From Hype to Happening: Exploring the Realities of Machine Learning & AI

Measuring Current with the Analog Discovery 2
June 6, 2018
Accelerate Video Analytics Development with DeepStream 2.0
June 20, 2018

From Hype to Happening: Exploring the Realities of Machine Learning & AI

Despite the hype surrounding machine learning and artificial intelligence, many companies still see these technologies as tools of the future. And, while some are too busy worrying about how AI might rob them of their jobs, the brands looking to stay relevant and fresh have adopted these tools to gain a competitive edge. Leaders recognize that, to survive in this ever-evolving world, their business needs to be where the consumers are every step of the way, and that means integrating technologies that empower and engage employees and customers alike, all while providing the best experience possible.

For those companies that have remained hesitant, change can seem rather daunting. ML and AI represent a new era in business, after all, despite their looming presence in recent years. But, considering how far personal technologies have come within the last decade alone, leaders no longer need to fear the unknown, for these tools are already widespread.

Everyday consumers are accustomed to the conveniences of Netflix and Waze, which learn user preferences as they interact with the applications, and with some concentrated investments, brands can enjoy the same predictive benefits at work as they do in play.

Myths: Busted
With machine learning and artificial intelligence comes the rumors of automation. Because these advanced tools can potentially act as substitutes for human labor, those who aren’t familiar with the intricacies of said technologies often cower in fear, ignoring them at all costs to preserve the business and its employees. Many people are already worried that technology will threaten their livelihood or eliminate their jobs all together. Yet, while the “robots” will likely assume some roles, as people have feared, ML and AI will ultimately create new jobs that are uniquely human, which no computer could ever replicate.

In an article published by the Massachusetts Institute of Technology Sloan Management Review, researchers assessed the current environment within companies that have already implemented AI and machine learning systems. According to the research, three new categories of AI-driven business and technology jobs have emerged: trainers, explainers, and sustainers. Each role complements the tasks performed by cognitive technology in an effort to ensure that the machines remain effective and responsible.

Trainers essentially teach the technology how to mimic human behaviors. While some algorithms teach the AI to detect the complexities of human communication, other trainers must educate systems on how to show compassion. Explainers, on the other hand, bridge the gap between technologists and business leaders by providing clarity. When the AI technology recommends actions that go against the norm or when said “smart” tools make mistakes, these explainers must hold the given algorithm accountable
and rationalize the result for those who might not understand the technical jargon. Sustainers, subsequently, help guarantee that AI systems are operating properly and that any issues are addressed with adequate urgency. Thus, an ethics compliance manager will be integral for companies that still have yet to establish full confidence in the tools they’ve elected.

While these might not be the jobs businesses are used to, these roles open employees to new opportunities for growth. By adapting their current skills for this evolving environment, those who have practically paved the path for these tools will be responsible
for keeping AI in line—which means they can rest easy at night. Computers won’t replace them during our lifetime, but they will need to embrace flexibility in order to remain fresh and relevant in today’s fast-paced world.

Beyond the fears of what machine learning and artificial intelligence could do to the workforce, many leaders have hesitated to integrate these technologies because they regard them as tools of the future. They’re still stuck in the “hype” phase despite the fact that ML and AI represent the here and now—they’re happening. In fact, International Data Corporation (IDC) forecasts that spending on all artificial intelligence and machine learning systems will grow from the estimated $12 billion spent in 2017 to $57.6 billion by 2021.

Regardless of the myths and mysteries that come along with artificial intelligence and machine learning technologies, these tools aren’t as scary as they might seem. Much like Big Data and the Internet of Things, ML and AI have become impossible to ignore, for they are integral to the future of business. Leaders try to rationalize their hesitation by claiming that ML and AI are too new, but considering the concept has been around for nearly 60 years, it’s clear that these tools have had the time to mature. However, those who remain reluctant need not invest in an entirely new infrastructure up front. “Instead, they should focus on tackling the low-hanging fruits that can be improved upon by implementing smaller platforms that carry out basic ML and AI tasks,” says Prem Pusuloori, CTO at ISM, Inc.



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