Companies are using AI to screen candidates now

Human job recruiters can only physically juggle so many candidates at once. HireVue, a company with a “video interview intelligence platform,” wants to make that easier by using artificial intelligence to do the heavy lifting for you and screen multiple candidates at once.

Candidates can use HireVue’s mobile or desktop app to set up a video interview with an employer and record answers to interview questions at their convenience.

When I tested the demo on my smartphone, I was asked to answer what my ideal career would be. It was slightly awkward seeing my own face staring back at me, but HireVue gives you an unlimited number of chances until you can record with saying “ummm.” So far, it seems like any normal video application.

Then the A.I. kicks in.

Using voice and face recognition software, HireVue lets employers compare a candidate’s word choice, tone, and facial movements with the body language and vocabularies of their best hires. The algorithm can analyze all of these candidates’ responses and rank them, so that recruiters can spend more time looking at the top performing answers.

HireVue’s AI can judge your tone and vocabulary for employers

HireVue said it doesn’t want to replace recruiters; instead, it wants to make the job interview process more efficient. At its best, it can serve as an initial screener before job seekers can get to the promised land of interviewing with a human.

As part of its positive testimonies, HireVue said SHIPT, a grocery delivery service, tripled its recruitment rate as recruiters no longer had to deal with technical difficulties and coordinating video times. Goldman Sachs, Under Armour, Unilever, and Vodafone are also among the companies that have used the platform.

By having each candidate answer the same questions, HireVue said it makes its process more structured, which can help eliminate biases.

“Structured interviews are much better and subject to less bias than unstructured interviews,” HireVue founder Mark Newman told Fast Company. “But many hiring managers still inject personal bias into structured interviews due to human nature.”

In other words, the algorithm is only as objective as the human minds that guide it. So if the employer’s ideal candidate is already biased against certain characteristics, HireVue’s platform would only embed these biases further, potentially making discriminatory practices a part of the process. Human recruiters would need to recognize their own personal biases before they could stop feeding them into HireVue. It’s one more reminder that behind each robot lies a human who engineered it.

Source: theladders.com-Companies are using AI to screen candidates now

Advertisements

Robots will not lead to fewer jobs – but the hollowing out of the middle class

Moravec’s paradox says that robots find difficult things easy and easy things difficult, which might lead to humans taking lower-paid manual work. Photograph: Fabian Bimmer/Reuters

Throughout modern history there has been a recurrent fear that jobs will be destroyed by technology. Everybody knows the story of the Luddites, bands of workers who smashed up machinery in the textile industry in the second decade of the 19th century.

The Luddites were wrong. There has been wave after wave of technological advance since the first Industrial Revolution, and yet more people are working than ever before. Jobs have certainly been destroyed. Banks, for example, no longer employ clerks to log every transaction in ledgers with quill pens. At this time of year, 150 years ago, the fields would have been full of people with scythes and pitchforks bringing in the harvest. That work is now done by motorised harvesters.

The reason new technology has not been the cause of mass unemployment is that new kit will only be used when it makes the productive process more profitable. Higher productivity frees up the resources to buy other goods and services. The rural workers that Thomas Hardy described in Tess of the D’Urbervilles found work in factories and offices. What’s more, it was better paid work, and so the upshot was an increase in living standards.

Similarly, the age of robots will lead to more jobs. Kallum Pickering, analyst with Berenberg, says there is a big hole in the argument that artificial intelligence (AI) will lead to vast numbers of workers joining the dole queue.

“Producers will only automate if doing so is profitable. For profit to occur, producers need a market to sell to in the first place. Keeping this in mind helps to highlight the critical flaw of the argument: if robots replaced all workers, thereby creating mass unemployment, to whom would the producers sell? Because demand is infinite whereas supply is scarce, the displaced workers always have the opportunity to find fresh employment to produce something that satisfies demand elsewhere.”

That, though, is not the end of the story. Robots will create more jobs, but what if these jobs are less good and less well paid than the jobs that automation kills off? Perhaps the weak wage growth of recent years is telling us something, namely that technology is hollowing out the middle class and creating a bifurcated economy in which a small number of very rich people employ armies of poor people to cater for their every whim.

This is certainly a much more likely threat than mass job destruction. What’s more, it fits with the history of the recent past, the theory of automation, and recent trends in the labour market.

Christian Siegel from the University of Kent’s school of economics has found that labour markets in the advanced countries of the west started to polarise as far back as the 1950s as they became more dominated by the service sector. Growth was strong during this period, but the job creation tended to be either at the top end of the pay scale or at the bottom end, while employment opportunities in traditional middle-class sectors of the economy declined. The arrival of IT in the 1980s merely accentuated a process already underway.

