How Open Source Is Changing Software Innovation

Al Gillen

Open-source software has come a long way. After a period of maturation, most visibly to the wider public during the late 1990s and early 2000s – during the early days of Linux – the approach to developing technology under an open-use license, also known as open-source software, has now become mainstream.

In recent years, we have seen many commercially focused companies put both existing intellectual property and new projects that are being incubated into open source. This trend has been particularly strong with software used by developers as platforms or tools. Today, the vast majority of developer tools and platforms are open source or derived from open-source technology.

As enterprises across industries rush headlong into digital transformation, many have begun to emulate tech industry practices in how they use and produce software innovation and have thus increased adoption of, and even contribution to, open source. So what are the benefits of open-source engagement for the enterprise? Here are six broad benefits of using and contributing to open source.

  1. Not re-inventing the wheel. The most obvious reason to use open-source software is to build software faster without having to re-implement solutions to already solved problems. Companies must move fast to stay at the top of their game – and that means grabbing the best solutions contributed by a well-honed ecosystem and building their own added innovation on top of it. Doing anything else is suboptimal and will ultimately lead to a more burdensome maintenance and update responsibility, and ultimately falling behind competitors. Contributing software customization and adding value back to the larger open-source community can bring the benefit of better vetting and quality improvement of the code by the community.
  1. Ensuring strategic safety. It used to be that IT organizations bought important software only from large, established software vendors. Open source innovation now allows smaller players to provide viable solutions while assuring the buyers that they can have control over the technical direction of the software, thus avoiding unreasonable price increases or unnecessary product changes, and minimizing the potential for lock-in. The broadening of software supplies also expands the range of software solutions available to enterprises and keeps the larger software vendors on their toes. Using software that builds on an open source code-base also allows enterprises to participate in the technology’s evolution and maintain more control over the destiny of the products based on this software.
  1. Efficient experimentation and business acceleration. In the age of digital transformation, experimentation is the new mantra. Digital disruptors like Netflix, Uber, and Airbnb have revolutionized their industries and put the accelerated startup culture on the map with the famous “fail fast and often in the past” mantra. Modern enterprises have finally come to realize that to survive the disruption and keep up, they must adopt as much of that experimental culture as possible and overcome their fears of failure. Experimentation of this kind implies a speed in product and service development that building software in-house simply cannot deliver. By taking existing code developed by others, and leveraging this code in new offerings, enterprises can truly speed up their product cycles. Open source provides the digital shoulders that enterprises can stand on to compete. By further contributing new value back to open source, enterprises have a chance of generating mindshare for their offerings, also known as free marketing.
  1. The efficiency of standardized practices. Using open-source solutions means using somewhat standardized (in a de facto sense) solutions to problems. Such standardization of software patterns related to certain industries and verticals enforces a normalized and more optimized set of organizational practices that tend to be portable across that industry. This practice can simplify business process and allow companies to focus on competitive differentiation, rather than wasting resources on things that are not core to their business success.
  1. Cleaner and safer software. Creating software in open source means that engineers operate in daylight, enabling them to avoid the traps of plagiarized software and more easily stay clear of patents and copyrights. Additionally, the visibility open source provides can lead to more secure software and fewer vulnerability surprises, especially if a significant community evolves around the project and performs regular critical reviews. Many companies that create proprietary software have difficulties turning their large code-bases into open source because of the time-consuming intellectual property and security scrubbing processes needed to open the code. Open source IP-based businesses avoid this problem from the get-go. Starting new software initiatives in open source avoids these IP issues.
  1. Attracting, retaining, and motivating top developer talent. Beyond a good pay scale and a supportive work environment, there is little that can push developers to do high-quality work more than peer approval and the opportunity for recognition or even fame. Contributing software back to the community and allowing developers to enjoy the public recognition of their peers can be a powerful motivator and an important tool for employee retention. A similar dynamic is in play in the hiring process as tech companies compete with each other to build their software engineering teams. Offering the opportunity to be visible in a broader developer community, or attain a level of peer recognition, is potentially more important than paying top wages for star developers.
  1. Community-led innovation. With a diverse group of vendors and customers participating in open source efforts, open-source solutions tend to rapidly add functionality relevant to the audience faster than proprietary solutions can typically achieve. As a result, open source adopters are able to influence prioritization of capabilities added to open-source initiatives and quickly accomplish goals specific to their environment.

