How likely are you to be replaced by a robot or a computer program? It depends, according to a new report,How Vulnerable Are American Communities to Automation, Trade and Urbanization? Workers in data entry, telemarketing and watch repair are most likely to be targeted by automation, while surgeons...not so much.

The study, prepared by the Center for Business and Economic Research (CBER) and the Rural Policy Institutes Center for State Policy at Ball State University, found that the rise of automation and offshoring could extend such job losses beyond the factory floor.

Automation is likely to replace half of all low-skilled jobs, says CBER director Michael Hicks. More worrisome is that there is considerable concentration of job loss risks across labor markets, educational attainment and earnings. This accrues across industries and is more pronounced across urban regions, where economies have concentrated all net new employment in the United States for a generation.

The study also found that low risk of automation is associated with much higher wages, averaging about $80,000 a year. Occupations with the highest risk of automation have incomes of less than $40,000 annually.

The top automatable occupations, number of jobs and average annual salary includes data entry keyers, 216,000, $29,000; mathematical science occupations, 1,800, $66,210; telemarketers, 237,000, $23, 530; insurance underwriters, 103,000, $65,000; tax preparers, 90,400, $36,450; photographic process workers and processing machine operators, 28,800, $26,590; library technicians, 101,800, $34,750.

The leastautomatable occupations, number of jobs and average annual salary includes recreational therapists, 18,000, $45,890; emergency managers, 10,000, $67,330; first-line supervisors of mechanics, installers and repairers, 447,100, $63,010; mental health and substance abuse social workers, 117,000, $42,170; audiologists, 13,200, $74,890; orthotrists and prosthetists, 8,300, $64,430; health technologists and technicians, 102,200, $41,260; and hearing aid specialists, 5,900, $49,600.

While drafters, computer programmers, data entry keyers, statisticians and mathematicians and film and video editors were considered the most offshorable occupations, the list of least offshorable occupations closely mimicked the list of least automatable occupations, with the edition of the 6,800 oral and maxillofacial surgeons who average an annual wage of $233,900.

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Audiologists, Emergency Managers and Occupational Therapists Face Low Risk from Automation - EHS Today

Brooks Automation, Inc. (NASDAQ:BRKS)

Q3 2017 Earnings Conference Call

August 2, 2017 4:30 P.M. ET

Executives

Lindon Robertson - Executive Vice President and Chief Financial Officer

Steve Schwartz - President and Chief Executive Officer

Analysts

Paul Knight - Janney Montgomery Scott

Amanda Scarnati - Citi

Operator

Ladies and gentlemen, thank you for standing by and welcome to the Brooks Automation Q3 Fiscal Year 2017 Financial Results Conference Call. [Operator Instructions] As a reminder, this call is being recorded, Wednesday, August 2, 2017. I would now like to turn the call over to Lindon Robertson, Executive Vice President and Chief Financial Officer. Please go ahead.

Lindon Robertson

Thank you, Ash, and good afternoon, everyone. We would like to welcome each of you to the third quarter financial results conference call for the Brooks fiscal year 2017. We will be covering the results of the third quarter ended on June 30, and then we will provide an outlook for the fourth fiscal quarter ending September 30 of this year.

A press release was issued after the close of the markets today and is available at our Investor Relations page of our website, http://www.brooks.com, as are the illustrated PowerPoint slides that will be used during the prepared comments during the call.

I would like to remind everyone that during the course of the call, we will be making a number of forward-looking statements within the meaning of the Private Litigation Securities Act of 1995. There are many factors that may cause actual financial results or other events to differ from those identified in such forward-looking statements.

I would refer you to the section of our earnings release titled Safe Harbor Statement, the Safe Harbor slide on the aforementioned PowerPoint presentation on our website and our various filings with the SEC, including our annual reports on Form 10-K and our quarterly reports on Form 10-Q.

We made no obligation to update these statements should future financial data or events occur that differ from the forward-looking statements presented today. I would also like to note that we may make reference to a number of non-GAAP financial measures, which are used in addition to, and in conjunction with, results presented in accordance with GAAP.

We believe that these non-GAAP measures provide an additional way of viewing aspects of our operations and performance. But when considered with GAAP financial results and a reconciliation of GAAP measures, they provide an even more complete understanding of the Brooks business. Non-GAAP measures should not be relied upon to the exclusion of the GAAP measures themselves.

On the call with me today is our Chief Executive Officer, Steve Schwartz. We will open with his remarks on the business environment and our third quarter highlights then we'll provide an overview of the third quarter financial results and a summary of our financial outlook for the quarter ending September 30, which is our fourth quarter of the fiscal year 2017.

We will then take your questions at the end of those comments. During our prepared remarks, again we will, from time to time, make reference to the slides I mentioned available to everyone on the Investor Relations page of our Brooks website.

With that, Id like to turn the call over now to our CEO, Steve Schwartz.

Steve Schwartz

Thank you, Lindon. Good afternoon, everyone, and thank you for joining our call. We're particularly pleased to announce the results from a very strong June quarter in part because the results that weve delivered, but more importantly because were able to demonstrate the earnings power of our business, which is made up of a portfolio of strong market leading technology positions and key growth segments of the semi-conductor and Life Sciences markets. A foundation that we strongly believe will continue to deliver going forward.

