Uncanny Valley

Uncanny Valley refers to the unsettling feeling experienced when an entity closely resembles a human but exhibits subtle unnaturalness. It impacts human-robot interaction, entertainment, and design, with challenges in fine-tuning and ethical considerations. Examples include humanoid robots and virtual avatars, provoking an eerie response in observers.

Table of Contents

Origins and Definitions:

The term “uncanny valley” was coined by Japanese roboticist Masahiro Mori in 1970. He introduced the concept in a paper titled “Bukimi no Tani” (The Uncanny Valley), published in the Japanese journal “Energy.” Mori’s primary focus was on human reactions to humanoid robots, but the concept has since been extended to encompass various AI-driven entities and even computer-generated characters in movies and video games.

The “uncanny valley” graphically represents the relationship between human-likeness and emotional response. It suggests that as a robot or AI becomes more human-like in appearance and behavior, our emotional response to it becomes increasingly positive—up to a point. However, when the entity reaches a certain level of similarity to a real human but falls short in some aspects, our response takes a sharp negative turn, creating a “valley” in the graph. If the entity continues to become even more human-like beyond this valley, our emotional response gradually becomes positive again.

Key Characteristics:

Increasing Likeness: As an entity becomes more human-like in terms of appearance, movement, and behavior, it elicits a more positive emotional response from humans. This is evident in the initial upward slope of the uncanny valley graph.
Dip in Comfort: The most intriguing aspect of the uncanny valley is the sudden dip or valley that occurs when the entity closely resembles a human but has subtle differences or imperfections. At this point, humans often experience discomfort, unease, or even fear.
Resemblance to Corpse: One notable feature of the uncanny valley is that the discomfort experienced at the valley’s bottom is often likened to the feeling of encountering a corpse or a lifeless human. This unsettling resemblance contributes to the phenomenon’s eerie nature.
Sensitivity to Specific Traits: The uncanny valley is sensitive to specific human-like traits. For example, facial features, skin texture, and eye movement are crucial factors contributing to the perception of human-likeness and, consequently, to the depth of the valley.

Real-World Implications:

The uncanny valley has significant implications across various fields, including robotics, entertainment, healthcare, and marketing:

Robotics: In the field of robotics, understanding the uncanny valley is essential for designing robots that can interact effectively with humans. Engineers and designers must carefully navigate the valley to create robots that are both lifelike and comfortable for human interaction.
Entertainment: Filmmakers, animators, and game developers are keenly aware of the uncanny valley when creating computer-generated characters. Striking the right balance between realism and avoiding the valley is crucial for audience engagement.
Healthcare: In healthcare, humanoid robots are increasingly used for tasks like patient care and companionship. The uncanny valley can influence how patients and caregivers perceive and accept these robots.
Marketing and Advertising: Marketers sometimes use humanoid robots or AI-powered avatars for promotional purposes. Understanding the uncanny valley helps them design more effective and relatable campaigns.

Psychological Mechanisms:

To grasp the uncanny valley’s psychological mechanisms, it’s essential to consider several contributing factors:

Evolutionary Psychology: Some researchers suggest that our discomfort in the uncanny valley may have evolutionary roots. Early humans needed to quickly distinguish between members of their group and potential threats. Entities that fell into the uncanny valley might have signaled danger due to their similarity to humans but subtle deviations.
Cognitive Dissonance: Cognitive dissonance theory proposes that when we encounter something that closely resembles a human but feels not quite right, it creates a cognitive conflict. Our brain struggles to reconcile the expectation of encountering a fellow human with the reality of encountering something different. This conflict generates discomfort.
Perceptual Mismatch: Humans are highly attuned to detecting subtle inconsistencies or incongruities in their surroundings. When an entity in the uncanny valley exhibits a perceptual mismatch—where it looks or behaves almost like a human but not quite—our brain registers this discord and triggers discomfort.
Lack of Empathy: Empathy is a crucial component of human interaction. When an entity falls into the uncanny valley, it may lack the genuine emotional cues that evoke empathy. This absence of empathy-inducing signals can contribute to our discomfort.

Future Considerations:

As technology advances and AI-driven entities become increasingly sophisticated, the uncanny valley remains a relevant and evolving concept. Several considerations are worth noting:

Improving Human-Robot Interaction: Researchers and designers continue to explore ways to bridge or circumvent the uncanny valley, making interactions with robots and AI more comfortable and productive.
Ethical Concerns: The uncanny valley raises ethical questions about how we should treat AI-driven entities that closely resemble humans. Should they have rights or protections? How can we ensure ethical treatment in various applications?
Cross-Cultural Variations: Cultural factors can influence the perception of the uncanny valley. Different cultures may have varying levels of acceptance and discomfort regarding humanoid robots or AI. Understanding these variations is crucial in a globalized world.

