The use of LLMs by people lacking expertise and experience, and for purposes they were not originally intended for, is, on the one hand, a fine example of technological generativity; on the other hand, it is having profound and consequential effects on trust relationships.
The term “explainability” is a multifaceted concept within the realm of computer science. In essence, it encompasses various aspects and capacities of a system to effectively convey its internal processes, decision-making, capabilities, and constraints to its users. Providing explanations can notably enhance initial trust, especially when trust is measured as a multidimensional concept that includes aspects such as competence, benevolence, integrity, intention to return, and perceived transparency.
Mega-platforms have, with the addition of one extra ingredient, combined lock-in and loyalty to create a grave, and perhaps unexpected, consequence. The extra ingredient is psychology; and the unexpected consequence is what might be called digital dependence.
Social trust is violated when surveillance technologies fuel clandestine campaigns to construct oppressive systems used to control (and punish) members of society.
“Nudging” is the term used in the IEEE standards work on Ethics for AI Design. An AI system that applies deep learning to manipulating human decisions, with detailed analysis of the targeted individual, is a disturbing potential that must affect our trust in both the systems and those that direct their applications.
Figure 1. Privacy concerns arise for individuals when there is a high expectation of control over information pertaining to them… Read More
Uber isn’t in the taxi business. It’s not really in the dispatch business, or even in the tech business. It’s… Read More
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