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AI ethics issues News
October 08, 2021
Some government and business leaders want more AI regulation to ensure that systems don't discriminate against or harm others. Others say too much regulation will stifle innovation.
September 20, 2021
AI recruiting tools focus on hiring efficiency rather than efficacy, according to an Accenture-Harvard Business School study. The U.N. believes AI is fostering human rights abuse.
May 14, 2021
Biden's focus on AI includes funding research and development, manufacturing chips in the U.S. and preparing a workforce to use AI tools.
April 21, 2021
Updates include new federated learning capabilities within IBM Watson Studio and more insights into how predictions are made in IBM Planning Analytics with Watson.
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To ensure model accuracy, businesses need to understand why their machine learning models make their decisions. Certain tools and techniques can help with that. Continue Reading
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision. Continue Reading
Executives are aware of the value artificial intelligence in its many forms can bring to enterprises yet devising a viable AI strategy can be as complex as the technology itself. Continue Reading
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Ethical AI black box problems complicate user trust in the decision-making of algorithms. As AI looks to the future, experts urge developers to take a glass box approach. Continue Reading
Tiny ML, multi-modal learning, responsible AI -- learn about the top trends in AI for 2021 and how they promise to transform how business gets done. Continue Reading
A biased AI system can lead businesses to produce skewed, harmful and even racist predictions. It's important for enterprises to understand the power and risks of AI bias. Continue Reading
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Neural networks have many use cases. Businesses interested in using AI should consider both the challenges and potential gains of deploying neural nets. Continue Reading
Companies can use AI to help the environment, including by using it to prevent forest fires and reduce factory waste. At the same time, AI has its own carbon footprint. Continue Reading
AI can both help and hurt the environment. While companies use artificial intelligence to increase factory efficiency and lower energy costs, training AI demands a lot of energy. Continue Reading
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Improving AI explainability and interpretability are keys to building consumer trust and furthering the technology's success. Continue Reading
By employing a diverse team to work on AI models, using large, diverse training sets, and keeping a sharp eye out, enterprises can root out bias in their AI models. Continue Reading
Though data bias may seem like a back-end issue, the enterprise implications of an AI software using biased data can derail model implementation. Continue Reading