Category: today i learned (til)

When you think of perfume, what kinds of ingredients come to mind? Some people may think about flowery scents like rose, cherry blossom, or jasmine. Others may think of sweet notes vanilla, cinnamon, or honey. For some, the note “ambergris” may come to mind, but what is it? It can be described as a unique, musky scent with hints of the ocean. The original scent is actually derived from the intestines of sperm whales. How in the world would part of an animal’s digestive system end up in a perfume bottle?

Have you ever seen a humanoid design that looks just off? Whether it’s the subtle placement of facial features, an abnormal glint in the eyes, or even just a subconscious lurking feeling that something’s not right, you’ve likely experienced the sensation often described as the uncanny valley.  

 

What is the uncanny valley?

The concept of the uncanny valley was first introduced in the early 1970s by a robotics professor, Masahiro Mori. Mori describes the term as an irregular representative of a linear relationship, stating, “as robots appear more humanlike, our sense of their familiarity increases until we come to a valley.” (Mori et al., 1970) This ‘valley’ he refers to is a point in the relationship between human ‘likeness’ and familiarity in which familiarity plummets before increasing again. Mori designed a graphical relationship indicating this phenomenon, which can be viewed in the image below. This dynamic can be even further exacerbated by attentional human-like cues added, such as movement or touch sensation (Mori et al., 1970). 

 

 

(Original diagram created by Masahiro Mori, who coined the uncanny valley term in the early 70s.) Source: Wikimedia Commons [https://commons.wikimedia.org/w/index.php?curid=2041097]

 

The actual origin of the uncanny valley is a question sought after and theorized on by many researchers. A few common hypotheses about its origin have been proposed though. Some examples that will be further discussed below are categorization uncertainty and perceptual mismatch. Unfortunately these hypotheses and actual root of the phenomenon is under researched area, making it difficult to tie a definitive cause (Kätsyri et al., 2025). 

 

Categorical perception deals with one’s predisposition to better perceive something if it distinctly falls into a mental category. This causes things felt to fall into discrete categories to be highlighted in their uniqueness, and those that remain similar to have an understated emphasis on difference (Goldstone & Hendrickson, 2009). The hypothesis is that a cognitive dissonance is created when the uncanny valley is reached in a humanoid design. Essentially, at this stage, there is a difficulty in the mental categorization process, with ambiguity in the design making it hard to determine if the figure falls into the ‘human’ category or the ‘robot/inhuman’ category. This uncertainty is thought to bring the discomforting feeling described by the effect (Kätsyri et al., 2025).

 

Another hypothesis is rooted in the idea of perceptual mismatch. This theory follows a similar line of reasoning to the categorization uncertainty hypothesis, being that the uncanny valley effect is thought to be brought on by a feeling of discomfort that arrives by the brain’s difficulty to discern something. In this case, it relates to the perceptual confusion brought along by something with high human likeness with a feature that is inhuman or artificial in appearance. The discrepancy between a primarily human perception and an identifying feature that is misaligned with that is thought to create the uncomfortable feeling of uncanniness (Kätsyri et al., 2025). 

 

Uncanny Valley and AI

As time has gone on, the general public has witnessed the rapid development of technology. With our world’s rising implementation of artificial intelligence (AI) run programs, generative technologies, and interfaces, the question arises, how does this concept intersect with AI? Can the uncanny valley phenomenon expand beyond visual design?

 

A recent study explores these perceptions in action and how it affects user interaction and emotional responses. Deepali Kishnani, a student at MIT, employed an experimental structure that examined text interactions between participants and 3 variables – a bot engineered to be ‘human-like’, a bot engineered to be ‘uncanny-like’, and a human for control. After conversing with one of the 3, the participant ranked the system on anthropomorphism, animacy, likeability, perceived intelligence, and safety (Kishnani, 2025). 

 

Based on the rating and analysis of the results, it was concluded that there is evidence that the uncanny valley is present in text-based interaction, as the ‘uncanny-like’ bot was consistently rated lowest on all dimensions. Findings also revealed that people are having an increasingly more difficult time distinguishing human interaction from AI interactions, as 60% of participants in the human control group incorrectly identified their chat companion as AI (Kishnani, 2025).

