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Using AI-driven solutions to understand ourselves

August 17, 2017

For thousands for years, humans have attempted to predict how we think. From the great ancient Greek philosophers to psychologists of the 21st century, many have tried to determine the mechanisms under which human beings perceive, understand, predict, and manipulate their environments in an increasingly complex world. The field of artificial intelligence (AI) goes even farther. Since the 1950’s, pioneers in the field have sought not to understand how we think, but how to build intelligent entities. Initially, artificial intelligence was confined to the realm of chess games and simple tasks; however, with the birth of Alexa, Watson, and other sophisticated programs, AI has come into its own as a field of endless possibility.

Coleman: the future of Infor AI

This past July, Infor announced the release of its new artificial intelligence product – Coleman. Named for Kathrine Coleman Johnson, the physicist and mathematician whose contributions to the early NASA space missions were featured in the Oscar-nominated movie Hidden Figures, Coleman is an enterprise-grade, industry-specific AI platform for Infor Cloudsuite applications. Acting as a smart partner to augment the user’s work, Coleman helps to automate jobs and help people use technology more efficiently. It uses image recognition, voice interaction, and automation to respond to questions, recommend improvements, and take full control of some basic tasks at the user’s option. Some elements of Coleman are available today, such as predictive inventory management for healthcare, price optimization management for hospitality, and forecasting, assortment planning and promotion management for retailers. However, one of Infor’s earliest ventures into the field of artificial intelligence began in the area of human capital management.

Artificial Intelligence and Talent Science

Infor Talent Science has spent the last 15 years building, implementing, and improving an artificial intelligence framework that allows employers to identify, select, and develop their talent. With the amount of data we gather on job applicants – in application forms, through our assessment, and employees working day to day on their jobs – we now have the ability to train AI platforms like Coleman to make our jobs easier by helping ensure we bring the right people into our organizations. Goal- and utility-based AI systems like Talent Science can predict who our high performers will be, who will stay on the job longer, and who is most likely to receive a promotion. Additionally, AI can help us avoid potentially negative outcomes associated with hiring – like adverse impact against protected groups. While some fear that AI-driven hiring will increase homogeneity of race, gender, and ethnicity in a workplace, systems can be trained to avoid exactly those negative outcomes while maximizing validity and positive predictive outcomes.

AI-driven Human Capital Management

In closing, let’s consider two concepts supported by AI concepts – better results and automation.

Better results: With Talent Science, we have documented statistically significant results across multiple industries, like how a retailer made AI-infused hiring decisions that led to a sales increase of $58 per hour.

Automation: This makes the life of recruiters easier. Through AI-driven hiring, we are able to help recruiters zero in on the right candidates faster and managers to identify people for the next opportunity.

Like Amazon’s Alexa helps us to place orders more effectively or select music that is most aligned with our taste, Talent Science’s AI capabilities automates the process of candidate selection, succession planning, and development. I’m looking forward to what Infor and Coleman can create in the immediate and long-term future.

Jill Strange, Ph.D., Vice President, Science Applications

  • Talent Science
  • North America
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