Examples

Humanoid Robots: Humanoid robots, which closely resemble humans in their appearance and movements, often traverse the Uncanny Valley as designers strive to make them more relatable and user-friendly.

Virtual Avatars: In the realm of virtual reality and gaming, realistic avatars that mimic human actions and expressions can trigger Uncanny Valley responses if their design and animations are not well-calibrated.

Computer-Generated Characters: Animated characters in movies, video games, or simulations that bear a strong resemblance to humans must carefully navigate the Uncanny Valley to avoid unsettling audiences and users.

Key Highlights of the Uncanny Valley:

Human-Like Appearance: The Uncanny Valley concept arises when an entity closely resembles a human in appearance.
Slight Imperfections: Subtle deviations from human likeness, often in facial features or movement, trigger feelings of unease.
Unease and Discomfort: The discomfort experienced by observers increases as the entity becomes more human-like but still exhibits noticeable unnaturalness.
Robotics: The Uncanny Valley has implications in designing humanoid robots, as achieving a balance between human-likeness and comfort is crucial.
Animation and Gaming: In the context of animation and gaming, the concept applies to the creation of characters that aim for realism but fall into the Uncanny Valley.
Virtual Reality: The concept is relevant to virtual reality experiences that use human-like avatars, as even minor discrepancies can evoke discomfort.
Human-Robot Interaction: Managing the Uncanny Valley is essential for improving the acceptance and interaction with humanoid robots.
Entertainment: The Uncanny Valley impacts the design of engaging and relatable characters in entertainment media.
Fine-Tuning: Achieving the right balance of realism without triggering discomfort is a challenge in various applications.
Cultural Differences: Responses to entities in the Uncanny Valley can vary across different cultures.
Ethics: Ethical considerations arise when creating human-like entities, as they can evoke strong emotional responses and raise questions about the blurring line between human and machine.

Connected Thinking Frameworks

Convergent vs. Divergent Thinking

Convergent thinking occurs when the solution to a problem can be found by applying established rules and logical reasoning. Whereas divergent thinking is an unstructured problem-solving method where participants are encouraged to develop many innovative ideas or solutions to a given problem. Where convergent thinking might work for larger, mature organizations where divergent thinking is more suited for startups and innovative companies.

Critical Thinking

Critical thinking involves analyzing observations, facts, evidence, and arguments to form a judgment about what someone reads, hears, says, or writes.

Biases

The concept of cognitive biases was introduced and popularized by the work of Amos Tversky and Daniel Kahneman in 1972. Biases are seen as systematic errors and flaws that make humans deviate from the standards of rationality, thus making us inept at making good decisions under uncertainty.

Second-Order Thinking

Second-order thinking is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and eventuality. It also discourages the tendency for individuals to default to the most obvious choice.

Lateral Thinking

Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.

Bounded Rationality

Bounded rationality is a concept attributed to Herbert Simon, an economist and political scientist interested in decision-making and how we make decisions in the real world. In fact, he believed that rather than optimizing (which was the mainstream view in the past decades) humans follow what he called satisficing.

Dunning-Kruger Effect

The Dunning-Kruger effect describes a cognitive bias where people with low ability in a task overestimate their ability to perform that task well. Consumers or businesses that do not possess the requisite knowledge make bad decisions. What’s more, knowledge gaps prevent the person or business from seeing their mistakes.

Occam’s Razor

Occam’s Razor states that one should not increase (beyond reason) the number of entities required to explain anything. All things being equal, the simplest solution is often the best one. The principle is attributed to 14th-century English theologian William of Ockham.

Lindy Effect

The Lindy Effect is a theory about the ageing of non-perishable things, like technology or ideas. Popularized by author Nicholas Nassim Taleb, the Lindy Effect states that non-perishable things like technology age – linearly – in reverse. Therefore, the older an idea or a technology, the same will be its life expectancy.

Antifragility

Antifragility was first coined as a term by author, and options trader Nassim Nicholas Taleb. Antifragility is a characteristic of systems that thrive as a result of stressors, volatility, and randomness. Therefore, Antifragile is the opposite of fragile. Where a fragile thing breaks up to volatility; a robust thing resists volatility. An antifragile thing gets stronger from volatility (provided the level of stressors and randomness doesn’t pass a certain threshold).

