AI News, More Job Automation But More Jobs Too, Say U.S. Tech CEOs
More Job Automation But More Jobs Too, Say U.S. Tech CEOs
Or, as the report from KPMG puts it: “The majority of technology companies plan to increase their human workforce at least 6 percent over the next three years while adding cognitive systems to create a new class of digital labor that can enhance human skills and expertise.” Bob Melk, president ofjob search firm Dice, told me that software engineers in particularl should benefit from this trend towards workforce automation and machine learning.
Where machines could replace humans—and where they can’t (yet)
As automation technologies such as machine learning and robotics play an increasingly great role in everyday life, their potential effect on the workplace has, unsurprisingly, become a major focus of research and public concern.
Automation, now going beyond routine manufacturing activities, has the potential, as least with regard to its technical feasibility, to transform sectors such as healthcare and finance, which involve a substantial share of knowledge work.
Last year, we showed that currently demonstrated technologies could automate 45 percent of the activities people are paid to perform and that about 60 percent of all occupations could see 30 percent or more of their constituent activities automated, again with technologies available today.
In this article, we examine the technical feasibility, using currently demonstrated technologies, of automating three groups of occupational activities: those that are highly susceptible, less susceptible, and least susceptible to automation.
Toward the end of this article, we discuss how evolving technologies, such as natural-language generation, could change the outlook, as well as some implications for senior executives who lead increasingly automated enterprises.
In discussing automation, we refer to the potential that a given activity could be automated by adopting currently demonstrated technologies, that is to say, whether or not the automation of that activity is technically feasible.2 2.We define “currently demonstrated technologies”
Occupations in retailing, for example, involve activities such as collecting or processing data, interacting with customers, and setting up merchandise displays (which we classify as physical movement in a predictable environment).
The cost of labor and related supply-and-demand dynamics represent a third factor: if workers are in abundant supply and significantly less expensive than automation, this could be a decisive argument against it.
For example, the large-scale deployment of bar-code scanners and associated point-of-sale systems in the United States in the 1980s reduced labor costs per store by an estimated 4.5 percent and the cost of the groceries consumers bought by 1.4 percent.3 3.Emek Basker, “Change at the checkout: Tracing the impact of a process innovation,”
Almost one-fifth of the time spent in US workplaces involves performing physical activities or operating machinery in a predictable environment: workers carry out specific actions in well-known settings where changes are relatively easy to anticipate.
Through the adaptation and adoption of currently available technologies, we estimate the technical feasibility of automating such activities at 78 percent, the highest of our seven top-level categories (Exhibit 2).
Since predictable physical activities figure prominently in sectors such as manufacturing, food service and accommodations, and retailing, these are the most susceptible to automation based on technical considerations alone.
Within manufacturing, 90 percent of what welders, cutters, solderers, and brazers do, for example, has the technical potential for automation, but for customer-service representatives that feasibility is below 30 percent.
A service sector occupies the top spot: accommodations and food service, where almost half of all labor time involves predictable physical activities and the operation of machinery—including preparing, cooking, or serving food;
We calculate that 47 percent of a retail salesperson’s activities have the technical potential to be automated—far less than the 86 percent possible for the sector’s bookkeepers, accountants, and auditing clerks.
The heat map in Exhibit 3 highlights the wide variation in how automation could play out, both in individual sectors and for different types of activities within them.4 4.For a deeper look across all sectors in the US economy, please see the data representations from McKinsey on automation and US jobs, on public.tableau.com.
Long ago, many companies automated activities such as administering procurement, processing payrolls, calculating material-resource needs, generating invoices, and using bar codes to track flows of materials.
Examples include operating a crane on a construction site, providing medical care as a first responder, collecting trash in public areas, setting up classroom materials and equipment, and making beds in hotel rooms.
Already, some activities in less predictable settings in farming and construction (such as evaluating the quality of crops, measuring materials, or translating blueprints into work requirements) are more susceptible to automation.
The hardest activities to automate with currently available technologies are those that involve managing and developing people (9 percent automation potential) or that apply expertise to decision making, planning, or creative work (18 percent).
For now, computers do an excellent job with very well-defined activities, such as optimizing trucking routes, but humans still need to determine the proper goals, interpret results, or provide commonsense checks for solutions.