 

With the now confirmed presence of possible uncanny valley in AI chatbot interactions, an additional question of how it influences trust from users arises. Another study explores this concept, seeking how the anthropomorphism of AI systems induces concern into the patron, instigating fear of human-natured negative actions onto the inhuman bot (Kim et al., 2024). This study specifically introduces a concept known as ‘uncanny valley of the mind,’ which focuses more on human-like intentions rather than human-like appearance. They suggest that the uncanny valley of the mind is brought on when a chatbot is perceived to have human-like mentalites (also known as a ‘digital mind’), they will also possess human-like intentions- such as the ability to misuse information (Kim et al., 2024).

 

To test this phenomenon, researchers created 2 chatbots that could be accessed through facebook messenger, one ‘anthropomorphized’ and one ‘non-anthropomorphized.’ Through a series of interactions, the bot asked for personal information and later synthesized either an ad containing that information or a generic ad without it. Interestingly, when the anthropomorphized bot presented the user with a personalized ad, participants reported increased privacy concerns. This effect was not present in the non-anthropomorphized ads, regardless of it being the personalized or non-personalized ad. With this being said, it was determined that higher anthropomorphism in chatbots decreases consumer trust/likelihood to purchase a product when personal information is included in the pitch (Kim et al., 2024).

 

What Does this Mean for the Future of AI?

It seems that as the days go on, more applications of AI are created and present in a multitude of functions. As implementations into features like writing programs, customer service, and ad-personalization grows, opportunity for distrust in these systems increases along with it. The research above proves that the uncanny valley can seep into perceptions of these AI powered systems, so how will producers handle this realization?

 

In my opinion, there are two ways this industry can progress to mediate this issue from a psychological standpoint. Either producers will make efforts to develop AI systems that are less uncanny and more perceptual humans or consumers will begin to gravitate away from trust. Historically both of these things have occurred in product development and examples regarding the uncanny valley can even be observed. 

 

A great exemplification of both of these mediations is the design of ‘Sonic the Hedgehog’ in the 2020 film rendition. When the first trailer released, fans of the franchise were horrified by the uncanny design of their beloved main character. Sonic, a very cartoonish character, had been adapted to his life action role by combining realistic CGI texturing and a flurry of human-like features on a very non-human creature. The uproar after the release was instant, with many fans taking to social media to detest the movie and state their refusal to endorse it. (Alexander, 2020) This is an example of the consumers gravitating away from trust. Producers were then forced to change the design to be more appealing and cartoonish, exemplifying the need for producer design in a way that is more appealing to consumers. 

 

The true outcome of how AI develops can only be told by time. Until then, be a critical consumer. Do you find yourself experiencing a lurking, unsettling, off feeling when chatting with AI systems?

 

References:

Alexander, B. (2020, February 17). How “Sonic the Hedgehog” avoided death by Twitter with a dramatic, game-saving redesign. USA Today. https://www.usatoday.com/story/entertainment/movies/2020/02/13/sonic-the-hedgehog-movie-redesign-how-backlash-made-character-better/4730593002/

Goldstone, R. L., & Hendrickson, A. T. (2009, December). Categorical perception. WIREs Cognitive Science. https://wires.onlinelibrary.wiley.com/doi/10.1002/wcs.26

Kim, W., Ryoo, Y., & Choi, Y. K. (2024). That uncanny valley of mind: When anthropomorphic ai agents disrupt personalized advertising. International Journal of Advertising, 1–30. https://doi.org/10.1080/02650487.2024.2411669

Kishnani, D. (2025, March 7). The uncanny valley: An empirical study on human perceptions of AI-generated text and images. The Uncanny Valley: An Empirical Study on Human Perceptions of AI-Generated Text and Images. https://dspace.mit.edu/handle/1721.1/159096

Kätsyri, J., Förger, K., Mäkäräinen, M., & Takala, T. (2025, November 1). A review of empirical evidence on different uncanny valley hypotheses: Support for perceptual mismatch as one road to the valley of eeriness. Frontiers. https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2015.00390/full#B19

Mori, M. (1970). The Uncanny Valley. https://www.almendron.com/tribuna/wp-content/uploads/2018/01/morunc.pdf 

Introduction:

On a hot July day, what you wear to stay cool matters. There are common remedies to help you stay cool: wearing cotton and light colors to allow for air circulation and light reflection. Some textiles, like wool, insulate heat to help you stay cool during the winter months and others, like polyester, prevent sweat from absorbing into its fibers. As global temperatures rise and daily heat records are broken more often, these traditional “summer” fabrics can only do so much to keep you cool because of their one big drawback: they trap the body’s infrared radiation induced heat (Tang, 2025).

