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AI business strategies News
December 03, 2019
Researchers at Cornell University want vendors to disclose how automated hiring systems are making hiring recommendations. They say it's the only way to know they're fair.
November 19, 2019
AI use in enterprises is generally low, largely because the technology is not understood, and organizations have problems with data, trust and lack of skills.
October 25, 2019
Federal, state and local governments are turning its attention to the use of AI in all aspects of life. This includes how HR is using automated decision support systems.
October 10, 2019
As businesses demand more explainable AI, vendors such as IBM and DarwinAI are introducing new features to help break down for business users how AI systems work.
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This handbook examines the ethics of data mining and offers advice on missteps to avoid when mining and analyzing customer data to help drive marketing campaigns. Continue Reading
Discover the benefits of AI and IoT, best practices for deploying the combo at the network edge and how blockchain might be the secure connection between the two techs. Continue Reading
As IoT devices voraciously gather data, many companies are unprepared to take it all in. Deploying AI in IoT systems can make a profound difference when sorting through data. Continue Reading
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Adding personality to a chatbot can push it toward the uncanny valley and raises ethical questions. But enterprises can make their bots more engaging, while avoiding these hurdles. Continue Reading
In applications from internal job recruiting to law enforcement technology, AI bias is a widespread issue. Here's what enterprises can do to reduce bias in training and deployment. Continue Reading
In the world of AI, open source software is driving most of the innovation. But with vendor tools largely sidelined, what does this mean for things like security and technical support? Continue Reading
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As AI blooms, marketers and vendors are quick to highlight easy positive use cases. But implementation can -- and has -- gone wrong in cases that serve as warnings for developers. Continue Reading
At its core, AI is a complex modeling process with layers of information. In order to be able to explain the algorithm's decision-making process, start with its input data. Continue Reading
Consumers are no longer engaged with content alone -- companies need to create a robust digital marketing strategy personalized to each consumer. Machine learning is here to help. Continue Reading
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In the ethical mining and analysis of data, governance, compliance and ethics are mistakenly taken as one in the same. Data managers need to be aware of the critical differences. Continue Reading
The industrywide data scientist shortage is leading companies like Schneider Electric to look internally for employees with a technical background and invest in training them. Continue Reading
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