How do you bring artificial intelligence into an organization that's functioned perfectly well without it for decades? That was the challenge faced by Humana Chief Data and Analytics Officer Slawek Kierner when he joined the Fortune 42 healthcare insurance provider in December 2018. Kierner, who had served as Microsoft's PowerBI, Dynamics, Cloud and AI Chief Data and Analytics Officer at Microsoft before joining Humana, recounted his experience of bringing AI to Humana during the AI Summit in New York this month. In a session at the event, Kierner presented the process of introducing AI to the organization, and Adam Wenchel, co-founder and CEO of machine learning monitoring startup Arthur, introduced Kierner and facilitated a question-and-answer session afterward with his own questions plus questions from the audience. Wenchel pointed out how quickly AI in the enterprise has evolved.

At a time when more companies are building machine learning models, Arthur.ai As demand for this type of tool has increased this year, in spite of the pandemic, the startup announced a $15 million Series A today. The investment was led by Index Ventures with help from newcomers Acrew and Plexo Capital, along with previous investors Homebrew, AME Ventures and Work-Bench. The round comes almost exactly a year after its $3.3 million seed round. As CEO and co-founder Adam Wenchel explains, data scientists build and test machine learning models in the lab under ideal conditions, but as these models are put into production, the performance can begin to deteriorate under real-world scrutiny.

Machine learning is a complex process. You build a model, test it in laboratory conditions, then put it out in the world. After that, how do you monitor how well it's tracking what you designed it to do? Arthur wants to help, and today it emerged from stealth with a new platform to help you monitor machine learning models in production. The company also announced it had closed a $3.3 million seed round, which closed in August.

In January, Liz O'Sullivan wrote a letter to her boss at artificial intelligence startup Clarifai, asking him to set ethical limits on its Pentagon contracts. WIRED had previously revealed that the company worked on a controversial project processing drone imagery. O'Sullivan urged CEO Matthew Zeiler to pledge the company would not contribute to the development of weapons that decide for themselves whom to harm or kill. At a company meeting a few days later, O'Sullivan says, Zeiler rebuffed the plea, telling staff he saw no problems with contributing to autonomous weapons. Clarifai did not respond to a request for comment.

In January, Liz O'Sullivan wrote a letter to her boss at artificial intelligence startup Clarifai, asking him to set ethical limits on its Pentagon contracts. WIRED had previously revealed that the company worked on a controversial project processing drone imagery. O'Sullivan urged CEO Matthew Zeiler to pledge the company would not contribute to the development of weapons that decide for themselves whom to harm or kill. At a company meeting a few days later, O'Sullivan says, Zeiler rebuffed the plea, telling staff he saw no problems with contributing to autonomous weapons. Clarifai did not respond to a request for comment.

In January, Liz O'Sullivan wrote a letter to her boss at artificial intelligence startup Clarifai, asking him to set ethical limits on its Pentagon contracts. WIRED had previously revealed that the company worked on a controversial project processing drone imagery. O'Sullivan urged CEO Matthew Zeiler to pledge the company would not contribute to the development of weapons that decide for themselves whom to harm or kill. At a company meeting a few days later, O'Sullivan says, Zeiler rebuffed the plea, telling staff he saw no problems with contributing to autonomous weapons. Clarifai did not respond to a request for comment.

Adam Wenchel, Vice President of AI and Data Innovation at Capital One, knows his way around AI. He's an Artificial Intelligence trailblazer with more than 20 years of experience in the field. "If you changed the rules of chess, a human grandmaster would be able to adapt. They wouldn't be quite as good at it, but they'd be able to play the game." He took the only two AI classes available at his college in the late 1990's and his first gig after graduation was working in AI at DARPA--the agency that created the internet. Just outside the door sit all the trappings of smart people trying to solve difficult problems: open spaces, curved monitors, free snacks and the soft ticking of keyboards punctuated by a vintage mechanical keyboard around a corner somewhere.

Powerful machine-learning methods have taken the tech world by storm in recent years, vastly improving voice and image recognition, machine translation, and many other things. Now these techniques are poised to upend countless other industries, including the world of finance. But progress may be stymied by a significant problem: it's often impossible to explain how these "deep learning" algorithms reach a decision (see "The Dark Secret at the Heart of AI"). Adam Wenchel, vice president of machine learning and data innovation at Capital One, says the company would like to use deep learning for all sorts of functions, including deciding who is granted a credit card. But it cannot do that because the law requires companies to explain the reason for any such decision to a prospective customer.

Powerful machine-learning methods have taken the tech world by storm in recent years, vastly improving voice and image recognition, machine translation, and many other things. Now these techniques are poised to upend countless other industries, including the world of finance. But progress may be stymied by a significant problem: it's often impossible to explain how these "deep learning" algorithms reach a decision. Adam Wenchel, vice president of machine learning and data innovation at Capital One, says the company would like to use deep learning for all sorts of functions, including deciding who is granted a credit card. But it cannot do that because the law requires companies to explain the reason for any such decision to a prospective customer.