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Amidst the frantic warnings that automation may take the jobs of human workers, it is vital for talent management leaders to be a voice for a more nuanced approach. The advance of technology is inevitable, but rather than an "either-or" choice between humans and machines, innovative talent leaders are finding creative and optimal combinations of human and machine interaction.

Such combinations reveal new sources of value for both people and organizations, and they represent a formidable opportunity for savvy talent leaders to expand the value proposition of learning—as well as ensure the sustainability of their organizations.

Working With the Supercomputer

Consider the savvy combination of humans and machines that is embodied in IBM's work on “cognitive" computing—best exemplified by IBM's Watson, a combination of algorithms, interfaces, hardware and software that was capable of winning the television game Jeopardy over its human opponents.

Now, Watson interacts with physicians researching oncology treatments for cancer, scanning thousands of research studies and conversationally interacting with physicians about the implications and findings. The supercomputer's algorithms can digest thousands of scientific articles much more efficiently than biochemists, producing promising hypotheses for the scientists to study.

The advantage of a machine like Watson in medicine is undeniable. The U.S. Sloan-Kettering Cancer Center estimates that only 20% of the knowledge doctors use to diagnose patients is based on published scientific evidence, while IBM's Watson computer can thoroughly scan medical literature on certain cancers, as well as search up to 1.5 million patient records, in order to present doctors with verbal opinions about the best treatment. For humans, it would take at least 160 hours of reading a week just to keep up with new publications.

This is not so much machines replacing humans, but architecting work to optimize the combination of automation (in the form of the Watson supercomputer) and human physicians.

Fading Boundaries in the Workforce

The same principle applies to improving Watson itself. Making Watson “smarter" requires more than simply feeding it more information or making it more conversational. Some of the biggest advances will come with improving Watson's ability to work with humans—and building that capability requires human insight.

Not only does improving Watson require thinking beyond the computer, it also requires thinking beyond the traditional IBM workforce of regular full-time employees. Some of the best talent for this work lies beyond IBM's organizational boundary. How do you get a cadre of workers—inside and outside of IBM—motivated and qualified to invent new applications for “cognitive"?

Obed Louissaint, the Vice President for HR, IBM Watson, Watson Health, Research, Technical Talent & Corporate Functions described how IBM's answer was to create “IBM Watson Academy," a virtual hub for training on a massive scale, including global challenges and thought-provoking idea exchanges, such as, “What do you think should be the next Grand Challenge in computer science?" The Academy's focus is on cognitive training accessible to employees of IBM itself, but also to employees of IBM's clients, IBM's development partners, and students in schools and universities around the world.

Building an Ecosystem of Talent

For example, upon its launch, Watson Academy piloted an IBM-made MOOC, adapted from a Columbia University graduate-level course taught by an IBM Watson researcher, which included students and faculty from 19 universities in 10 countries. In addition, the Academy launched an online interface that delivers learning in a broad variety of media, ranging from mastery modeling videos through hands-on guided practice.

This creates flexible learning mosaics that appeal to learners and are at the same time easy to maintain and update. The idea is to make IBM's best tools and lessons about cognitive available to the entire ecosystem of workers inside and outside of IBM, to rapidly create a qualified workforce ready and willing to develop the next big thing for Watson.

The Academy has also used contests to get attention and motivate these current and future workers to train themselves on cognitive using tools on the website and then compete to showcase their best solutions. Contests expand the rewards for learning beyond money to include reputation and the thrill of winning against the best in the world.

The future of learning will rely on a mix of algorithms, cloud-based data and human-machine interfaces. Optimizing that brave new world will require that leaders reframe how they think about the work, the workforce and the fundamental relationship between people and automation. As IBM has found, even the smartest machine can benefit from some help from the human mind.

Photo: Creative Commons