Will A Robot Take Your Marketing Job?

Tom Pick

Are you panicked yet that artificial intelligence (AI) will soon put you out of work? Could a robot take your marketing job? Some of the brightest minds in Silicon Valley are warning of massive job displacement across the economy in the next decade.

But there remain good reasons not to be terribly alarmed. At least, not for a while.

First, the bad news: according to ThinkGrowth.org, “Between nine percent and 47% of jobs are in danger of being made irrelevant due to technological change (in the next 15 years), with the worst threats falling among the less educated.”

Some panelists at SXSW this spring were even more apocalyptic. Bill Gates said, “AI is the biggest threat to the human race. I can’t believe more people are not worried about this.” Steve Wozniak added, “Fast machines will eventually get rid of slow humans.”

There’s no question the nature of work will continue to change. Automation has been gradually displacing human labor since before the industrial revolution. And AI will expand the range of tasks machines can perform through “smart” automation.

Yet the future for workers may not be so bleak after all, particularly in skilled trades and in creative professions like marketing. Here’s why.

Robots can’t make it alone – even in manufacturing

Robots have been used in manufacturing since 1959. And it’s true, automation in general, and robots in particular, have had a significant impact on factory employment. The number of U.S. workers employed in manufacturing fell 39% from its peak in 1977 to 2012. Five million factory jobs have disappeared since 2000, partly due to trade, but primarily due to automation.

However, those trends don’t quite tell the whole story. The United States has actually added 1 million manufacturing jobs since employment in the sector bottomed out in 2010. And growth is continuing. According to the latest figures from the Bureau of Labor Statistics (BLS):

“In February (2017), employment in manufacturing rose by 28,000. The manufacturing diffusion index increased from 50.0 in January to 65.4, its highest level since November 2014. A value above 50 indicates that more component industries gained jobs than lost them.”

Factories are having trouble finding workers – at least finding those with the right skills. In Minnesota, for example, “nearly 5,000 manufacturing jobs are unfilled – a number that will likely grow as more and more employees move into retirement.” And nationwide, Bloomberg projects, “Over the next decade, 3.4 million manufacturing jobs are expected to become available as baby boomers retire and economic growth spurs work opportunities… but a skills gap could result in 2 million of those jobs staying unfilled.”

How is it possible that employment may grow and factories may face (human) worker shortages even as robotics and AI technologies advance? Simple: Automation increases productivity (which increases societal wealth) and makes the United States more competitive globally. We’ll need more workers and more robots.

Driverless vehicles roll forward slowly

A recent U.S. government report, Artificial Intelligence, Automation, and Economy, predicts driverless automated vehicle (AV) technology may eliminate 2.2 to 3.1 million existing U.S. jobs. But any such job losses that occur won’t happen immediately or abruptly. They will be spread out over time.

Further, the report concedes that certain types of drivers (e.g., long-haul truckers transporting goods) are more likely to be replaced than others (school bus drivers transporting children, for example). The study also notes, “New jobs will also likely be created, both in existing occupations – cheaper transportation costs will lower prices and increase demand for goods and all the related occupations such as service and fulfillment – and in new occupations not currently foreseeable.”

And those projected job losses assume AV technology will become reliable and trusted. Though great progress has been made (driverless vehicles are being tested in several cities beyond San Francisco, Detroit, and Pittsburgh), some of the hardest work remains. As the expression among software developers goes, the first 90% of a project takes 10% of the time; and the last 10% of the project takes the other 90%.

AV technology will need to work nearly flawlessly before adoption becomes widespread. Business Insider has reported that lawyers are “salivating” over self-driving cars because they are “going to get a whole host of new defendants,” with deep pockets, in the event of any crashes.

Development of AV technology that works dependably regardless of weather, daylight, and other conditions remains challenging. As Gary Marcus, a best-selling author, entrepreneur, and professor of psychology at NYU, pointed out in TechCrunch regarding AI, “look, for example, at a driverless car; that’s a form of intelligence, modest intelligence, the average 16-year-old can do it, as long as they’re sober, with a couple of months of training. Yet Google has worked on it for seven years and their car still can only drive –  as far as I can tell, since they don’t publish the data … on sunny days, without too much traffic.”