For more on future-focused digital innovation, see Business Networks: The Platforms For Future Innovation.

Comments

Al Gillen

About Al Gillen

Al Gillen is As Group Vice President of Software Development and Open Source at IDC. He oversees IDC’s software development research portfolio. Research disciplines in this group include developer research covering census, demographics and developer activities; platform and cloud application services for developers, and developer lifecycle and quality assurance products. In addition, Al jointly oversees IDC’s DevOps research program, and runs a program focused on the ecosystem of open source software pan-industry. In his 18th year at IDC, Al has participated in numerous IDC research areas, including infrastructure software (operating environments and virtualization software), enterprise servers, and developer software and services. He has long tracked open source software in infrastructure software markets, and now has expanded open source coverage to cover other market segments.

Want Disruptive Change? There’s An Algorithm For That (Or Soon Will Be)

Jessica Schubert

Trust me – it’s not you. Our world really is more unpredictable than ever. Even the best-laid strategies are being disrupted, whether they are focused on the workplace’s culture, technical environment, market dynamics, customer behavior, or business processes. But central to these uncertainties is one constant: an algorithm guiding every step along the evolutionary trail to digital transformation.

“Each company has a predictable algorithm that’s driving its business model,” said Sathya Narasimhan, senior director for Partner Business Development at SAP, on a live episode of Coffee Break with Game Changers Radio, presented by SAP and produced and moderated by SAP’s Bonnie D. Graham. “When we understand how data affects outcomes and bring sensor data online, it’s easier for the infrastructure to process this information to create additional insights,” she explained. Sathya was joined on the program by a panel of thought leaders featuring Darwin Deano, principal at Deloitte Consulting LLP, and Patricia Florissi, global CTO for Dell EMC Sales.

This observation is very telling of the predictive power of algorithms. Think about it: Amazon proposes what should be in your shopping cart. Netflix recommends the next movie you should watch. Google is serving up ads that tug at your heart (and wallet). And all of this wouldn’t be possible without an algorithm running in the background that predicts what people want, how they behave, and what will influence their actions.

Click to listen to the full episode.

Digital technology nears a tipping point – toward enlightenment

Smart business leaders know that tomorrow’s competitive edge requires rapid innovation across their organization today. Machine learning, Internet of Things, artificial intelligence, blockchain, analytics, and Big Data – there are so many choices available. And businesses have a great opportunity now to begin figuring out how to harness and invest in them.

Patricia believes that this reality may soon reach a tipping point as data volumes continue to swell. “We are entering an enlightened age where there is so much data and computing and processing power that we can infer that our quality of life will fundamentally improve,” she observed.

Recent disruption in agriculture certainly proves Patricia’s point. Although the Internet of Things has been around for 20 years, farmers and their suppliers are just starting to capitalize on the generated data because the power needed to process and analyze it has finally arrived. Now, farmers are collecting and analyzing data generated from GPS and sensors buried in the field soil and embedded in farming equipment to improve crop yields and resource use. This is a significant advancement as farmers find new ways to increase food production – possibly by as much as 70% – to keep pace with a global population that is projected to grow from 7.6 billion today to 9 billion by 2050.

Darwin added that technology is now so affordable that the digital landscape is “starting to see patterns emerge, where some archetypes are beginning to develop as the technology matures.”

The predictive power of algorithms and humans drives business outcomes

One of the best examples of the maturing landscape of technology and algorithms is the current state of artificial intelligence and deep learning.

“Artificial intelligence has evolved, especially with deep learning, to teach computers or to help computers automatically learn how we do things and what we do without being told the rules,” Patricia commented. “The more data being observed, the more patterns can be detected and the more accurate the generalization.”

However, Darwin cautioned against heavy reliance on this technology. “We need to protect ourselves against the erosion of basic cognitive skills, which can be an unintended side effect,” he warned. With cognitive technology, people must have rapid interpretation and response, and algorithms may not always be able to satisfy that need. Humans must maintain the cognitive skills required to do this themselves.

Whether employees have the processing speed and full insight they need to make decisions boils down to a company’s willingness to invest in capabilities required to get work done effectively. “I have realized, after spending the last six years assessing developing strategies for various companies, that businesses gain market share and grow faster because of the investments they make to improve the predictive power of their algorithms,” mentioned Sathya.