Revenue at $182 million was up 7% from March and up 23% over the prior year. Gross margins increased sequentially by 100 basis points to reach 40%, which is a very meaningful threshold for the company, and a heavy lift from the 32% to 33% gross margins we delivered in fiscal 2011, the year we first entered the Life Sciences space and began to restructure our semiconductor product portfolio.

The top line and gross margin performance led to a non-GAAP earnings per share of $0.36, more than double what we delivered in the June quarter one year ago, and up 27% from the March quarter. Growth came from both segments as we delivered our eighth consecutive quarter of growth in Life Sciences and semiconductor, which is riding the wave of strong momentum in the capital equipment space, also benefited from our expanding market share position in our key growth segments.

The part that we find most energizing is the momentum that weve established inside the company to continually ratchet down on costs and improve efficiency, while we advance new product development and sales activity to deliver top line growth. We continue to see more potential and thats what drives us even harder.

Today, we report on some of the highlights from the quarter and give color as to what makes us enthusiastic about the prospects from the very solid positions weve captured in two important markets. Ill begin my comments today with a recap of our Life Sciences business performance.

Revenue came in at a robust $37 million, thats up 6% from March and represents organic growth of 27% from the June quarter one year ago. And including organic growth and revenue from acquisitions was our seventh consecutive quarter of greater than 25% growth.

Bookings at $42 million had another $7 million to backlog, which now stands at $260 million. And though gross margin was slightly softer on mix, Life Sciences delivered $2 million of operating profit in the quarter even as we made additional investments to expand our global sales team.

Ill add just a few additional highlights from the quarter. Our automated storage systems business grew 63% versus prior year coming from both bio and cryo automation solutions we delivered to compound and bio-banks, cell therapy, and regenerative medicine applications.

In a particularly positive sign, our BioStore three cryo system bookings topped $2 million for the quarter with account penetrations in North America, Europe, China, and the Middle East. We had 26 new customers expanding our base across a broad spectrum of customers in the Pharma, Biotech, healthcare clinical, and academic end markets.

We also delivered on some important milestones that will generate future revenue. We launched BioStudies, a bioinformatics platform that enables customers to virtualize and visualize all of their global samples. And we received a first order from a major bio-bank by demonstrating the utility of this configurable sample management software platform.

We completed and commercially launched two new configurations of a BioStore III cryo automation products, one that stores a common Life Sciences industry standard sample container called an SPS rack and the other a variable temperature version of the BIII C for customers select the automated configuration and liquid nitrogen sample security, but would want the store at user selectable temperature set points anywhere between minus 80 and minus 190 Celsius. Initial units of both new products have already been shipped to a major customer.

In our consumables and instruments sector, we released a universal instrument that will allow customers to simultaneously cap and de-cap 96 sample tubes of various types and brands. This is the first in the market. And we just recently developed a new small footprint minus 80 degree C automated store that expands our customer universe to include those who need automated minus 80 storage, but for whom up to 300,000 samples is adequate storage capacity.

And at the beginning of last month, we completed the acquisition of Pacific Bio-Material Management or PBMMI, a highly regarded biological sample transport and storage company with customers that include Memorial Sloan Kettering and Mount Sinai Hospital, plus an a list of research and academic institutions that they won because of their high quality and outstanding service capability.

Along with the strong and talented team we had more East and West Coast geographic footprints and more than 250 customers that meaningfully expands our academic market presence. And with each sample under management, we have the possibility to deliver more value to customers from the broader portfolio of offerings that weve developed at Brooks over the years.

Our cold chain sample management portfolio is proving its value, as we provide customers with a one-stop shop for all of their cold sample needs. Were working to increase the depth and breadth of all of our offerings along the cold chain. Our new product development initiatives and the addition of PBMMI are all representative examples of this strategy in action.

In Life Sciences, our priority is growth. We continue to invest in new products additional go-to-market sales capability and acquisitions that allow us to grow in this important and expanding space of sample management. And although were focused on growth, were careful to strike the right balance to maintain profitability as we grow. This business has tremendous earnings leverage and we know that if we elected to slow investment for growth, we could deliver much higher profitability.

As a matter of fact, we maintain our position that the potential profit margin of Life Sciences is greater than in our semiconductor opportunity, but for now we believe that the best thing that we can do for shareholders is to continue to make investments to capture more of this market through targeted investments in organic and inorganic growth opportunities. We believe that were taking the right steps, and I illustrate with two examples.

First, weve meaningfully expanded our customer base over the years. When we started in the automated stores and services space, we acquired companies that gave us approximately 200 customers. At the beginning of fiscal 2015, when we acquired FluidX, a consumables and instruments company, we added another 300 customers. BioStorage Technologies came with an additional 300 customers and PBMMI 250 more bringing the number of customer relationships to more than 1000.

Over the past three years, this represents a five-fold increase in the number of potential opportunities we have to expand our cold chain offerings. Weve already started to leverage this portfolio to win more business at many of these customers who are eager to streamline their sample management solutions.

In terms of results, Life Sciences revenue for the first three quarters of fiscal 2017 was $105 million, almost equal to the $108 million of revenue we delivered in all of fiscal 2016. That represents 37% growth over the same period one year ago, and for the fiscal year-to-date bookings totaled $154 million, up 35% over the same period last year.

Were forecasting another strong quarter for Life Sciences and we expect to deliver double-digit sequential revenue growth in Q4 with revenue above $40 million and we expect revenue will continue to grow in every quarter of 2018.