The body is always emitting infrared radiation, but this radiation typically is let off into the air. However, fabrics like wool, polyester, and cotton, absorb or reflect this radiation back to your body and trap heat. This problem is exactly what scientists studying radiative cooling textiles hope to combat (Yu et al., 2025). 

What Scientists are Doing:

Researchers are reengineering textiles at the molecular level to design radiative cooling textiles that release the infrared radiation the body lets off instead of reflecting it back to the body like traditional textiles (Tang, 2025). These thermoregulating textiles focus on the movement of heat and light through fibers rather than just controlling airflow and moisture retention. Through the careful design of specific polymers, coating fibers, and embedding of nanoparticles, how radiation interacts with fabric can be manipulated. For example, some of these textiles have been made from engineering polyethylene that reflects visible light but is transparent to infrared radiation, allowing for heat to escape from the body (Yu et al., 2025). 

Outside of science labs, early prototypes of these thermal textiles are being tested by research teams and companies. Specifically, several research teams, like brrro and IRCool textiles at Stanford University, are testing radiative cooling textiles that appear to lower body temperature by a few degrees even in the direct sun, which is a major development as extreme heat events become more common (Yu et al., 2025). Additionally, these thermal textiles are being tested for use as athletic wear and for architectural purposes (Tang, 2025). 

Not Quite Cool Enough, Yet:

Despite major developments in the use of these thermal textiles, there are still several challenges that textile researchers are facing. One of the major problems is that polyethylene, the main polymer being used in these thermal textiles, is difficult to recycle, receiving criticism from environmental activists (Tang, 2025). Additionally, these polymers are difficult to dye due to their amorphous structure, limiting their aesthetic uses in industry. While radiative cooling textiles offer a promising improvement in keeping you cool in the warmer months, their presence remains primarily in the researching and prototype phases rather than the mass-market clothing industry (Yu et al., 2025). 

Conclusion:

As temperatures continue to rise, the fabrics we wear have an ever important role in keeping us cool and safe. Radiative cooling textile advancements show how science intersects design to create clothing that works with the body’s heat flow for maximized comfort and functionality. While there is a long road ahead of these textiles becoming commercially available, their innovation marks a step towards cooler clothing. 

References:

Tang, B. (2025). Recent progress in the development of radiative cooling textiles. Nanomanufacturing, 5(2), 22. https://www.mdpi.com/2673-7248/5/2/22 

Yu, Z., Zhang, L., & Li, Y. (2025). Next-generation passive cooling textiles for personal thermal management. Nano Research Energy, 4(1), 713-725. https://link.springer.com/article/10.1007/s40820-025-01713-4

For sure most people have already experienced some ‘disliking’ sounds before. For example, the emergency sirens, high-pitched yellings, public space noises, etc. What’s about daily life sounds? From the snoring, sniffling, heavy breathing, a few people might be triggered into intense negative emotion such as rage or disgust (Salamon, 2023). This is a sign of misophonia.

What is Misophonia? 

According to Kumar et al (2021), “misophonia is a common disorder characterized by the experience of strong negative emotions of anger and anxiety in response to certain everyday sounds” (para. 1). Most of the known triggers for misophonia are human-orofacial actions such as eating and chewing, including images and silent videos (Kumar et al, 2021). 

Patients and causes

The cause of misophonia remains unknown, but an experiment with 15 members of the same family suggests a possible hereditary factor (Sanchez & Silva 2017). These 15 Caucasians with misophonia span across 3 generations, with more than half being women. The younger generations reported to have misophonia earlier than their parents, with the youngest starting at age 2. Surprisingly, 80% of the women with misophonia have all of their children also diagnosed with misophonia, suggesting this is a genetic disorder. According to a study published in 2023 by journal PLOS One, nearly one out of five adults experience similar conditions, with women responding more intensely than men (Salamon, 2023).

