"Digital transformation today is more than just automating tasks or speeding up calculations. It’s reshaping how we make decisions. People used to rely on their own experience and negotiation skills, but now algorithms are often taking over."
"Artificial intelligence is only as good as the data it gets and the goals it's built to reach. To create AI that people really trust, we need to make sure our data is reliable and fair."
"Trust is often viewed as a personal bond, where one person depends on another's abilities, goodwill and honesty. When trust is broken in relationships, it feels like betrayal rather than just disappointment."
"A practical strategy is to distinguish reliance from trust. Reliance involves expecting a machine to perform tasks accurately, while trust encompasses deeper expectations that machines currently cannot fulfill."
Digital transformation reshapes decision-making, shifting reliance from personal experience to algorithms. This shift enhances efficiency but risks spreading inequality if data is inaccurate or unbalanced. Trust in AI hinges on the reliability and fairness of data. A data trust scoring framework is crucial for translating fairness concepts into actionable ratings for data sets. Trust in AI differs from human trust, as machines lack moral judgment, necessitating a focus on transparency and fairness. Distinguishing reliance from trust is vital for effective AI integration.
Read at InfoWorld
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