Ill now turn to the semiconductor business, which remains our main cash and profit engine. In our semiconductor business, we set a number of new high water marks as we successfully tested our operational capabilities against another surge in customer demand. We delivered revenue of $145 million, up 8% sequentially and up 22% versus the same quarter one year ago.

Its important to note that this 8% quarter-over-quarter growth was net of reduction in our CCS revenue of approximately $5 million, due to the decrease in leading-edge foundry spending that some of our OEM customers have already mentioned. This makes the growth in our semi business all the more impressive as its driven mostly by 3-D memory capacity and advanced packaging.

Ill provide a quick update on these three growth drivers, starting with vacuum automation. The tremendous growth in vacuum process technologies, primarily deposition and etch led us to yet another record in vacuum robots with revenue up 14% from this previous record we delivered in March. These are unprecedented times and were reaping the benefits of our powerful market position in the vacuum automation space.

Year-over-year our vacuum robot business was up 56% and indications are that were in for a period of sustained strength in the equipment industry and that vacuum process steps that serve 3-D memory will continue to be in high demand into 2018. Our leading market position at more than 15 OEMs who supply vacuum equipment virtually assures that if any capacity additions are a benefit for Brooks.

In advanced packaging, we saw a 60% increase in automation solutions, from $9 million in March to more than $14 million in the June. Advanced packaging growth was driven by strong investment by Chinese OEMs, as well as increased shipments of 200 mm vacuum systems to support the unique packaging needs for MEMS, power, and plasma dicing markets. We also added to our share by winning the automation design for an advanced packaging lithography tool.

Looking forward, we see positive momentum for additional investment in leading-edge foundry to support integrated fan-out. The advanced packaging business is robust and the in the opportunities that exist are expanding to a broader number of companies, which are building lines to adapt these new technologies. As a result, we feel that were at a step change from the $40 million annual run rate that we sustained from most of the last couple of years to something that can be meaningfully higher.

The only part of our semiconductor business that was not up in the June quarter was contamination control solutions, which still came in at a healthy $20 million, but was down from record $25 million in the March quarter. This reduced level was expected as leading-edge 10 and 7 nm foundry spending, which drove extremely high shipments in December and March has subsided as that manufacturing capacity is brought online.

On the positive side, we believe we have one 100% market share for all 10 nm and 7 nm manufacturing capacity thats being installed and in these technology nodes ramp, so too will our CCS business, but were forecasting CCS to be down again in the September quarter by another $6 million to $8 million as leading-edge foundry spending is expected to remain low.

That said, we are counting on new factory capacity in China and the restart of foundry spending to be meaningful drivers of additional market opportunities in 2018 and our forecast, which are based on new fab capacity expansion plans are for CCS business to grow again in 2018.

Finally, in the quarter we also supported another jump in our cryo vacuum pump business, which was up 10% from the prior quarter and up more than 50% from the prior year as both ion implantation and PVD activity has strengthened. Our Polycold cryochillers business that supports applications for advanced displays was similarly in very high demand, more than double the level of the same quarter one year ago, and at levels weve not seen for several years.

We anticipate similar revenue for our cryo vacuum products in the September quarter. In total, we forecast our semiconductor business to be down approximately 7% to 8% at September, after our record June quarter, which included a couple million dollars of pull-ins to help customers who wanted more product in June, but even with the pause in September, well be very busy in manufacturing operations as we will be preparing for what we are forecasting to be some high demand quarters after that. So although revenue will be slightly less, well be no less busy in our preparedness for a strong demand outlook.

Overall, were extremely pleased with our performance. Were in two growth businesses that are supported by strong market dynamics in which we hold defensible positions that we continue to build. Our outlook for Life Sciences for more quarters and years of accelerated top line and margin expansion as we continue to build a growth engine centered in the sweet spot of sample management.

This market is exploding as bio samples are the key elements to support drug discovery, cell therapy, regenerative medicine, and cancer research. The demands for our capabilities are accelerating and our ability to define standards of handling and transport are going to be essential for our success and to the benefit of the industry.

In the semiconductor space, were benefiting from the strong growth in 3-D memory and all of the vacuum equipment that requires. We are well positioned for advanced packaging automation opportunities where we have shown our capability to capture share and were far and away to market choice for CCS solutions for wafer and radical carrier cleaning. All-in, we see another strong quarter in September, even with the pause in the semiconductor business. We remain extremely bullish about our position in both markets and we anticipate growth in the December quarter from both segments.

That concludes my formal remarks, and Ill now turn the call back over to Lindon.

Lindon Robertson

Thank you, Steve. Please refer now to the PowerPoint slides available on the Brooks website under our investor relations tab. To start the remarks, I would like to draw your attention to Slide 3, which is consolidated view of our operating performance. Our top line revenue increased 7%, sequentially to $182 million, driven by an 8% increase in semiconductor solutions, and a 6% increase in Life Sciences.

In the GAAP results, operating income expanded 27%, driving GAAP based earnings per share upwards $0.05 to $0.25 per share. Looking at the non-GAAP picture, adjusted earnings per share was $0.36 per share, an increase of 27% from second quarter. Non-GAAP gross margin increased 100 basis points to 40%, driven by improvement in the semiconductor segment.

