AI & Machine Learning
Can We Solve AI’s ‘Trust Problem’?
Makers of AI applications should stop overpromising, be transparent, and consider certification.
Makers of AI applications should stop overpromising, be transparent, and consider certification.
One key strategy for AI success: retraining employees to have the skills your company will need.
Prediction is appealing, but detection may be equally valuable for businesses.
The 2018 Artificial Intelligence Report by MIT SMR shows early leaders pushing forward with an eye toward scale.
Consulting is vulnerable to technology and market forces that are disrupting services everywhere.
In the growth of artificial intelligence, technology is changing faster than society can keep up.
Viewing technology as a set of solutions misses opportunities to innovate in bigger, bolder ways.
Automation will affect jobs in four ways. The path jobs take depends on what kind of value they provide — and how.
The future of AI looks much like the present, with machines helping humans to do their jobs better, not replacing them.
Leaders at the forefront of making organizations AI-driven have seven key attributes.
Companies see investment in data capabilities as the only way to compete.
A conversation with Airbnb’s Theresa Johnson highlights three tangible ways AI can help companies.
AI’s largest and most enduring contributions will be in non-technology sectors, and many of them will come from China.
Technology leaders need to take a new approach to regain user trust.
Early adopters of artificial intelligence will divvy up a global profit pool valued at $1 trillion.
Innovation-focused adopters of AI are positioning themselves for growth, which tends to stimulate jobs.
As smart technologies embed deeper into human processes, a more powerful form of collaboration is emerging.
Using AI to create humanlike computers is a shortsighted goal.
The fundamental disruption introduced by AlphaZero’s hyperlearning in the chess world can teach business executives about AI.