The Dyslexic Advantage (20 page)

D-strengths aren't simply creative in a general or unconstrained way. They aim to predict—to simulate the world as it really exists, has existed, or will exist. D-strengths use episodic simulation to construct
true narratives
; they are N-strengths in their most practical mood, with their work clothes on and their sleeves rolled up. N-strengths may simply aim at being compelling. D-strengths must be
accurate
.

Let's compare the similarities and differences between D-strengths and N-strengths by seeing how Sarah employs them in her two very different—yet surprisingly similar—careers.

The Advantages of D-Strengths

T
he first time we spoke with Sarah she quickly informed us, “I'm going to tell you everything as a story, because that's how I experience the world.” The conversation that followed proved this assertion to be entirely true.

It's not surprising that Sarah has a highly narrative memory and reasoning style. As we discussed in part 5, many individuals with dyslexia do, and Sarah displays many of the features commonly seen in such individuals. For example, Sarah is a classic “family historian with a poor memory.” As she told us, “I'm the family elephant: all my cousins come to me when they want to find out what happened when and where.” Sarah also struggles with rote memory, which is common for individuals with dyslexia with this pattern: “I have no rote memory at all. I can only remember things if they fit into a structure.” Typically, this structure is a story: “Stories are what I remember—they stick in my memory.”

In fact, narrative is more than a reasoning style for Sarah. It's also a second career. Sarah Andrews is the author of ten highly regarded mystery novels that feature the exploits of professional geologist and amateur detective Em Hansen. In these novels, Em uses her skills as a geologist—and her prodigious powers of episodic simulation—to solve mysteries.

But the first problem Em solved was one of Sarah's. Sarah told us, “When I was in my thirties and working in the high-stress atmosphere of the oil business, I had trouble settling down to do my geology work if I'd witnessed an event that had a strong story to it. But I discovered that if I went ahead and wrote down the story or anecdote . . . I could squeegee it out of my mind and focus on the work I was supposed to be doing. Writing just seems to get the stories out of me.”

Sarah described the mental mechanism she uses to construct her stories in a way that closely mirrors our description of episodic construction: “As time passed, the anecdotes gathered like lint in my mind, so I made fabric from it, and the bits of fabric needed to be rearranged in order to move tensions and troubles toward resolution. . . . [This fabric formed] a patchwork quilt of memories, in which I took various events and reorganized them into new events.”

Sarah soon realized that before she could turn these “patchworks” into novels, she needed to figure out how to explain to nongeologists what geologists do and how they think; but before she could do that, she had to explain those things to herself. This preparation required two solid years of introspection, but it was worth the effort because it enabled Sarah to describe geology in all its complexity and wonder in a way that her readers could understand. It also led to many deep insights about “geological reasoning,” which Sarah has described in several fascinating essays. One of these insights concerns the narrative nature of geology. Although the rocks and minerals that are geology's focus may initially seem “nonnarrative” and “impersonal,” Sarah insists that geology is every bit as narrative as mystery writing because the rocks tell stories if we are tuned to listen.

Sarah isn't alone in this contention. Jack Horner, the world-famous paleontologist (and dyslexic) whom we met in chapter 11, has also identified a narrative element in geology, which he describes in his book
Dinosaurs under the Big Sky
: “Geology is the most important science for a dinosaur paleontologist to know because we find dinosaur skeletons in rocks. Our knowledge of geology helps us understand where to look, what to look for, and how old the fossils are. Geological information is essential because it helps paleontologists figure out what happened to animals, what may have killed the animals, and what happened to their remains after they died. Geology tells us the stories in the rocks.”
¹

Narrative construction in geology differs from writing novels primarily in the constraints that reality places upon the construction process. While the novelist seeks to create an interesting and compelling scene that resembles something that
could
happen given particular hypothetical conditions—a scene, as Sarah told us, that “rings true”—the geologist tries to use available facts to predict precisely what the earth's past or future conditions actually were or will be. This requirement that constructed scenes accurately predict distinguishes D-strengths from N-strengths.

The role that episodic simulation plays in geological reasoning can be seen in the description that Sarah gave us of her research on rock formation: “I took in everything I had ever observed and projected myself backward in time, seeing the landscape on which the sands had been deposited before they became rock.”

This description reflects several of the features of episodic construction that we've already discussed. “Taking in everything” means forming memories through observation, so the components of these memories can be used later for episodic construction. “Projecting myself backward in time” means combining memory fragments through episodic simulation into mental scenes that “predict” what the past was like. In other words, Sarah's method of geological reasoning involves constructing mental images of past landscapes by recombining memories of personal observations of the current landscape, rather than reasoning in a logical, sequential, step-by-step fashion using abstract principles or verbal or mathematical models.

Sarah further described this process of construction when she wrote of thinkers like herself: “We are great sponges for
observed patterns
, both the concrete patterns of visual observations and the more abstract patterns of process and response. . . . Repeated patterns become ideas, and new patterns lead to new paradigms. . . . [We] can, using the barest shreds, ‘see' through solid rock, back through time, and into future events.”
²

According to Sarah, this constructive process can combine even the “barest shreds” of observed patterns—whether patterns of physical objects, like rocks or sand dunes, or of processes affecting those objects, like wind or flooding—to build mental scenes in which the remote past, unobserved present, or distant future may be simulated. Importantly, this constructive process isn't limited to building “static” or “snapshot” scenes of single points in the past or the future but can create a continuous and interconnected series of scenes that allow the observer to “see through time” in a form very much like a time-lapse film.