Still, robots and AI already have displaced some workers and will continue to expand into new jobs, particularly those that deal with things rather than people. It will likely be a long time before robots are trusted to care for children or adults with special needs, but they’ve already been running warehouses for years.

Public policy will need to address those job losses, for example with displacement assistance and retraining programs. But standing in the way of AI and robotic progress would be counterproductive (literally); by increasing productivity, they raise living standards across society. Schemes like a robot tax are a bad idea.

So, robots can weld and they can drive – but can they market?

Technology has eliminated wide swaths of employment in the past, from telephone operators and electric typewriter repairers, to photo technicians and video rental store cashiers. It’s now threatening various types of clerks, professional drivers, even insurance underwriters and appraisers.

But AI is more likely to change how marketers work than to replace them. It will supplement the efforts of human workers rather than take their jobs. Why?

First, consider one type of technology already in wide use: marketing automation software. Despite the label, these applications don’t “automate” marketing; they merely enable marketing professionals to set up sequences of email messages that are then automatically sent out using human-defined sequences and branches.

There are marketing professionals, agencies, and consultants who specialize in optimizing the use of marketing automation systems. In the words of Marketing Week, marketing automation platforms “don’t destroy jobs, they just change what jobs are needed.”

Second, there are several distinctly human characteristics essential to marketing that will likely prove vexing to mimic with silicon.

  • Interpretation: An AI-based tool like PaveAI can evaluate 16 million possible correlations within Google Analytics then produce a report showing the most significant findings. But it still requires a human to interpret the results.

For example, knowing that the highest conversion rate correlates with visitors who land on your homepage on a weekday during business hours is about as unsurprising as any data point could be to a B2B marketer. But discovering the lowest conversion rate is associated with a particular section of your website that visitors often reach through organic search is far more interesting, and actionable.

Sentiment analysis presents another type of problem. Words like bomb, sick, mad, bad, and beast are generally considered negative terms to associate with your brand; yet all have, within recent memory, had a positive connotation in slang. People get that (hopefully). Machines will likely struggle.

  • Creativity: Marketing is an almost uniquely left brain and right brain profession. Data analysis, where AI can help, is of course vital.

But emotion plays a significant role in every considered purchase process, impacting both consumer and B2B buying decisions.

The creative side of marketing appeals to our emotions, and that side requires distinctly human creativity. It’s difficult to imagine, for example, even the most sophisticated AI systems coming up with something like E-TRADE’s invest in vests commercial.

  • Originality:  AI can help marketers optimize current channels, but it won’t develop radically new ideas. For example, AI can help optimize and personalize email content – but AI never would have come up with the idea of using email for marketing in the first place (that was Gary Thuerk of Digital Equipment Corporation).

AI may help with optimizing messaging and timing on social networks. But it couldn’t have spontaneously computed Oreo’s famous dunk-in-the-dark tweet… Or suggested creating a profile for KFC’s famous founder on LinkedIn. And it certainly wouldn’t have invented a sporting event to support brand content marketing, as Red Bull has done with Crashed Ice.

  • Perspective: Not every question, in any realm of life, has a clear-cut answer. Even when looking at the same underlying data, reasonable and intelligent people can disagree, based on their beliefs, assumptions, experiences, and definitions – in short, based on their perspective.

For example, is it possible to accurately measure the ROI of social media marketing efforts? AI could provide an answer – and with the right data sources, even perform the calculations – but it couldn’t provide the perspective on the answer that a human thought leader provides.

In marketing content, it’s often the perspective that’s as interesting as the answer. It’s difficult to imagine an AI system weaving a narrative from a unique or interesting perspective. It’s even harder to imagine AI writing this post.

