Data, AI, & Machine Learning

What if, instead of perpetuating harmful biases, AI helped us overcome them?

Makers of AI applications should stop overpromising, be transparent, and consider certification.

Recording expectations improves decision quality, risk management, and leadership development.

Digital tools are making the hiring process easier and more precise — despite their limitations.

Both consumers and businesses should be cognizant of potential decision-making biases online recommendations introduce.

The automotive sector believes that machine learning can help them achieve their marketing goals, but that doesn’t necessarily mean it invests in that ambition.

MIT SMR’s 2018 Strategic Measurement study reveals how organizations using ML to enhance KPI-driven decision-making are pulling ahead of their competitors.

Retailers have new challenges in getting customers to accept different prices on different channels.

Viewing technology as a set of solutions misses opportunities to innovate in bigger, bolder ways.

The future of AI looks much like the present, with machines helping humans to do their jobs better, not replacing them.