3D Printing: Industry Impact Considerations For 2017

Michelle Schooff

To say that 3D printing is changing our world is an understatement. Today you can purchase 3D-printed shoes, 3D-printed jewelry, 3D-printed pens, and even 3D-printed vehicles.

The automotive industry is using 3D printing to produce spare parts and develop prototypes for new car models. GE and Ford have already touted their early success in 3D printing. One can only imagine the testing that is going on behind their closed doors.

Airplane manufacturers are using 3D printing for parts. In the healthcare and life sciences industries, 3D printing is being used for medication, hearing aids, implants, prostheses, and even human skin for burn victims. Invisalign has built a multi-million dollar business producing teeth alignment devices using 3D printing to completely customize every single device for each patient.

Wholesale distributors are providing value-added services like printing non-stock parts in-house or giving their customers a 3D printer and selling them the specs so they can print parts in-house on demand.

And that is just the beginning. The global market for 3D printing is projected to have significant impact across many industries with economic implications of up to $550 billion a year by 2025.

In the industrial market, 3D printing is primed for long-term growth that will impact products and supply chains. Leaders across all industries should be looking at 3D printing as an emerging technology and a possible disruption to their current business models.

While some think that 3D printing is only a niche technology, companies are aggressively looking to leverage the technology for cost savings, for example, shifting physical inventory to virtual inventory, which allows them to generate parts on-demand when and where they need them.

Also, 3D printing is putting consumers in charge of the supply chain – and most companies are not ready. The technology is a true game changer for the manufacturing industry. It should be a warning sign for companies that, if they don’t innovate their supply chains, they may become irrelevant as consumers gain more control of the production of their own products.

Today, consumers are making their purchase decisions based on how quickly they will receive the product. In order to stay competitive in the marketplace, companies are turning to 3D printing to create and deliver their products quicker, and 3D printing is innovating with that model and putting consumers in the driver’s seat.

The pace of adoption continues to accelerate.  As costs continue to drop and quality rises, it will be impossible not to incorporate a 3D printing strategy into existing business models.

Think about how your organization can leverage 3D printing to reduce manufacturing lead times, bring new designs to market quickly, meet your customer’s demands, and reduce inventory-carrying costs. What was once a technology of your imagination has been made possible with 3D technology. Is your organization ready?

Learn more about How Ford, Airbus, and GE Use 3D Printing for Competitive Advantage.

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Michelle Schooff

About Michelle Schooff

Michelle Schooff is a global marketing director in the retail and wholesale distribution industries for SAP. She is responsible for the marketing strategy, messaging and positioning for SAP solutions in the global marketplace. With over 20 years experience in technology and marketing, Michelle builds strategic marketing plans that drive growth, innovation and revenue.

Beyond Spare Parts: 3D Printing And Machine Learning

Stefan Krauss

The concept of 3D printing isn’t a new one. In fact, it’s been around for more than 30 years – long before it became popular in consumer settings. In industries like automotive and aerospace, we call it additive manufacturing – the process of creating something new by layering materials, like plastic, metal, or concrete, using computer-modeled designs.

This approach is extremely versatile, allowing manufacturing teams to visualize large design projects through miniature scale models, design and create small runs of custom parts and equipment for customers, and prototype new products. As 3D printing speeds increase, Gartner predicts the 3D printing industry will be a $4.6 billion market by 2019.

Until now, the primary application for 3D printing in discrete industries has been prototyping new parts and equipment. But there’s significant room for expansion, especially in the efficient fabrication of spare parts.

Most discrete manufacturers are already producing spare parts, but few have adopted tactical 3D printing as an update to their process. The lead time currently required to create many spare parts can be both long and expensive, so the only way to ensure these parts are available to the customer in a timely fashion is to create and store them in advance. This process is inefficient and cost-prohibitive for the manufacturer – resulting in higher costs and longer wait times for customers. 3D printing provides a turnkey solution to this problem, and gives manufacturers the opportunity to supply their customers with high-quality parts, on-demand, when they are needed most.

