You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Looking concussion in the eye

MIT Technology Review

Robin Kazmier

Ask three neurologists if someone has a concussion, says Rosina Samadani ’89, SM ’92, and you’ll get four different opinions. A concussion, typically caused by a blow to the head, is an injury that temporarily impairs brain function. But the damage usually doesn’t show up on brain scans—and with no clinical standard, or even an agreed-upon symptom checklist, diagnosis comes down to a judgment call based on hard-to-assess things like how nauseated or drowsy someone feels. Samadani and her sister, Uzma ­Samadani, an associate professor of neurosurgery at the University of Minnesota, want to change that.

About seven years ago, Uzma was trying to determine whether severely brain-injured patients were improving, so she developed an eye-tracking device to see if they could follow a moving video on a screen. The practice of assessing eye movement to detect brain injury dates back thousands of years, but it largely died out with the advent of radiology and CT scanning. “As soon as radiology came along and you had these beautiful pictures of the brain,” Uzma says, “people stopped relying so much on looking at physical eye movements.”

As she evaluated the data gathered by her device, she realized it was allowing her to detect not only the patients’ tracking ability but also restrictions in their eyes’ range of motion. It dawned on her that these restrictions indicated problems with specific nerve pathways, meaning she had found a way to measure—and possibly locate—brain injury.

Eyeball and pupil movement are controlled by three pairs of cranial nerves that emerge from the brain stem and extend forward, one nerve along each side of the brain, to connect with the eye muscles. Pressure on those nerves slows their activity. Since each cranial nerve pair governs different aspects of eye movement, Uzma reasoned, eye-tracking data could reveal which nerves are affected by pressure or damage in the brain, and even point to the site of an injury. For example, if movement is impaired in both eyes but the eyes are coordinated, that likely means the injury is in the brain stem, which would affect both sides of the nerve pair. If only one eye is affected, that suggests the injury is in a section of nerve that has already emerged from the brain stem.

Uzma planned to make the technology available free online, but she realized that few facilities would have the resources to properly set it up. So she founded Oculogica in 2013 to sell it in ready-to-use form. She got input on starting the business from Rosina, who’d studied mechanical engineering at MIT, earned a PhD in biomedical engineering from Northwestern University, and had 18 years of experience in the medical-device industry as a health-care consultant and founder of two startups. The sisters had never imagined they would collaborate professionally, but Uzma thought Rosina had the perfect skill set for Oculogica; she hired her as CEO in 2015.

The company’s tabletop eye-tracking device, a machine called EyeBox, sends a small video clockwise around the perimeter of a rectangular screen for 220 seconds. (The test videos, which include a Shakira music video, were carefully vetted to meet a list of about a dozen criteria; for example, they can’t have flashing lights.) As a patient watches the video from a stable headrest, a binocular camera separately tracks each eye and gathers about 100,000 data points at high frequency. The data feed into algorithms that calculate nearly 100 different metrics quantifying such things as speed, coordination, and range of motion. Using statistical analysis and machine learning, Uzma identified the metrics most strongly correlated with concussion in clinical studies, and she developed an algorithm based on those metrics to score the severity of a brain injury. A score of 10 or above is Oculogica’s threshold for concussion. (Uzma has seen scores as high as the low 30s; Rosina says she usually scores 1.5 to 2.5 in her normal, healthy state.) EyeBox also detects intracranial swelling, which can be caused by a concussion and other brain conditions.

While other medical eye trackers are on the market, those require a baseline and assess only attention—essentially, the patient’s willingness to follow a chosen stimulus, assuming the capacity to do so. EyeBox, which doesn’t require baseline testing, measures the function of the cranial nerves, providing what has been so elusive in brain injury medicine: a physiologic indicator of brain function. This type of objective assessment could lead to a way of classifying brain injuries and tracking recovery. The hope, Rosina says, is that it would “open the floodgates on developing appropriate therapies.”

EyeBox is in clinical trials, and Oculogica is working on getting FDA clearance for concussion diagnosis—something no other device currently has. The Department of Defense, the United States Olympic Training Center, and two high schools in Beaver Dam, Wisconsin, are among the organizations that have tested the device. Other EyeBox studies are under way at Boston Children’s Hospital, the Mayo Clinic, and Children’s Hospital of Philadelphia.

An operator console shows an EyeBox test in progress. To take the test, a subject watches a video travel around a screen for 220 seconds as EyeBox’s camera tracks her eye movements.

As Oculogica awaits the results of those studies, Uzma continues to identify new metrics and refine the device’s algorithms, and the company is developing a more portable version of EyeBox. A smaller version could be used in the field by the military, or possibly even on the sidelines by coaches and trainers.

Beaver Dam High School’s head football coach, Steve Kuenzi, says the only approved test now available to coaches requires kids to answer questions on a computer, both before an injury and after. “I’m not a big believer in what it tells you,” Kuenzi says, explaining that you can’t know how much effort a student puts into such a test. Studies also show that baseline tests can be unreliable: athletes can purposely do poorly to increase the odds they’ll be able to keep playing after an injury.

When Rosina tested EyeBox on about 100 of Kuenzi’s players, she approached him about retesting several who’d received high scores. First on her list was a player who had been hit hard in practice the night before but passed a traditional concussion assessment. Another was a student who had been injured in a game a few days earlier; most of the others played in “high-collision” positions.

“The first kid she mentioned to me, it kind of sold me,” ­Kuenzi says. The fact that a player who had just suffered a major hit had the highest score—above 10—“was pretty telling,” he says. Another student tested low but then got hit in practice that afternoon; when Rosina tested him with EyeBox again at the hospital that night, his score jumped significantly, says his mother, Kelly Braker. He was tested repeatedly over the following months, and Braker was reassured as his score gradually declined. “You’re like, okay, obviously he’s getting better,” she says.

By minimizing the guesswork involved in diagnosing concussions, Kuenzi says, that kind of tool can be a big help to coaches trying to protect players and defend a sport increasingly seen as too dangerous. “You’re talking the brain,” he says. “We’re not gonna mess around with that.”