The future of algorithms: blockchain, humanity, and ecosystems

As technology and processing power become more mature and powerful, new opportunities for digital innovation will inevitably emerge in the near future.

For Sathya, this future hinges on the arrival of blockchain as a mainstream technology. “We are likely entering an environment where we are relying on fewer regulations and less government interference in how businesses work. To ensure that this new paradigm does not undermine the standard of living of people and the society they live in, multiple parties – such as manufacturers, suppliers, financial services, customers, and government – will need to work together in a way that is less intrusive, more efficient and transparent, and trusted and secure.”

Darwin believes that this change will bring about a new renaissance. “We’re talking about humans being replaced by artificial intelligence, machine learning, and the Internet of Things. However, technology automated to the nth degree will actually free us from acting like technology zombies always engaged with smartphones.”

Patricia anticipates that Sathya’s and Darwin’s predictions will eventually bring about an era of optimized ecosystems and innovative models. “Companies that learn how to nurture, cultivate, and enable vibrant ecosystems, platforms, and new business models will be the digital beginners,” she said. “They are redefining how transactions are conducted and the currency used. Ultimately, the ecosystem, cross-education, and cross-pollination will be key to their transformation.”

Listen to the SAP Radio show “Future-Proof Your Business: Digital Solutions Now!” on demand.

Comments

Jessica Schubert

About Jessica Schubert

Jessica Schubert is the director of Global Partner Marketing, Deloitte Alliance Lead, at SAP. Her specialties include strategic partnerships, business alliances, go-to-market strategy, product marketing, and demand generation.

CIO Priorities For 2018: IT Thought Leaders Share Their Predictions

Rod Tansimore

For a provocative look into the near future of technology applications in business, we asked leading members of the SAP ecosystem to share their prophecies. For CIOs, who are rapidly evolving into an advisory role, the demands increasingly call for tough decisions on where to invest: what technologies, what skills, what new business models? Here’s what our gurus have to say.

Mala Anand, SAP, President, SAP Leonardo and Analytics

2018 will be the tipping point for cloud analytics with the growth of cloud data and applications. This trend will fuel demand for end-to-end cloud analytic platforms that deliver a rich set of analytic capabilities to discover, plan, predict, visualize, prepare, collaborate, model, simulate, and manage while leveraging common data logic. The software-as-a-service (SaaS) model offers business a way to take advantage of continual product innovations in a seamless experience with a common user experience, and will address analytical requirements throughout the organization at a lower TCO vs. fragmented solutions that cause inconsistencies and distorted data views.

Christine Ashton, SAP, Digital Office ERP Cloud, Global Chief Digital Officer

2018 will see a fundamental shift in the role of the CIO in businesses that recognize the value of instant, limitless scalability and immediate access to innovation. Postmodern CIOs will become innovation leaders with a seat – and a key voice – among the C-suite. This will mean:
• Moving from operating IT to innovating business operations
• Swapping owning software for leveraging interlocking solutions across an ecosystem
• Shifting from managing teams to growing an inclusive, confident workforce
• Changing the focus from keeping the lights on to delivering differentiation

The driver behind each will be to equip successful, business-wide digital transformation.

Mark Barrenechea, OpenText, CEO and Chief Technology Officer

As IoT-connected devices push the limits of the cloud, a new paradigm where the cloud and edge computing meet will emerge. Edge computing moves processing power closer to the source of data, sending only data worth keeping to the cloud. Reducing costs and stored volumes of IoT-related data, the device itself will process time-sensitive data, quicker and with reduced network latency. As the number of devices continues to increase, edge computing will push the cloud into a supporting role. Together, the cloud and edge computing will provide the infrastructure needed to support the ever-expanding IoT universe. @markbarrenechea, @opentext

Brian Berns, Knoa Software, CEO

Most companies have little to no insight into how their employees are interacting with their ERP software. This lack of visibility is very costly, as it directly leads to a decrease in employee productivity. In 2018, businesses will increasingly adopt user analytics to gain insight into employee engagement with their software suites. This trend will be accelerated by the move to cloud and mobile enterprise solutions, as well as by the increased importance of user experience for a new generation of knowledge workers. User analytics are bound to become a key technology for IT organizations, which will enable them to measure application usage and identify inhibitors to adoption such as clunky user interfaces, process complexity, and heavy customization.