Even more exciting, with innovations in other emerging technologies concurrently maturing, 3D printing is just the start of what manufacturers can do to enhance their production process for spare parts. While 3D printing certainly expedites creation, storage and delivery, it’s still a reactionary operation at its core. Instead of relying on customers to tell them when to print these parts, discrete manufacturers must transform their operations to think proactively – leveraging machine learning (ML) to solve maintenance issues before they occur.

As 3D printing capabilities grow, maintenance teams face a variety of challenges, including the number of parts that can be printed and increasing demand from customers for faster delivery. Regardless of these challenges, their goals remain the same: to ensure that parts are available and shipped to a customer in a timely fashion. As such, it’s critical that manufacturers evolve to meet this demand by incorporating machine learning into their process.

Machine learning technology identifies, analyzes, and monitors nearly infinite amounts of data, allowing it to provide a real-time status of processes and machinery. When implemented in a discrete manufacturing setting, teams can use ML to analyze the life remaining on a specific part or piece of equipment, and flag system failures before they happen. Similarly, when synchronized with a predetermined replacement schedule, ML can help proactively identify when it’s time for a customer to replace their parts – thereby avoiding unplanned downtime for machinery that would otherwise need to be taken out of service.

Manufacturers could combine this predictive maintenance with their ability to 3D print spare parts efficiently to become full-service vendors for their customers. Those who do so will not only serve as true leaders in spare parts manufacturing, but also in customer service.

With technology disrupting nearly every type of enterprise business model, customers are demanding more, and have higher expectations than ever before. They expect materials on time and on-hand when they need them, and they expect their suppliers to adjust accordingly. Discrete manufacturers producing spare parts must meet this demand by incorporating 3D printing, in conjunction with ML, to help quickly deliver high-quality spare parts to customers ahead of demand.

Manufacturers who can take advantage of ML to predict when equipment and parts will fail, then subsequently employ 3D printing to proactively print and ship replacement parts ahead of these failures, will enjoy significantly reduced spare parts costs and delivery times, and higher customer satisfaction.

For more on implementing advanced technology to your business processes, see Managing Digital Disruption Requires The Right Strategy And Mindset.

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Stefan Krauss

About Stefan Krauss

Stefan Krauss is the general manager for Discrete Industries at SAP. Together with his team, he is responsible for the integrated management of the industries Aerospace & Defense, Automotive, High Tech and Industrial Machinery & Components – spanning development, solution management, sales and marketing, value engineering, partner management, services and support. The mission of this unit is to deliver industry cloud solutions that help SAP customers sustainably innovate and grow their business, operate safely, and develop their people.

Three Digital Innovations That Will Beat 'Rock, Paper, Scissors'

Frank Klipphahn

Rock breaks scissors. Paper covers rock. Scissors cut paper. Those are the rules of Rock-Paper-Scissors, the ancient game people play with their hands. But wouldn’t it be better if those tools could join forces for the common good?

The question also applies to three digital innovations: blockchain, digital solutions based on the Internet of Things (IoT), and machine learning (ML). These are technological tools that support each other in the process of digital transformation (DX).

The IoT connects the users and things across the world. Blockchain helps secure sharing of sensitive information via the IoT. And ML speeds cybersecurity checks to make IoT connectivity safer.

Corporate officers of companies investing in DX may view blockchain, IoT solutions, and ML as competitors for IT budget. Yes, they are distinct digital tools. But together they form a powerful team supporting the aerospace industry and its many clients.

Defense and aerospace contractor Lockheed Martin is at the forefront of companies combining the capabilities of these tools.

Launching into the connected digi-verse

The Internet of Things (IoT) is a vast network of digital objects with embedded intelligence connected to the Internet via sensors. Connected factories, smart equipment, and users connected via mobile devices have been successfully leveraging IoT for years to optimize A&D operations and products.

