Artificial intelligence has been in the news a lot lately, specifically related to machines’ ability to deep learn, or more closely mimic the actions of a human brain. In the near future, will a computer’s algorithms be able to do the project manager’s job as well as you can?
It started in 2011. Stanford professor Andrew Ng holed up at the Google X Lab at the company’s Silicon Valley headquarters and initiated a project dubbed “Google Brain.”
Google Brain encompassed a connected network of 16,000 computers programmed to mimic aspects of human brain activity by looking for recurring patterns on the Internet. In a period of three days, the Brain had successfully trained itself to recognize a cat based on 10 million digital images taken from YouTube videos.
Google Brain was an example of an artificial neural network, designed after the densely interconnected neurons of the human brain. Possessing about a million simulated neurons and a billion simulated connections, Google Brain was ten times larger than any deep neural network before it, and in the last few years, Ng has made networks that are ten times larger than the original Brain.
The Google Brain and its subsequent neural networks represent what many consider to be the new frontier of artificial intelligence – deep learning. Deep learning trains computers to recognize patterns in data and then classify and categorize them as a human brain could do instantaneously. At present, deep learning in the form of image and speech recognition is used in applications such as Facebook’s tagging feature and the iPhone’s Siri. AI experts are already working on computational linguistics applications that will allow machines to easily decipher the variety of human languages – both spoken and written.
Machines may elbow their way in…
The maturation of deep learning along with machines’ ability to perform more complex algorithms will be a powerful combination. Within the next five years, we could see computers undertaking the following project management functions:
- Defining the scope of a project
- Aligning with other business areas
- Analyzing risks
- Developing project schedules, timelines, and budgets
- Assigning tasks to the appropriate resources
- Implementing software and other technical components
- Documenting project progress
- Assessing project outcomes
…But they won’t be able to push you out
As we’ve talked about here before, the more straightforward the task, the faster it will be turned over to smart machines. Nevertheless, there will still be aspects of project management that machine learning won’t master any time soon. Back in 2013, economist Tyler Cowen published a book called Average is Over. In it, he suggests that knowing a lot about your job won’t be enough to stay competitive against the rise of the machine. Instead, you’ll have to understand your role and industry in a way that’s more creative and intuitive. This concept absolutely applies to project managers, who are certain to retain their titles well into the coming decades.
In his conversation with Harvard Business Review’s Walter Frick, Cowen argues that Mark Zuckerberg’s work with Facebook is a classic example of a human leapfrogging any potential machine capability. Zuck’s clearly a great programmer, but had he just gone out to be paid as a programmer, he wouldn’t have been rich and famous. But, as a psychology major, Zuck understood how to appeal to users and get them coming back to the site. It was the integration of programming with human interpersonal knowledge that made Zuck what he is today.
Strong interpersonal skills are even more essential to project managers than they are to Silicon Valley gurus. Project managers have to regularly employ diplomatic and persuasion skills that machines are a long way from learning. They need to set team expectations and motivate each team member to do his or her best. These responsibilities require a human touch.
Cowen’s point about the changing emotional role of teachers also applies to project managers. “Teachers will be more like coaches or tutors than carriers of information. They’ll steer you to the program, tell you which classes to take, and be a kind of role model to get you excited about doing the work,” he says.
New skills required when machines are your colleagues
Project managers of the near future should be prepared to narrow the scope of their role and work side-by-side with computers and algorithms. Since machines will take over many of the core PM functions mentioned above, project managers will become translators. “Software is bad at common sense in a lot of ways and it misses a lot of context. It’s people who can provide that context,” says Cowen.
Along these lines, you will need to learn how to ask machines the right questions to get the right information, and how to assess what machines can and can’t do. “It’s a kind of meta rationality. Knowing not to overrule the programs very much, but also knowing they’re not perfect, and knowing when to probe,” says Cowen. “People who can judge that there’s more to the matter than the software can grab; people who can judge the fact that there’s a need for a different kind of software for the problem – these will be the type of human managers that are needed.”
Until robots replace us, let’s first determine how today’s software like Excel can be hindering our success as project managers.Posted in Project Management, Team & Project Management | Tagged algorithms, applications, artificial intelligence, career, change management, computational linguistics, deep learning, emotional intelligence, Google Brain, influence, personal development, productivity, project management, skill acquisition, team collaboration, troubleshooting, Working Teams