![]() Concepts represented by points that are near to each other are more psychologically similar than are points that are conceptually distant. Similarity between concepts is a function of the distance between the concepts in space. Transformation - If one thing can be changed into another thing easily, either in the real world or in a person's mind, people might say the things are similar (a seed is similar to a plant. Similarity (psychology) Similarity refers to the psychological degree of identity of two mental representations.Also, if the first parts of the words for two things are the same, people might say the things are similar. Phonetics - If the words for two things sound the same, people might say the things are similar. ![]() Hierarchy - If one thing is a small part of a larger thing, people might say the things are similar.Functions - If two things are used for the same reasons, people might say the things are similar.(coins and wheels are similar, because they are both round.) Similar features could include: shape, texture (what the surface looks like), material (what something is made out of), color, weight, size, temperature, and other features. Features - If something about two things are the same, people might say the things are similar.How do people decide that two things are similar? When it comes to similarity, this might include listing words, using categories as clues for learning new words, sorting objects into groups, or other tasks that have to do with comparing things to one another.ĭepending on how quickly people do these tasks, or how many mistakes they make, psychologists can find out what rules they are using to decide if things are similar. Once a model can respond with the correct (similar) words, then it is likely that the rules the computer program uses are the same rules that people use to decide whether words are similar.īehavioral research Īnother way that psychologists look into similarity is by putting people in special situations and watching what they do. Computer models do this by applying some set of rules to a large collection of real world text (called a corpus). For instance, a person might say that "cat" and "dog" are similar words, so a good computer model should be able to take the word "dog" and respond with the word "cat" in a list of similar words. Then they will write a computer program that tries to simulate the same answers that the humans gave. Scientists will, for example, ask people to rate a number of objects as more or less similar to each other. ![]() One important tool used by psychologists to look into similarity is computer modeling. ![]() Many psychologists try to find out what rules people use when they decide that two things are similar. What is the similarity principle Gestalt Principle : Similarity 1 The principle of similarity states that things which share visual characteristics such as shape, size, color, texture, value or orientation will be seen as belonging together. How do the attitudes that humans maintain about these intelligent systems reflect those that they maintain about other humans? How do they differ? And, what do these similarities and differences reveal about human cognition more generally? In this talk, I discuss a series of experiments related to these questions and highlight how they are helping us develop smarter artificial intelligence.Similarity in the area of cognitive psychology refers to things or ideas that people put together in the same groups, or categories, in their minds. Gestalt psychology focuses on how we perceive individual items as a whole. Google Maps), are increasingly the subjects of such attitudes. AI systems, from conversational virtual assistants (e.g. Some illustrative examples are: they believe that others will follow through on promises, hope that pets will remember and abide by basic training while they are home alone, and trust that a fiduciary will act in their best interest. Humans maintain a broad set of attitudes (mental states) towards the thinking-things that they encounter. My research exists at the intersection of human cognition and technology and is best described as an attempt to answer two related questions: 1) How do humans think about the minds of machines? 2) How do (or can) machines think about the minds of humans? I blend behavioral, data, and computer science approaches in service of answering these questions. I am also a first-generation college graduate (Utah State) from South-Central Idaho and most everyone I know calls me Nik. in Carnegie Mellon University’s Department of Social and Decision Sciences in May of 2020. I am a computational social scientist who researches how humans think about what machines know and how machines can think about what humans know. Smarter AI Through Psychology (And some psychological insights from AI) Institute for Creative Technologies, University of Southern California
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