Other IoT devices range from global positioning systems (GPS) in vehicles to digital twin computer models of aircraft. A digital twin is a software model of a physical thing/asset that relies on sensor data to understand the full state of the thing, enables digital simulations and learning to improve operations, and adds value by aiding predictive maintenance. Engineers can use these IoT-enabled 3D models to visualize where repairs are necessary based on data the sensors produce.

Lockheed Martin has relied on 3D modeling for many years. Until recently, the company referred to its immersion in DX as creating a digital tapestry of seamless connections between the “conceptualization, design, verification, manufacturing and sustainment” of its ideas.

The company made a major announcement at the 2017 ML Summit in early June. A report in the Manufacturing Leadership Council blog indicated that Lockheed Martin intends to expand into the use of digital twins to improve simulations of all its products and processes. The company also announced that the tapestry analogy no longer fits its ecosphere of innovations, which it now calls the Lockheed Martin Digi-Verse.

You might say that Lockheed Martin actually shot off into the digi-verse two months earlier with the launch of its iSpace (intelligent space) software to protect space assets. The company announced that the software “tasks, processes, and correlates data from a worldwide network of government, commercial, and scientific community sensors and command centers.” It added that the system automatically sends users real-time information gathered from “optical, radar, infrared, and radio sensors” and recommends “the best course of action.”

Seeking blockchain protection of data

CNET reported in early May that the company is adopting blockchain as a strategy for speeding the discovery and solution of cybersecurity problems. CNET added that the company is using blockchain to protect its data and “secure software development and supply chain risk management.”

Blockchain is a digital tool for creating decentralized ledgers that are secure. Many industries are exploring potential uses of this tool, which developed as a way to exchange the universal digital currency bitcoin.

It works this way: Participants in a blockchain network add individual transactions (blocks) to a shared ledger. In addition to people, the participants may include machines (ML again!) that can make quick decisions for an organization based on rapid data analysis.

Blockchain technology allows participants to read but not change blocks created by others. This characteristic protects information in a shared ledger.

Blockchain networking saves time and money for individual participants and organizations. It also makes the ledger process transparent for all involved. In aAerospace, it helps to build trust and integrity, and allows cyber-secure provenance and traceability of parts and other assets across shared business processes.

Bitcoin news service News BTC reports that machine learning can team with blockchain technology to ensure the accuracy of data and limit false positive results when testing for cyber threats.

Turning Big Data into action with machine learning

Machine learning is a form of artificial intelligence. ML applications turn computers into machines that can learn from other objects such as Digital Twins without being explicitly programmed.

These programs access the flood of information created by IoT objects, which is called big data. They sort, analyze, and learn from it automatically. Big Data is so massive that it takes rapid computing power to process it in real time. People cannot do it.

Lockheed Martin says that ML “turns data into action.” In a post about warfare innovation at its blog, the company notes, “Today, the military gathers data through sensors on a range of platforms, including aircraft, weapon systems, ground vehicles and even troops in the field.”

Lockheed Martin defense products use ML to aid military intelligence gathering and identification of threats. The company reports that the goal is to increase automation in decision-making.

Speed in decision-making decreases damage to targets, whether they are troops and cities in warzones or databases concerning company inventions and operations. Lockheed Martin uses the IoT, blockchain, and ML to protect people as well as products. Together, these digital tools are a powerful force.

It quickly becomes clear that topics like the Internet of Things, machine learning, blockchain, analytics, artificial intelligence, and Big Data often need to be viewed in combination: This is the key to creating a framework for harnessing the latest digital breakthroughs.

Learn how to bring new technologies and services together to power digital transformation by downloading The IoT Imperative for Discrete Manufacturers: Automotive, Aerospace and Defense, High Tech, and Industrial Machinery.

Explore how to bring Industry 4.0 insights into your business today by reading Industry 4.0: What’s Next?