  • Persuasiveness: Great marketing in any form – text, visual, video – combines logic with emotion to move buyers to act. AI has logic literally at its core, but trying to teach AI to understand human emotions has so far been an enormous challenge.

Robots: The new job creators?

An analysis by The Economist on the impact of robots and AI on employment suggests not only that the fear of massive job losses is likely overblown, but that in some cases automation may actually increase the number of jobs for humans. A study of the American job market from 1982 to 2012 found that:

“Employment grew significantly faster in occupations (for example, graphic design) that made more use of computers, as automation sped up one aspect of a job, enabling workers to do the other parts better. The net effect was that more computer-intensive jobs within an industry displaced less computer-intensive ones. Computers thus reallocate rather than displace jobs, requiring workers to learn new skills. This is true of a wide range of occupations…

“So far, the same seems to be true of fields where AI is being deployed. For example, the introduction of software capable of analyzing large volumes of legal documents might have been expected to reduce the number of legal clerks and paralegals, who act as human search engines during the ‘discovery’ phase of a case; in fact, automation has reduced the cost of discovery and increased demand for it. Judges are more willing to allow discovery now, because it’s cheaper and easier… The number of legal clerks in America increased by 1.1% a year between 2000 and 2013.”

The analysis also reiterates that almost every new wave of technology in the past has raised the specter of mass unemployment, only to end up creating more jobs than were destroyed. The term “technological unemployment” sounds like a concept Gates or Wozniak may have devised. The phrase was in fact coined by economist John Maynard Keynes in the 1930s. The total U.S. labor force more than doubled in the following five decades.

In marketing, AI will take over routine and data analysis-intensive tasks, but also create new opportunities for human employees – for example, in training and teaching AI systems. AI is already being used in areas like personalizing product recommendations and more granularly targeting advertising.

But AI requires human training, testing, and teaching both during the implementation phase and on an ongoing basis. Both human testing and human judgment are needed upfront in terms of preparing AI platforms for the real world and determining when they are ready to go live.

A Harvard Business Review article points out the level at which AI systems are “good enough” varies widely by application; a mistake by Alexa or Siri in understanding speech and ordering the wrong item is annoying. A mistake by a self-driving vehicle may be fatal.

Once live, AI platforms – just like a human graduating from college and entering the workforce – need continued training over time to increase their capabilities and stay current with changing tastes and technology. And that means people, as explained in VentureBeat: “AI’s advancement up the value chain is only possible with the aid of human intelligence.”

Historically, technological advancements have always ended up creating more jobs than they destroyed. Today may prove to be different, but for now, it appears robots are more likely to be workplace assistants rather than job terminators. As a marketer, you probably don’t have to worry about robots or AI taking your job. But you will need to be prepared to work with these technologies to do your job better.

For more on marketing in today’s digital-driven environment, read Primed: Prompting Customers to Buy.

Photo: The Adventurist and MOCIST Flickr via Compfight cc

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AI, Blockchain, And Cloud Fuel Banking’s Evolution

John Bertrand

Artificial intelligence (AI), blockchain, and cloud technologies are increasingly appearing on the horizon. This could be exactly what the banker ordered, given the legal mandates for open banking and General Data Protection Regulation for 2018. These three key technologies can fuel the financial services industry’s evolution into the digital age.

Artificial intelligence

AI is a collection of machine learning, natural language processing, and cognitive computing designed for scale. It is this scalability that is exciting, as it can create exponential growth and deliver today’s required personalized communications. For example, in July 2017 UK payments processed 21 million payments per business day. If 0.5% of the daily volume needed additional review, 105,000 items would need to be checked, often manually and with rules-based, tick-the-box solutions. AI would significantly increase productivity by matching payment behavior and pattern recognition, and simply asking the question, “does this look right?” AI-powered chatbots could help business users and consumers answer inquiries and enhance the customer experience.

Blockchain

Blockchain is also a mix of technologies that enables us to trust someone we do not know and protects us from cybercriminals. The block contains vital information about a party, and the chain is the sequence of third-party, verified events that have taken place over the history of the transaction. Blockchain is fully encrypted and can be permissioned for private and public groups. Given the manual, paper-based state of the supply chain, it is not surprising that we’re seeing many new proofs of concepts and pilots using blockchain.

