Responsible AI



Fairness Is In The AI Of The Beholder

Brandon Purcell December 1, 2021
The value of responsible AI is clear. The pathway to it ... not so much. Discover how to operationalize responsible AI.

Taming The Supply Chain Tiger — Practical Measures To Mitigate Logistics Congestion

George Lawrie October 27, 2021
In a recent blog, my colleague Alla Valente described the increased risk of late shipments in complex, interconnected supply chains. As she pointed out, any element may fail as a result of random events such as strikes or earthquakes. Project managers following critical chain methodology build project “buffers” to absorb random shock. But in logistics, […]

Connected Insurance: Reality Or Hype?

Jeffery Williams August 16, 2021
I speak often with clients about the role of technology in insurance. Of the many innovations we discuss, connected insurance may be the most polarizing. Connected insurance (CI) is nascent across most insurance lines. But evolving consumer preferences and increasing competition from digital-first startups require forward-thinking insurers to harness emerging technology and invest in CI […]

Prepare For AI That Learns To Code Your Enterprise Applications (Part 2)

Diego Lo Giudice July 8, 2021
The future of work for application development and delivery professionals will look very different. Learn how to prepare for it today.

Singapore’s Model AI Governance Framework Sets Out To Help Organizations Deploy AI Responsibly

Achim Granzen February 5, 2021
Principal Analyst Achim Granzen examines how Singapore’s AI governance initiatives can serve as a model for other organizations.

AI Drives The Evolution Of Technology And Data Governance

Achim Granzen January 26, 2021
Learn why data and tech governance initiatives must evolve to embrace ethics and risk this year.

Explaining Explainable AI

Brandon Purcell December 18, 2020
In 2020, one message in the AI market came through loud and clear: AI’s got some explaining to do! Explainable AI (XAI) has long been a fringe discipline in the broader world of AI and machine learning. It exists because many machine-learning models are either opaque or so convoluted that they defy human understanding. But […]