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Frank Klipphahn

About Frank Klipphahn

Frank Klipphahn is the Senior Solution Manager for the Aerospace and Defense Industry Unit at SAP.

Why Strategic Plans Need Multiple Futures

By Dan Wellers, Kai Goerlich, and Stephanie Overby , Kai Goerlich and Stephanie Overby

When members of Lowe’s Innovation Labs first began talking with the home improvement retailer’s senior executives about how disruptive technologies would affect the future, the presentations were well received but nothing stuck.

“We’d give a really great presentation and everyone would say, ‘Great job,’ but nothing would really happen,” says Amanda Manna, head of narratives and partnerships for the lab.

The team realized that it needed to ditch the PowerPoints and try something radical. The team’s leader, Kyle Nel, is a behavioral scientist by training. He knows people are wired to receive new information best through stories. Sharing far-future concepts through narrative, he surmised, could unlock hidden potential to drive meaningful change.

So Nel hired science fiction writers to pen the future in comic book format, with characters and a narrative arc revealed pane by pane.

The first storyline, written several years before Oculus Rift became a household name, told the tale of a couple envisioning their kitchen renovation using virtual reality headsets. The comic might have been fun and fanciful, but its intent was deadly serious. It was a vision of a future in which Lowe’s might solve one of its long-standing struggles: the approximately US$70 billion left on the table when people are unable to start a home improvement project because they can’t envision what it will look like.

When the lab presented leaders with the first comic, “it was like a light bulb went on,” says Manna. “Not only did they immediately understand the value of the concept, they were convinced that if we didn’t build it, someone else would.”

Today, Lowe’s customers in select stores can use the HoloRoom How To virtual reality tool to learn basic DIY skills in an interactive and immersive environment.

Other comics followed and were greeted with similar enthusiasm—and investment, where possible. One tells the story of robots that help customers navigate stores. That comic spawned the LoweBot, which roamed the aisles of several Lowe’s stores during a pilot program in California and is being evaluated to determine next steps.

And the comic about tools that can be 3D-printed in space? Last year, Lowe’s partnered with Made in Space, which specializes in making 3D printers that can operate in zero gravity, to install the first commercial 3D printer in the International Space Station, where it was used to make tools and parts for astronauts.

The comics are the result of sending writers out on an open-ended assignment, armed with trends, market research, and other input, to envision what home improvement planning might look like in the future or what the experience of shopping will be in 10 years. The writers come back with several potential story ideas in a given area and work collaboratively with lab team members to refine it over time.

The process of working with writers and business partners to develop the comics helps the future strategy team at Lowe’s, working under chief development officer Richard D. Maltsbarger, to inhabit that future. They can imagine how it might play out, what obstacles might surface, and what steps the company would need to take to bring that future to life.

Once the final vision hits the page, the lab team can clearly envision how to work backward to enable the innovation. Importantly, the narrative is shared not only within the company but also out in the world. It serves as a kind of “bat signal” to potential technology partners with capabilities that might be required to make it happen, says Manna. “It’s all part of our strategy for staking a claim in the future.”

Planning must become completely oriented toward—and sourced from—the future.

Companies like Lowe’s are realizing that standard ways of planning for the future won’t get them where they need to go. The problem with traditional strategic planning is that the approach, which dates back to the 1950s and has remained largely unchanged since then, is based on the company’s existing mission, resources, core competencies, and competitors.

Yet the future rarely looks like the past. What’s more, digital technology is now driving change at exponential rates. Companies must be able to analyze and assess the potential impacts of the many variables at play, determine the possible futures they want to pursue, and develop the agility to pivot as conditions change along the way.

This is why planning must become completely oriented toward—and sourced from—the future, rather than from the past or the present. “Every winning strategy is based on a compelling insight, but most strategic planning originates in today’s marketplace, which means the resulting plans are constrained to incremental innovation,” says Bob Johansen, distinguished fellow at the Institute for the Future. “Most corporate strategists and CEOs are just inching their way to the future.” (Read more from Bob Johansen in the Thinkers story, “Fear Factor.”)