Overall, healthcare has a technical potential for automation of about 36 percent, but the potential is lower for health professionals whose daily activities require expertise and direct contact with patients.
One of the biggest technological breakthroughs would come if machines were to develop an understanding of natural language on par with median human performance—that is, if computers gained the ability to recognize the concepts in everyday communication between people.
The actual level will reflect the interplay of the technical potential, the benefits and costs (or the business case), the supply-and-demand dynamics of labor, and various regulatory and social factors related to acceptability.
E-commerce players, for example, compete with traditional retailers by using both physical automation (such as robots in warehouses) and the automation of knowledge work (including algorithms that alert shoppers to items they may want to buy).
The greater challenges are the workforce and organizational changes that leaders will have to put in place as automation upends entire business processes, as well as the culture of organizations, which must learn to view automation as a reliable productivity lever.
Understanding the activities that are most susceptible to automation from a technical perspective could provide a unique opportunity to rethink how workers engage with their jobs and how digital labor platforms can better connect individuals, teams, and projects.6 6.See Aaron De Smet, Susan Lund, and William Schaninger, “Organizing for the future,”
McKinsey Quarterly, January 2016., It could also inspire top managers to think about how many of their own activities could be better and more efficiently executed by machines, freeing up executive time to focus on the core competencies that no robot or algorithm can replace—as yet.
The Future of Jobs and Jobs Training
Automation, robotics, algorithms and artificial intelligence (AI) in recent times have shown they can do equal or sometimes even better work than humans who are dermatologists, insurance claims adjusters, lawyers, seismic testers in oil fields, sports journalists and financial reporters, crew members on guided-missile destroyers, hiring managers, psychological testers, retail salespeople, and border patrol agents.
Moreover, there is growing anxiety that technology developments on the near horizon will crush the jobs of the millions who drive cars and trucks, analyze medical tests and data, perform middle management chores, dispense medicine, trade stocks and evaluate markets, fight on battlefields, perform government functions, and even replace those who program software – that is, the creators of algorithms.
A recent study by labor economists found that “one more robot per thousand workers reduces the employment to population ratio by about 0.18-0.34 percentage points and wages by 0.25-0.5 percent.” When Pew Research Center and Elon University’s Imagining the Internet Center asked experts in 2014 whether AI and robotics would create more jobs than they would destroy, the verdict was evenly split: 48% of the respondents envisioned a future where more jobs are lost than created, while 52% said more jobs would be created than lost.
At the same time, recent IT advances offer new and potentially more widely accessible ways to access education.” Jobholders themselves have internalized this insight: A 2016 Pew Research Center survey, “The State of American Jobs,” found that 87% of workers believe it will be essential for them to get training and develop new job skills throughout their work life in order to keep up with changes in the workplace.
Some 1,408 responded to the following question, sharing their expectations about what is likely to evolve by 2026: In the next 10 years, do you think we will see the emergence of new educational and training programs that can successfully train large numbers of workers in the skills they will need to perform the jobs of the future?
Respondents see a new education and training ecosystem emerging in which some job preparation functions are performed by formal educational institutions in fairly traditional classroom settings, some elements are offered online, some are created by for-profit firms, some are free, some exploit augmented and virtual reality elements and gaming sensibilities, and a lot of real-time learning takes place in formats that job seekers pursue on their own.
focus on nurturing unique human skills that artificial intelligence (AI) and machines seem unable to replicate: Many of these experts discussed in their responses the human talents they believe machines and automation may not be able to duplicate, noting that these should be the skills developed and nurtured by education and training programs to prepare people to work successfully alongside AI.
One such comment came from Simon Gottschalk, a professor in the department of sociology at the University of Nevada, Las Vegas: “The skills necessary at the higher echelons will include especially the ability to efficiently network, manage public relations, display intercultural sensitivity, marketing, and generally what author Dan Goleman would call ‘social’ and ‘emotional’ intelligence.
[This also includes] creativity, and just enough critical thinking to move outside the box.” Another example is the response of Fredric Litto, a professor emeritus of communications and longtime distance-learning expert from the University of São Paulo: “We are now in the transitional stage of employers gradually reducing their prejudice in the hiring of those who studied at a distance, and moving in favor of such ‘graduates’ who, in the workplace, demonstrate greater proactiveness, initiative, discipline, collaborativeness – because they studied online.” Other respondents mentioned traits including leadership, design thinking, “human meta communication,” deliberation, conflict resolution, and the capacity to motivate, mobilize and innovate.
