We all interact with AI almost daily-when we deposit checks through an app, when we talk to Siri and Alexa, when we scroll through our personalized social media feeds

"When AI works well, it makes our lives easier. But when AI goes bad, it can have far-reaching negative effects. Biases in race, gender, class and other markers have made their way through to the output of even the most well-intentioned and thought-out AI systems.

If you are involved in AI, whether as a data scientist building the model or a business decision-maker defining the model's objectives, you need to understand the ways in which AI can go bad, because the harmful effects are felt not just by the business but by our society. Here are two examples of this phenomenon..."

Have you heard automation is the new black? And what better automation of a process than using a computer software to perform humanlike activities aka Artificial Intelligence (AI)

"Whether we realize it or not, artificial intelligence is all around us, playing an active role in our daily lives. The fun part is that many of us fear it just because we don't know its real power and what wonders we can do with it.

Sure, there are pros and cons of AI, but if we just focus on the pros, we can keep the cons under control. Artificial intelligence can not only make our lives better, it can supercharge our businesses. Automotive, healthcare, finance, travel, and so many other industries can perfect their businesses with it. Here are the three key areas of a business that can be automated with AI..."

Lawrence Livermore National Laboratory (LLNL) is looking for participants and attendees from industry, research institutions and academia for the first-ever Machine Learning for Industry Forum (ML4I), a three-day virtual event starting Aug. 10

"The deadline for submitting presentations or industry use cases is June 30. The deadline for attendee registration is July 29. Pre registration is now open.

The forum aims to foster and illustrate the adoption of machine learning methods for practical industrial outcomes, with a strong emphasis on manufacturing. Over the course of the event, attendees will engage in dialog about applications, tools and techniques and special topics centered around machine learning's impact and potential in industry. Topics will include process control and optimization, computer vision and robotics, workflows, hardware and software, dataset augmentation and curation, supply chain optimization and physics-constrained learning. The forum also will highlight industry use cases..."

See all Archived IT - AI articles See all articles from this issue