Blog Post

The 5 Obstacles in the Way of Automation

These 5 Challenges Are What’s Keeping Us From Advancing Automation

Automation has unrivaled potential to change our global workforce forever. Already, millions of workers (and some entire industries) have lost their jobs due to basic types of automation, like assembly line robots or search algorithms. In the next 13 years or so, we may lose up to 800 million more.

We’re making astounding progress in the realm of machine learning, AI, and automation, to the point where some technological optimists are already making plans for a fully jobless future. But at the same time, we’re years to decades away from automating even some of the more basic professional jobs.

Why? Because there are fundamental limitations preventing automation from moving forward.

Why Aren’t We Automating Everything?

So what’s really standing in the way of us making more progress in the automation space?

1. Job complexity. The most obvious stopping point is the sheer complexity of certain types of jobs. Basic tasks, which always follow the same routine, and have clear answers to every question that arises, are easy to automate with a basic algorithm. But jobs that require more ambiguous types of decision-making, such as incorporating human emotions and indefinable instincts, are much more difficult to tackle. The problem grows even more complex when human interactions are required.

2. Processing power. Machines need more data than humans do to “learn” a task. And we’re not just talking slight differences here; they need hundreds of thousands of times more raw data than humans need. Image and video recognition programs need to be fed millions of examples before they truly understand their subjects, and that eats up a ton of processing power. Accordingly, advanced machine learning algorithms (and the capacity for automation) require enormous servers, which are impractical for ground-level applications.

3. Consumer adoption and trust. Automated tools are already available for millions of tasks, from sending out batches of SMS texts to regulating pharmaceuticals. But consumers aren’t necessarily ready to adopt them. For example, many modern consumers hate the idea of riding in a self-driving car, because it means surrendering control to a machine they don’t fully trust. If customers aren’t willing to buy or support a new type of automation, companies and innovators aren’t going to be as interested in pursuing it.

4. Specialization vs. generalization. Today, we have the technology to create AI-driven, automated solutions for all kinds of problems—but very specific ones. Specialized AI can be custom-made to “understand” a certain topic, or behave in exactly the right way to make one type of decision, but creating a generalized AI, which can make more complex decisions and be applied to many different disciplines, is much harder. We’re decades away from seeing the rise of a truly successful general AI, which means every form of automation we’ll have for the next few years will be hyper-focused on one (or a few related) tasks.

5. Legal regulations. For some types of automation, legal regulations can also be a problem. For example, autonomous driving algorithms have come a long way, but industry moguls and regulators are still concerned about how those programs could be applied to the trucking industry. For roles that pose an inherent risk to human life or health, lawmakers are taking automation seriously.

How Fast Can We Grow?

Despite these challenges, experts in machine learning, innovative engineers, and visionary entrepreneurs are all competing to see who can come up with the next world-changing device or program. Each year, we see rise to new AI breakthroughs and gadgets in almost every industry, making iterative progress toward what could really be a jobless future.

Obstacles related to human concerns and intervention, such as overcoming legal, regulatory, and consumer adoption barriers, are the biggest impediments here. As for sheer processing power, and coming up with solutions for the most difficult jobs to automate, it’s hard to imagine we’re more than a few years away from a breakthrough—at least with today’s machine learning pace.

In the meantime, we all can take advantage of the automated tools currently within our grasp, and make our jobs a little easier—long before they have a chance of being replaced.

More Stories By Larry Alton

Larry Alton is an independent business consultant specializing in social media trends, business, and entrepreneurship. Follow him on Twitter and LinkedIn.