So in short, we can train small numbers of individuals (tens of thousands) per year using today’s community colleges and university systems, but probably not more.” Several respondents argued that job training is not a primary concern at a time when accelerating change in market economies is creating massive economic divides that seem likely to leave many people behind.
Most experts seem to have faith that rapid technological development and a rising wariness of coming impacts of the AI/robotics revolution are going to spur the public, private and governmental actions needed for education and training systems to be adapted to deliver more flexible, open, adaptable, resilient, certifiable and useful lifelong learning.
As automation puts increasing numbers of low- and middle-skill workers out of work, these models will also provide for certifications and training needs to function in an increasingly automated service sector.” Michael Wollowski, an associate professor of computer science at the Rose-Hulman Institute of Technology, commented, “We will definitely see a vast increase in educational and training programs.
Our established systems of job training, primarily community colleges and state universities, will continue to play a crucial role, though catastrophically declining public support for these institutions will raise serious challenges.” David Karger, a professor of computer science at MIT, wrote, “Most of what we now call online learning is little more than glorified textbooks, but the future is very promising.
The more likely enhancement will be to take digital enhancements out into the world – again, breaking down the walls of the classroom and school – to inform and enhance experience.” An anonymous respondent echoed the sentiment of quite a few others who do not think it is possible to advance and enhance online education and training much in the next decade, writing, “These programs have a cost, and too few are willing to sacrifice for these programs.” More such arguments are included in later sections of this report.
There will be a greater need for such systems as the needs for new expertise in the workforce [increase] and the capacity of traditional education systems proves that it is not capable of meeting the need in a cost-effective manner.” The president of a technology LLC wrote, “Training, teaching are all going online, partly because of high costs of campus education.” Richard Adler, distinguished fellow at the Institute for the Future, predicted, “AI, voice-response, telepresence VR and gamification techniques will come together to create powerful new learning environments capable of personalizing and accelerating learning across a broad range of fields.” Ray Schroeder, associate vice chancellor for online learning at the University of Illinois, Springfield, commented, “It is projected that those entering the workforce today will pursue four or five different careers (not just jobs) over their lifetime.
They will further fuel the scaling of learning to reach even more massive online classes.” Fredric Litto, an professor emeritus of communications and longtime distance-learning expert from the University of São Paulo, replied, “There is no field of work that cannot be learned, totally or in great part, in well-organized and administered online programs, either in traditional ‘course’ formats, or in self-directed, independent learning opportunities, supplemented, when appropriate, by face-to-face, hands-on, practice situations.” Tawny Schlieski, research director at Intel and president of the Oregon Story Board, explained, “New technologies of human/computer interaction like augmented and virtual reality offer the possibility of entirely new mechanisms of education.
As these tools evolve over the next decade, the academics we work with expect to see radical change in training and workforce development, which will roll into (although probably against a longer timeline) more traditional institutions of higher learning.” Many respondents said real-world, campus-based higher education will continue to thrive during the next decade.
Some say major universities’ core online course content, developed with all of the new-tech bells and whistles, will be marketed globally and adopted as baseline learning in smaller higher education locales, where online elements from major MOOCs can be optimally paired in hybrid learning with in-person mentoring activities.
… Human bodies in close proximity to other human bodies stimulate real compassion, empathy, vulnerability and social-emotional intelligence.Frank Elavsky Uta Russmann, communications/marketing/sales professor at the FHWien University of Applied Sciences in Vienna, Austria, said, “In the future, more and more jobs will require highly sophisticated people whose skills cannot be trained in ‘mass’ online programs.
Traditional four-year and graduate programs will better prepare people for jobs in the future, as such an education gives people a general understanding and knowledge about their field, and here people learn how to approach new things, ask questions and find answers, deal with new situations, etc.
Many people have gained these skills throughout history without any kind of formal schooling, but with the growing emphasis on virtual and digital mediums of production, education and commerce, people will have less and less exposure to other humans in person and other human perspectives.” Isto Huvila, professor at Uppsala University, replied, “The difference between educating to perform and educating to make the future is the difference between vocational [education] and higher (university) education.