At the bottom line, we produced 25 million of non-GAAP net income and 37 million in adjusted EBITDA. Comparing these results on a year-over-year basis to third quarter of fiscal 2016, revenue was 23% higher and our adjusted EBITDA has increased 93%.

Turn with me over to Slide 4 to start our discussion of segment results. The Life Science business grew 6% sequentially and 26% year-over-year with $37 million of revenue. BioStorage revenue increased 9%, sequentially, while the remaining core Life Sciences revenue grew 4%.Gross margins came in at 38%, 2 points lower than the prior quarter. Softness occurred on both the storage and the infrastructure business.

On the BioStorage services side, the result was driven by mix as genomic services revenue came in higher. Storage service margins remained very strong. On the infrastructure side, the business had certain projects driving a lower margin this quarter. We expect margins to return to 40% next quarter. In the third quarter, new orders in contracts totaled $42 million adding backlog to the business.

Year-to-date, Life Science bookings totaled $154 million, up 35% compared to just $114 million for the same year-to-date period in 2016. The fuel is there to continued organic growth above 20% year-over-year, and we will have the added benefit of our latest acquisition of PBMMI in the BioStorage space. They had $10 million of revenue in the past 12-months and are also growing. This latest acquisition fits the margin profile of our current BioStorage business that being about 40% to 45%.

Lets turn to those semiconductor business on Slide 5. This business accelerated with 8% sequential revenue growth this quarter. As Steve indicated, we saw some customers pulling product through in the final weeks ahead of our anticipated schedules. Across the product lines, we saw double-digit sequential expansion in vacuum robots and atmospheric robots and cryopumps and services and in our Polycold line. The offset bringing us down to 8% was in contamination control solutions, which was still above $20 million.

As we have shared previously, these systems sell for approximately 1 million each. So, the timing of the fab line expansions can cause a swing in our quarterly revenue. Based on our fab customer schedules, we anticipate another drop in contamination control shipments again in our fourth quarter and are rebounded in the 2018 calendar year, just as Steve outlined.

As the strikes some variability in our revenue lines well continue to give you visibility to the specifics, but I also want to emphasize the moment this business has provided. We acquired this business in 2014 for 32 million from an owner that saw 28 million of revenue in their prior year. In 2015, we had $44 million of revenue and in 2016 $52 million and we will be above $80 million when we finish 2017. We foresee another year of growth in our fiscal 2018.

The adjusted gross margins for semiconductor solutions struck above 40% this quarter. The value of our newest products and the reduction of fixed cost over the past 18 months have made 40% possible. The additional volumes this quarter had drove over the line on improved absorption of overhead.

Let me drop a highlight around this point. Our $10 million of expansion in the top line dropped through to operating income at a rate above 60%. In the year-to-date picture, our semiconductor revenue has grown 24%, and has dropped through to operating profit at a rate of 50%.

Lets turn to the balance sheet on Page 6. With the growth of the business, weve seen expansion of receivables and inventory. The increase in deferred revenue reflects the life science bookings that often carry advance payments. We finished the quarter with $120 million of cash, cash equivalents, and marketable securities and no debt. We carried $49 million of this cash in the U.S. at the close of the quarter, which enable closing the $34 million acquisition of PBMMI at July without touching a credit revolver.

Lets turn over to Slide 7. Net income of $17 million drove cash flow from operations of $18 million. Were in our seventh year of paying a dividend returning $7 million to shareholders in this quarter alone. Capital expenditures were $2 million, bringing the total for our first three quarters to $7 million.

Cash from operations has accumulated to $61 million for the nine months ended June 30, rounding out free cash flow to $55 million year-to-date. In total, our cash balances expanded by $29 million since the beginning of the year to $120 million on this report. I will highlight again that this is prior to using $34 million on the acquisition of our latest BioStorage acquisition on July 5.

Slide 8 addresses the outlook of our fourth fiscal quarter of 2017. Fourth quarter revenue is expected to be in the range of $172 million to $178 million. Adjusted EBITDA is anticipated to be between $30 million to $33 million. Non-GAAP earnings per share is expected to be $0.27 to $0.31 per share. And the GAAP earnings per share is expected to be $0.17 to $0.21.

As we drive to this guidance, were very cognizant of the step change, our business has made in this past year. The annual numbers represent a 22% growth at the top line, the non-GAAP earnings per share is more than double the $0.47 we turned in 2016.

So that concludes our prepared remarks, so I will now turn the call back over to Ash, our operator, to take questions from the line.

Question-and-Answer Session

Operator

[Operator Instructions] And our first question comes from the line of Paul Knight with Janney Montgomery Scott. Your line is now open. Please proceed with your question.

Paul Knight

Hi Steve, could you put some color around the equipment versus the service size, the revenue in the quarter and any attributes on why maybe a little softer, was it capital equipment? And then lastly, the Pac bio deal was closed, correct?

Steve Schwartz

The Pac bio deal was indeed closed. So Paul let me give you a little bit on the quarter. So out of the 37 million, I'm going to give you a really rough numbers, the stores was about 20%, a little bit more 25%. The consumables and instruments was probably about 15%, and the bulk of the business was the services and the service combined. So when we look at the bio storage and service combined that was about half.

Paul Knight

Okay. And then you are offering genomic services as part of your strategy obviously, is that your fastest growing business?