Systems Thinking

Systems thinking is a holistic means of investigating the factors and interactions that could contribute to a potential outcome. It is about thinking non-linearly, and understanding the second-order consequences of actions and input into the system.

Vertical Thinking

Vertical thinking, on the other hand, is a problem-solving approach that favors a selective, analytical, structured, and sequential mindset. The focus of vertical thinking is to arrive at a reasoned, defined solution.

Maslow’s Hammer

Maslow’s Hammer, otherwise known as the law of the instrument or the Einstellung effect, is a cognitive bias causing an over-reliance on a familiar tool. This can be expressed as the tendency to overuse a known tool (perhaps a hammer) to solve issues that might require a different tool. This problem is persistent in the business world where perhaps known tools or frameworks might be used in the wrong context (like business plans used as planning tools instead of only investors’ pitches).

Peter Principle

The Peter Principle was first described by Canadian sociologist Lawrence J. Peter in his 1969 book The Peter Principle. The Peter Principle states that people are continually promoted within an organization until they reach their level of incompetence.

Straw Man Fallacy

The straw man fallacy describes an argument that misrepresents an opponent’s stance to make rebuttal more convenient. The straw man fallacy is a type of informal logical fallacy, defined as a flaw in the structure of an argument that renders it invalid.

Streisand Effect

The Streisand Effect is a paradoxical phenomenon where the act of suppressing information to reduce visibility causes it to become more visible. In 2003, Streisand attempted to suppress aerial photographs of her Californian home by suing photographer Kenneth Adelman for an invasion of privacy. Adelman, who Streisand assumed was paparazzi, was instead taking photographs to document and study coastal erosion. In her quest for more privacy, Streisand’s efforts had the opposite effect.

Heuristic

As highlighted by German psychologist Gerd Gigerenzer in the paper “Heuristic Decision Making,” the term heuristic is of Greek origin, meaning “serving to find out or discover.” More precisely, a heuristic is a fast and accurate way to make decisions in the real world, which is driven by uncertainty.

Recognition Heuristic

The recognition heuristic is a psychological model of judgment and decision making. It is part of a suite of simple and economical heuristics proposed by psychologists Daniel Goldstein and Gerd Gigerenzer. The recognition heuristic argues that inferences are made about an object based on whether it is recognized or not.

Representativeness Heuristic

The representativeness heuristic was first described by psychologists Daniel Kahneman and Amos Tversky. The representativeness heuristic judges the probability of an event according to the degree to which that event resembles a broader class. When queried, most will choose the first option because the description of John matches the stereotype we may hold for an archaeologist.

Take-The-Best Heuristic

The take-the-best heuristic is a decision-making shortcut that helps an individual choose between several alternatives. The take-the-best (TTB) heuristic decides between two or more alternatives based on a single good attribute, otherwise known as a cue. In the process, less desirable attributes are ignored.

Bundling Bias

The bundling bias is a cognitive bias in e-commerce where a consumer tends not to use all of the products bought as a group, or bundle. Bundling occurs when individual products or services are sold together as a bundle. Common examples are tickets and experiences. The bundling bias dictates that consumers are less likely to use each item in the bundle. This means that the value of the bundle and indeed the value of each item in the bundle is decreased.

Barnum Effect

The Barnum Effect is a cognitive bias where individuals believe that generic information – which applies to most people – is specifically tailored for themselves.

First-Principles Thinking

First-principles thinking – sometimes called reasoning from first principles – is used to reverse-engineer complex problems and encourage creativity. It involves breaking down problems into basic elements and reassembling them from the ground up. Elon Musk is among the strongest proponents of this way of thinking.

Ladder Of Inference

The ladder of inference is a conscious or subconscious thinking process where an individual moves from a fact to a decision or action. The ladder of inference was created by academic Chris Argyris to illustrate how people form and then use mental models to make decisions.

Goodhart’s Law

Goodhart’s Law is named after British monetary policy theorist and economist Charles Goodhart. Speaking at a conference in Sydney in 1975, Goodhart said that “any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” Goodhart’s Law states that when a measure becomes a target, it ceases to be a good measure.

Six Thinking Hats Model

The Six Thinking Hats model was created by psychologist Edward de Bono in 1986, who noted that personality type was a key driver of how people approached problem-solving. For example, optimists view situations differently from pessimists. Analytical individuals may generate ideas that a more emotional person would not, and vice versa.

