Plainsight featured on ClickAI Radio with Grant Larsen, Episode 137 How AI Ethics Affects Your Business!

Plainsight’s Co-Founder & CEO, Carlos Anchia, and co-founder & CPO, Elizabeth Spears, recently sat down with Grant Larsen of ClickAI Radio to discuss how AI ethics can affect your business.

In this episode Carlos, Elizabeth, and Grant tackle the complex topic of ethics in the field of artificial intelligence, answering questions and exploring topics such as:

  • How and when AI should be applied 
  • How to ask the right questions before training a machine learning model
  • Why keeping track of data and models with version control can help
  • And more!

You can listen to the full episode on Youtube or through Apple Podcast.

More Plainsight Blog Posts:

5 Ways Agribusinesses Can Prevent Recalls, Shutdowns, and Delays with Vision AI

5 Ways Agribusinesses Can Prevent Recalls, Shutdowns, and Delays with Vision AI

Investments in computer vision technology can help agribusinesses and food manufacturers of all types spot signs of trouble early and stop costly, potentially deadly recalls before they happen. Deployed across the production and manufacturing cycles, these models can detect hazards ranging from contaminants and foreign objects to defective equipment and non-compliant behavior. Organizations capture hundreds of thousands of hours of visual data in the form of video footage and imagery every day, and computer vision allows these businesses to put this data to work for process transformation.

How Can Vision AI Predict and Prevent Supply Chain Disruptions?

How Can Vision AI Predict and Prevent Supply Chain Disruptions?

Introducing computer vision across the supply chain can help manufacturers predict and prevent the types of conditions that lead to these kinds of disruptions. From potential contaminants and foreign objects to defective products and packaging to unsafe or unsanitary behavior, computer vision is the key to recognizing supply chain obstacles early and stopping shortages in their tracks. AI solutions could prove especially useful in volatile, high-production periods where errors and disruptions are both especially likely and especially costly.