Steve Schwartz

It turns out that all of the elements are growing pretty significantly. The genomics is a little bit, is not as steady. In the aggregate it is growing, but the samples that we provide to that are growing considerably. So thats a business thats still up and down for us, but year-on-year well see growth in the genomic services, but we find the activity there is sometimes budget -related and so there are bursts in that business, more so than the steady annuity that we get from the consumables and from the storage elements.

Paul Knight

And youve been posting somewhere in the 20s on organic growth, do you see that as a number thats ahead of this?

Steve Schwartz

We do. So for the foreseeable quarters we see that continuing to grow in the 20% plus range.

Paul Knight

Okay. Thank you.

Steve Schwartz

Thanks Paul.

Operator

Our next question comes from the line of Amanda Scarnati with Citi. Your line is now open. Please proceed with your question.

Amanda Scarnati

Hi thanks for taking the question. Just continuing on the Life Sciences business, Steve I think you mentioned that profitability could be greater than semi down the road, and what are the puts and takes to get there, is it adding more scale into the business, is it continuing to integrate the acquisitions that have been done or are there other things that are already in process that are helping to drive profitability up.

Steve Schwartz

See original here:

Brooks Automation's (BRKS) CEO Steve Schwartz on Q3 2017 Results - Earnings Call Transcript - Seeking Alpha

For most of this decade, call center automation efforts involving voice technologies have focused on speech analytics to monitor agents' interactions with customers. That is changing.

New voice tools provide the ability to initiate CRM contacts through voice interfaces, such as with Google Home and Amazon Echo. They can also divine new insights about customer experiences through voice analysis of calls that supplement traditional consumer surveys, and may even replace them in the future.

But these voice tools can help only to a point, as software vendors and their customers await better natural language processing (NLP) support.

"It's at a point where it's really accepted -- you talk to your car, you talk to your phone," said John Joseph, CEO of Scribe Software, a company based in Manchester, N.H., that focuses on CRM data integrations. His team demonstrated at the Salesforce World Tour stop in Boston in May a Salesforce-Amazon Echo implementation that enables voice-activated report generation.

"There's still a long way to go in terms of natural language [processing technology] understanding everything -- but it's remarkable where we are," he said.

The reason voice recognition or virtual assistants are still kind of dumb -- despite massive cloud compute power that can run circles around humans -- is that they are very literal, and they often over-simplify a human's request to the point where they miss the original premise. This can lead to off-topic suggestions or some variation of "Sorry, I don't understand."

On top of that, humans have powers of comprehension computers don't: We instinctively understand tone and emotion, and we can hear the syntactic nuance of clichs and other local idioms (such as the interchangeable use of soda, pop, tonic or Coke).

There's still a long way to go in terms of natural language understanding everything -- but it's remarkable where we are. John JosephCEO, Scribe Software

Think about this statement: Police help dog bite victim. How is NLP likely to interpret that? An NLP system has to work hard to figure out what you're saying (think I scream versus ice cream) before it can tackle context and hazard a guess as to what a customer is asking.

All that being said, companies hope to integrate more call center automation tools built around NLP as it improves, according to Deloitte customer operations leader Andy Haas, who co-authored a report analyzing the results of a survey of 450 call center executives earlier this year.

Business leaders are considering and even experimenting with next-generation voice recognition feeding into NLP, which, in turn, feeds into analytics systems that can automate customer service through the insights the analytics glean from the conversation, Haas said. While simple, targeted tasks can be completed now, operations executives pretty much agree that adequately reliable automation technology is a long way off from digitizing customer interactions; as in, decades.

"There might be a tipping point in the future, but it's not there yet," Haas said. "I don't think my clients think it's in the next five years, just like operations managers don't think interactions will be all-digital in the next five years. Will it happen in the next 20 years? Maybe."

One possible way new voice tools could advance call center automation is through analytics to determine customer sentiment for the purpose of future sales and customer retention efforts. For decades, the post-call follow-up survey has been the main method fueling such initiatives, but voice analytics are starting to supplement surveys.

There could be a point down the road where these audio mining systems replace surveys, and they could actually offer deeper insights about customer sentiment than the blunt instrument of the three-question, multiple-choice survey few take the time to fill out.

Haas said his survey showed that while call center volumes are going down in general, the interactions which escalate to calls are make or break in terms of the customer's relationship to the company. Call analytics tools, therefore, will become more and more important vehicles for customer retention.

"As you apply analytics, it will make an easier ROI [for investing in the technology]," Haas said. "It's going to be less pure volume, but more meaningful interaction."

Greg Hirschi, director of customer service operations at smartphone and tablet case manufacturer OtterBox, runs a 270-agent call center based in Colorado. The company regularly conducts customer surveys, which get 30% to 40% response, and the rich information they yield has led directly to eight-figure redesigns of customer experience processes, one example being warranty service, he said. Analytics can extend those insights to offer product teams feedback for future OtterBox models.

"From a consumer insight standpoint, for us, it's deeply valuable to understand how they use our products and what we can do to better design them," Hirschi said. "There's a knowledge gap between perceived customer use and actual customer use, and we use voice analytics to bridge that gap."

Terry Leahy, president and CEO of call analytics software vendor CallMiner, said he believes the old-school customer survey as a service tool should be replaced, and the funds companies invest in them would be better spent elsewhere. That being said, customer surveys will never go away he added. Call analytics can offer insight to marry with the results of surveys and to deepen a company's knowledge about its customer experience.