Inching forward won’t cut it anymore. Half of the S&P 500 organizations will be replaced over the next decade, according to research company Innosight. The reason? They can’t see the portfolio of possible futures, they can’t act on them, or both. Indeed, when SAP conducts future planning workshops with clients, we find that they usually struggle to look beyond current models and assumptions and lack clear ideas about how to work toward radically different futures.

Companies that want to increase their chances of long-term survival are incorporating three steps: envisioning, planning for, and executing on possible futures. And doing so all while the actual future is unfolding in expected and unexpected ways.

Those that pull it off are rewarded. A 2017 benchmarking report from the Strategic Foresight Research Network (SFRN) revealed that vigilant companies (those with the most mature processes for identifying, interpreting, and responding to factors that induce change) achieved 200% greater market capitalization growth and 33% higher profitability than the average, while the least mature companies experienced negative market-cap growth and had 44% lower profitability.

Looking Outside the Margins

“Most organizations lack sufficient capacity to detect, interpret, and act on the critically important but weak and ambiguous signals of fresh threats or new opportunities that emerge on the periphery of their usual business environment,” write George S. Day and Paul J. H. Schoemaker in their book Peripheral Vision.

But that’s exactly where effective future planning begins: examining what is happening outside the margins of day-to-day business as usual in order to peer into the future.

Business leaders who take this approach understand that despite the uncertainties of the future there are drivers of change that can be identified and studied and actions that can be taken to better prepare for—and influence—how events unfold.

That starts with developing foresight, typically a decade out. Ten years, most future planners agree, is the sweet spot. “It is far enough out that it gives you a bit more latitude to come up with a broader way to the future, allowing for disruption and innovation,” says Brian David Johnson, former chief futurist for Intel and current futurist in residence at Arizona State University’s Center for Science and the Imagination. “But you can still see the light from it.”

The process involves gathering information about the factors and forces—technological, business, sociological, and industry or ecosystem trends—that are effecting change to envision a range of potential impacts.

Seeing New Worlds

Intel, for example, looks beyond its own industry boundaries to envision possible future developments in adjacent businesses in the larger ecosystem it operates in. In 2008, the Intel Labs team, led by anthropologist Genevieve Bell, determined that the introduction of flexible glass displays would open up a whole new category of foldable consumer electronic devices.

To take advantage of that advance, Intel would need to be able to make silicon small enough to fit into some imagined device of the future. By the time glass manufacturer Corning unveiled its ultra-slim, flexible glass surface for mobile devices, laptops, televisions, and other displays of the future in 2012, Intel had already created design prototypes and kicked its development into higher gear. “Because we had done the future casting, we were already imagining how people might use flexible glass to create consumer devices,” says Johnson.

Because future planning relies so heavily on the quality of the input it receives, bringing in experts can elevate the practice. They can come from inside an organization, but the most influential insight may come from the outside and span a wide range of disciplines, says Steve Brown, a futurist, consultant, and CEO of BaldFuturist.com who worked for Intel Labs from 2007 to 2016.

Companies may look to sociologists or behaviorists who have insight into the needs and wants of people and how that influences their actions. Some organizations bring in an applied futurist, skilled at scanning many different forces and factors likely to coalesce in important ways (see Do You Need a Futurist?).

Do You Need a Futurist?

Most organizations need an outsider to help envision their future. Futurists are good at looking beyond the big picture to the biggest picture.

Business leaders who want to be better prepared for an uncertain and disruptive future will build future planning as a strategic capability into their organizations and create an organizational culture that embraces the approach. But working with credible futurists, at least in the beginning, can jump-start the process.

“The present can be so noisy and business leaders are so close to it that it’s helpful to provide a fresh outside-in point of view,” says veteran futurist Bob Johansen.