Robots are likely to result in a further hollowing out of middle-class jobs, and the reason is something known as Moravec’s paradox. This was a discovery by AI experts in the 1980s that robots find the difficult things easy and the easy things difficult. Hans Moravec, one of the researchers, said: “It is comparatively easy to make computers exhibit adult-level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.” Put another way, if you wanted to beat Magnus Carlsen, the world chess champion, you would choose a computer. If you wanted to clean the chess pieces after the game, you would choose a human being.

Dhaval Joshi, economist at BCA research, believes Moravec’s paradox will have a big impact on the labour market. He considers two scenarios for a stylised economy with three jobs: a high-income innovator, a middle-income manufacturer and a low-income animal tender.

In scenario one, the innovator comes up with a machine that dispenses with the need for the animal tender. The machine is more productive than the animal tender and so the innovator uses his extra income to buy manufactured goods. That provides the opportunity for the animal tender to retrain as a more highly paid manufacturer.

In scenario two, the innovator invents a machine that makes the middle-income manufacturer obsolete. Again, the innovator has more disposable income and uses it to purchase animal tending services. The middle-income manufacturer now has to make a living as a more lowly paid animal tender.

In the modern economy, the jobs that are prized tend to be the ones that involve skills such as logic. Those that are less well-rewarded tend to involve mobility and perception. Robots find logic easy but mobility and perception difficult.

“It follows,” says Joshi, “that the jobs that AI can easily replicate and replace are those that require recently evolved skills like logic and algebra. They tend to be middle-income jobs. Conversely, the jobs that AI cannot easily replicate are those that rely on the deeply evolved skills like mobility and perception. They tend to be lower-income jobs. Hence, the current wave of technological progress is following scenario 2. AI is hollowing out middle-income jobs and creating lots of lower-income jobs.”

Recent developments in the labour market suggest this process is already well under way. In both Britain and the US, economists have been trying to explain why it has been possible for jobs to be created without wage inflation picking up. Britain has an unemployment rate of 4.4% but average earnings are rising by just 2.1%. Something similar has happened in the US. The relationship between unemployment and pay – the Phillips curve – appears to have broken down.

But things become a bit easier to understand if the former analysts and machine operators are now being employed as dog walkers and waiting staff. Employment in total might be going up, but with higher-paid jobs being replaced by lower-paid jobs. Is there any hard evidence for this?

Well, Joshi says it is worth looking at the employment data for the US, which tends to be more granular than in Europe. For many years in America, the fastest-growing employment subsector has been food services and drinking places: bar tenders and waiters, in other words.

AI is still in its infancy, so the assumption has to be that this process has a lot further to run. Wage inflation is going to remain weak by historic standards, leading to debt-fuelled consumption with all its attendant risks. Interest rates will remain low. Inequality, without a sustained attempt at the redistribution of income, wealth and opportunity, will increase. And so will social tension and political discontent.

Source: The Guardian-Robots will not lead to fewer jobs – but the hollowing out of the middle class

1 in 4 would trust robots for insurance advice

 

Men were found to be more accepting of insurance advice given by robots.

Be it car, pet, home or life insurance, one in four UK adults would trust an automated robotic service to provide insurance advice.

The CenturyLink EMEA survey of over 1,200 adults in the UK also revealed what type of advice consumers would feel comfortable in taking from a robot. Nearly one in five (19%) would trust robotic guidance on how to claim for something, for example a car accident or contents theft.

A further 18% would seek robotic advice as to which insurance provider would give them the best offer for their needs, but only 15% would trust robotic technology to manage and send relevant documents required to set up a policy, such as passports and proof of identification documents.

Car insurance came out top as the insurance policy that consumers most trusted to be led by robotic services (19%), beating pet insurance (12%), holiday insurance (13%) and phone insurance (9%). This could point towards the frequency that people renew insurance policies for certain products, or could expose consumers views on how often they might need to interact with, or claim for something, with a specific type of policy.

“It is interesting to see the growing trust that consumers have in robotic advice for insurance matters, particularly that almost a fifth (19%) would trust automated advice just as much as they would from a human. Businesses must take note of the views of the consumers and adapt their strategies to reflect this shift in the way buyers like to receive their services,” said Jay Hibbin, director of insurance and financial services CenturyLink EMEA.

Interestingly, the research findings also revealed a generational split in views towards robotic advice. Those between the ages of 16 and 34 placed most trust in automated services (33%), whilst only 21% of those between the ages of 45 and 55+ would be happy with this form of interaction. Men are also more accepting of this kind of advice, with almost a third (30%) placing trust in insurance robots, as opposed to only 23% of women.

“The insurance industry is going through a rapid period of change and businesses are having to think about how they streamline services in order to survive and thrive. Time-poor IT teams at insurance enterprises have been, perhaps unfairly, described as “anti-innovation” and “risk averse” but now is the time to shake off these stereotypes,” said Mr Hibbin.