"We are now selling to marketing more than we ever did before, and that's where the budget for the survey usually is," Leahy said. "I think it's safe to say that you'll be seeing budget for surveys being diverted [toward] a better way to understand the actual voice of the customer than a derivative of it, which is the survey ... But surveys are never going away."

Voice-over Internet Protocol (VoIP) phones have, for years, extended call center work to employees who want to work at home. But even the old-dog VoIP technology is teaching call centers new tricks.

Ryan Nichols, general manager of Zendesk Talk, said CRM systems are creating deeper and deeper VoIP integrations, such that service agents can escalate calls from channels to voice while in a customer's recording, without interruptions. This reduces call times dramatically because there's no cold-call script to launch into the discussion -- it's already going on via text, and the voice call is a continuation of that.

"Conversations don't need to come in via PSTN [public switched telephone network] anymore," Nichols said. "Someone doesn't have to dial in a 1-800 number they found on the website and navigate down to an agent."

These VoIP integrations have become so tight, he said, call centers are either no longer using traditional phone systems or they're skipping them altogether when equipping new facilities. Customer agents are the better for it because, when they can see context in the customer record, as well as the chat history, agents can perform more effective service.

Nichols is watching with interest how companies such as Uber and Lyft integrate voice into their smartphone apps, as well as home voice assistants such as Amazon Echo. Still, he said, there's a long way to go before we read a lot of CRM success stories tied to voice recognition and the NLP those types of implementations require.

"The question is, what happens when people have problems?" Nichols said, echoing what analysts have said all year: NLP is unreliable enough that the biggest challenge is understanding when and how to escalate service to better channels before losing the customer.

"How do you build a bridge between this conversation that's happening around your core service and your traditional support channels?"

Guide to buying call center speech analytics

The benefits and negatives of real-time speech analytics

Best and worst call analytics practices

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Call center automation advances, but only as far as NLP can take it - TechTarget

A startup called B12 builds websites with the help of friendly robots. Human designers, client managers, and copywriters still do much of the workbut they dont coordinate it.

That job has been given to a software program called Orchestra.

As its name implies, Orchestra conducts a swarm of workers, most of whom are freelancers, and other robots to complete projects. When a client requests website improvements, which B12 sells a la carte, Orchestra generates a new Slack group, identifies team members who are both available and appropriate to complete specific tasks, and hands off work to humans and automated processes in the appropriate order. It constructs a hierarchy of workers who can check and provide feedback on each others work.

Automation is often associated with repetitive work such as torquing a bolt or combing through contracts during an audit. Orchestra and other systems like it demonstrate that the management of that work, and even work too complex to fully automate, also involves tasks with high automation potential. According to a McKinsey analysis, 25% of even a CEOs current job can be handled by robots, and 35% of management tasks can be automated.

The future of work may have become the hot topic, but the future of management may involve an equally drastic change.

Almost a decade of research on how to automate coordination and other managerial tasks has focused on managing crowds of freelancers, which with platforms like Amazons Mechanical Turk can be easily recruited from all around the world.

Employees at a company called MobileWorks (which now builds databases of sales leads and is called LeadGenius), for instance, published a paper with researchers at the University of Berkeley in 2012 describing a dynamic work routing system that automatically priced taskseverything from managing a Twitter account to digitizing stacks of business cardsand assigned them to qualified workers. Multiple workers completed the same task to help check for accuracy. If they disagreed, the task was served to other workers and, if they continued to disagree, marked for review by managers, workers who had already demonstrated high speed and accuracy. Workers who made a lot of mistakes were assigned to practice tasks until they improved.

At Stanford, a group of researchers (including Daniela Retelny, who is now B12s director of product) has published papers about how to coordinate crowds to complete projects that involve interdependent tasks, such as prototyping an app. One strategy, called flash teams, used software to automatically assemble a team of freelancers and hand tasks between them, like an assembly line. The process effectively turned napkin sketches into functional web applications and recruited users to test themall within a single day. Another called flash organizations, discussed in a paper published earlier this year, placed freelancer teams into a hierarchy and allowed members to suggest changes to the organizational structure as they worked. Those teams completed prototype designs for a card game, an app for use by EMTs, and a client training portal for use by a business services company.

B12 isnt the only company to incorporate these strategies. A startup called Gigster uses a similar system to build software and websites. Konsus, which offers business services such as data entry and PowerPoint design, has created automated workflows that hand work between its pool of freelancers and automated processes.

What all this means for the job of managing people within a company isnt necessarily straightforward. To the extent that we can build systems that aid coordination and awareness for teams performing routine tasks, that seems the most likely to reduce the need for managers, says Michael Bernstein, a Stanford researcher who is an advisor to B12 and co-authored the papers on flash teams and organizations. But to the extent that managers are providing informal and evolving coordination support, that will still be useful in my opinion.

A Bain report published in April suggested that by the end of 2027, most of a companys activity will be automated or outsourced.Teams will be self-managed, leading to a vast reduction in the number of traditional managers, the reports authors write. Employees will have no permanent bosses, but will instead have formal mentors who help guide their careers from project to project.

