-- *Mar*Great question! You’ve touched on some really important points about the nature of *scientific evidence* and the relationship between machines, statistics, perception, and emotions. Let’s break it down: What is scientific evidence?
At its core, *scientific evidence* refers to the data and observations that support or refute a hypothesis, theory, or claim. It typically comes from: 1. *Experiments*: Controlled environments where variables are manipulated to observe outcomes. 2. *Observations*: Data collected through observation, often in natural settings or through measurements. 3. *Statistics*: The mathematical analysis of data, which helps determine whether an observed effect is significant or due to chance. 4. *Peer Review*: The process by which other experts in the field scrutinize and validate findings before they are accepted as part of the scientific body of knowledge. The role of *machines* or technology in this process is critical in modern science. Machines can help gather vast amounts of data, model complex phenomena, and even detect things that are too small, too fast, or too far to see with human eyes (like particles at the quantum level or signals from distant galaxies). But machines are not the *deciders*—humans interpret the data. Can there be trustworthy evidence without emotions? This is a nuanced question. In science, *objective* reasoning is the goal, and emotions are typically kept out of the data analysis itself. For instance, statistical models, machine analysis, and controlled experiments are designed to minimize biases and emotional influences. But the *interpretation* of evidence, especially when it involves the broader implications of the data, can be influenced by human perception, values, and emotions. Humans bring their experiences, cognitive frameworks, and biases to the table when interpreting evidence. For example, in a medical study, even if the statistical evidence points to the efficacy of a new drug, the societal, ethical, or emotional context might influence how that evidence is applied or communicated. *So can understanding exist without emotion?* Not entirely. Emotions, in a way, shape how we perceive the world and assign meaning to what we observe. Even in science, emotions play a role in motivation (curiosity, awe, excitement) and in how we prioritize certain areas of research. The need to *understand* often arises from a mix of intellectual curiosity and personal or societal emotional drives (like wanting to solve a problem, help others, or explain the mysteries of existence). The problem of invisible connections and the limits of perception: You raised a good point about not being able to see 99.9965% of "totality"—this likely refers to things like dark matter, quantum phenomena, or other aspects of the universe that are invisible or inaccessible to our direct senses. Scientific evidence in such cases often comes from indirect measurements, mathematical modeling, and statistical inference. *We trust that certain things exist or behave in specific ways based on patterns observed in the data*, even if we can't directly experience them. In such cases, science relies on: 1. *Models*: These are approximations of reality that try to explain the underlying structures or behaviors that are not directly observable. 2. *Correlation and causation*: Often in science, even if we cannot *see* a phenomenon directly, we can observe its effects. For example, we cannot see gravity directly, but we can observe its effects on objects. 3. *Mathematical consistency*: The beauty of many scientific theories is that they can predict phenomena that have not yet been directly observed, based on the consistency of their underlying mathematics (e.g., the predictions of general relativity before confirming black holes). How do emotions tie into this? *Emotions are part of human perception*, and human perception is how we make sense of the world. We cannot fully extricate ourselves from emotional states, biases, or cognitive filters when understanding scientific phenomena. But we strive to minimize the influence of emotion in formal scientific inquiry. That’s why things like double-blind trials, statistical significance, and peer review are so important: they reduce personal bias and emotional influence. Summary: - *Scientific evidence* is based on data gathered through observation, experimentation, and analysis, with an emphasis on objectivity and repeatability. - Machines play a significant role in collecting and analyzing data, but humans interpret the results. - Emotions and personal biases affect how we interpret evidence, but science tries to minimize their influence in order to arrive at objective conclusions. - While we might not be able to see everything (e.g., dark matter or quantum phenomena), scientific evidence can still be based on indirect observations, mathematical modeling, and statistical reasoning. - Understanding without emotion is impossible in human terms. Emotion and perception shape how we approach and internalize knowledge, even in fields as "objective" as science. Would you say that the role of emotion in interpreting scientific evidence is something you find more of an issue, or do you think it’s a natural part of how we make sense of complex phenomena? -- You received this message because you are subscribed to the Google Groups "Thatha_Patty" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion visit https://groups.google.com/d/msgid/thatha_patty/CACDCHCJ4V7d%3Dnz%2Bb-dezCNAdSZ8_jfZu_-orpjNMx_az%3D7s7ag%40mail.gmail.com.