But this does not mean that alternative means and paths of learning and accreditation would not be useful as … complementary to the traditional system that has limitations as well.” Dana Klisanin, psychologist/futurist at Evolutionary Guidance Media RD, wrote, “Educational institutions that succeed will use the tools of social media and game design to grant students’ access to teachers from all over the world and increase their motivation to succeed.
… Online educational programs will influence the credentialing systems of traditional institutions, and online institutions will increasingly offer meet-ups and mingles such that a true hybrid educational approach emerges.” Will training for skills most important in the jobs of the future work well in large-scale settings by 2026?
Functions requiring emotional intelligence, empathy, compassion, and creative judgment and discernment will expand and be increasingly valued in our culture.” Tiffany Shlain, filmmaker and founder of the Webby Awards, wrote, “The skills needed to succeed in today’s world and the future are curiosity, creativity, taking initiative, multi-disciplinary thinking and empathy.
A mindset of persistence and the necessary passion to succeed are also critical.” Louisa Heinrich, founder at Superhuman Limited, commented, “Lateral and system-thinking skills are increasingly critical for success in an ever-changing global landscape, and these will need to be re-prioritised at all levels of education.” An anonymous technologist commented, “Programming and problem solving, learning how to work with artificial intelligence and robotics will become more important, and more and more workers will be replaced by software/hardware-based ‘workers.’ Automation will reduce the need for the current workforce, and the divide between the upper class and the lower class will continue to eat the middle class.” Some who are pessimistic about the future of human work due to advances in capable AI and robotics mocked the current push in the U.S. to train more people in technical skills.
A few people mentioned that young adults need to be taught how to have face-to-face interaction, including one who said they “seem to be sorely lacking in these skills and can only interact with a cellphone or laptop.” Because so many intricacies of the workplace – the human, soft and hard – are learned on the job, respondents said they expect apprenticeships and forms of mentoring will regain value and evolve along with the 21st‑century workplace.
Through evolving technologies (e.g., blockchain), this may provide opportunities for learners to document and frame their own learning pathways.” An instructional designer with 19 years of experience commented, “The pattern I’m seeing is toward individualized learning – almost on the level of tutoring or apprenticeship.
The key to the future will be flexibility and personal motivation to learn and tinker with new things.” As they anticipate the appearance of effective new learning environments and advances in digital accountability systems, many of these experts believe fresh certification programs will be created to attest to workers’ participation in training programs and the mastery of skills.
People with new types of credentialing systems are seen as more qualified than traditional four-year and graduate programs.” Many workplaces place a higher value on real-world work portfolios than they do on a degree or certification, yet their hiring systems – including AI bots programmed to scan resumés – still use the commonly accepted credentials as a basis for interviewing candidates.
software engineering and system administration professional commented, “The reliability of the traditional educational system is already being questioned – in some fields it’s considered common sense that certifications and degrees mean little, and that a portfolio, references, and hands-on interviews are much more important for assessing a candidate’s ability.
I believe that many – not all – areas of instruction should shift to competency-based education in which the outcomes needed are made clear and students are given multiple paths to achieve those outcomes, and they are certified not based on tests and grades but instead on portfolios of their work demonstrating their knowledge.” While the first three themes found among the responses to this canvassing were mostly hopeful about advances in education and training for 21st‑century jobs, a large share of responses from top experts reflect a significant degree of pessimism for various reasons.
Among the other reasons listed by people who do not expect these kinds of transformative advances in job creation and job skill upgrading: Some among the 70% of respondents who are mostly optimistic about the future of training for jobs also echoed one or more of the points above – mentioning these tension points while hoping for the best.
Thomas Claburn, editor-at-large at Information Week, wrote, “I’m skeptical that educational and training programs can keep pace with technology.” Traditional models train people to equate what they do with who they are (i.e., what do you want to be when you grow up) rather than to acquire critical thinking and flexible skills and attitudes that fit a rapidly changing world.Pamela Rutledge Andrew Walls, managing vice president at Gartner, wrote, “Barring a neuroscience advance that enables us to embed knowledge and skills directly into brain tissue and muscle formation, there will be no quantum leap in our ability to ‘up-skill’ people.
Remy Cross, assistant professor of sociology, Webster University, commented, “Lacking a significant breakthrough in machine learning that could lead to further breakthroughs in adaptive responses by a fully online system, it is too hard to adequately instruct large numbers of people in the kinds of soft skills that are anticipated as being in most demand.