Cloud

Cloud computing gives improved security, scale, and agility to respond to market demands and can decrease banks’ cost bases. The advances in cloud technologies permit software applications to move seamlessly between legacy, private cloud, and public cloud solutions. One such technology, containers, allows the applications to flow safely across the end-to-end processes regardless of the underlying technologies, much like how shipping containers transformed the inefficient, non-scalable 20th century transportation industry to the one today.

Finance’s digital evolution

These technologies are could be the savior of financial services industry. Financial services are rapidly becoming a technology-driven sector, evidenced by the increasing amount of money being spent in this area.

  • Financial services is now one of the largest buyers of software
  • IDC expects this figure to grow more than five percent over 2016’s spending
  • The forecast of $2.7 trillion in worldwide IT spending by 2020 is led by the financial services industry

Legacy banks and financial services firms can either build the technology themselves or work with fintechs to do so; either way it has to be done. Eminent evolutionary biologist Charles Darwin could have been discussing this new banking environment when he noted:

It is not the strongest of the species that survive, nor the most intelligent, but the one most responsive to change. 

Potential impacts of financial services’ digital evolution include:

  • Low-cost centers using AI to increase straight-through processing (STP) to 100%, thus removing cost, increasing customer satisfaction, and reducing liabilities from errors
  • Administration of trade finance through blockchain to reduce costs and increase certainty of ownership at any point in time
  • Spare computer capacity created by using the cloud, enabling banks to meet peak-day requirements and increase cybersecurity

Security is now a bottom-line concern. See The Future of Cybersecurity: Trust as Competitive Advantage.

This article was originally published on Finextra.

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Robots Are Moving Into Our Human Resources Functions

Agnes Desplechin

“When we react it will be too late,” said Elon Musk, CEO of Tesla Motors (a pioneer in the connected car market), in July at the U.S. National Governors Association Summer Meeting. The businessman expressed his concern about the development of artificial intelligence and the delay in terms of regulation that would represent “a fundamental risk to the existence of human civilization.”

Today, the thought that humans can (in some activities) be substituted by robots no longer belongs solely to fictional works such as Frankenstein (1818) or current television shows Black Mirror and Westworld.

Concerns about potential failures caused by robots are very real and present today. Even before the most advanced prototypes of robots and the possibilities offered by artificial intelligence were considered, economist John Maynard Keynes prophesied the substitution of man by machines. In “Economic Possibilities for Our Grandchildren,” published in 1930, he questioned the effects of automation on jobs, well-being, and happiness, seeking to find solutions to the issue of “technological unemployment.”

A century later, the replacement of human workers by robots is anticipated across the job spectrum. According to Laurent Alexandre, technocrat, urological surgeon, and artificial intelligence (AI) advocate, all professions will, in the near future, be threatened by AI, which will soon be everywhere. Indeed, AI it is already in your pocket; Siri and Google Assistant are early chatbots, conversational robots that will replace salesmen, attorneys, journalists, and eventually, human resource assistants.

To better understand the stakes, we must understand what AI is. Consider a machine without AI, which makes decisions based on manually defined rules. When a machine facing a large data flow learns to analyze and make decisions, intelligence is born; this is machine learning. If you’re still confused about machine learning based on this description, let’s take the example of email that you define manually as “spam” within your mailbox. Once it learns the form, structure, sender, and other details that led you to mark a message as spam (i.e., the rules you defined, even subconsciously), the machine can make the decision that a message is spam. Unlike human intelligence, the machine can be caught off guard when there are exceptions.

How AI develops is of great interest in the context of HR functions. Some examples include using automated and intelligent filters for recruitment, using robots for interviews, or having chatbots act as human resource assistants in order to answer recurring questions from employees.

