Robotic Process Automation

Smart Machines: The New ‘Human’ Capital?

As algorithms and robots get smarter, workforce planning systems need to strike the optimum balance between people and machines.
John BoudreauDecember 1, 2014
Smart Machines: The New ‘Human’ Capital?

Stephen Hawking and colleagues warn that “success in creating artificial intelligence would be the biggest event in human history.… Unfortunately it might also be the last.”

John Boudreau

John Boudreau

From self-driving cars, to intelligent assistants on smart phones, to IBM’s Watson beating humans at Jeopardy, to potentially autonomous military weapons, the effects of increasingly sophisticated automation are undeniable. With leading companies like Google spending millions to acquire artificial intelligence (AI) and robotics startups, financial markets are also betting that AI will become a bigger part of our lives and society.

When it comes to your strategy for people and human capital, the age of smart machines is often framed in traditional terms of job losses and gains. Oxford researchers predict that 45% of American occupations will be automated within the next 20 years. The first stage will be using computational power to replace jobs that rely on such things as pattern recognition, data gathering and distillation, and computational algorithms. Jobs like transportation/logistics, production labor and administrative support will go after that.

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However, if you think your job is safe, the researchers also predict that artificial intelligence will eventually put jobs in management, science, engineering and the arts at risk.

Can sophisticated jobs in finance and investing be automated? Consider computer traders, once epitomized by hundreds of humans shouting on a trading floor. An Economist article titled “Dutch Fleet” notes that with the advent of trading algorithms in ultra-fast computer systems, some Amsterdam-based trading firms that formerly relied on traders and saw large bid-ask spreads now occupy a “high-volume, low-margin industry in which market-makers take a sliver of revenue from lots of transactions.” One firm saw a peak of 3,000 trades in 60 seconds. Trading is now the province of algorithms, software and decisions made in milliseconds by automated systems.

The analogy between commodities trading and human capital recruiting is obvious. It seems likely that planning and managing your people will be done more and more by algorithms, not humans. Algorithms can increasingly predict things like employee turnover and future job performance better than typical supervisors or hiring managers. An analysis of 17 studies on applicant evaluations concluded that equations outperform human applicant-selection decisions by 25%. A recent HR-technology conference provided stunning examples of the power of automation to improve and replace human processes in managing people, and admonished HR and organization leaders to prepare for a future driven by predictive analytics.

For CFOs and CHROs, it is tempting to focus on the job displacement and economic cost savings that future technology will produce. Yes, it will mean massive shifts in the balance between the humans and machines doing the work, with a resulting impact on productivity and costs.

Yet, beneath the surface of this issue is something more nuanced. Your concept of work and human capital may need to change, not simply to think about machines versus humans, but about a more nuanced future as humans and machines collaborate.

For example, algorithms can digest thousands of scientific articles much more efficiently than biochemists, producing promising hypotheses for scientists to study. The U.S. Sloan-Kettering Cancer Center estimates that only 20% of the knowledge that human doctors use to diagnose patients is based on published scientific evidence, because it would take at least 160 hours of reading a week just to keep up with new publications. IBM’s Watson computer has been trained to read the medical literature on certain cancers, search up to 1.5 million patient records, interact with doctors in real time with natural language, and present verbal opinions about the best treatment.

I have written that “deconstructing” work will revolutionize talent management by revealing new opportunities to get work done, ones that today are obscured by typical job descriptions or organization charts. The job of “software engineer” includes software coding, project management and team leadership. Rather than hire software engineers to complete a computer coding job, why not deconstruct the job, take out the coding, and employ TopCoder or other talent platforms to post your coding tasks to thousands of freelance coders worldwide? Rather than maintain your own R&D function internally, why not form an alliance with other firms to pool your R&D, as Eli Lilly and Immunocore did?

Scientists working side by side with conversational algorithms show the power of combining the idea of deconstructing work with the idea of the smart machine. The trick is to get the balance right. Today’s human capital planning systems are still largely built on a platform of job descriptions and organization charts, which can lead to a traditional mindset of deciding whether to replace humans with machines. Learning to creatively deconstruct the work and your organization chart can reveal ways to optimize your talent and your work that strike a more creative balance of humans with machines — essentially, an alliance with the machines.

The authors of “The Second Machine Age,” Erik Brynjolfsson and Andrew McAfee, point out that machines are unlikely to take over all jobs. “I don’t think this means that everything those leaders do right now becomes irrelevant,” McAfee told McKinsey Quarterly. “I’ve still never seen a piece of technology that could negotiate effectively or motivate and lead a team.” He suggested that an increasingly important skill for senior managers will be to figure out, “Where do I actually add value and where should I get out of the way and go where the data take me?”

Leaders not only should ask that question about their own jobs, they should partner with their HR leaders to answer it with respect to the full spectrum of current and future work. Deconstruct, automate and reconstruct.

Might the future bring a conversational computer with a seat at the strategic workforce planning table? Let’s just not name it after Toby on the television show “The Office.”

John Boudreau is professor and research director at the University of Southern California’s Marshall School of Business and Center for Effective Organizations, and author of Retooling HR: Using Proven Business Tools to Make Better Decisions About Talent.