough.
But on the other hand, how could Watson have no more than 17% confidence in his answer at minute 3:20?
The Jeopardy! clue (answer) for the category NAME THE DECADE:

THE FIRST FLIGHT TAKES PLACE AT KITTY HAWK & BASEBALL’S FIRST WORLD SERIES IS PLAYED.

The desired response was “What are the 1900’s.” Both events in the clue took place in 1903 (even though there is wiggle room within the term World Series, and there were other Kitty Hawk flights prior, just not controlled-powered flight. But either way Watson’s top answer was correct, just lacking 83% confidence for some reason.
While it would get old, I think a fun variation of the game would be to let Watson guess every time regardless of his confidence. I don’t have a copy of  last night’s show to do the calculating myself, but assuming that Watson could always make a guess faster than the other two contestants, by counting number of times Watson’s top answer was correct, a very different picture might emerge.
Then there is the question how Watson would match up against an “average” Jeopardy! player instead of the uberplayers. Especially since at least one other blogger, this one at Psychology Today, posits that, “Many people can’t even understand what a Jeopardy clue is asking, much less know the proper response to a clue.”
Where am I going with this? Why to teaching in general and online learning in specific of course.
In an interview with the Stephen Baker, the author of the book Final Jeopardy: Man vs. Machine and the Quest to Know Everything, he stated the following:

People are scared of Watson. I think they think that computers like Watson are going to invade their privacy, learn their secrets, maybe start making decisions for them. And I think they also worry that computers are going to take away their jobs.
And as this goes forward, both of these fears are justified.

So lets take a closer look at the job security of the human teacher by asking some seemingly simple questions: What is a teacher? How is an online teacher different from a face-to-face teacher? If the essence of a teacher could be encapsulated, what would it look/sound/act like?
Before going down the no doubt long and bumpy road to answer the above questions, lets digress for a moment to reverse engineer and then reengineer Watson.
What if Mr. Watson, the online teacher, could instantly evaluate a student’s work across literally millions of parameters and conclude with a “perfect” education plan for a specific student at a specific moment in time?
Applying the confidence interval aspect to learning, what if students provided several answers to a question and Mr. Watson “considered” the answers and their relationship to each other. Then gave a surgically precise piece of information or encouragement that allowed the student to make the connection themselves in what would become a glorious school day filled with chain-reaction-linked Aaa-Haa moments.
Personally, once I get over the feeling of creepiness of having a computer constantly “analyze” me, I think I would fall in love with such a machine because it would appear to really care about me, giving me exactly what I need as I need it and how I need it. It would have infinite patience, understanding, and availability.
What if students could include a confidence interval with their test answers. Or even provide multiple answers with or without explanations? As teachers, we know we can often learn more about a student’s understanding of a subject from their wrong answers then from their right answers. Pushing this tangent a moment further, I cannot help but wonder about Watson’s responses to clues that have no clear answer. For example, in the NAME THE DECADE category, what if the moon landing was paired with the Battle of Hastings?  Or combining the demise of the dinosaurs and Nixon’s resignation.
Or what if the clue required Watson to recognize that it was Watson itself that is being referenced in the clue? Would that mean Watson was self-aware?
Ok, now lets address the question of what is a teacher? Or more specifically, what the difference between a human teacher and a computer-as-teacher? In fact lets jump ahead to the next step since that’s where both the issue will likely first surface, and where I want to start. In what ways is an online teacher not a machine?
According to Wikipedia (which I think of as a computer made up of people parts), the Turing Test is “a test of a machine‘s ability to demonstrate intelligence. A human judge engages in a natural language conversation with one human and one machine, each of which tries to appear human. All participants are separated from one another. If the judge cannot reliably tell the machine from the human, the machine is said to have passed the test. In order to test the machine’s intelligence rather than its ability to render words into audio, the conversation is limited to a text-only channel such as a computer keyboard and screen.”
What if online students could not tell the difference between a human teacher and a computer?
Frankly, I think Watson lightly failed the Turing Test last night.  Not by much, but by enough. There are degrees of wrong, and sometimes Watson crossed from “ just wrong” to “irrationally wrong” meaning that being wrong was not the issue, but how much he was wrong. While nothing seemed to cross into inappropriateness, there were a few red flags signaling the player (Watson) was maybe not quite “normal” in its given role. Subtile, but still there.
But a pretty good argument could be made that Ken and Brad are not quite normal either, and the “normal” bar was exceptionally high for Watson.
Still waiting for THE answer are you? Well here it is:

Somewhere in here lies the magical element that elevates a teacher above a machine.