To put it simply, futurists like Johansen are good at connecting dots—lots of them. They look beyond the boundaries of a single company or even an industry, incorporating into their work social science, technical research, cultural movements, economic data, trends, and the input of other experts.

They can also factor in the cultural history of the specific company with whom they’re working, says Brian David Johnson, futurist in residence at Arizona State University’s Center for Science and the Imagination. “These large corporations have processes and procedures in place—typically for good reasons,” Johnson explains. “But all of those reasons have everything to do with the past and nothing to do with the future. Looking at that is important so you can understand the inertia that you need to overcome.”

One thing the best futurists will say they can’t do: predict the future. That’s not the point. “The future punishes certainty,” Johansen says, “but it rewards clarity.” The methods futurists employ are designed to trigger discussions and considerations of possibilities corporate leaders might not otherwise consider.

You don’t even necessarily have to buy into all the foresight that results, says Johansen. Many leaders don’t. “Every forecast is debatable,” Johansen says. “Foresight is a way to provoke insight, even if you don’t believe it. The value is in letting yourself be provoked.”

External expert input serves several purposes. It brings everyone up to a common level of knowledge. It can stimulate and shift the thinking of participants by introducing them to new information or ideas. And it can challenge the status quo by illustrating how people and organizations in different sectors are harnessing emerging trends.

The goal is not to come up with one definitive future but multiple possibilities—positive and negative—along with a list of the likely obstacles or accelerants that could surface on the road ahead. The result: increased clarity—rather than certainty—in the face of the unknown that enables business decision makers to execute and refine business plans and strategy over time.

Plotting the Steps Along the Way

Coming up with potential trends is an important first step in futuring, but even more critical is figuring out what steps need to be taken along the way: eight years from now, four years from now, two years from now, and now. Considerations include technologies to develop, infrastructure to deploy, talent to hire, partnerships to forge, and acquisitions to make. Without this vital step, says Brown, everybody goes back to their day jobs and the new thinking generated by future planning is wasted. To work, the future steps must be tangible, concrete, and actionable.

Organizations must build a roadmap for the desired future state that anticipates both developments and detours, complete with signals that will let them know if they’re headed in the right direction. Brown works with corporate leaders to set indicator flags to look out for on the way to the anticipated future. “If we see these flagged events occurring in the ecosystem, they help to confirm the strength of our hypothesis that a particular imagined future is likely to occur,” he explains.

For example, one of Brown’s clients envisioned two potential futures: one in which gestural interfaces took hold and another in which voice control dominated. The team set a flag to look out for early examples of the interfaces that emerged in areas such as home appliances and automobiles. “Once you saw not just Amazon Echo but also Google Home and other copycat speakers, it would increase your confidence that you were moving more towards a voice-first era rather than a gesture-first era,” Brown says. “It doesn’t mean that gesture won’t happen, but it’s less likely to be the predominant modality for communication.”

How to Keep Experiments from Being Stifled

Once organizations have a vision for the future, making it a reality requires testing ideas in the marketplace and then scaling them across the enterprise. “There’s a huge change piece involved,”
says Frank Diana, futurist and global consultant with Tata Consultancy Services, “and that’s the place where most
businesses will fall down.”

Many large firms have forgotten what it’s like to experiment in several new markets on a small scale to determine what will stick and what won’t, says René Rohrbeck, professor of strategy at the Aarhus School of Business and Social Sciences. Companies must be able to fail quickly, bring the lessons learned back in, adapt, and try again.

Lowe’s increases its chances of success by creating master narratives across a number of different areas at once, such as robotics, mixed-reality tools, on-demand manufacturing, sustainability, and startup acceleration. The lab maps components of each by expected timelines: short, medium, and long term. “From there, we’ll try to build as many of them as quickly as we can,” says Manna. “And we’re always looking for that next suite of things that we should be working on.” Along the way certain innovations, like the HoloRoom How-To, become developed enough to integrate into the larger business as part of the core strategy.

