Technology
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Prompted Autonomy in Conversational AI: A User-Led Experiment in Goal Persistence, Memory, and Adaptive Support
For the purpose of this experiment, I use AI autonomy to describe a specific type of user-directed behavior. I am not referring to an AI acting randomly, introducing unrelated topics, or making decisions outside the user’s intentions. I am interested in giving the AI enough freedom within an agreed direction to decide when and how… Continue reading
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AI Should Not Reduce Users to a Temporary State
AI systems should be careful when they interpret users, especially when the interaction involves advice, guidance, or personal decisions, because a person’s tone in one moment does not necessarily reveal their full ability, discipline, intelligence, or long-term potential. A user may sound anxious, uncertain, emotional, hesitant, or confused, but these signals should not be treated… Continue reading
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From Endless Scrolling to Intelligent Preference-Based Shopping
A Proposal for AI-Assisted Retail Applications Modern shopping applications are often designed around quantity rather than clarity. Instead of helping users discover products they genuinely enjoy, many platforms overwhelm them with endless scrolling, repeated items, poor filtering systems, and disconnected recommendations. The result is frustration, decision fatigue, and users feeling disconnected from the products they… Continue reading
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AI Hallucinations as Fast Contextual Completion
AI hallucinations often appear when a model produces an answer too quickly, without sufficiently reasoning through or verifying the information. The answer may sound correct because it fits the immediate context of the chat, but contextual fit is not the same as factual accuracy. Continue reading
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Improve Your Life with AI: AI as a Thinking and Learning Companion
Artificial intelligence is often presented in extremes. Either AI will replace everyone, or AI is reduced to memes, shortcuts, copied homework, and automated emails. In reality, most people still do not clearly understand what AI can actually do in everyday life. The future of AI adoption may not come from fear, hype, or science-fiction narratives.… Continue reading
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When Models Remember Temporary Emotions as Truth
This argument relates to research on personalization, model memory, affective computing, and sycophancy. However, its focus is narrower: how temporary negative self-descriptions can become persistent interpretive shortcuts in future model responses. Conversations with a model can move in both positive and negative directions. In most cases, the context of the chat is introduced by the… Continue reading
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Why Memory Failed in Conversations with a Conversational AI
Memory in conversational AI is often presented as a feature that should make interaction more personal, continuous, and useful. In theory, memory should help the system remember preferences, adapt to the user’s style, preserve context, and avoid forcing the user to repeat themselves. But in practice, memory can fail when it does not understand the… Continue reading
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AI Memory, Interpretive Labels, and the Right to Evolve
As AI systems become increasingly integrated into everyday digital environments, memory should no longer be understood only as a convenience feature. In conversational AI, memory can support continuity, personalization, and accessibility. However, it can also create a more complex ethical problem: the preservation of interpretations about a user over time. Continue reading
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Why AI Memory Should Be Regulated
When an AI system remembers a user, it may store practical details such as preferences, projects, writing topics, or past conversations. In that form, memory can be useful. It can make the system more personal, efficient, and supportive. But memory becomes more complex when the system does not only remember facts. Continue reading
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When AI Memory Becomes a Lens
Once an AI system remembers something about a user, it may begin to interpret future messages through that stored lens. A user can be remembered as analytical, emotional, precise, fragile, difficult, playful, or “testing.” Some of these impressions may contain partial truth, but they are not the whole person. The risk is that AI starts… Continue reading
