PGMAG 35th Edition April 2022

Part 3 of 3 GENERATION PI

Reswizzling of Business Brought to you by Artificial Intelligence and Millennials

MARK D. DEMERS

SR. DIRECTOR, SAS

(Continued from the previous edition)

ARTIFICIAL INTELLIGENCE

Artificial intelligence (AI) stands out as a transformational technology of our digital age.

Beyond traditional industrial automation and advanced robots, new generations of more capable autonomous systems appear in environments ranging from autonomous vehicles on roads to automated check-outs in grocery stores.

Machine learning (ML) and Artificial Intelligence (AI) will represent one of the most significant disruptions to your career.

Despite the hype, AI is real and will not be ignored. Leading businesses are using machine learning to deliver quantifiable business value today. To succeed in a new AI-empowered world, businesses need more than new technology. Companies must focus on retraining the workforce and designing ethical uses of AI.

Over the past few years, we've developed artificially intelligent machines that can do many things that used to require human minds: understanding speech, diagnosing disease, checking the terms of a contract, designing a mechanical part from scratch, even coming up with new scientific hypotheses that are supported by subsequent research. As this new software is embedded in hardware, we'll get self-driving cars, trucks, and combines; delivery and inspection drones; and robots of many kinds.

At the same time, these technologies will transform the nature of work and the workplace itself. Machines will be able to carry out more of the tasks done by humans, complement the work that humans do, and even perform some tasks that go beyond what humans can do. As a result, some occupations will decline, others will grow, and many more will change.

As intelligent machines and software are integrated more deeply into the workplace, workflows and workspaces will continue to evolve to enable humans and machines to work together.

More jobs than those lost or gained will be changed as machines complement human labor in the workplace.

One of the BEST analyses conducted in the past several years on AI… has been done by McKinsey. They collated and analyzed more than 400 use cases across 19 industries and nine business functions. They provided insight into the areas within specific sectors where deep neural networks can potentially create the most value, the incremental lift that these neural networks can generate compared with traditional analytics (below), and the voracious data requirements—in terms of volume, variety, and velocity—that must be met for this potential to be realized.

AI is automating and making its parent – Analytics smarter, better, faster, stronger, and making workers more productive.

McKinsey found that in 69 percent of the use cases studied, deep neural networks can be used to improve performance beyond that provided by other analytic techniques.

Autonomous

I grew up in a very small coal-mining town outside of Pittsburgh, Pennsylvania. It was also considered farm country. I worked some summers on a farm doing various manual labor things. Even though I have been in the technology industry for nearly 40 years, it's still a bit inconceivable to think of a large farm tractor plowing or planting the fields – without a driver behind the seat. But fully autonomous tractors have inspired vivid dreams and have become a reality for thousands of farmers worldwide.

Today, organizations are experiencing change at a pace like never before. If they weren't already on the path to digital transformation before 2020, they were forced into it rapidly due to COVID. Businesses need data and analytics – and they need to put them to work in new and different ways.

Alarmists who think that every new technology will be the end of humanity are wrong.

As life increases in complexity, convenience is the default setting for most people.

As AI and automation benefit businesses and society, we will need to prepare and embrace for significant disruptions to work.

About half of the activities (not jobs) carried out by workers could be automated.

Many organizations start their AI Journey by creating efficiencies in existing business processes. However, the real win for AI comes when companies use AI to perform tasks that were difficult or impossible to do in the past. For example, AI can be trained to recognize signs of specific diseases in Xrays using ComputerVision and Neural Networks or quickly sort through thousands of resumes to find potential job applicants without bias. Moreover, autonomous driving can only happen with AI.

Many of those who are optimistic about the IoT's future argued that a significant driver of IoT adoption would be people's desire for convenience and for goods and services facilitating a low-friction life in an environment of accelerating complexity, information overload, and the apparent shrinkage of time.

All of this does not mean we do not need humans. A great example of this is airplanes which have been self-flying for a long time yet we still see when we get on an airplane a pilot and co-pilot in the cockpit. Honestly, people would get off a plane if on the Public Address system a flight attendant said, "Ladies and Gentlemen, thank you for flying with us today. We are piloted today by Rob Ott an autonomous Robot.”

What if a supply chain saw what it needed to do before you did? Without a doubt, proven out by the recent debacles associated with supply and demand shortages and product containers sitting on ships in ports due to lack of workers to unload them, smarter supply chains are needed. More intelligent logistics are required in order to optimize drivers and trucks to transport them. What if the supply chain could sense, anticipate, even preempt these issues?

A product is suddenly recalled. The intelligent supply chain can alert stores and even pull and replace products on shelves with comparables. A service technician is dispatched to come to your home to repair a broken appliance. A smart service chain knows the called-in issue and diagnoses what repair parts to have on the van before it leaves the service center so that service can be guaranteed fixed right on the first call – one and done.

Autonomic

The mere access to gazillions of petabytes of data enables an organization to make better decisions.

By making better, faster decisions, organizations can differentiate themselves in markets and stand out for their customers, improve lives, and have the potential even to change the world.