Latest Stories
When talking IoT we often focus on the devices, the sensors, the hardware itself. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). When we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing. IoT is not about the devices, its about the data consumed and generated. The devices are tools, mechanisms, conduits. This paper discusses the considerations when dealing with the...
SYS-CON Events announced today that IoT Global Network has been named “Media Sponsor” of SYS-CON's @ThingsExpo, which will take place on June 6–8, 2017, at the Javits Center in New York City, NY. The IoT Global Network is a platform where you can connect with industry experts and network across the IoT community to build the successful IoT business of the future.
DXWorldEXPO LLC announced today that Kevin Jackson joined the faculty of CloudEXPO's "10-Year Anniversary Event" which will take place on November 11-13, 2018 in New York City. Kevin L. Jackson is a globally recognized cloud computing expert and Founder/Author of the award winning "Cloud Musings" blog. Mr. Jackson has also been recognized as a "Top 100 Cybersecurity Influencer and Brand" by Onalytica (2015), a Huffington Post "Top 100 Cloud Computing Experts on Twitter" (2013) and a "Top 50 C...
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
To Really Work for Enterprises, MultiCloud Adoption Requires Far Better and Inclusive Cloud Monitoring and Cost Management … But How? Overwhelmingly, even as enterprises have adopted cloud computing and are expanding to multi-cloud computing, IT leaders remain concerned about how to monitor, manage and control costs across hybrid and multi-cloud deployments. It’s clear that traditional IT monitoring and management approaches, designed after all for on-premises data centers, are falling short in ...
When applications are hosted on servers, they produce immense quantities of logging data. Quality engineers should verify that apps are producing log data that is existent, correct, consumable, and complete. Otherwise, apps in production are not easily monitored, have issues that are difficult to detect, and cannot be corrected quickly. Tom Chavez presents the four steps that quality engineers should include in every test plan for apps that produce log output or other machine data. Learn the ste...
Evan Kirstel is an internationally recognized thought leader and social media influencer in IoT (#1 in 2017), Cloud, Data Security (2016), Health Tech (#9 in 2017), Digital Health (#6 in 2016), B2B Marketing (#5 in 2015), AI, Smart Home, Digital (2017), IIoT (#1 in 2017) and Telecom/Wireless/5G. His connections are a "Who's Who" in these technologies, He is in the top 10 most mentioned/re-tweeted by CMOs and CIOs (2016) and have been recently named 5th most influential B2B marketeer in the US. H...
The best way to leverage your Cloud Expo presence as a sponsor and exhibitor is to plan your news announcements around our events. The press covering Cloud Expo and @ThingsExpo will have access to these releases and will amplify your news announcements. More than two dozen Cloud companies either set deals at our shows or have announced their mergers and acquisitions at Cloud Expo. Product announcements during our show provide your company with the most reach through our targeted audiences.
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by ...
When building large, cloud-based applications that operate at a high scale, it's important to maintain a high availability and resilience to failures. In order to do that, you must be tolerant of failures, even in light of failures in other areas of your application. "Fly two mistakes high" is an old adage in the radio control airplane hobby. It means, fly high enough so that if you make a mistake, you can continue flying with room to still make mistakes. In his session at 18th Cloud Expo, Le...
CloudEXPO New York 2018, colocated with DXWorldEXPO New York 2018 will be held November 11-13, 2018, in New York City and will bring together Cloud Computing, FinTech and Blockchain, Digital Transformation, Big Data, Internet of Things, DevOps, AI, Machine Learning and WebRTC to one location.
Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settlement products to hedge funds and investment banks. After, he co-founded a revenue cycle management company where he learned about Bitcoin and eventually Ethereal. Andrew's role at ConsenSys Enterprise is a mul...
DXWorldEXPO | CloudEXPO are the world's most influential, independent events where Cloud Computing was coined and where technology buyers and vendors meet to experience and discuss the big picture of Digital Transformation and all of the strategies, tactics, and tools they need to realize their goals. Sponsors of DXWorldEXPO | CloudEXPO benefit from unmatched branding, profile building and lead generation opportunities.
Daniel Jones is CTO of EngineerBetter, helping enterprises deliver value faster. Previously he was an IT consultant, indie video games developer, head of web development in the finance sector, and an award-winning martial artist. Continuous Delivery makes it possible to exploit findings of cognitive psychology and neuroscience to increase the productivity and happiness of our teams.
Digital transformation has increased the pace of business creating a productivity divide between the technology haves and have nots. Managing financial information on spreadsheets and piecing together insight from numerous disconnected systems is no longer an option. Rapid market changes and aggressive competition are motivating business leaders to reevaluate legacy technology investments in search of modern technologies to achieve greater agility, reduced costs and organizational efficiencies. ...