Mandela Effect

The Mandela effect is a phenomenon where a large group of people remembers an event differently from how it occurred. The Mandela effect was first described in relation to Fiona Broome, who believed that former South African President Nelson Mandela died in prison during the 1980s. While Mandela was released from prison in 1990 and died 23 years later, Broome remembered news coverage of his death in prison and even a speech from his widow. Of course, neither event occurred in reality. But Broome was later to discover that she was not the only one with the same recollection of events.

Crowding-Out Effect

The crowding-out effect occurs when public sector spending reduces spending in the private sector.

Bandwagon Effect

The bandwagon effect tells us that the more a belief or idea has been adopted by more people within a group, the more the individual adoption of that idea might increase within the same group. This is the psychological effect that leads to herd mentality. What in marketing can be associated with social proof.

Moore’s Law

Moore’s law states that the number of transistors on a microchip doubles approximately every two years. This observation was made by Intel co-founder Gordon Moore in 1965 and it become a guiding principle for the semiconductor industry and has had far-reaching implications for technology as a whole.

Disruptive Innovation

Disruptive innovation as a term was first described by Clayton M. Christensen, an American academic and business consultant whom The Economist called “the most influential management thinker of his time.” Disruptive innovation describes the process by which a product or service takes hold at the bottom of a market and eventually displaces established competitors, products, firms, or alliances.

Value Migration

Value migration was first described by author Adrian Slywotzky in his 1996 book Value Migration – How to Think Several Moves Ahead of the Competition. Value migration is the transferal of value-creating forces from outdated business models to something better able to satisfy consumer demands.

Bye-Now Effect

The bye-now effect describes the tendency for consumers to think of the word “buy” when they read the word “bye”. In a study that tracked diners at a name-your-own-price restaurant, each diner was asked to read one of two phrases before ordering their meal. The first phrase, “so long”, resulted in diners paying an average of $32 per meal. But when diners recited the phrase “bye bye” before ordering, the average price per meal rose to $45.

Groupthink

Groupthink occurs when well-intentioned individuals make non-optimal or irrational decisions based on a belief that dissent is impossible or on a motivation to conform. Groupthink occurs when members of a group reach a consensus without critical reasoning or evaluation of the alternatives and their consequences.

Stereotyping

A stereotype is a fixed and over-generalized belief about a particular group or class of people. These beliefs are based on the false assumption that certain characteristics are common to every individual residing in that group. Many stereotypes have a long and sometimes controversial history and are a direct consequence of various political, social, or economic events. Stereotyping is the process of making assumptions about a person or group of people based on various attributes, including gender, race, religion, or physical traits.

Murphy’s Law

Murphy’s Law states that if anything can go wrong, it will go wrong. Murphy’s Law was named after aerospace engineer Edward A. Murphy. During his time working at Edwards Air Force Base in 1949, Murphy cursed a technician who had improperly wired an electrical component and said, “If there is any way to do it wrong, he’ll find it.”

Law of Unintended Consequences

The law of unintended consequences was first mentioned by British philosopher John Locke when writing to parliament about the unintended effects of interest rate rises. However, it was popularized in 1936 by American sociologist Robert K. Merton who looked at unexpected, unanticipated, and unintended consequences and their impact on society.

Fundamental Attribution Error

Fundamental attribution error is a bias people display when judging the behavior of others. The tendency is to over-emphasize personal characteristics and under-emphasize environmental and situational factors.

Outcome Bias

Outcome bias describes a tendency to evaluate a decision based on its outcome and not on the process by which the decision was reached. In other words, the quality of a decision is only determined once the outcome is known. Outcome bias occurs when a decision is based on the outcome of previous events without regard for how those events developed.

Hindsight Bias

Hindsight bias is the tendency for people to perceive past events as more predictable than they actually were. The result of a presidential election, for example, seems more obvious when the winner is announced. The same can also be said for the avid sports fan who predicted the correct outcome of a match regardless of whether their team won or lost. Hindsight bias, therefore, is the tendency for an individual to convince themselves that they accurately predicted an event before it happened.

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More Resources

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Origins and Definitions:

Key Characteristics:

Real-World Implications:

Psychological Mechanisms:

Future Considerations:

Examples

Key Highlights of the Uncanny Valley:

Connected Thinking Frameworks

Related

More Resources

About The Author

Gennaro Cuofano

Origins and Definitions:

Key Characteristics:

Real-World Implications:

Psychological Mechanisms:

Future Considerations:

Examples

Key Highlights of the Uncanny Valley:

Connected Thinking Frameworks

Related

More Resources

About The Author

Gennaro Cuofano

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