Artificial Intelligence

CIO100 2018 #31-100: Stella Ward, Canterbury District Health Board

CIO100 2018 #31-100: Mikal Todd, solarcity New Zealand

CIO100 2018 #31-100: Shayne Tong, Auckland District Health Board

CIO100 2018 #21: John Bell, Fletcher Building

IBM bets big on the ‘incumbent disruptor’

In the AI era, your data is your most valuable asset. Learn how you can reduce your organization’s risk and protect it.

IBM bets big on the ‘incumbent disruptor’

IBM's gambit will hinge on whether or not enterprise leaders can reshape and reorient organizations built for one era to meet the needs of the next.

Up, down or out? Perspectives on artificial intelligence in health care today

There are several high-value applications for artificial intelligence in health care. Challenges with underlying data sources and new ethical concerns have emerged as significant factors driving adoption.

Busting bias in AI

Bias in AI systems can lead to unintended consequences. Making sure you you understand the ways AI systems are interpreting the data they receive is one way to address the problem.

9 machine learning myths

When technology is as hyped as machine learning is, misunderstandings and misconceptions abound. Here's a clear-eyed look at what machine learning can and can't deliver.

Artificial intelligence gives HR an opportunity to transform the enterprise

Human resources has to play a strategic role in leveraging AI to shape future of work and organization agility.

Moving toward outcome-based intelligence

Newer machine learning techniques coupled with better programming techniques and more data-driven skills should make a difference, and so should better tools to directly connect outcomes to the core models.