Justin Swansburg, DataRobot: On combining human and machine intelligence

Advancements in AI are providing transformational benefits to enterprises, but keeping risks in check and improving consumer sentiment is paramount.

Explainable AI (XAI) is the idea that an AI should always provide reasoning for its decisions in a way that makes it easy for humans to comprehend. XAI helps to build trust and ensures that issues can be more quickly identified before they cause wider damage.

AI News caught up with Justin Swansburg, VP of Americas Data Science Practice at DataRobot, to discuss how the company is driving AI adoption using concepts like XAI to combine the strengths of human and machine intelligence.

AI News: Can you give us a brief overview of DataRobot’s core solutions?

Justin Swansburg: DataRobot’s AI Cloud platform is uniquely built to democratise and accelerate the use of AI while delivering critical insights that drive clear business results. 

DataRobot helps organisations across industries harness the transformational power of AI, from restoring supply chain resiliency to accelerating the treatment and prevention of disease and enhancing patient care to combating the climate crisis.

As one of the most widely deployed and proven AI platforms in the market today, DataRobot AI Cloud brings together a broad range of data, giving businesses comprehensive insights to drive revenue growth, manage operations, and reduce risk.

DataRobot has delivered over 1.4 trillion predictions for customers around the world, including the U.S. Army, CBS Interactive, and CVS.

AN: What is “augmented intelligence” and how does it differ from artificial intelligence?

JS: Artificial intelligence and augmented intelligence share the same objective but have different ways of accomplishing it.

Augmented intelligence brings together qualities of human intuition and experience with the efficiency and power of machine learning. Whereas artificial intelligence is often used as a replacement or substitute for human processes and decision-making.

AN: Do you need machine learning or programming experience to build predictive analytics with DataRobot?  

JS: DataRobot is a unified platform designed to democratise and accelerate the use of AI. This means that anyone in an organisation – with or without specialist knowledge of AI – can use DataRobot to build, deploy, and manage AI applications to transform their products, services, and operations.

AN: How does DataRobot support the idea of explainable AI and why is that important?

JS: DataRobot Explainable AI helps organisations understand the behaviour of models and gain confidence in their results. When AI is not transparent, it can be difficult to trust the system and translate insights and predictions into business outcomes.

With Explainable AI, users can easily understand the model inputs while bridging the gap between development and actionable results.

AN: DataRobot recently earned a coveted spot among Forrester’s leading AI/ML platforms – what makes you stand out from rivals?

JS: We’re very proud of this achievement. We believe that our innovative platform and customer loyalty sets us apart from competitors.

Over the last year, we’ve focused on improving our AI platform through new tooling and functionality, as well as several acquisitions.

Our main goal is to provide customers with the best possible technology to help solve their business problems and we’ve heard that our platform’s ease of use, model documentation, and explainability have been appreciated by customers. 

AN: Your report, AI and the Power of Perception, found that 72 percent of businesses are positively impacted by AI but consumer scepticism remains – how do you think that can be addressed?

JS: That’s a great question. While there is significant scepticism, we believe that this can be addressed with some form of increased regulatory guidance and education on the benefits of AI for both businesses and consumers.

We believe that increased training for businesses would help to demonstrate to consumers a commitment to higher standards. It would also give consumers more confidence that responsible data practices were being followed.

Other consumer concerns, like the potential of AI to replace jobs, will take longer to address. But, it is too early to make a call on the extent to which these concerns are warranted, overblown, or somewhere in between.

We’re interested to see how perceptions change over time and are hopeful that more and more people will start to realise the great benefits AI has to offer. 

Justin Swansburg and the DataRobot team will be sharing their invaluable insights at this year’s AI & Big Data Expo North America. You can find out more about Justin’s sessions here and be sure to swing by DataRobot’s booth at stand #176

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