The report suggests new types of leadership will emerge. Rather than aiming to become a professional manager (to take expert bricklayers, so to speak, and make them managers of other bricklayers), top talent would shift to contribute directly to a companys service or product and communicate directly with each other rather than through managers (they should beguilds of bricklayers). In this new company structure, there would be multiple tracks for career advancement. Some tracks will recognize and reward the efficient management of routine processes, they write, while others, just as highly prized, will value the coaching and development of apprentices as they migrate from one role to another.

Roger Dickey, the CEO of Gigster, imagines a system that automates this type of career advancement for freelancers based on the quality of work (B12 already has some hierarchy of freelancers, as do LeadGenius and Gigster). Leaders can oversee as many as 20 projects at a time, offering guidance to their team, recommending bonuses to people who are doing well, coaching, training and jumping in when an issue is escalated, he wrote in a recent blog post on LinkedIn. Companies are then able to hire an entire team of freelancers to manage a project, knowing that there is a hierarchical structure in place to support them.

In any case, if we have truly entered a fourth industrial revolution, as the World Economic Forum recently declared, it follows that work wont be the only aspect of an organization to see sweeping changes.

Our philosophy is that anything that can be automated around these workflows will be, says Nitesh Banta, B12s co-founder and CEO. The efficiencies are too great not to automate.

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Robots are replacing managers, too - Quartz

The rise of automation isnt all doom and gloom for Indian IT.

Even as traditional IT jobs, such as data entry and server maintenance, are expected to decline over the next five years, new-age jobs are emerging, according to a report by Simplilearn, a San Francisco- and Bengaluru-based online professional skilling platform. New career paths for Indias IT workforce will open up in digital domains such as big data, artificial intelligence (AI), the Internet of Things (IoT), cloud computing, and cybersecurity, the company said in a press release on Aug. 01. Simplilearn surveyed 7,000 IT professionals, and mined job portals such as LinkedIn and Naukri.com for its assessment.

Here are the roles that are likely to have the most vacancies in the next few years:

But just because there are tens of thousands of openings for a web services consultant doesnt necessarily make it the most lucrative option. For instance, big data architect openings are far fewer in number but pay much more, according to the report. While a web services consultant position offers a median salary of Rs9.27 lakh ($14,461) annually, a big data architect could rake in Rs20.67 lakh ($32,234).

With technology evolving fast, its become all the more important for techies to keep their skills up to date with short learning programmes, according to Kashyap Dalal, the chief business officer of Simplilearn.

It is more a cultural shift people will need to go through, he said. They need to get used to the fact that every year, theyll have to learn something. Everybody will need to make some time, and companies will need to facilitate it, too.

The urgency to re-skill or perish is especially striking people with mid-level experience: Nearly 57% of the 7,000 IT professionals looking to level up on Simplilearn had four to 10 years of work experience, the companys report said. Meanwhile, only 11% of those with under four years of experience were seeking the online courses. This could be because early-stage employees, i.e. fresh college graduates, often receive in-house training at their respective companies, Dalal suggested, so they dont have to seek out their own resources, unlike their more experienced counterparts.

Around 41% of those looking to skill up on Simplilearn were from Indias IT capital Bengaluru, which is home to the most tech professionals, Dalal said, besides startups and older IT establishments such as Infosys and Wipro. The Delhi-National Capital Region (NCR), which is now Indias hottest startup destination, followed with 25%.

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Automation will bring new jobs to India, and these are the skills needed to work with robots - Quartz

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Designing a power-supply system for industrial automation equipment requires a thorough understanding of the surroundings and conditions that affect the functionality of the wide range of equipment involved. The most important design decision is whether to use linear power supplies or switch-mode power supplies (SMPS).

Today, SMPS are the most popular because of their high efficiency. However, they do have downsides that make linear supplies more desirable. Linear supplies also have their disadvantages, but often turn out to be the best choice for industrial use. Even better is a have your cake and eat it too solution: Use a linear supply with low-dropout (LDO) regulators.

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Linear vs. SMPS

As mentioned, the primary reason for using switch-mode supplies is their high efficiency. Typical figures vary with the application, but efficiencies of greater than 90% are typical. High efficiency translates into minimum power loss in the supply with its attendant low heat dissipation. In large complex industrial settings with lots of equipment efficiency, power usage and heat dissipation become critical factors in terms of operating costs.

The main disadvantage of the SMPS is its noise generation. High-frequency pulse-width-modulated (PWM) pulses are filtered to form the desired dc level, but the resulting ripple and radiated or conducted noise generated can negatively impact the powered equipment and nearby devices.

Linear supplies with linear regulators dont have the noise problem. Furthermore, ripple is greatly reduced by large capacitive filters and the feedback action of the regulator circuitry.

1. Often, a traditional linear IC regulator architecture will use a Darlington bipolar series pass transistor.

The big issue with these supplies, though, is that the efficiency is very poor (Fig. 1). A series pass transistor between the dc input voltage and the regulated dc output requires a minimum amount of voltage drop in order to maintain regulation. This voltage, called the dropout or headroom voltage, is usually a minimum of 1.5 to 2.5 V or more.

Since the output current passes through the pass transistor, this device will dissipate a significant amount of power, all of which shows up as heat. As the input or output voltages vary, the feedback senses the change and drives the pass transistor to adjust its conductance to compensate from any variation. This linear operation requires the minimum overhead be observed to maintain regulation. The overall benefit is no noise generation traded off for efficiency.

One way to get the benefits of low noise and good efficiency concurrently is to use a LDO regulator.

