Technology Implementation

Facial recognition tech can identify and analyze key emotional states — but must be used with care.

Avoiding the technology trap, AI needs a human touch, and good storytelling with data.

Blockchain is vulnerable in some ways that conventional systems are — and in ways all its own.

History shows we should focus more on policy than technology challenges when confronting automation.

Preparing for CEO turnover, demystifying AI, and operating in the age of online outrage.

Tom Davenport, Alex Breshears, and Abbie Lundberg discuss the specific challenges enterprises face in machine learning, and how they can create an end-to-end, factory-like capability.

Stanford’s Bob Sutton examines the non-financial debts that companies carry on Three Big Points.

The most effective use of AI: Symbiotic systems enabling humans and AI to work to their strengths.

How companies are making AI pay; tread cautiously in a transparent world; CIOs step up their game.

CIOs steeped in technical operations must change gears and develop a strategic focus.

Gain actionable insights from peers and AI experts during a live Twitter chat.

Early AI winners align organizational and business strategies to build value and manage risk.

Our flawed approach to the AI race, corporate boards get less cozy, and not much love for Libra.

If companies want to compete with blockchain, they must first cooperate to develop standards.

AI offers the potential to break down silos and make collaboration more effective.

Alternating between always-on connectivity and heads-down focus is essential for problem-solving.

Automation can go far beyond cars. Self-driving company capabilities are closer than we realize.

#MITSMRChat participants shared ideas about best practices for organizations implementing AI.

Data and algorithms can mitigate gender bias in venture capital funding.

As AI becomes more ubiquitous, we need clear systems for keeping it in check.