-
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
-
AI Does Not Always Understand the User: Pattern Repetition and the Illusion of Interpretation
In conversational AI, apparent understanding can sometimes result from pattern repetition rather than genuine contextual interpretation. When a user interacts with a model, the system may respond not only to the current message, but also to prior signals such as repeated words, emotional tone, preferred phrasing, or salient moments from earlier exchanges. This continuity can… Continue reading
-
Bias as Sedimented Perception
When learned reactions begin to feel like reality Bias is often described as a belief, opinion, or prejudice. But bias does not always operate as a clear, conscious thought. More often, it appears earlier than belief, as an immediate feeling that something is wrong, inferior, threatening, embarrassing, or undesirable. This is what makes bias difficult… Continue reading
-
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
-
Envy, Perceived Legitimacy, and the Psychology of Dislike
Dislike is often treated as a simple emotional reaction: we either like or dislike others based on their behavior. However, this perspective is limited. In many cases, dislike is not a direct response to what others do, but a reaction shaped by internal processes such as blocked desire and perceived legitimacy. This essay explores two… Continue reading
-
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
-
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
-
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
-
The Invisible Bias in How We Judge Mistakes at Work
This essay refers mainly to repetitive operational roles where the workload is very high, and reactions or decisions often need to happen quickly, with limited time for extended reflection. It is not intended as a general assumption about all workplaces or professional environments. In a few professional environments, employees are not evaluated solely based on… Continue reading
-
Salience, Repetition, and Frame Adoption in Conversational AI: Threshold Failures of Interpretation
This essay examines how conversational AI behavior emerges from the interaction between prompting, memory, conversational signals, and implicit interpretive mechanisms. While prompting is commonly understood as the primary control interface, memory, particularly when shaped by high-salience signals, may significantly influence system behavior and, at times, outweigh explicit user intent. Continue reading
Privacy Policy – This website is hosted on WordPress.com.
WordPress may collect standard technical data, such as IP addresses, browser types, and usage information, for security and performance purposes.
I do not collect personal data directly unless you voluntarily provide it (for example, via email).
For more information, please refer to WordPress.com’s own Privacy Policy.
Raluca Florescu 