This ability to create
a continuously connected series of scenes
is especially valuable for imagining and predicting the effects of
processes
that take place over long periods of time, like erosion, flooding, or the movement of the earth's crust along fault lines. Each of these processes occurs at its own unique rate, or along its own “time dimension.” Episodic simulation is valuable for thinking about these processes because it can be used to predict their combined effects without losing sight of the impact each exerts. It allows geologists to “mentally experiment” by independently varying these processes, changing the rate or extent of their effects. That's why it's the ideal tool for “reading stories” in complex fields and for generating hypotheses, evaluating solutions or plans, or predicting the possible results of different actions.

Sarah points to why episodic simulation is especially valuable in situations that are changing, uncertain, or ambiguous in the following statement: “By working qualitatively we can mentally bridge gaps without having to plug in assumptions, and, as a result, it becomes possible to work with uncertainties, rather than simply overriding them.”
³

By “working qualitatively” Sarah means working with data whose form still resembles the original observations. These data consist of memory fragments that have been acquired from the original observations and can be used to construct scenes that simulate past, present, or future conditions in a form similar to the original observations.

We can get an idea of why this “qualitative” episodic simulation–based approach is so powerful by comparing it with its alternative:
abstract reasoning
. Abstract reasoning uses verbal, mathematical, or symbolic abstractions rather than episodic memory fragments. These abstractions have been created by
combining and converting
the original observations into generalizations that differ from those observations in form. These abstractions are stored in semantic memory as decontextualized facts. These abstract generalizations are often useful for reasoning about routine or typical cases, but less useful for thinking about unusual, unexpected, or unprecedented cases. This loss of usefulness in unusual settings occurs because the very process of creating generalizations means that the data must be averaged out, which causes the information from exceptional cases to become effectively diluted out by the more typical results.

We can highlight some of the benefits of using more “primary” or “separated” data that better reflect the differences between cases with several examples. Think first of a baseball team with thirty players. The team's batting average can be calculated by combining the personal averages of all the players. Let's say our team's average is 0.250, or one hit in every four at bats. Now, most of the individual players will have averages that are close to 0.250, but a few poor hitters may have averages around 0.100, and a few excellent ones may have averages near 0.350. If we want to predict future performance, the team average will be fairly good at predicting the batting success of the team as a whole. It will also be fairly good at predicting the success of the average hitters. But this generalized average will be poor at predicting the performances of the best and the worst hitters. We could much more accurately predict the performances of these “outliers” by using their past
individual
performances—that is, by retaining the data in a form that better reflects the original events and doesn't dilute the information relating to these special cases with the more typical data.

Here's a second example that also demonstrates how qualitative reasoning can be better in new or unprecedented situations. Let's say we want to predict how a particular batter will perform against a pitcher who he or she has never faced before. That player's overall batting average—which combines the results of batting against all pitchers—will be less useful than considering how that player has batted against pitchers with styles similar to the new pitcher. This pitcher-to-pitcher comparison is precisely the kind of “qualitative” reasoning process that Sarah described, and it provides information that abstract generalizations cannot.

These examples help illustrate some of the advantages that D-strengths (like episodic simulation and qualitative reasoning) have for working and making predictions in situations where the important information is changing, incompletely known, or ambiguous. By building mental scenes using the “raw data” of observed patterns as they exist in the real world, rather than using verbal or numerical abstractions, we can arrive at practical, best-fit solutions for difficult, unusual, or unprecedented problems without having to “assume away” ambiguities. This process of “using what fits” rather than relying entirely on abstract analysis or secondhand models is extremely powerful for solving practical problems.

Trade-offs with D-Strengths

W
hile D-strengths can provide tremendous advantages in dynamic situations, they can create drawbacks in other settings. One of the biggest drawbacks is a reduction in speed and efficiency.

So far we've spoken of Dynamic and Narrative reasoning as if they were largely active processes in which a person constructs, searches, sorts, and simulates at will. Often, however, this isn't the case.

When we ask individuals with dyslexia who rely heavily on Dynamic or Narrative reasoning to describe their reasoning methods to us, it's striking how many portray a kind of backward process in which the answers appear first, essentially fully formed, after which a more conscious process must be pursued to connect this answer with the initial conditions. Douglas Merrill's description of his problem-solving method is typical: “I usually begin by visualizing what I think the end stage should be, then I work backward. I can't exactly describe what I do because it feels more intuitive than traditional storytelling or deduction.”

Sarah Andrews echoed this description when she wrote of herself and others like her: “Given a problem and an hour to solve it, we typically spend the first three minutes intuiting the answer, then spend the other fifty-seven backtracking . . . to check our results through data collection and deductive logic.” According to Sarah, this intuitive approach “functions in leaps rather than by neatly ratcheting intervals” and is “less lineal than iterative or circular.”
¹

This intuitive approach—used very heavily by individuals with dyslexia who excel in Dynamic and Narrative reasoning—can be very powerful, but it does present a problem: when viewed from the outside it can look an awful lot like goofing off. Sarah shared an example of this from her own life. One day at work she was standing by her office window staring serenely out at the mountains while trying to let her mind “ease itself around a problem.” Her CFO walked by her door, looked in, and saw one of “his people” staring out the window, so he snapped at her to get back to work. Sarah calmly replied, “You work in your way, I'll work in mine. Now stop interrupting me.” Sarah later wrote of this episode, “What this CFO didn't know was that staring into space is precisely how we work. It is our capacity to throw our brains into neutral and let connections assemble . . . that makes it possible for us to see connections that others can't. We relax into the work.”
²