… While there have been generational gains in the developments of online communities, a large-scale educational experience (either MOOC or on-demand broadcasts) will not be able to duplicate that.” Stowe Boyd, managing director of Another Voice and a well-known thinker on work futures, discussed the intangibles of preparing humans to partner with AI and bot systems: “While we may see the creation and rollout of new training programs,” he observed, “it’s unclear whether they will be able to retrain those displaced from traditional sorts of work to fit into the workforce of the near future.
And employers may play less of a role, especially as AI- and bot-augmented independent contracting may be the best path for many, rather than ‘a job.’ Homesteading in exurbia may be the answer for many, with ‘forty acres and a bot’ as a political campaign slogan of 2024.” Luis Miron, a distinguished university professor and director of the Institute for Quality and Equity in Education at Loyola University in New Orleans, wrote, “Bluntly speaking, I have little confidence in the educational sector, K-16, having the capacity and vision to offer high-quality online educational programs capable of transforming the training needs of the wider society.
… Successful education models will begin developing ‘mixed methods’ to leverage technology with traditional delivery and rewrite certification processes with practice-relevant standards.” Justin Reich, executive director at the MIT Teaching Systems Lab, observed, “There will continue to be for-profit actors in the sector, and while some may offer choice and opportunity for students, many others will be exploitative, with a great[er] focus on extracting federal grants and burdening students with debt than actually educating students and creating new opportunities.” John Paine, a business analyst, commented, “The competing desires 1) to make educational activity available to all and 2) to monetize the bejeezus out of anything related to the internet will limit the effectiveness of any online learning systems in a more widespread context.” danah boyd, founder of Data
Whether the traditional programs or new programs will be better at teaching adaptive learning remains to be seen.” Cory Salveson, learning systems and analytics lead at RSM US, responded, “The nature of work today, and in future, is such that if people want to keep increasingly scarce well-paying jobs, they will need to educate themselves in an ongoing manner for their whole lives.” Some of these experts say those who aren’t motivated to continue to learn and grow will be left behind.
So, not only does the self-direction factor pose a problem for teaching at scale, the fact that a high degree of self-direction may be required for successful completion of coursework towards the new workforce means that existing structures of inequality will be replicated in the future if we rely on these large-scale programs.” Among the 30% of respondents who said they did not think things would turn out well in the future were those who said the trajectory of technology will overwhelm labor markets, killing more jobs than it creates.
They foresee a society where AI programs and machines do most of the work and raise questions about people’s sense of identity, the socio-economic divisions that already distress them, their ability to pay for basic needs, their ability to use the growing amount of “leisure time” constructively and the impact of all of this on economic systems.
The current automation is based on ‘general purpose’ technologies – machine learning, Turing complete computers, a universal network architecture that is equally optimized for all applications – and there’s good reason to believe that this will be more disruptive, and create fewer new jobs, than those that came before.” Glenn Ricart, Internet Hall of Fame member and founder and chief technology officer of US Ignite, said, “Up to the present time, automation largely has been replacing physical drudgery and repetitive motion – things that can and should improve the quality of people’s work lives.
How will we cope with a workforce that is simply irrelevant?” The question isn’t how to train people for nonexistent jobs, it’s how to share the wealth in a world where we don’t need most people to work.Nathaniel Borenstein Nathaniel Borenstein, chief scientist at Mimecast, replied, “I challenge the premise of this question [that humans will have to be trained for future jobs].
There is also the massive sociological economic impact of general automation and AI that must be addressed to redistribute wealth and focus life skills at lifelong learning.” Tom Sommerville, agile coach, wrote, “Our greatest economic challenges over the next decade will be climate change and the wholesale loss of most jobs to automation.
There will also be a parallel call for benefits, professional development, and compensation that smooths out the rough patches in this on-demand labor life, but such efforts will lag behind the exploitation of said labor because big business has more resources and big tech moves too fast for human-scale responses of accountability and responsibility.
As a society we need to take advantage of that, and nurture our natural hunger for knowledge and productive work while respecting and encouraging our diversity, a fundamental balancing feature of all nature, human and otherwise.” Jeff Jarvis, professor at the City University of New York Graduate School of Journalism, wrote, “At a roundtable on the future convened by Union Square Ventures a few years ago, I heard this economic goal presented: We need to see the marginal cost of teaching another student fall to zero to see true innovation come to education, allowing change to occur outside the tax-based (and thus safe) confines of public education.