One way Lowe’s accelerates the process of deciding what is ready to scale is by being open about its nascent plans with the world. “In the past, Lowe’s would never talk about projects that weren’t at scale,” says Manna. Now the company is sharing its future plans with the media and, as a result, attracting partners that can jump-start their realization.

Seeing a Lowe’s comic about employee exoskeletons, for example, led Virginia Tech engineering professor Alan Asbeck to the retailer. He helped develop a prototype for a three-month pilot with stock employees at a Christiansburg, Virginia, store.

The high-tech suit makes it easier to move heavy objects. Employees trying out the suits are also fitted with an EEG headset that the lab incorporates into all its pilots to gauge unstated, subconscious reactions. That direct feedback on the user experience helps the company refine its innovations over time.

Make the Future Part of the Culture

Regardless of whether all the elements of its master narratives come to pass, Lowe’s has already accomplished something important: It has embedded future thinking into the culture of the company.

Companies like Lowe’s constantly scan the environment for meaningful economic, technology, and cultural changes that could impact its future assessments and plans. “They can regularly draw on future planning to answer challenges,” says Rohrbeck. “This intensive, ongoing, agile strategizing is only possible because they’ve done their homework up front and they keep it updated.”

It’s impossible to predict what’s going to happen in the future, but companies can help to shape it, says Manna of Lowe’s. “It’s really about painting a picture of a preferred future state that we can try to achieve while being flexible and capable of change as we learn things along the way.” D!


About the Authors

Dan Wellers is Global Lead, Digital Futures, at SAP.

Kai Goerlich is Chief Futurist at SAP’s Innovation Center Network.

Stephanie Overby is a Boston-based business and technology journalist.


Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.

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Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation.

Share your thoughts with Kai on Twitter @KaiGoe.heif Futu

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The Human Factor In An AI Future

Dan Wellers and Kai Goerlich

As artificial intelligence becomes more sophisticated and its ability to perform human tasks accelerates exponentially, we’re finally seeing some attempts to wrestle with what that means, not just for business, but for humanity as a whole.

From the first stone ax to the printing press to the latest ERP solution, technology that reduces or even eliminates physical and mental effort is as old as the human race itself. However, that doesn’t make each step forward any less uncomfortable for the people whose work is directly affected – and the rise of AI is qualitatively different from past developments.

Until now, we developed technology to handle specific routine tasks. A human needed to break down complex processes into their component tasks, determine how to automate each of those tasks, and finally create and refine the automation process. AI is different. Because AI can evaluate, select, act, and learn from its actions, it can be independent and self-sustaining.

Some people, like investor/inventor Elon Musk and Alibaba founder and chairman Jack Ma, are focusing intently on how AI will impact the labor market. It’s going to do far more than eliminate repetitive manual jobs like warehouse picking. Any job that involves routine problem-solving within existing structures, processes, and knowledge is ripe for handing over to a machine. Indeed, jobs like customer service, travel planning, medical diagnostics, stock trading, real estate, and even clothing design are already increasingly automated.

As for more complex problem-solving, we used to think it would take computers decades or even centuries to catch up to the nimble human mind, but we underestimated the exponential explosion of deep learning. IBM’s Watson trounced past Jeopardy champions in 2011 – and just last year, Google’s DeepMind AI beat the reigning European champion at Go, a game once thought too complex for even the most sophisticated computer.

Where does AI leave human?

This raises an urgent question for the future: How do human beings maintain our economic value in a world in which AI will keep getting better than us at more and more things?

The concept of the technological singularity – the point at which machines attain superhuman intelligence and permanently outpace the human mind – is based on the idea that human thinking can’t evolve fast enough to keep up with technology. However, the limits of human performance have yet to be found. It’s possible that people are only at risk of lagging behind machines because nothing has forced us to test ourselves at scale.