“By working on, and investing, in digital transformation strategies, IT leaders that can meet the new demands, and expectations, of consumers. If insurers are to stay competitive and keep up with the challengers that are nipping at their heels, they must look to how they implement and maintain technologies such as these to provide services fit for the future”.

Source: cbronline-1 in 4 would trust robots for insurance advice

Do You Know Your Business Like the Back of Your Hand?

If you asked both an executive and an associate what their company does you might receive surprisingly different answers. Executives, understandably, often have limited knowledge of the every-day business processes, (for example it is not a CEO’s job to know how many reports are run per day), but this gap in knowledge could be costing your business.

The Key Assessment Questions

In order to boost your understanding of company operations, the following questions must be considered:

  • What processes exist?
  • How are they executed?
  • What problems exist? (I.e. where are mistakes made?)
  • What causes the greatest client satisfaction/dissatisfaction?
  • What causes the greatest employee satisfaction/dissatisfaction?
  • Which activities require the greatest amount of financial investment?
  • Where is that investment beneficial and/or wasted?

These questions are the cornerstones to process improvement. Without adequate insight on the current process state, one cannot identify what needs changing and how to implement these changes. Creating a fluid and robust global process is the first step in approaching the Future of Work. Only once the workflow has been transformed and optimized should automation be applied.

The Value of Process Maps

The creation of “As-Is” process maps is incredibly valuable in a business assessment. The maps should be captured with the assistance of employees who perform the tasks day-in, day-out. This will highlight how the work is actually being done, as opposed to how executives think it is being done. No one designs bad processes, but individual and unstructured practises develop easily due to changing client demands, updated system architecture and associates finding ways to reduce the time-consuming and tedious parts of their work. The identified workarounds can then be pin-pointed and addressed in process improvement initiatives.

Process Mapping Must Be Designed to a key-stroke and click level

When the automation is being considered, process maps must be designed to key-stroke and click level. Robotic Process Automation (RPA) requires very granular instructions and it is important to demonstrate that the work is entirely rules-based and structured. Having detailed process maps will greatly assist an RPA developer and will lead to quicker configuration and implementation.

The Legacy of BPO

Over the last three decades Business Process Outsourcing (BPO) established itself as the solution for managing business costs. Repetitive and transactional tasks were sent abroad to locations where resources were plentiful and work could be done for a fraction of the in-house cost. This was the best solution at the time, but it has often led to disconnected global processes. Companies have had to sacrifice some control over the process and human workers have become the integration point for technology. This means that employees are being held prisoner by systems that cannot perform effectively and the business is driven by systems instead of by processes and people.

As technology has progressed, BPO solutions have stagnated. Eventually we will run out of cheaper offshore options, yet many businesses have not advanced much beyond this model and many industries are lagging behind in leveraging new innovations. As a result, companies are not making the most of their human workforce. With the ability to think critically, people are our great problem solvers. Their skill set could be offering businesses far greater benefits if they were placed in less manual and tedious roles.

One company that was prepared to innovate its operations was the communications company BT. Fifteen years ago they undertook a £15 million automation initiative with the aim of examining all existing systems and linking them together into one seamless workflow. Providing the integration between systems is truly what RPA was built for and in harnessing this new technology, BT has continued its development as one of the leading global communications companies and secured a strong foundation of processes for further Future of Work technologies.

Summary

Insight is invaluable to businesses and can inspire process improvement and transformation. It is important to assess exactly what occurs in a process rather than what is expected to occur, because standard operating procedures are easily adaptable by employees.

Additionally, modern automation technology is now competitive in both price and functionality. By transforming processes for digital automation, people are freed to focus on the value-added tasks that are more stimulating and rewarding. In turn, companies will see higher levels of job satisfaction and employee retention.

Source: symphony-Do You Know Your Business Like the Back of Your Hand?

Top RPA Conversations So Far

Earlier this year, we made several interesting predictions as to what would dominate the conversation throughout 2017 in the automation landscape as part of a preview for the year in RPA. After consulting with industry thought-leaders, analysts, and RPA specialists, we zeroed-in on a handful of critical topics poised to drive important discussions about RPA trends and developments. As we pass the midpoint of the year, we thought it would be interesting to revisit our predictions and determine which conversations have not only been taking place, but have also proved to be critical talking points for those within the automation industry.

Why is this look back to the beginning of 2017 in terms of automation so important? A 2016 study from the industry research firm Gartner suggested the demand for RPA tools is growing quickly…”at about 20 percent to 30 percent each quarter.” This growth was projected to continue into 2017 and thus far industry analysts believe it has, at least through Q1 and Q2 of this year.

With these statistics and figures in mind, let’s take a moment to check the pulse of the automation industry thus far in 2017 by considering which predictions and projections have evolved to be critical conversations in RPA.