A separate research focusing more on severe cases of misophonia suggest that the disorder involves brain regions, including the mirror neuron system, orofacial motor area, and both auditory and visual cortex. These areas seem to respond to sensory stimulation associated with the production of trigger sounds, potentially causing the patients to unknowingly mirror the perceived action (Kumar et al, 2021). The study further suggests that extreme negative reactions occur in misophonia possibly due to a sense of loss of control, invasion of personal space, or interference with current goals and actions. Kumar et al (2021) also highlight that automatic mimicry of eating behavior is commonly learned within families since young age, which may explain why a family member usually becomes the initial source of sound triggers developing misophonia. This finding is consistent with Sanchez and Silva’s study (2017), where younger generations tend to experience misophonia earlier than their parents – suggesting environmental factors contribute to the disorder.

According to Cleveland Clinic, a worldwide nonprofit academic medical center and healthcare provider, about 50%-80% of reported misophonia patients are women (Cleveland Clinic, n.d.) The information page suggests brain structure differences, family history or genetics are causes of the disorder. 

Cure and Prevention

Even though most people reported that misophonia has zero to minimal effect on their life (Sanchez & Silva 2017), many might encounter daily life struggles as residents in busy areas. There are people who cannot eat out at restaurants due to the eating noises, feeling uncomfortable in dark spaces which enhance hearing functions like in movie theater, etc – in some cases, misophonia can become socially impairing (Salamon, 2023). For the few severe situations, body reactions can include blood pressure increases, chest pressure or tightness, goosebumps, heart rate increases, or sweating (Cleveland Clinic, n.d.). As misophonia is a lifelong condition, it could worsen or introduce chronic diseases.

Unfortunately, as the exact sources and causes of misophonia remain uncertain, there is no exact cure for it and therefore it is not officially recognized as a medical condition (Cleveland Clinic, n.d.). Many patients are able to manage the condition using sound aversion methods like wearing earplugs or headphones, listening to white noise, practicing deep breath or muscle relaxation (Salamon, 2023). 

It’s very important to not criticize behavioral symptoms (Salamon, 2023) as chances are that they are experiencing some medical conditions. Much of the older generation lived with misophonia all their life without getting treatment. Sadly, they resist going to doctors because of the stigma surrounding mental disorders. Although misophonia is still an unofficial disorder, many experts recognize the patterns. If you ever encounter someone potentially experiencing misophonia and thinking they have gone mad, it would be nice to tell them about the disorder, and suggest ways to manage the condition in daily life.  

References

• Kumar, S., Dheerendra, P., Erfanian, M., Benzaquén, E., Sedley, W., Gander, P. E., Lad, M., Bamiou, D. E., & Griffiths, T. D. (2021). The motor basis for Misophonia. The Journal of Neuroscience, 41(26), 5762–5770. https://doi.org/10.1523/jneurosci.0261-21.2021 
• Misophonia: What it is, triggers, symptoms & treatment. Cleveland Clinic. (n.d.). https://my.clevelandclinic.org/health/diseases/24460-misophonia
• Salamon, M. (2023, September 1). When everyday noises upset you. Harvard Health. https://www.health.harvard.edu/diseases-and-conditions/when-everyday-noises-upset-you 
• Sanchez, T. G., & Silva, F. E. (2018). Familial misophonia or selective sound sensitivity syndrome : Evidence for autosomal dominant inheritance? Brazilian Journal of Otorhinolaryngology, 84(5), 553–559. https://doi.org/10.1016/j.bjorl.2017.06.014 

The Science of Smell

Of the five senses, scientists understand the least about smell. We recognize scents when small airborne molecules stimulate receptors in the back of our nose, which then send signals to our brain. Humans have about 500 different types of receptors, each one specific to a different scent molecule (“How the nose decodes complex odors”, 2020).

But what makes some molecules have scents? Well, the molecules must be able to travel through the air to the back of the nose, so they have to be volatile. Volatility is how easily the molecule evaporates at room temperature. The more a molecule evaporates into the air, the more likely it is that it reaches the receptors in the back of our nose. Even then, there must be a receptor for that specific molecule for it to be recognized (Gang, 2005).