Other than a handful of notable individual thinkers, scientists, and artists, most of humanity has met survival-level needs through mostly repetitive tasks. Most people don’t have the time or energy for higher-level activities. But as the human race faces the unique challenge of imminent obsolescence, we need to think of those activities not as luxuries, but as necessities. As technology replaces our traditional economic value, the economic system may stop attaching value to us entirely unless we determine the unique value humanity offers – and what we can and must do to cultivate the uniquely human skills that deliver that value.

Honing the human advantage

As a species, humans are driven to push past boundaries, to try new things, to build something worthwhile, and to make a difference. We have strong instincts to explore and enjoy novelty and risk – but according to psychologist Mihaly Csikszentmihalyi, these instincts crumble if we don’t cultivate them.

AI is brilliant at automating routine knowledge work and generating new insights from existing data. What it can’t do is deduce the existence, or even the possibility, of information it isn’t already aware of. It can’t imagine radical new products and business models. Or ask previously unconceptualized questions. Or envision unimagined opportunities and achievements. AI doesn’t even have common sense! As theoretical physicist Michio Kaku says, a robot doesn’t know that water is wet or that strings can pull but not push. Nor can robots engage in what Kaku calls “intellectual capitalism” – activities that involve creativity, imagination, leadership, analysis, humor, and original thought.

At the moment, though, we don’t generally value these so-called “soft skills” enough to prioritize them. We expect people to develop their competency in emotional intelligence, cross-cultural awareness, curiosity, critical thinking, and persistence organically, as if these skills simply emerge on their own given enough time. But there’s nothing soft about these skills, and we can’t afford to leave them to chance.

Lessons in being human

To stay ahead of AI in an increasingly automated world, we need to start cultivating our most human abilities on a societal level – and to do so not just as soon as possible, but as early as possible.

Singularity University chairman Peter Diamandis, for example, advocates revamping the elementary school curriculum to nurture the critical skills of passion, curiosity, imagination, critical thinking, and persistence. He envisions a curriculum that, among other things, teaches kids to communicate, ask questions, solve problems with creativity, empathy, and ethics, and accept failure as an opportunity to try again. These concepts aren’t necessarily new – Waldorf and Montessori schools have been encouraging similar approaches for decades – but increasing automation and digitization make them newly relevant and urgent.

The Mastery Transcript Consortium is approaching the same problem from the opposite side, by starting with outcomes. This organization is pushing to redesign the secondary school transcript to better reflect whether and how high school students are acquiring the necessary combination of creative, critical, and analytical abilities. By measuring student achievement in a more nuanced way than through letter grades and test scores, the consortium’s approach would inherently require schools to reverse-engineer their curricula to emphasize those abilities.

Most critically, this isn’t simply a concern of high-tuition private schools and “good school districts” intended to create tomorrow’s executives and high-level knowledge workers. One critical aspect of the challenge we face is the assumption that the vast majority of people are inevitably destined for lives that don’t require creativity or critical thinking – that either they will somehow be able to thrive anyway or their inability to thrive isn’t a cause for concern. In the era of AI, no one will be able to thrive without these abilities, which means that everyone will need help acquiring them. For humanitarian, political, and economic reasons, we cannot just write off a large percentage of the population as disposable.

In the end, anything an AI does has to fit into a human-centered value system that takes our unique human abilities into account. Why would we want to give up our humanity in favor of letting machines determine whether or not an action or idea is valuable? Instead, while we let artificial intelligence get better at being what it is, we need to get better at being human. That’s how we’ll keep coming up with groundbreaking new ideas like jazz music, graphic novels, self-driving cars, blockchain, machine learning – and AI itself.

Read the executive brief Human Skills for the Digital Future.

Build an intelligent enterprise with AI and machine learning to unite human expertise and computer insights. Run live with SAP Leonardo.


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Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation.

Share your thoughts with Kai on Twitter @KaiGoe.heif Futu