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AI 'hallucinates' constantly, but there's a solution - Live Science
One of the biggest challenges that decision-makers, business leaders, and operations managers face with AI technology is their high rate of "hallucination." Unchecked, this can lead to disastrous consequences, especially when AI systems are rooted in company operations and strategic decision-making.
AI 'hallucinates' because they were originally built to process and produce accurate and reliable results based on their programmed instructions and database inputs. However, their algorithms can sometimes go awry, leading to incorrect or misleading results.
Software developers and engineers have noticed that AI systems, coupled with their machine learning counterparts, often struggle with reality. It is a conundrum: while they're designed to learn from experience, their ability to discern the truth can deteriorate, leading to misinformation.
According to many experts, the hallucination problem isn’t entirely abysmal. It has a fix: AI algorithms can be refined and corrected to stay more attuned to reality. Supervised learning can be implemented, where the AI is trained using labeled data to differentiate between fake and real. Another way to address this is to have humans in the loop where AI-generated information needs to be reviewed and double-checked.
A structured multi-step approach forward could include:
- Establish a standard of oversight and control.
- Audit and monitor AI systems continuously.
- Implement rigorous tests to evaluate the AI's accuracy, and constantly update system training data.
Human oversight, strengthening algorithms, and ensuring the AI is always recalibrating to new standards, means that the adverse consequences of hallucinations can be mitigated significantly. It also should be noted that with constant advancements in technology, a more refined and efficient AI system designed to better discern truth is just around the corner.
Source: "artificial intelligence" - Google News, Link
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