Orlando Cintra, SAP, SVP, SAP Cloud Platform, Latin America & Caribbean

Companies and C levels will realize that IT is the solved part of the equation. That said, they will turn a lot of attention to proving real business cases with high value so they can innovate with real purpose. Companies in an on-premise model will start to see their costs increasing dramatically compared with the cloud, since all the major players’ investments are going to cloud. Finally, innovation experts, data scientists, tech gurus, and specialists with good track records with success innovation projects will be in demand. The market will not produce talent to meet the expected demand. Companies In the niche to prepare new professionals will have big growth.

Ratnang D. Desai, Deloitte Consulting LLP, Managing Director

2018 will be the year when rapid evolution of technology will force organizations to “Reimagine Everything.” It is not enough to simply reengineer a business process. IT will play a critical role in helping organizations reimagine how disruptive technologies such as cognitive, cloud, and blockchain will fundamentally transform all functions. IT will take the next big step in its transformation, as well. IT and the business will work as true partners and collaborate seamlessly to quickly harness the power of disruptive technologies and turn it into a sustained competitive advantage.

Archana Deskus, Hewlett Packard Enterprise, Global Chief Information Officer

We live in a hybrid data and compute world, requiring flexibility and new architectures with sophistication to span edge to core, enabling distributed machine learning systems to distill end-to-end data insights. Increasingly, we will see the use of machine learning to turn that insight into action, in real time, enabling the hypercompetitive enterprise to disrupt business models and industries to create new experiences and revenue models. None of this will be possible without powerful, future-proof software-defined and memory-driven infrastructure that is consumed in novel, flexible ways. Outcomes as a Service will be the ideal IT delivery model going forward.

Mark Dudgeon, IBM, Global SAP Chief Technology Officer

I expect to see adoption of SAP S/4HANA ramp up significantly in 2018, with SAP S/4HANA Cloud providing an increasingly relevant option for organizations. Blockchain will be an increasingly hot topic, with a number of cross-industry and line-of-business use cases starting to come into mainstream – resolving issues with fractured ecosystem networks, providing transparency and single version of the truth across enterprises. Augmented reality (AR) and virtual reality (AR) are niche technologies in the world of business IT, but I expect to see the use cases expanding beyond training and education into areas such as service and maintenance.
Twitter: @MarkPDudgeon
LinkedIn: MarkPDudgeon

Mike Golz, SAP, Senior Vice President and Regional Chief Information Officer, Americas

As digital transformation takes hold and disrupts more industries, companies need to move from declaring it as critical (78% according to a recent Oxford Economics study) to truly committing to a digital strategy (currently at a dismal 3% in the same study). Whether the change primarily affects a company’s business model, its business processes, or the way people work, the underlying technologies, like machine learning, human/digital interfaces, IoT, or blockchain, are fairly well understood by now. Look no further than your phone. Chances are that you are using them as a consumer today. 3-D printing might look like an exception to consumerization; however, my insoles are based on iPhone pictures uploaded to an app.

Paul Lewis, Hitachi Vantara, Chief Technology Officer, Americas

During 2018, the nature of the CIO’s job will change from the role of “delivery executive” to that of “IT business executive,” realigning the focus from project status and infrastructure uptime to delivering on the three business imperatives. These are: operational efficiency, new customer experiences, and diversified business models of the corporations’ digital transformation strategy. People development will also become the primary consideration for innovation in IoT, AI, and cloud, which are creating a necessity to upskill, re-skill, and replace expertise and experience across disciplines by utilizing platforms to access partner ecosystems of talent, technology, and information.

Follow Paul on his Blog and LinkedIn.