RPA deployment will increase across new industries

At the outset of 2017, RPA adoption patterns were poised to experience a significant shift as companies in new and emerging industries discovered the power of automation solutions to enhance their business operations. While the adoption of automation technologies has functioned in somewhat of an opportunistic manner by early adopter companies, wider adoption moments have come to the forefront in such industries as healthcare, insurance, banking, manufacturing, and retail. This also dovetails with industries that have already experienced the benefits of RPA increasing their deployments into the front-office and other customer-facing tasks, actions which have yet to be fully realized by many companies.

In a 2016 report that surveyed the adoption of eight new technologies — including robotics and automation — by the professional services firm Deloitte suggested that:

More companies are increasing investments in these technologies. New technology investments over $1 million have increased…[and some companies are planning to] spend at least $100 million on new technologies over the next two years.

Rather than just being a way for companies to streamline their business operations, RPA and other automation platforms are transitioning from a luxury to a necessity. This conversation has not only persisted as the year progressed, but the drumbeat for automation platforms as a key aspect of any given company’s operation strategy has only increased as global economies and industries become more and more connected.

Automation will replace more tasks, not actual jobs

The emergence and proliferation of automation has caused a certain degree of panic over the possibility these technologies could replace the need for human employees in the workplace. Especially as automation moves from the back-office to more customer-facing tasks, customer relations-related areas such as call centers and other customer service platforms have suddenly become the subject of how and when automation could render these functions less necessary from a manual intervention standpoint. However, as we’ve moved through 2017, this concern has continually been minimized be the actuality of automation deployment.

Automation certainly has the ability to replace certain tasks or remove human personnel from specific department or business moments, especially those that are tedious, repetitive, and time-consuming: in fact, that’s what it is meant to do. However, this doesn’t mean the entire workforce will be replaced by robots. In fact, a 2017 publication by the McKinsey Global Institute suggests that:

The right level of detail at which to analyze the potential impact of automation is that of individual activities rather than entire occupations. Given currently demonstrated technologies, very few occupations—less than 5 percent—are candidates for full automation. However, almost every occupation has partial automation potential.

This kind of automation paints a hopeful picture for the future, one where humans and automation work side by side, which is the critical point of this conversation: debunking the myth RPA will essentially replace all methods of human intervention. In point of actual fact, RPA and human personnel will work in conjunction with each other which will allow human employees to focus on higher-level tasks that are meaningful and interesting, thus creating a space for automation to work through more repetitive, high volume tasks.

AI and machine learning will advance RPA

It has long been discussed how intelligent technologies like artificial intelligence, cognitive computing, and machine learning are expected to develop in the coming years and decades. In addition, a critical element of discussion within the automation landscape is how these technological developments will integrate and bolster automation functionality.

In a recent discussion with Forbes, Ash Ashutosh, the founder and CEO of Actifio, predicted that:

Just as most companies evolved to include cloud capabilities and features, 2017 will bring machine learning to almost every aspect of IT…[these technologies] will usher in a new era of data understanding and analysis.

While this is certainly a salient point, what’s less often considered is how RPA solutions will combine with intelligent technologies to deliver even greater automation potential. No longer can these technologies be viewed as disparate from each other when companies consider automation and how RPA can help enhance their business operations.

But what’s perhaps most important in this discussion is how intelligent technologies will be able to learn and make decisions beyond their initial programming. This means they are able to learn from previous actions and deal with unforeseen exceptions in a business process. Because RPA is able to quickly generate and gather data, combining RPA with intelligent technologies means that the “learning” process can take place at accelerated rates. While these two technologies are only starting to be used together, the smart automation they can produce means that companies will be able to foster both increased productivity and creativity going forward.

Source: UIpath-Top RPA Conversations So Far for 2017

Robotic Process Automation The Question of If Rather When

RPA is one of the most efficient emerging technologies that can deliver results in terms of business efficiency, customer acquisition, customer engagement, and experience.

Robotic Process Automation (RPA) is in its early days. Having said that at times, the hype could get ahead of the reality. It is no longer a question of “if?” rather “when?”. RPA promises a lot for the enterprises especially in the areas of:

  • Customer Experience by improving process quality, increasing accuracy, reducing response-time, and allowing higher predictability
  • Business Efficiency by increasing the consistency in processes and tasks to reduce output variation, improves productivity by freeing up the brains and hands to do more value added tasks, enhances flexibility to respond to flux in demands and allows geographical independence.

This, in turn, enables enterprises to undergo a significant Digital transformation and expedite business processes, reduce errors and cut operational costs.

The physical and digital worlds are converging at esoteric speed. In 2004, when we all watched the famous Sci-fi action movie, iRobot, we never anticipated that a significant piece of work being taken over by robots would be a reality, but yes, it is knocking our front door now, is real and here to stay.