The whole process seems simple enough, but most scents are a combination of tens to hundreds of different scent molecules. The smell of chocolate and cocoa products, for example, is made of over 600 scent molecules (Counet et al., 2002). Scientists still don’t fully understand how more complicated scents work, (Gottfried & Wilson, 2011) but most have been found to be made of just a few major compounds, such as the southern magnolia flower. Its scent comes from a mixture of 14 different molecules, but two, beta-caryophyllene and beta-cedrene, are the main compounds (Garg & Kumar, 1999).

Many common scents can be traced back to specific molecules. Even small changes in a molecule can cause large changes in its scent. Check out a few familiar scents below!

Common Scent Molecules

6-Acetyl-2,3,4,5-tetrahydropyridine gives popcorn and baked goods their typical smell. A slight change creates 2-Acetyl-1-pyrroline, which is the main component of rice’s smell (Dhrubo, 2015).

4-Anisaldehyde is used a lot in the fragrance industry. It has a very strong sweet floral scent and is very similar to vanillin. Vanillin, as you may have guessed, is the main component of vanilla’s scent. Natural vanilla extract is made of hundreds of different molecules, but synthetic vanilla scent is usually just pure vanillin (Dhrubo, 2015).

Benzaldehyde has an almond-like odor and is very useful in the fragrance industry because of its simple structure (Dhrubo, 2015).

Cinnamaldehyde makes up for around 90% of the scent of cinnamon (Dhrubo, 2015).

Natural honey is an extremely complicated scent, made up of 187 volatile compounds, and varies based on its nectar source (Mahmoud et al., 2024). Phenylacetaldehyde is the main component of honey’s scent, but methyl phenylacetate is used for a synthetic honey scent because of its strength. It only takes a little bit of methyl phenylacetate to make a perfume or candle honey-scented (Dhrubo, 2015).

Even fresh cut grass has its own molecule. (Z)-3-hexenal is one of the molecules released when grass is damaged, and is what gives it that freshly mowed lawn smell (Dhrubo, 2015).

If you want to learn more about fun molecules, the American Chemical Society (ACS) has been publishing a “Molecule of the Week” since 2001. This past week’s molecule was myristicin, which is a primary component of many spices such as nutmeg, dill, parsley, and anise. Interestingly, its structure is very similar to that of amphetamines and can cause hallucinations if ingested in high doses (much higher than used for cooking). On their website, they have an archive of over one thousand molecules, complete with properties, history, and fun facts! Click here to check it out.

 

How the nose decodes complex odors. (May 12, 2020). National Institute of Health. https://www.nih.gov/news-events/nih-research-matters/how-nose-decodes-complex-odors

Gang, D. (June 2005). Evolution of Flavors and Scents. Annual Review of Plant Biology. 56, 301-325. https://www.annualreviews.org/content/journals/10.1146/annurev.arplant.56.032604.144128

Gottfried, J., Wilson, D. (2011). Neurobiology of Sensation and Reward. National Library of Medicine. https://www.ncbi.nlm.nih.gov/books/NBK92786/

Counet, C., Callemien, D., Ouwerx, C., Collin, S., (March 15, 2002). Use of Gas Chromatography−Olfactometry To Identify Key Odorant Compounds in Dark Chocolate. Comparison of Samples before and after Conching. Journal of Agricultural and Food Chemistry, 50(8), 2385–2391. https://pubs.acs.org/doi/10.1021/jf0114177

Garg, S., Kumar, S., (1999). Volatile constituents from the flowers of Magnolia grandiflora L. from Lucknow, India. Journal of Essential Oil Research 11(5),, 633-634. https://aromadb.cimapbioinfo.in/web_essentialoil_details.php?id=CRESOL159

Mahmoud, M., Kilic-Buyukkurt, O., Aboul Fotouh, M., Selli, S. (October 2024). Aroma active compounds of honey: Analysis with GC-MS, GC-O, and molecular sensory techniques. Journal of Food Composition and Analysis, 134(106545). https://www.sciencedirect.com/science/article/pii/S0889157524005799#:~:text=Compounds%20such%20as%20phenylacetic%20acid,the%20distinctive%20smell%20of%20honey.

