It is easy to get caught up in the hype of machine learning, artificial intelligence (AI), as the promise of this relatively new technology has been credited with saving everything from our health
to our work life
and even our planet
. Realistically speaking, however, in many ways, we are still a long way off from achieving these promises.
A more immediate and perhaps even more profound impact of AI can be found within the enterprise, via the aggregation of big data and the application of machine learning. Machine learning, a subset of the broader AI field, is the area of AI most likely to provide direct and tangible benefits to an organization for the foreseeable future.
Most executives today can articulate the high-level benefits of AI and machine learning, as they are becoming key components of business strategies and service offerings. Possessing this definitional understanding, however, will only get you so far.
The harder question to answer -- one that will prove to have the greatest impact on business and leadership success -- is whether you understand the deeper promise and limitations of AI in your particular field. More importantly, are you able to separate the promise from the reality? To do so may well require a more practical working knowledge of how to use (and perhaps even code!) machine learning technologies.
Move Over, Programming -- There's A New Language In Town
For years, we've taught up-and-coming leaders that programming is the new literacy. While programming has become the lingua franca of digital disruption, we are rapidly moving beyond the time where simple functional programming is sufficient to enable the next generation of business capabilities. Rather, machine learning is our new literacy that will define and shape businesses and industries at large, perhaps in even more profound ways than the internet did.
If you want to lead an organization into this new era of disruptive digital revolution, it's critical that you become literate in the language that will matter most, and for this reason, a functional working knowledge of machine learning should be considered a must-have skill for those who truly want to shine in the C-suite.
Not only is the study of machine learning surprisingly fun and intellectually stimulating, but it proves invaluable to achieving a deeper understanding of the possibilities and limitations of the field -- both in general and for your specific business.
It's Never Too Late To Learn, Especially With So Much Opportunity
Since the beginning of the technological revolution, businesses have been able to grow and thrive while keeping management and leadership functions quite separate from IT departments. A basic knowledge among executive leaders was more than sufficient for helping to oversee technical innovation and growth within the organization.
In yet another way digital transformation has disrupted business, we now recognize leadership must be deeply connected to technology and innovation in order to progress and succeed in the market. It is no longer possible for the C-suite to remain siloed from the nuts and bolts of new technologies. For this reason, leaders should place significant value on cultivating a hands-on knowledge of machine learning tools.
The advent of cheap computing resources, vast amounts of (in some cases) publicly available data and, most importantly, the availability of extremely powerful, free and open-source machine learning tools and powerful libraries that abstract away the complex underlying math, make it feasible for almost anyone to get their hands dirty when it comes to machine learning with just a little technical orientation, discipline and time.
As the CEO of a technology company, I've personally delved into the world of machine learning over the last year, starting with simpler machine learning implementations and more recently dipping my toes into the fascinating world of deep learning and neural networks. While I'm certainly not writing code that will find its way into production, this ‚??hobby‚?? work has had three important benefits:
1. It enables me to converse at a much deeper level with our developers, data scientists and cyber researchers who are building our machine learning models and tools, making my management and investment decisions better informed.
2. It gives me the ability to better assess the reality behind competitor and partner claims about their technologies and capabilities. Knowing the right questions to ask, based on experience, is a powerful tool to separate hype from reality.
3. I've used my machine learning skills to participate in our company's bi-annual hackathon. This sends a powerful signal to the organization: If the CEO can code a complex convolutional neural network to detect malware anomalies, then we should all be lifting our sights toward the art of the possible.
Cassie Kozyrkov, the chief decision intelligence engineer at Google, recently discussed
the impact data scientists with strong leadership skills will have on the organizations they serve. She rightly points out that we need to ‚??train a new breed of thinker: the decision-maker who has the skills to make data science teams successful.‚??
I would add that executives today can also cultivate machine learning skills to add to their own leadership capabilities, developing a filter through which to separate the wheat from the chaff and provide invaluable direction for their organizations and position them to lead under a new wave of digital disruption.
Since modern machine learning is really only a few years old, now is the ideal time to bridge the technical gap and teach yourself the language of machine learning. It will help you better position your company as an innovative thought leader and stay a step ahead of 99% of your competitors. What's more, I'm confident you will enjoy the process and benefit from your newfound knowledge for many years to come.
The article was originally published here