RPA virtually connects multiple disparate systems while executing repetitive work more accurately and reliably than people can do. At the same time, it necessarily doesn’t mean the complete replacement of human workforce by the robots, making humans redundant in their work environments. If RPA has to be effective, along with right intervention and human touch points, it is important to identify the right work that can be automated and executed under RPA by careful evaluation.

  • Type of transactions
  • Availability of knowledge to power automation
  • End to end process improvement
  • Total cost of ownership
  • Ease and time to deploy
  • Scalability & flexibility for the future requirements
  • Return of Investment.

RPA should be considered as an enabler that will free up people from doing high volume, highly mundane tasks that are better suited for robots, who can work tirelessly and continuously without making errors and the human workforce can take on more creative, collaborative and interactive work that makes them productive and efficient. Leveraging technologies to make machines work for you than they replacing you, that is the message that needs to be driven to avoid the fear of jobocalypse.

Any RPA project, undertaken, will be changing the nature of the work and the way it is executed currently, however, with better quality and improved efficiency. At the same time, it warrants to be conscious of balancing automation with right decision-making ability. Technologies like big data, analytics, Artificial intelligence and Machine Learning, in tandem with RPA can drive improved decision making and there by providing a new layer of engagement and transform enterprises to become customer centric.

With RPA, applications attempts to understand natural human communication such as touch, gesture, speech or even to the extent of reading neural signals and convert that to actions and communicate back in similar natural language. Artificial Intelligence variants like natural language processing, knowledge representation and reasoning, in the form of the algorithms equipped with machine learning capabilities, self- trains the applications to take right decisions. In parallel, the transactions and processes are being enriched with insights; predictive & prescriptive, and intelligence generated from ever growing repository of data; real time or operational, video streams, photographs, handwritten comment cards, data from security kiosks and other varied sources.

RPA is one of the most efficient emerging technologies that can deliver results in terms of business efficiency, customer acquisition, customer engagement, and experience.

What we are witnessing is the tip of the iceberg, and with Artificial Intelligence and Machine Learning evolving in tandem, RPA will become the catalyst, orchestrating the next level of digital transformation.

Source: bwdisrupt.businessworld.in-Robotic Process Automation The Question of If Rather When

AI Demystified: Shaping the future for positive change

The debate between Mark Zuckerberg and Elon Musk on the misunderstandings of artificial intelligence (AI) has brought to the forefront concerns and dangers of a robot takeover.

Often misrepresented and misunderstood, AI continues to serve as a source of significant intrigue. It has long been lauded as the future of work, but according to notable Hollywood movies, is also a harbinger of a robot takeover.

Futuristic movies, like I, Robot, and Avengers: Age of Ultron, portray AI as the precursor to a robot revolution wherein a seemingly innocuous utilization of the tool devolves into dystopia. And in many cases, despite being an effective money making tool, it is a mischaracterization of AI. Still, it is believable because of the lack of public fluency on the issue.

As the idiom states: “We fear what we don’t understand.”

With anxieties abound, it is important to understand that every technology shift has its own set of winners and losers. The advent of the car was initially rejectedby the public, and even ridiculed by horse owners. The only difference, is that the pace of advancing technology is now much quicker than it was in the past. When we do not understand a technology, we automatically tend to demonize it.

Similarly with AI, being able to define it and have awareness towards how it is impacting various industries for positive change will offer a more profound understanding that may ease concerns and lead it to be more widely accepted.

What is AI?

The first step in busting AI myths is to arrive at a reasonable, inclusive and thoughtful definition of the term.

Oxford Dictionary defines AI as, “The theory and development of computer systems able to perform tasks that normally require human intelligence. Examples include tasks such as visual perception, speech recognition, decision making under uncertainty, learning, and translation between languages.”

This definition is effective because it makes clear that AI is, in many instances, simply streamlining a process to make it more efficient. And while it is executing tasks that “require human intelligence,” the tasks themselves – like mass data analysis or translation, complex calculations or immediate responsiveness – are rarely those which people are otherwise capable of or willing to perform.

The Robot Workforce

There are concerns about how AI will impact the workforce and the global economy. For example, some fear that the rise of AI will lead to the replacement of jobs. In fact, researchers at Oxford University projected that 47 percent of U.S. employment may end up “at risk” with the expansion of AI.

However, it is important to keep an open mind on the opportunities it presents.

AI alone, is not enough. It requires humans to help AI understand language and make subjective decisions for a business. With the availability of online education, workers are able to receive the training and schooling that will present new employment opportunities. There are tailored courses for data scientists or machine learning engineers specifically designed to assist with AI.

