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.

April 21, 2021 21 Apr'21
IBM Watson updates focus on data privacy and explainability

Updates include new federated learning capabilities within IBM Watson Studio and more insights into how predictions are made in IBM Planning Analytics with Watson.
April 09, 2021 09 Apr'21
Check model accuracy with Facebook AI's new data set

Facebook paid people for their likenesses in its new Casual Conversations data set. The data set can help researchers check for bias in their AI models.
April 07, 2021 07 Apr'21
Research manager resigns amid Google AI ethics controversy

Prominent Google AI research manager Samy Bengio resigns from the company following months of internal discord and the termination of two AI researchers.
February 19, 2021 19 Feb'21
CTO on the need for AI ethics and diversity

A CTO talks about the importance of diverse data sets when creating AI models and how a lack of diversity can create bias in systems.

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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
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
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

Learn to apply best practices and optimize your operations.

Tackling the AI bias problem at the origin: Training data

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
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
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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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
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
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