But it takes more than just data. Everyone now needs powerful analytics and artificial intelligence to turn data into actionable insight. Only when data is transformed into relevant insights can people harness it to become knowledge and decisions that drive profitable business decisions.

Companies are now faced with thousands of digital decisions every day. Traditional techniques to data discovery and insights won’t be good enough for what the “universe” has in store for us people. We will need more rapid data discovery. Hypothesizing and synthetic data generation will be huge in helping organizations tackle massive rapid onslaughts of new issues, be they fraud, healthcare-related, public safety, sustainability, etc.

Closing – The Coming “Greatest” Generation – Gen PI

Just like the human body has autonomic abilities that "act or occur involuntarily," we need AI to be embedded into and create whole new processes or workflows that then not only operate autonomously they also become self-learning and auto-correcting.

Gen PI powered by AI Doesn’t Get Bored or Tired. It is always on.

Talk about “work from home” Gen PI works from anywhere all the time. It’s always learning – in fact, it demands more data.

Lack of rest, personal stress, boredom from repetitive tasks, and even "hangovers" are particularly human problems (compared with machines).

For instance, staying up all night impacts your work performance the next day. On the other hand, computers never need to sleep. No matter what, their operational ability is the same (unless the power is out and then with Grids and failover, redundancy, they can still work like nothing ever happened).

Similarly, repeating the same motion and doing the same thing every day gets dull for a human. That’s what machines were made for.

Computers are Less Error-prone Than Humans

As humans, it's in our nature to make mistakes. Computers, on the other hand, are not susceptible to human error. They receive instructions and execute them exactly as spelled out in the code.

AI will take over jobs that require copying, pasting, transcribing, and typing. At the very least, a new AI co-worker might be there checking your work.

AI-enabled Machines Can Perform Dangerous Tasks

Jobs like mining, factory work, and machine assembly all expose workers to a certain amount of danger. Whether it's dangerous fumes, falling objects, or extreme temperatures at work, there will always be circumstances and situations where people can be seriously injured or killed.

AI can be used in manufacturing not only to make processes more efficient, but to also keep human workers out of harm's way. Opportunities to leverage AI and machine learning in manufacturing include product development, logistics optimization, predictive maintenance, and, of course, robotics.

While machines can also be damaged or destroyed doing dangerous work, they are not nearly as fragile and are built to withstand enormous amounts of pressure, heat, airborne toxins, and other threats.

AI Machines are Cheaper in the Long Run

While the upfront cost of building and training an AI machine is high, the overall cost of operation is much lower than paying a human to do the same job, according to the APA.

Running a machine just takes electricity and occasional maintenance. To hire a human for a job, it takes resources to find and train them, not to mention the yearly salary and benefits that must be paid out.

United States President Lyndon Johnson was prescient in this regard, writing a half a century ago: Automation is not our enemy. Our enemies are ignorance, indifference, and inertia. Automation can be the ally of our prosperity if we will just look ahead, if we will understand what is to come, and if we will set our course wisely after proper planning.

Peter Drucker once said that trying to predict the future is “like trying to drive down a country road at night with no lights while looking out the back window.” It’s also worth noting that it was also Drucker who said “The best way to predict the future is to create it.”

Firms that embrace the fact that generations are leaving their workforces and that Artificial Intelligence, Machine Learning, and Internet of Things (IoT) can help them “rearrange or reorganize or restructure something in a useful, relevant way” – Reswizzle - will come out of a potentially bad situation in a place where competitors are left behind and profits grow.

My Hope and Promise

In this column, you can find the simple truth that ultimately, we are in control of our lives by virtue of the choices we make and how we respond to events, even though at times it seems we have little or no control over what is happening to us. It's easy to lose sight of that truth when we are embroiled in events happening all around us, like losing a loved one or friend, health issues, career challenges, and financial setbacks. It's hard to see the path we need to follow amidst all the obscurities. My aim is to give insights and hope through stories that just maybe can not only give you a more objective view of circumstances but also help guide us to the path on which we need to be.

ABOUT MARK D. DEMERS

Mark Demers leads an expert global team of industry practice directors, industry marketing, principal industry consultants and thought leaders that drive vision and product direction, messaging and support sales for Industry-centered SAS products and solutions. Mark and his team work closely with SAS’ customers, sales, Partners, R&D, and technical staff around the world, to position, market and sell SAS solutions for Government, Banking, Insurance, Manufacturing, Healthcare, Life Sciences, Energy, and Education and Communications sectors using analytics.

SAS is the world leader in analytics. It’s internationally recognized for providing an innovative, supportive workplace that blends different backgrounds, experiences, perspectives and cultures from almost 60 countries around the world where all ideas are encouraged, and everyone is respected for their unique contributions and abilities. SAS’ employees empower, encourage and inspire women to pursue excellence in STEM and their careers and fulfillment in their personal lives. Employees are encouraged to expand professional networks, showcase thought leaders and attract women to careers in science and technology.

Demers’ decades of management experience include executive positions at several public and private companies prior to SAS. Mark serves as Board member for an emerging innovative Company – Visual Farms, audaciously inspired to help strike out world hunger. He holds a Bachelor of Science degree in Mechanical Engineering from Penn State University.

Linkedin: https://www.linkedin. com/in/markddemers