AI’s contribution is often measured in terms of time and cost savings, but it can also lead to more impartiality and efficiency. Even so, the human aspects and ethics must remain the core part of the HR role. As Elon Musk suggests, we must now ensure AI retains our standards, and, crucially for the HR profession, keeps the “human” in human resources.

Will intelligent machines and HR one day walk hand in hand? AI offers prospects that are very promising and prompt many questions that will shape the evolution of our profession.

AI’s ability to end bias hinges on teaching it to play fair and constantly questioning the results.
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Diving Deep Into Digital Experiences

Kai Goerlich

 

Google Cardboard VR goggles cost US$8
By 2019, immersive solutions
will be adopted in 20% of enterprise businesses
By 2025, the market for immersive hardware and software technology could be $182 billion
In 2017, Lowe’s launched
Holoroom How To VR DIY clinics

From Dipping a Toe to Fully Immersed

The first wave of virtual reality (VR) and augmented reality (AR) is here,

using smartphones, glasses, and goggles to place us in the middle of 360-degree digital environments or overlay digital artifacts on the physical world. Prototypes, pilot projects, and first movers have already emerged:

  • Guiding warehouse pickers, cargo loaders, and truck drivers with AR
  • Overlaying constantly updated blueprints, measurements, and other construction data on building sites in real time with AR
  • Building 3D machine prototypes in VR for virtual testing and maintenance planning
  • Exhibiting new appliances and fixtures in a VR mockup of the customer’s home
  • Teaching medicine with AR tools that overlay diagnostics and instructions on patients’ bodies

A Vast Sea of Possibilities

Immersive technologies leapt forward in spring 2017 with the introduction of three new products:

  • Nvidia’s Project Holodeck, which generates shared photorealistic VR environments
  • A cloud-based platform for industrial AR from Lenovo New Vision AR and Wikitude
  • A workspace and headset from Meta that lets users use their hands to interact with AR artifacts

The Truly Digital Workplace

New immersive experiences won’t simply be new tools for existing tasks. They promise to create entirely new ways of working.

VR avatars that look and sound like their owners will soon be able to meet in realistic virtual meeting spaces without requiring users to leave their desks or even their homes. With enough computing power and a smart-enough AI, we could soon let VR avatars act as our proxies while we’re doing other things—and (theoretically) do it well enough that no one can tell the difference.

We’ll need a way to signal when an avatar is being human driven in real time, when it’s on autopilot, and when it’s owned by a bot.


What Is Immersion?

A completely immersive experience that’s indistinguishable from real life is impossible given the current constraints on power, throughput, and battery life.

To make current digital experiences more convincing, we’ll need interactive sensors in objects and materials, more powerful infrastructure to create realistic images, and smarter interfaces to interpret and interact with data.

When everything around us is intelligent and interactive, every environment could have an AR overlay or VR presence, with use cases ranging from gaming to firefighting.

We could see a backlash touting the superiority of the unmediated physical world—but multisensory immersive experiences that we can navigate in 360-degree space will change what we consider “real.”


Download the executive brief Diving Deep Into Digital Experiences.


Read the full article Swimming in the Immersive Digital Experience.

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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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Jenny Dearborn: Soft Skills Will Be Essential for Future Careers

Jenny Dearborn

The Japanese culture has always shown a special reverence for its elderly. That’s why, in 1963, the government began a tradition of giving a silver dish, called a sakazuki, to each citizen who reached the age of 100 by Keiro no Hi (Respect for the Elders Day), which is celebrated on the third Monday of each September.

That first year, there were 153 recipients, according to The Japan Times. By 2016, the number had swelled to more than 65,000, and the dishes cost the already cash-strapped government more than US$2 million, Business Insider reports. Despite the country’s continued devotion to its seniors, the article continues, the government felt obliged to downgrade the finish of the dishes to silver plating to save money.

What tends to get lost in discussions about automation taking over jobs and Millennials taking over the workplace is the impact of increased longevity. In the future, people will need to be in the workforce much longer than they are today. Half of the people born in Japan today, for example, are predicted to live to 107, making their ancestors seem fragile, according to Lynda Gratton and Andrew Scott, professors at the London Business School and authors of The 100-Year Life: Living and Working in an Age of Longevity.