While the concern exists that a sizeable number of jobs across all levels will be displaced by AI, a new study from Forrester Research argued that the development of AI and automation will actually transform and advance current jobs as humans get familiar working alongside their machine counterparts. Furthermore, Forrester estimated that in the next decade, 15 million new jobs will be created in the US as a result of AI and automation technology.

As the workforce modernizes, the door will open for new, previously unexplored jobs.

Change for Good

Healthcare is seen as one of the industries which will see tremendous benefits from AI-powered tools.

At a recent Stanford University conference, Andy Slavitt, former acting director, Center for Medicare and Medicaid Services (CMS), said that the expansion of AI in healthcare is designed to address productivity concerns. Specifically, “We need to be taking care of more people with less resources, but if we chase too many problems and business models or try to invent new gadgets, that’s not going to change productivity. That’s where data and machine learning capabilities will come in.”

CB Insights reported that there are now over 100 AI-based healthcare startups. The companies have wide-ranging aims, from aiding oncology treatment to reducing administrative responsibilities for doctors and nurses to powering digital journaling tools. In each case, AI is enhancing productivity through machine learning and deep data analysis.

This is precisely why AI-anxiety is misguided. These are unexplored tools, each of which has the potential to revolutionize healthcare delivery and improve outcomes for the issue which they are intended to address.

As the healthcare industry undergoes several paradigm shifts – from fee-for-service to value-based care, impersonal to precision medicine, traditional to digital healthcare delivery – AI is becoming essential. There are, for example, an overwhelming number of cancer variations that depend upon one’s family history, upbringing, DNA, environment, work and medical history. Coordinating care delivery and analyzing treatments and outcomes is essential, but with finite manpower and resources, impossible without the use of AI.

AI is a catch-all and a flashpoint, a source of concern and of intrigue. But it does not need to be. Instead, it should be recognized for what it is – a state-of-the-art way to utilize limited resources to advance an industry. It is not without its share of concerns, like other innovation groundswells before it. But it is also not an issue to be feared.

Eliezer Yudkowsky, an American AI researcher and writer who champions friendly AI, wrote in Singular Hypotheses: A Scientific and Philosophical Assessment, “By far the greatest danger of Artificial Intelligence is that people conclude too early that they understand it.” Misinformed generalizations that lead to stigmatizing attitudes, fears and misconceptions, limit the public’s scope to further the conversation surrounding the benefits of AI development.

With a broader and deeper understanding of the technology and the opportunities it presents, I am hopeful that fear and hesitation will become excitement. Unlike it had initially been thought to be, AI is not all doom and gloom.

Source: itproportal-AI Demystified: Shaping the future for positive change

What if Humans are Really the Ones Taking Jobs Away from Robots?

Many people view the growth of AI as a threat to their current employment, but for some it is actually an opportunity.

There’s a lot of talk and fear these days about robots taking jobs away from humans. As AI and machine learning grows, we hear more stories of robots replacing humans when it comes to customer service, transportation, financial management, and more and even holding positions on boards of directors and as managers. A report from Forrester found that robots will eliminate 6% of all U.S. jobs by 2021, which can be a cause for concern for employees in at-risk industries like logistics, consumer services, and customer service. Between driverless cars, chatbots, and smart home appliances and concierges like Alexa and Siri, there’s lots of room for growth in the AI field that can make life easier, streamline processes, and take humans out of the picture. Some people view it as an opportunity, but for many people it is a serious threat to their current employment.

But here’s another way to look at it: instead of robots taking jobs away from humans, what if humans are actually taking jobs away from robots? Consider this: Over the last few decades, companies have been organized to focus on process and maintain the status quo. Between standardized workspaces, rigid rules, and traditional HR programs, the focus was on getting work done and producing results with little thought to the individual employee. We all worked the same schedule, did the same type of work, and took breaks at the same time. If you’ve ever set foot in a traditional customer service call center, you can tell this is true, as employees simply fill a chair and are easily replaceable by someone else who can work the same schedule. These process-centric, homogeneous jobs are perfect for robots and automation, though we didn’t know it at the time. When we created these generic systems we were in effect just creating holding patterns until robotic technology was ready to take over. Just like the old factories full of workers from the 19th and 20th centuries have been replaced in large part by assembly lines and machines once the technology was available, so too are conditions that use humans where robots could easily do the job.

When we think about it that way, it’s not AI and robots taking away jobs from humans because humans were only the placeholders in the business framework until AI technology came along that could reclaim the jobs that had been designed for it in the first place. As a result, many organizations today are re-thinking and re-designing what they do with employees. This change creates lots of opportunities for human employees to try something new, branch out into new areas, and take advantage of new changes. Instead of the traditional definition of work as an 8-5 job in a cubicle, we’re now expanding our minds to think about work in a variety of ways–it can be anything from the traditional model to a flexible schedule, freelance-based workload, tele-commuting, or working in positions that didn’t exist just a few years ago. Now that we are done being placeholders for robots and automation, we can find more creative ways to apply ourselves within our organizations. For all the talk about robots taking away jobs, it is really allowing the us the opportunity to create new jobs and to change and expand how we think about work.