Greg McStravick, SAP, President of Database and Data Management

Data will continue to explode in 2018. Gartner predicts that 95% of new products will contain IoT capabilities, and that means companies will have to contend with a deluge of information even more voluminous than we see today. Organizations that have taken a wait-and-see approach to data management will be bulldozed over by those that made the early investments to make sense of it. Systems that enable data sharing, pipelining and governance along with intelligent machine learning and artificial intelligence in one connected landscape will be a game changer for every organization that wants to remain competitive. @McStravickGreg

Nathan Pearce, Capgemini UK, SAP Practice, Business Development and Innovation Lead

In 2018, we will witness another year of disruptive technologies. In particular, machine learning, combined with AI and data, will change the game in consumer engagement and personalization to help drive loyalty and advocacy. There will also be further developments upon VR and AR across many sectors. @npearce111

Manik Narayan Saha, SAP, Regional Chief Information Officer, APJ

Customers’ digital experience will continue to drive prioritization for companies around engagement, purchase decisions, and brand loyalty. I expect to see higher polarization between companies offering a great digital experience. AI will start to have an impact on traditional business processes – especially relating to back-office, shared services, and mid-office functions. Cloud will become the de facto standard to run the digital enterprise. Except in regulated industries, there is now even less of a compelling argument not to move to cloud-based services, and benefit from scale, agility, and speed. And I will be closely watching to see how the tech industry responds to EU GDPR, and helps customers make a successful transition. @maniksaha

Thomas Saueressig, SAP, Chief Information Officer, Global Head of IT Services

Machine learning and artificial intelligence will grow out of its experimental, early-adopter stage and hit the tipping point to broad adoption. Intelligent services will expand from consumer focus and supporting processes into the core of the enterprise and will become mainstream by 2019. The most underestimated theme I see will be the EU’s General Data Protection Regulation (GDPR). It will gain momentum in 2018 and eat up a fair amount of enterprises’ innovation capacities. Finally, advances in technology will not only shift our focus to other aspects of the services we offer, but will drastically change the way we work. New innovations are disrupting the status quo with exponential speed, requiring us to continuously adapt and learn.

Ronald van Loon, Simplilearn, Advisory Board Member & Big Data and Analytics Course Advisor

In 2018, machine learning applications will continue to mature, with each vendor featuring a domain-specific solution. Organizations need fully integrated, end-to-end data management platforms to handle increases in different data streams, including deep learning applications, while having the ability to transform this data into actionable insights. AI and deep learning applications in voice recognition and video analytics will also accelerate. Edge analytics will progress, corresponding with the massive increase in connected devices. It provides real-time analytic solutions at any point where data is generated, addressing data management challenges related to large amounts of data that can’t be centrally analyzed.

We invite you to stay tuned to the Digitalist Magazine to see where 2018 takes us. Best wishes for a productive and prosperous New Year.

Where will technology take finance in the coming year? See How Finance Is Thriving In A Digital World: 17 Experts Share Their 2018 Predictions.

Comments

Rod Tansimore

About Rod Tansimore

Rod Tansimore is a senior director of IT Technology Programs at SAP. He started his career as a systems engineer at IBM and moved on to hold numerous leadership roles in product management, product marketing, sales, and market development for large and small technology companies. Rod has B.S. in Engineering from Northwestern University and an MBA from Columbia University.

Tags:

Human Skills for the Digital Future

Dan Wellers and Kai Goerlich

Technology Evolves.
So Must We.


Technology replacing human effort is as old as the first stone axe, and so is the disruption it creates.
Thanks to deep learning and other advances in AI, machine learning is catching up to the human mind faster than expected.
How do we maintain our value in a world in which AI can perform many high-value tasks?


Uniquely Human Abilities

AI is excellent at automating routine knowledge work and generating new insights from existing data — but humans know what they don’t know.

We’re driven to explore, try new and risky things, and make a difference.
 
 
 
We deduce the existence of information we don’t yet know about.
 
 
 
We imagine radical new business models, products, and opportunities.
 
 
 
We have creativity, imagination, humor, ethics, persistence, and critical thinking.


There’s Nothing Soft About “Soft Skills”

To stay ahead of AI in an increasingly automated world, we need to start cultivating our most human abilities on a societal level. There’s nothing soft about these skills, and we can’t afford to leave them to chance.

We must revamp how and what we teach to nurture the critical skills of passion, curiosity, imagination, creativity, critical thinking, and persistence. In the era of AI, no one will be able to thrive without these abilities, and most people will need help acquiring and improving them.

Anything artificial intelligence does has to fit into a human-centered value system that takes our unique abilities into account. While we help AI get more powerful, we need to get better at being human.


Download the executive brief Human Skills for the Digital Future.


Read the full article The Human Factor in an AI Future.


Comments

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

Tags:

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.


Comments

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