The End of the Three-Stage Career

Assuming that advances in healthcare continue, future generations in wealthier societies could be looking at careers lasting 65 or more years, rather than at the roughly 40 years for today’s 70-year-olds, write Gratton and Scott. The three-stage model of employment that dominates the global economy today—education, work, and retirement—will be blown out of the water.

It will be replaced by a new model in which people continually learn new skills and shed old ones. Consider that today’s most in-demand occupations and specialties did not exist 10 years ago, according to The Future of Jobs, a report from the World Economic Forum.

And the pace of change is only going to accelerate. Sixty-five percent of children entering primary school today will ultimately end up working in jobs that don’t yet exist, the report notes.

Our current educational systems are not equipped to cope with this degree of change. For example, roughly half of the subject knowledge acquired during the first year of a four-year technical degree, such as computer science, is outdated by the time students graduate, the report continues.

Skills That Transcend the Job Market

Instead of treating post-secondary education as a jumping-off point for a specific career path, we may see a switch to a shorter school career that focuses more on skills that transcend a constantly shifting job market. Today, some of these skills, such as complex problem solving and critical thinking, are taught mostly in the context of broader disciplines, such as math or the humanities.

Other competencies that will become critically important in the future are currently treated as if they come naturally or over time with maturity or experience. We receive little, if any, formal training, for example, in creativity and innovation, empathy, emotional intelligence, cross-cultural awareness, persuasion, active listening, and acceptance of change. (No wonder the self-help marketplace continues to thrive!)

The three-stage model of employment that dominates the global economy today—education, work, and retirement—will be blown out of the water.

These skills, which today are heaped together under the dismissive “soft” rubric, are going to harden up to become indispensable. They will become more important, thanks to artificial intelligence and machine learning, which will usher in an era of infinite information, rendering the concept of an expert in most of today’s job disciplines a quaint relic. As our ability to know more than those around us decreases, our need to be able to collaborate well (with both humans and machines) will help define our success in the future.

Individuals and organizations alike will have to learn how to become more flexible and ready to give up set-in-stone ideas about how businesses and careers are supposed to operate. Given the rapid advances in knowledge and attendant skills that the future will bring, we must be willing to say, repeatedly, that whatever we’ve learned to that point doesn’t apply anymore.

Careers will become more like life itself: a series of unpredictable, fluid experiences rather than a tightly scripted narrative. We need to think about the way forward and be more willing to accept change at the individual and organizational levels.

Rethink Employee Training

One way that organizations can help employees manage this shift is by rethinking training. Today, overworked and overwhelmed employees devote just 1% of their workweek to learning, according to a study by consultancy Bersin by Deloitte. Meanwhile, top business leaders such as Bill Gates and Nike founder Phil Knight spend about five hours a week reading, thinking, and experimenting, according to an article in Inc. magazine.

If organizations are to avoid high turnover costs in a world where the need for new skills is shifting constantly, they must give employees more time for learning and make training courses more relevant to the future needs of organizations and individuals, not just to their current needs.

The amount of learning required will vary by role. That’s why at SAP we’re creating learning personas for specific roles in the company and determining how many hours will be required for each. We’re also dividing up training hours into distinct topics:

  • Law: 10%. This is training required by law, such as training to prevent sexual harassment in the workplace.

  • Company: 20%. Company training includes internal policies and systems.

  • Business: 30%. Employees learn skills required for their current roles in their business units.

  • Future: 40%. This is internal, external, and employee-driven training to close critical skill gaps for jobs of the future.

In the future, we will always need to learn, grow, read, seek out knowledge and truth, and better ourselves with new skills. With the support of employers and educators, we will transform our hardwired fear of change into excitement for change.

We must be able to say to ourselves, “I’m excited to learn something new that I never thought I could do or that never seemed possible before.” D!

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