But we will likely see a radical economic disruption in education – using new tools and means to learn and certify learning – and that is the way by which we will manage to train many more people in many new skills.” Cory Doctorow, activist-in-residence at MIT Media Lab and co-owner of Boing Boing (boingboing.net), responded, “There is, for the immediate and medium term, a huge shortage of IT talent, of course – especially security researchers and professionals.
An earlier and more enduring focus on stats and statistical literacy – which can readily be taught using current affairs, for example, analyzing the poll numbers from elections, the claims made by climate change scientists, or even the excellent oral arguments in the Supreme Court Texas abortion law case – would impart skills that transferred well into IT, programming and, especially, security.” Amy Webb, futurist and CEO at the Future Today Institute, commented, “Gill Pratt, a former program manager of the Defense Advanced Research Projects Agency (DARPA), recently warned of a Cambrian Explosion of robotics.
If there are unanticipated external events – environmental disasters, new pandemics and the like – that could devastate a country’s economy and significantly impact its workforce, which might catalyze the development of online learning opportunities.” Mike Roberts, Internet Hall of Fame member and first president and CEO of the Internet Corporation for Assigned Names and Numbers (ICANN), responded, “MOOCs and related efforts are in their infancy, so ‘yes,’ there will [be] considerable expansion as more is learned about what works and what doesn’t work.
And most importantly, we do not mix education with religion – never.’” Anil Dash, entrepreneur, technologist, and advocate @AnilDash, predicted, “These credentials will start to become widespread, but acceptance and quality of the training programs will map to the existing systemic biases that inform current educational and career programs.” Henning Schulzrinne, Internet Hall of Fame member and professor at Columbia University, wrote, “Training programs have had the problem that short-duration generic programs are often not very effective except as a way to incrementally add very specific skills (‘learn how to operate the new industry-specific tool X in a week’) to the existing repertoire.
The MOOC-style programs have shown themselves to be most effective for this ‘delta’ learning for practicing professionals, not turning a high school graduate into somebody who can compete with a college graduate.” Jamais Cascio, distinguished fellow at the Institute for the Future, responded, “We will certainly see attempts to devise training and education to match workers to new jobs, but for the most part they’re likely to fall victim to two related problems.
As learning systems improve, we will soon (if we’re not already) be at a point where adaptive algorithms can learn new jobs faster than humans.” Kate Crawford, a well-known internet researcher studying how people engage with networked technologies, wrote, “We clearly need new educational and training programs to address the deepening precarity of the labor market.
K-12 teachers are constantly pulled from class time with students for professional development or during class are required to take attendance, [complete] grade assessments, fill out grade checks, practice fire drills – all degrading quality teaching time.
Large school systems can’t scale major improvements in current systems without leveraging the tools that society and industry are using to transform their practice.” Barry Chudakov, founder and principal at Sertain Research and StreamFuzion Corp., replied: “One serious drawback to fast-tracking needed educational and training programs: the people who are creating the jobs of the future have so little time to reflect and gain perspective on the people they will need – and how adding these people to their corporate culture changes that culture.
These entrepreneurs are so busy building technology infrastructures, filing patents, testing beta incarnations of ideas and processes – not to mention navigating the thicket of regulations and restrictions that surround many emerging technologies and industries – that they simply don’t have time to look around and see the implications of the changes their companies are creating.
Because all human processes and activities can now be quantified, and there is considerable exploration and technology development in the application of quantification to everything from our sleep patterns and shopping habits to our emotions and online behaviors, many new and important business models are emerging from quantification and the learning algorithms that drive it.
Lastly, we don’t need large-scale training of workers – we need real education (not job-focused) and opportunities for people to pursue diverse pathways for career development and lifelong learning.” Patrick Tucker, technology editor at Defense One and author of “The Naked Future,” observed: “Online education offers the opportunity to gather data on student performance continuously, or telemetrically.
… What telemetric education offers is the opportunity to continuously and constantly evaluate a student to gain a much more comprehensive understanding of ability, retention of information, even how other behaviors and factors such as time of day, other calendar items, nutrition, amount of time on Pokemon Go, influence learning.