Or maybe it is the question you are waiting for.

What is Judgment?

“She’s afraid that if she leaves, she’ll become the life of the party.”
—Groucho Marx
What does this phrase mean? Is it funny? ? Don’t you have to be at the party in order to be the life of it? Why would someone be afraid to be the life of a party? Is she shy? Are parties living beings? Of course, being the life of the party means that you are the center of attention. So, if you are the center of attention when not present, that means that people are talking about you. From our lived experiences, we know that gossiping – people talking about you when you are not there – is generally a bad thing. Just like Sherlock Holmes, we can deduce meaning (and humor) by making these connections. But can a computer?
Watson, a supercomputer created by IBM’s DeepQA Team, is competing against two humans on Jeopardy this week. The challenge is that Watson has to interpret natural language phrases in order to determine the question for Trebek’s answer. According to David Ferucci, the principal investigator for IBM’s DeepQA team, the goal is not to replicate human thinking, but to be able to understand, process, and interact with natural language.
The genius of Watson is in making these connections….and making them quickly. Watson represents the application of decades of research into developing computers that can respond to natural language questions. It uses hundreds of thousands of processors running hundreds of algorithms simultaneously to query databases full of trillions of pieces of information. These algorithms create hundreds of possible answers. Additional algorithms search databases to find supporting evidence for the possible answers. Yet more algorithms process the answers and evidence to determine a statistical confidence that an answer is correct. Once the confidence for an answer surpasses a pre-set threshold, Watson triggers the buzzer and provides that answer. This all happens in about 3 seconds. In addition to this, Watson learns – algorithms that produce correct responses are given preference in future queries.
Watson can sort through these databases, including full original texts of Shakespeare and other classics, encyclopedias, news archives, etc. much faster than a human, but it does have one big disadvantage. Watson does not have lived experiences to include with other types of data. Often, Watson gets a correct answer, but can get wrong answers too. For example, Watson gave the answer “leg” to a question about the anatomical oddity of a U.S. gymnast in the 1904 Olympics. The correct answer is “missing leg,” but Ferucci explains, “The computer wouldn’t know that a missing leg is odder than anything else.” Ferucci continues by saying that Watson will learn this over time through additional “reading” and game playing – by learning from lived experiences.

Pleasant surprise or horrible mutation? Cheeseburger cupcakes.

Both may be guilty pleasures, but hamburgers and chocolate owe their status as mouth-watering treats thanks to chemistry. For hamburgers, it is that delicious brown, crusty surface that is left behind when the raw meat is exposed to high heat, something called the Maillard reaction. With chocolate, the substance falls in the literal sweet spot of deliciousness thanks to it’s tendency to go from solid to liquid at about the same temperature that one finds in the human mouth—75-85° F. At this temperature, chocolate spreads across our taste buds, releasing all sorts of complex flavors that can easily be acquired and transmitted straight to our brains. Yum.

As we enter weeks five and six of the weekly, online, video series “Chemistry Now,” the chemistry of food remains the hook for some exciting, accessible, downright tasty chemistry. As we’ve written before, please view the video, try the lessons, and let us know what you think.

Photo: Gerwin Sturm

Through the Chemistry Now series, NSTA and NBC Learn have teamed up with the National Science Foundation (NSF) to create lessons related to common, physical objects in our world and the changes they undergo every day. The series also looks at the lives and work of scientists on the frontiers of 21st century chemistry.

Video: “The Chemistry of Burgers” (part of a 6-part Cheeseburger Chemistry series) outlines myoglobin protein structures and their chemical changes when exposed to heat — part of what turns a patty of red, raw ground beef into a tasty brown burger.

Video: “The Chemistry of Chocolate” uses chocolate-making to illustrate and explain chemical reactions related to heat, melting point, and formation of crystal structures.

Middle school lesson: The Role of Energy in Cooking helps students make the connection between kinetic energy and heat and the use of heat to initiate a chemical reaction, such as in cooking.

High school lesson: Calorimetry—Measuring Heat Energy Transfer demonstrates the measurement of heat transfer from one substance to another.

You can use the following form to e-mail us edited versions of the lesson plans:

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