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Tag Archives | AI

deploying-artificial-intelligence

Three Ways To Prepare Your Workforce for Artificial Intelligence

Only 20% of U.S. companies are fully deploying artificial intelligence (AI) for decision-making in their businesses based on survey responses from 1,000 senior business executives. According to the news site Axios, 61% of organizations are just starting to adopt AI for decision-making, while 19% are categorized as having barely begun. Surveyed business leaders are hesitant […]

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machine-learning-models

Four Reasons Machine Learning Models Fail and How to Fix Them

Machine learning is a branch of artificial intelligence (AI) in which algorithms are trained to get better at solving problems on their own, similar to the functionality of a human brain. While organizations are rapidly adapting machine learning to enhance their business operations, many are failing to build machine learning models that work.  Why do […]

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data-drift-machine-learning

Four Ways to Build MLOps that Avoid “Data Drift” in Machine Learning

Organizations are increasingly adopting machine learning, a type of artificial intelligence that allows software applications to get better at predicting outcomes on their own. While these models can help businesses make better decisions, they have a major weakness. Once the data that support machine learning models become outdated, so too do the models—a problem known […]

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managing-bias-in-artificial-intelligence

NIST: Recommendations for Identifying and Managing Bias in AI

Organizations that fail to prevent bias from slipping into their artificial intelligence (AI) systems may soon find themselves in regulatory trouble. As we discussed in a previous post, the U.S. Federal Trade Commission announced in April that private companies that sell biased AI systems can be subject to laws under the FTC Act, which outlaws […]

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trust-in-AI

U.S. Standards Agency Announces New System To Measure Trust in AI

In order for humans to fully embrace artificial intelligence (AI), they need to trust it. While there hasn’t been a standard way for organizations to gage how much people trust their AI models, that could soon change. The National Institute of Standards and Technology (NIST), an agency that falls under the U.S. Department of Commerce, […]

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digital-transformation-for-growth

Six Ways Organizations Can Leverage Digital Transformation for Growth

Thousands of organizations all over the world underwent digital transformations during pandemic-related shutdowns as a means of survival. Now, as they emerge from lockdowns, many are beginning to use digital transformation as a tool for growth. Moving forward, organizational leaders need to determine key metrics that can help them meet their growth goals. Here are […]

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fair-ai-systems

U.S. Federal Trade Commission: Seven Ways to Help Ensure Fair AI Systems

In April, the European Union (EU) and the U.S. Federal Trade Commission (FTC) each released regulations aimed at curbing the potential risks of artificial intelligence (AI). While the FTC regulations apply nationally in the U.S., enforcement of the EU regulations is left to EU member states. Both regulations apply to private companies only, though they […]

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artificial-intelligence-regulations

Three Major Trends In Artificial Intelligence Regulation

Artificial intelligence (AI) regulations are coming. In March, five of the largest U.S. financial regulators sent banks an information request inquiring about how they are using artificial intelligence. Such a request indicates that the financial sector will soon be facing guidelines around the technology. Additionally, the U.S. Federal Trade Commission (FTC) released definitions in April […]

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machine-learning-questions

Four Machine Learning Questions Organizations Should Ask

Machine learning can deliver major benefits for organizations looking to scale their operations, especially those who continue to experience disruptions from the COVID-19 pandemic. However, there are plenty of challenges that come along with implementing this type of artificial intelligence. Before organizations jump headfirst, there are four major machine learning questions they should consider. 1) […]

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