That opportunity doesn’t come easily in a crowded classroom – especially not for women or minority students, many of whom feel that if they ask the wrong question or display ignorance, they’ll confirm some unflattering, broadly held perception about their social group.” David Golumbia, associate professor of digital studies at Virginia Commonwealth University, commented, “As an educator, I am completely unconvinced by the current rhetoric that says our educational system is unable to meet the needs of current or future workforces.
Four fundamentals of workplace automation
This research has examined the economic potential of disruptive technologies that can automate physical work (for example, advanced robotics, 3-D printing, and autonomous vehicles) as well as those that can automate knowledge work requiring intellectual effort and the ability to interact with others (for example, various types of artificial intelligence, machine learning, and deep learning).
Rather, certain activities are more likely to be automated, requiring entire business processes to be transformed, and jobs performed by people to be redefined, much like the bank teller’s job was redefined with the advent of ATMs.
Although we often think of automation primarily affecting low-skill, low-wage roles, we discovered that even the highest-paid occupations in the economy, such as financial managers, physicians, and senior executives, including CEOs, have a significant amount of activity that can be automated.
The organizational and leadership implications are enormous: leaders from the C-suite to the front line will need to redefine jobs and processes so that their organizations can take advantage of the automation potential that is distributed across them.
When we modeled the potential of automation to transform business processes across several industries, we found that the benefits (ranging from increased output to higher quality and improved reliability, as well as the potential to perform some tasks at superhuman levels) typically are between three and ten times the cost.
What follows here are four interim findings elaborating on the core insight that the road ahead is less about automating individual jobs wholesale, than it is about automating the activities within occupations and redefining roles and processes.
Amazon’s fleet of Kiva robots is equipped with automation technologies that plan, navigate, and coordinate among individual robots to fulfill warehouse orders roughly four times faster than the company’s previous system.
Similarly, in a world where the diagnosis of many health issues could be effectively automated, an emergency room could combine triage and diagnosis and leave doctors to focus on the most acute or unusual cases while improving accuracy for the most common issues.
Particularly in the highest-paid occupations, machines can augment human capabilities to a high degree, and amplify the value of expertise by increasing an individual’s work capacity and freeing the employee to focus on work of higher value.
Similarly, sales organizations could use automation to generate leads and identify more likely opportunities for cross-selling and upselling, increasing the time frontline salespeople have for interacting with customers and improving the quality of offers.
addition to analyzing the relationship between automatability and compensation levels, the inclusion of wages allows us to compare the potential costs to implement automation with labor costs, which inherently reflect supply, demand, and elasticity dynamics.
Our work to date suggests that a significant percentage of the activities performed by even those in the highest-paid occupations (for example, financial planners, physicians, and senior executives) can be automated by adapting current technology.7 7. Using
a linear model, we find the correlation between wages and automatability (the percentage of time spent on activities that can be automated by adapting currently demonstrated technology) in the US economy to be significant (p-value <
These interim findings, emphasizing the clarity brought by looking at automation through the lens of work activities as opposed to jobs, are in no way intended to diminish the pressing challenges and risks that must be understood and managed.
Clearly, organizations and governments will need new ways of mitigating the human costs, including job losses and economic inequality, associated with the dislocation that takes place as companies separate activities that can be automated from the individuals who currently perform them.
(The financial-services sector, where technology can readily manage straight-through transactions and trade processing, is a prime example.) On the other hand, businesses that are capital or hardware intensive, or constrained by heavy safety regulation, will likely see longer lags between initial investment and eventual benefits, and their pace of automation may be slower as a result.
Making such determinations will require executives to build their understanding of the economics of automation, the trade-offs between augmenting versus replacing different types of activities with intelligent machines, and the implications for human skill development in their organizations.
- On Wednesday, June 19, 2019
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Register for the workshop: Originally released on September 25, 2014. Join the crew at TechWiseTV for a rare, behind-the-scenes look at the Cisco Technical Assistance..
Democrats All Agree with Trump’s Immigration Plan! 😆
It's just too funny. They all agreed with it before they knew it was his plan. ⚠ Order your shirts from my online store here: - Available in t-shirt,..
Machine learning powering the workforce: Quick Access in Google Drive (Google Cloud Next '17)
Machine learning powers many of Google's products and services, because effiency, innovation and advanced capabilities are as important to our team as it is to yours. In this video, Mike Procopio...