AI ethics issues
Chatbots and other artificial intelligence technologies that interact with humans raise ethics questions that enterprises can't ignore. Is it acceptable to present a bot as a human? How do you eliminate AI bias? Do organizations need an AI code of ethics? Read what experts have to say on AI ethics issues, whether companies should self-impose an AI code of ethics and more.
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AI ethics issues News
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January 15, 2021
15
Jan'21
Diverse talent pools and data sets can help solve bias in AI
Bringing historically underrepresented employees into critical parts of the design process while creating an AI model can reduce or eliminate bias in that model.
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January 13, 2021
13
Jan'21
The power and limitations of enterprise AI
A panel at CES 2021, held virtually this year, discusses the areas in which modern-day AI and automation shine, and where they still struggle.
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January 12, 2021
12
Jan'21
White House issues guiding principles for AI regulations
While the recommendations for AI regulation in the White House memo are loose, they appear to show the government is beginning to embrace AI, and could be a start toward oversight.
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January 08, 2021
08
Jan'21
Doubts about Trump video show how hard deepfakes are to detect
Some Twitter users insist that a recent video of President Trump admitting his defeat in the election is a deepfake, although there's no proof. Deepfakes are difficult to detect.
AI ethics issues Get Started
Bring yourself up to speed with our introductory content
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artificial intelligence
Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. Continue Reading
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How and why are our devices listening to us?
Consumers are utilizing digital voice assistants and smartphones but may not realize how frequently companies listen in and sift through all the data these devices create. Continue Reading
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The peaks and pitfalls of hyper-personalization marketing
As consumers begin to revolt against unlimited personal data collection and usage, the longevity of hyper-personalized communication may be cut short. Continue Reading
Evaluate AI ethics issues Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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Bias in machine learning examples: Policing, banking, COVID-19
Human bias, missing data, data selection, data confirmation, hidden variables and unexpected crises can contribute to distorted machine learning models, outcomes and insights. Continue Reading
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In-depth guide to machine learning in the enterprise
Enterprises are adopting machine learning technologies at rapid rates. In this machine learning guide, we break down what you need to know about this transformative technology. Continue Reading
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5 AI risks businesses must confront and how to address them
Some risks associated with implementing AI systems are familiar to enterprise leaders; these five are unique to AI. Here's how to address them. Continue Reading
Manage AI ethics issues
Learn to apply best practices and optimize your operations.
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Building trustworthy AI is key for enterprises
Organizations need to focus on transparency in models, ethical procedures and responsible AI in order to best comply with guidelines for developing trustworthy AI systems. Continue Reading
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Machine learning and bias concerns weigh on data scientists
Data scientists are forever vigilant in their desire to identify and eliminate the many forms of bias that can compromise the credibility of machine learning models. Continue Reading
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Responsible AI champions human-centric machine learning
Encompassing ethics, transparency and human centricity, responsible AI is an effective approach to deploying machine learning models and achieving actionable insights. Continue Reading
Problem Solve AI ethics issues Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
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Data science's ongoing battle to quell bias in machine learning
Machine learning expert Ben Cox of H2O.ai discusses the problem of bias in predictive models that confronts data scientists daily and his techniques to identify and neutralize it. Continue Reading
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Here's how one lawyer advises removing bias from AI
Avoiding bias in AI applications is one of the central challenges in using the technology. Here's some advice on deploying AI technologies in a way that is fair. Continue Reading
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Supervise data and open the black box to avoid AI failures
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