Robots will undoubtedly continue to take over jobs that have long been filled by human placeholders, but them doing so shouldn’t be viewed as a threat to humans in the workplace–instead, let’s consider it an opportunity for humans to play a more integral role in our organizations.

Source: inc.com-What if Humans are Really the Ones Taking Jobs Away from Robots?

Top RPA Conversations So Far for 2017

Earlier this year, we made several interesting predictions as to what would dominate the conversation throughout 2017 in the automation landscape as part of a preview for the year in RPA. After consulting with industry thought-leaders, analysts, and RPA specialists, we zeroed-in on a handful of critical topics poised to drive important discussions about RPA trends and developments. As we pass the midpoint of the year, we thought it would be interesting to revisit our predictions and determine which conversations have not only been taking place, but have also proved to be critical talking points for those within the automation industry.

Why is this look back to the beginning of 2017 in terms of automation so important? A 2016 study from the industry research firm Gartner suggested the demand for RPA tools is growing quickly…”at about 20 percent to 30 percent each quarter.” This growth was projected to continue into 2017 and thus far industry analysts believe it has, at least through Q1 and Q2 of this year.

With these statistics and figures in mind, let’s take a moment to check the pulse of the automation industry thus far in 2017 by considering which predictions and projections have evolved to be critical conversations in RPA.

RPA deployment will increase across new industries

At the outset of 2017, RPA adoption patterns were poised to experience a significant shift as companies in new and emerging industries discovered the power of automation solutions to enhance their business operations. While the adoption of automation technologies has functioned in somewhat of an opportunistic manner by early adopter companies, wider adoption moments have come to the forefront in such industries as healthcare, insurance, banking, manufacturing, and retail. This also dovetails with industries that have already experienced the benefits of RPA increasing their deployments into the front-office and other customer-facing tasks, actions which have yet to be fully realized by many companies.

In a 2016 report that surveyed the adoption of eight new technologies — including robotics and automation — by the professional services firm Deloitte suggested that:

More companies are increasing investments in these technologies. New technology investments over $1 million have increased…[and some companies are planning to] spend at least $100 million on new technologies over the next two years.

Rather than just being a way for companies to streamline their business operations, RPA and other automation platforms are transitioning from a luxury to a necessity. This conversation has not only persisted as the year progressed, but the drumbeat for automation platforms as a key aspect of any given company’s operation strategy has only increased as global economies and industries become more and more connected.

Automation will replace more tasks, not actual jobs

The emergence and proliferation of automation has caused a certain degree of panic over the possibility these technologies could replace the need for human employees in the workplace. Especially as automation moves from the back-office to more customer-facing tasks, customer relations-related areas such as call centers and other customer service platforms have suddenly become the subject of how and when automation could render these functions less necessary from a manual intervention standpoint. However, as we’ve moved through 2017, this concern has continually been minimized be the actuality of automation deployment.

Automation certainly has the ability to replace certain tasks or remove human personnel from specific department or business moments, especially those that are tedious, repetitive, and time-consuming: in fact, that’s what it is meant to do. However, this doesn’t mean the entire workforce will be replaced by robots. In fact, a 2017 publication by the McKinsey Global Institute suggests that:

The right level of detail at which to analyze the potential impact of automation is that of individual activities rather than entire occupations. Given currently demonstrated technologies, very few occupations—less than 5 percent—are candidates for full automation. However, almost every occupation has partial automation potential.

This kind of automation paints a hopeful picture for the future, one where humans and automation work side by side, which is the critical point of this conversation: debunking the myth RPA will essentially replace all methods of human intervention. In point of actual fact, RPA and human personnel will work in conjunction with each other which will allow human employees to focus on higher-level tasks that are meaningful and interesting, thus creating a space for automation to work through more repetitive, high volume tasks.

AI and machine learning will advance RPA

It has long been discussed how intelligent technologies like artificial intelligence, cognitive computing, and machine learning are expected to develop in the coming years and decades. In addition, a critical element of discussion within the automation landscape is how these technological developments will integrate and bolster automation functionality.

In a recent discussion with Forbes, Ash Ashutosh, the founder and CEO of Actifio, predicted that:

Just as most companies evolved to include cloud capabilities and features, 2017 will bring machine learning to almost every aspect of IT…[these technologies] will usher in a new era of data understanding and analysis.

While this is certainly a salient point, what’s less often considered is how RPA solutions will combine with intelligent technologies to deliver even greater automation potential. No longer can these technologies be viewed as disparate from each other when companies consider automation and how RPA can help enhance their business operations.

