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Machine unlearning: Researchers make AI models ‘forget’ data

AI News

Retaining classes that do not need to be recognised may decrease overall classification accuracy, as well as cause operational disadvantages such as the waste of computational resources and the risk of information leakage. Perhaps most importantly, this method addresses one of AIs greatest ethical quandaries: privacy.

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AI for Money Managers: Avoid the Black Box – And Do This Instead

Unite.AI

The opportunities afforded by AI are truly significant – but can we trust black box AI to produce the right results? Instead of utilizing AI systems that they cannot explain – black box AI systems – they could utilize AI platforms that use transparent techniques , explaining how they arrive at their conclusions.

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How Large Language Models Are Unveiling the Mystery of ‘Blackbox’ AI

Unite.AI

Theyre making AI explanations accessible to everyone, not just tech professionals. This method is designed to simplify complex explanations of explainable AI algorithms, making it easier for people from all backgrounds to understand. The conversational agent translates this technical information into something easy to follow.

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Who Is Responsible If Healthcare AI Fails?

Unite.AI

Similarly, what if a drug diagnosis algorithm recommends the wrong medication for a patient and they suffer a negative side effect? At the root of AI mistakes like these is the nature of AI models themselves. Most AI today use “black box” logic, meaning no one can see how the algorithm makes decisions.

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Using AI for Predictive Analytics in Aviation Safety

Aiiot Talk

AI is today’s most advanced form of predictive maintenance, using algorithms to automate performance and sensor data analysis. Aircraft owners or technicians set up the algorithm with airplane data, including its key systems and typical performance metrics. Black-box AI poses a serious concern in the aviation industry.

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Enhancing AI Transparency and Trust with Composite AI

Unite.AI

The adoption of Artificial Intelligence (AI) has increased rapidly across domains such as healthcare, finance, and legal systems. However, this surge in AI usage has raised concerns about transparency and accountability. Composite AI is a cutting-edge approach to holistically tackling complex business problems.

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Is Rapid AI Adoption Posing Serious Risks for Corporations?

ODSC - Open Data Science

Security and Compliance Cybersecurity is one of the biggest risks of rising AI adoption. These models require substantial amounts of data, and many organizations use “black box” models where they’re unsure of how the system uses the information they give it.