Image Credit: Flickr When East Meets West by CiaoCessa

We start, as always, with you.  We’ll do half of the 30 Futures presentations in class. Volunteers first. Random victims next.

Next, we’ll talk about “What will Change Everything.” Small groups will choose one to present and ask questions about.

Finally, I want to give you a multiple choice selection.  We’ll do two sets and compare answers.

HW:  Read the following selection and write 6 multiple choice questions, including the answers.

MARTIN SELIGMAN
Psychologist; Director, the Positive Psychology Center, University of Pennsylvania;
Author, Learned Optimism

MUCH SMARTER PEOPLE

If we could teach intuition, people would be smarter.

Most of real world “intelligent” performance is based on intuition, not on reasoning. The expert surgeon just “knows” where to cut. The experienced farmer just “knows” that it is going to rain. The expert firefighter just “knows” that the roof is about to collapse. The judge just “knows” the defendant is lying. These finely honed intuitions are fast, unconscious, multidimensional, inarticulate, and are made confidently. What separates intelligent from mechanically stupid action is wrapped up in this mysterious process. If we could only teach intuition, we could raise human intelligence substantially.

I believe that the teaching of intuition is on the horizon by computationally driven simulation.

Intuition is a species of recognition, formally akin to the way we recognize that a table is a table. We are now close to understanding how natural classes are recognized. Consider the universe of objects all people agree are tables. There are a great many features of tables that are potentially relevant (but neither necessary nor sufficient singly or jointly) to being a table: e.g., flatness of the surface, number of legs, capacity for supporting other objects, function, compatibility with chairs, etc., etc. Each of these features can be assigned some value, which could either be binary (present vs. absent) or continuous. Different instances of tables will have different values along several of the dimensions, e.g., some, like dining room tables are flat, whereas others, like pool tables, have pockets. This means that the process of categorization is stochastic in nature. Upon observing a new object one can decide whether it is a table by comparing its features with the features of stored tables in memory. If the sum of its similarity to all of the tables in memory is higher than the sum of its similarity to other objects (e.g., chairs, animals, etc.) then one “knows” that it too is a table.

Now consider an “eagle” lieutenant recognizing a likely ambush. Here, is what this eagle has stored in her brain. She has a list of the dimensions relevant to an ambush site versus a non-ambush site. She has values along each of these dimensions for each of the ambush and non-ambush sites that she has experienced or learned about. She has a mental model which assigns weights to each of these basic dimensions or features (and to higher order features, such as the interaction between two dimensions). Based on past experiences with similar sets of features and knowledge of the outcomes of those feature sets, she can predict the outcome of the present feature set and based on her predictive model, choose how to respond to the possibility of this being an ambush.

This strongly implies that intuition is teachable, perhaps massively teachable. One way is brute force: simple repeated experience with forced choice seems to build intuition, and chicken-sexing is an example of such brute force. Professional Japanese chicken-sexers can tell male from female chicks at a glance, but they cannot articulate how they do it. With many forced choice trials with feedback, naïve people can be trained to very high accuracy and they too cannot report how they do it.

A better way is virtual simulation. A sufficient number of simulations, with the right variations, to allow a buildup of the mental model will result in a commander or surgeon who when it happens in real life has “seen it before,” will recognize it, and take the life saving action at zero cost in blood. It would be a waste of training to simulate obvious decisions in which most commanders or surgeons would get it right without training. Computational modeling of the future can derive a decision contour, along which “close calls” occur. These are the scalpel-edge cases that yield the slowest response times and are most prone to error. One could also systematically morph material along the decision contour and thereby over-represent cases near the boundary.

By so simulating close decisions in almost every human domain, vastly better intuition becomes teachable. Hence many more intelligent surgeons, judges, commanders, investors, and scientists.

So, first, we’ll read each other’s 30 Future paper. Actually, it would be awesome if you posted it onto the wiki as well.

Next, it’s Google time.  In each small group, choose one paragraph or similarly small part of the article to do a close read on and lead the class in a discussion about.  Your discussion should hit on issues of argument, evidence, rhetorical strategy, and effectiveness.

Then, I want to use Loren Eisley’s “The Bird and the Machine” to make some comparisons. We’ll read at least the first 4 pages and write a quick reaction of what we notice and what Eisley’s claims are.  Next, I’d like small groups to juxtapose paragraphs from the Google article with this one.  Which paragraphs have similarities in topic or idea? Or, which ones, when put next to each other, show something interesting in opposition?

Finally, I wanted to give you at least a bit of time to create your presentations for the 30 futures essays.  Remember, we’re looking for just about 3 minutes and NO bullets (ok, maybe one).

HW:  Presentations also please check out Edge Magazine’s 2009 Annual Question “What will Change Everything?”  Read 5 of them and then write your own (300-400 words).

So, we might do a bit of Obama. Just a taste to talk about his speech. Or even better..here.

Next, we have rough drafts of the expository speech. Let’s get 3 editors.

Editor 1: Look for proper set-ups for quotes, correct citation, and justifiable sources.

Editor 2: Look for clarity in understanding the current research and the think pieces made by experts.

Editor 3: Look for originality and creativity in the speculations and “What does it all mean?” sections.

Then, I’ll give you a bit of time to work.

Next, we’ll talk Google. In small groups, discuss what would happen if the Internet disappeared tomorrow.  Make a list of pros/cons. Also, each group should choose a specific quote that they thought made a good point or is a useful point of discussion.

Then, we talk about the article.  Each group will reveal their quote and the other groups will respond.

Finally, I’d like to take a shot at Digital Maoism in class.

HW:  Finish the Final Drafts. Start work on the presentations.

Image credit: boston.com

So, we’re going to talk “Women’s Brains” in class today, but first…we’re going to find the quotes Gould chooses and comment on each one.

• What is your initial reaction to the quote?
• Why do you think Gould uses it? What’s the purpose behind it?
• How would you respond to the person who makes the quote? Explain.

Next step. Share your outlines with a buddy.  Explain how you will move from the current research to expert ideas to speculations about the future.  What can we learn from these technologies?

Then, I want to watch a short TED speech from Jimmy Wales talking about Wikipedia.

Then, if we have time, I’d like to take a look at a technology related essay:  Is Google Making us Stupid.  Briefly summarize their contents and then explain which ideas do you tend to accept and which don’t you accept.  Quote at least once from the article.  300-400 words. Also, of course, your 30 Futures rough draft is due Wednesday.