But what’s perhaps most important in this discussion is how intelligent technologies will be able to learn and make decisions beyond their initial programming. This means they are able to learn from previous actions and deal with unforeseen exceptions in a business process. Because RPA is able to quickly generate and gather data, combining RPA with intelligent technologies means that the “learning” process can take place at accelerated rates. While these two technologies are only starting to be used together, the smart automation they can produce means that companies will be able to foster both increased productivity and creativity going forward.

Source: UIPath-Top RPA Conversations So Far for 2017

5 Pitfalls to Avoid with RPA Implementation

Do the benefits outweigh the costs? Do the liabilities cancel out the opportunities? Is there greater upside versus down? When it comes to deploying a robotic process automation (RPA) solution, these questions more often than not are answered on the positive side of the equation where the value proposition of RPA for companies in a variety of industries far exceeds any drawback. In today’s modern, global business climate, companies require some form of RPA solution to enhance operational functions, mitigate risks, and leverage a competitive advantage in crowded marketplaces.

Implementing an RPA software solution can be tricky and companies who do not fully understand the challenges can find themselves struggling to reap the benefits RPA provides; in fact, companies who do not address these challenges and create strategies to combat them can actually experience RPA as a negative value proposition. However, putting together an implementation team and creating a preliminary strategy to ensure smooth deployment is a company’s best bet to experience the greatest potential increases in productivity and revenue at the hands of RPA.

Let’s examine 5 pitfalls to avoid in RPA implementation and how companies can turn these pitfalls into opportunities to leverage growth and profitability.

Premature process automation plan

Most of the discussion around adoption of new technology tends to focus on slow acceptors and how business and IT resources cling to old ways of doing business – however, with RPA software the opposite is often true. Advantages are so drastic that the transition to automated processes takes place without clearly thinking things through the process. Process automation should be part – a focal part – of an overall process optimization strategy consisting of many elements or components. Before any process is automated, all processes should be filtered through a centralization, standardization and optimization filter. This doesn’t mean obvious automation opportunities should be delayed and it doesn’t mean centralization, standardization and optimization has to come first (in fact, automation savings may have to fund those efforts). But this does mean automation is directed only at relevant and well-qualified business processes.

Operational oversight

One of the great strengths of automation is accuracy – the fact that configured software never deviates from its algorithms. Of course, this can also be a critical weakness. Should any internal or external aspect of a business process change, the software will likely fail to perform. In order to avoid automation failures, changes or alterations will have to be planned, communicated, tested, and executed within a strong operational oversight framework. This will be an organizational and 3rd party challenge because many business processes are undocumented and revisions occur less formally than in a governed change control process. This level of operational oversight is rarely conducted successfully in a reactive mode, which means the framework should be proactively put in place before any deployment begins.

Optimism in effort

At the end of the day, robotic process automation software is robotic process automation software. The roadmap for RPA deployment should reflect a more conservative optimistic in effort than guidelines stipulate from product vendor or third-party advisory firms. Despite all the talk about the ease of implementation, the fact remains automation software is not quite that user-friendly and quick to configure. The fault lies in the nature of business processes and the fact software is literal – it can do only what it’s been told to do. Because humans are anything but literal, there are often missing rules in a process simply because the decisions-making only resonates with the human operator. It will take time for current process employees to identify and document the innate rules they follow without consciously thinking about them.

New or added roles

Via process automation, changes or turnover within a company or organization is a means to an outcome but not the outcome itself (though accuracy, efficiency and costs will improve). This means it’s important the deployment process incorporate new roles well beforehand. New team leads will be required to manage the output of robots rather than FTEs. This lead will have a variety of new and expanded responsibilities: maintaining and improving service levels for the human interventions needed for process exception-handling; a liaison with the IT Dept; and turnover management, proactively re-configuring robotic software in coordination with changes in process activities and rules. Depending upon the size of the deployment, a management slot above the lead position may be needed to implement the rollout across other business units.

Overconfidence in ability

While deploying robotic software to automate business processes entails risk and requires an investment of human and financial capital, the companies to undertake such deployment stand to experience two attractive benefits: the associated savings and cost-reduction, and complete operational control. An early part of the strategic plan should question whether automation should be done in-house or by a BPO provider. Experienced BPO providers have robust service offerings with well-integrated capabilities across technology, process optimization, change management, automation technology, and labor arbitrage. Outsourcing process automation does present its own set of issues, particularly the risk of becoming locked into a provider’s technology. With this technology changing so rapidly, entering into a long-term contract with a third party provider has to be balanced against an objective measurement of a company’s internal capability to do the job itself.

Source: UIpath-5 Pitfalls to Avoid with RPA Implementation