Dhrubo, J. S. (2015) Esters, Terpenes And Flavours: Make The Mood Cheers by Three Musketeers!. World Journal of Pharmaceutical Medicine, 4(8), 1-40. https://wjpr.s3.ap-south-1.amazonaws.com/article_issue/1438667348.pdf

And, the explosion of information across scientific and technical fields over the past few decades has created a world overflowing with data. Scientific publications, repositories, visualization platforms, as well as computational tools, have expanded dramatically to accommodate this surplus; however, the rate of knowledge production now exceeds the capacity of most audiences to process and internalize it meaningfully (Schröder et al., 2023). The dominant assumption remains that more information leads to more clarity, yet the trend of adding more slides, graphs, bullet points, along with articles, produces fact-stacked communication that fails to recognize that clarity does not come from completeness (Olson, 2013). Clarity emerges from narrative. Audiences do not automatically derive meaning from information. Although accuracy remains a priority in an information-dense world, narrative structure is often avoided in fear of oversimplification, even though effective communication is increasingly essential.

But, information alone does not create understanding. The pursuit of more information mirrors the linguistic pattern of “and, and, and,” a communication style that overwhelms audiences with unordered detail and no narrative arc (ABT Narrative Training Program, n.d.). The brain requires structure to make meaning. The human language network encodes experience and knowledge as causal chains, not isolated facts (Chen & Bornstein, 2024); therefore, understanding relies on semantic cognition, the ability to construct a mental situation model from relationships among elements. Without narrative causality, no such model can form (Schröder et al., 2023), so when information is embedded in a narrative framework, audiences understand faster, remember longer, and also make more informed decisions (Schröder et al., 2023). Even expert audiences benefit from narrative scaffolding. Therefore, the MIT Communication Lab explicitly teaches Randy Olson’s And, But, Therefore (ABT) narrative structure in scientific communication because raw information is insufficient; without a narrative, understanding does not transfer.

Therefore, understanding is the recognition of context, conflict, and resolution (Chen & Bornstein, 2024). The brain naturally thinks in stories, so Olson’s ABT model formalizes this cognitive pattern: “And” establishes shared reality, “But” highlights tension or a knowledge gap, and “Therefore” delivers implication or resolution (Olson, 2015). ABT is effective because it aligns with the brain’s cognitive architecture by providing meaning through structure, communicating the why, the stakes, as well as the direction; therefore, narrative is not optional for understanding. When findings are presented with contextual relevance, interpretation, and recall improve because ABT mirrors the brain’s process for constructing understanding.

We live in a world full of information, yet sharing it effectively is essential. But without a narrative structure, information fails to transfer. Therefore, the ABT model enables communication that conveys not only data, but meaning, memory, as well as insight. This article not only describes the ABT narrative but also embodies it through performing it. Using Randy Olson’s ABT-O-Meter, which quantifies narrative coherence, the writing scored an AND Frequency of 2.5% percent, which falls within the optimal 2% to 6% range, ensuring the writing remains connected but not repetitive. This article also has a Narrative Index score of 44, which remains above the threshold of 20 associated with narratively strong composition. This confirms that this article itself functions as a real-world example of the ABT framework in practice.

 

References

ABT Narrative Training Program. (n.d.). The ABT framework. https://abtframework.com/

ABT Narrative Training Program. (n.d.). Randy Olson’s ABT-ometer: Analyze your text using narrative metrics. https://abtnarrative.com/abt_analyzer.html

Chen, J., & Bornstein, A. M. (2024). The causal structure and computational value of narratives. Trends in Cognitive Sciences. https://doi.org/10.1016/j.tics.2024.01.003

MIT Communication Lab. (n.d.). Scientific storytelling: The ABT method. Massachusetts Institute of Technology. https://mitcommlab.mit.edu/cee/commkit/scientific-storytelling/

Olson, R. (2013). Randy Olson: Great Challenges Day [Video]. TEDMED. https://www.youtube.com/watch?v=ERB7ITvabA4

Olson, R. (2015). Houston, we have a narrative: Why science needs story. University of Chicago Press.

Schröder, K., Eberhardt, W., Belavadi, P., Ajdadilish, B., van Haften, N., Overes, E., Brouns, T., & Calero Valdez, A. (2023). Telling stories with data: A systematic review. arXiv. https://arxiv.org/pdf/2312.01164