LDO Operation and Benefits

One definition of LDO is a regulator that operates with a series-pass-transistor voltage drop of less than 1 V. A dropout voltage of 1 V or more defines a conventional linear regulator.

A dropout of less than 1 V can be achieved with a PNP bipolar series pass transistor, but modern designs generally use a P-type MOSFET with very low dropout voltages of less than 100 mV (in addition to low on-resistance) (Fig. 2). When working with low supply voltages of 3.3 V or less, low dropout levels become a significant percentage of the output, so less is more.

2. Heres a typical IC LDO circuit with a P-type MOSFET pass transistor.

The regulation process is similar to other series regulators in that any output voltage change is sensed and the gate drive to the MOSFET is varied to correct for the variation.

Key benefits of an LDO include:

The LDO is often used to power processors and field-programmable gate arrays (FPGAs) that require the fast transient response. And theyre ideal for critical linear circuits like signal-conditioning amplifiers, oscillators, and PLL synthesizers. In industrial-automation applications, LDOs make good regulators for sensors, data converters, and wireless/communications/networking circuits.

The Current-Limiting Issue

Some applications put excessive stress on power supplies, especially in industrial automation. High temperature and high voltages are very common. Another potential problem is excessive current draw or a short circuit. Sudden high current flow will typically damage the regulator unless its compensated for. That problem can be handled by incorporating LDOs with internal overcurrent protection.

Two basic types of current limiting are used in LDOs: brick wall and foldback. In the brick-wall method, a current limit is set and if that limit is exceeded, the LDO abruptly shuts down. The regulator continues to supply current at the cutoff level, but the output voltage is no longer regulated. The output voltage becomes the product of the current-limit value and the load resistance. The series pass transistor will continue to dissipate power until the internal protection process of thermal shutdown turns off the device.

The foldback method of current limiting attempts to keep total power dissipation at a constant level. If overcurrent conditions occur, the circuitry reduces the output current and theres a decrease in output voltage (Fig. 3). This keeps the power dissipation within the capability of the device. After that, thermal protection kicks in if elevated temperature conditions persist.

3. Looking at a comparison of output voltage vs. load current, it shows that foldback reduces the output voltage as output current exceeds the limit of the device.

Different LDOs use different methods of current limiting, so you should choose one that fits your application. For example, Texas Instruments offers the TPS7A16 LDO with brick-wall current limiting and the TLV71P LDO with foldback current limiting. More details on current limiting can be found at this reference.

Thermal Issues

While LDOs are more efficient than standard linear regulators, they still dissipate power. Most LDOs also include thermal-shutdown circuitry, which turns off the device if the temperature exceeds the limitusually in the 150-170 range. In some applications, a heat sink may be needed.

In addition, careful attention should be given to the thermal conditions in the power supply. Besides the thermal specifications of the IC itself, you should consider other factors such as PCB design and component placement in regards to the interaction with other devices. The greater the copper area devoted to the LDO, the better the heat dissipation. Other factors to consider are ambient temperature and airflow ventilation.

You can learn more about thermal considerations from videos that shows you how to measure thermal properties and how to avoid damaging an LDO through thermal excess. This and other LDO videos are available from Texas Instruments.

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LDOs Bring High Efficiency and Low Noise Regulation to Industrial Automation - Electronic Design

There is widespread concern these days that robots and automation will soon be permeating much of the American workforce -- taking over factory floors, performing hospitality jobs, becoming ubiquitous in the casinos of Las Vegas. Even Silicon Valley worries about automations effects, although they likely wont be as severe there as elsewhere.

Some recent studies add to these fears, predicting sizable job displacement from numerous forms of automation and artificial intelligence in virtually all corners of the economy. But just as automation will alter industries differently, its effects will be much more intensive in some regional economies.

To estimate the potential effects of automation in those areas, Governing utilized definitions in a University of Oxford study assessing the automatability of individual occupations, then compared them with the Department of Labors most recent occupational employment estimates for the 100 largest U.S. metro areas. About 65 percent of Las Vegas area jobs were found to be susceptible to automation, the highest in any metro area. Much of that stems from the regions large armies of servers, food preparers, cashiers and other occupations thought to be highly automatable. El Paso, Texas, and Cape Coral-Fort Myers, Fla., similarly employ many of these workers, and registered the next-highest shares of potential automatability.

Professors Carl Frey and Michael Osborne, who conducted the Oxford study, assigned a probability to each occupation by evaluating the extent to which its work activities require creativity, social intelligence and perception, and manipulation. Retail sales accounted for the single largest number of possible job displacements as a result of automation in most regions. The New York metro area, for instance, employs more than 500,000 retail salespersons and cashiers. Predominantly low-wage food service jobs are susceptible to drastic change as well, both in the United States and overseas. Robots will start delivering Dominos pizza orders in Hamburg, Germany, this summer.

Regions with higher education levels should fare better. But the Brookings Institutions Mark Muro points out that theres more to it than that. Physical jobs that are more complex or personalized -- the kinds you wont find on assembly lines -- may actually be less vulnerable to automation than routine office jobs. Often, lower-skill but physical, personal or direct-caring occupations seem quite durable, Muro says.

Middle-class, white-collar jobs, on the other hand, can be significantly liable to automation. A forthcoming report from Brookings reviews hundreds of U.S. occupations, finding use and knowledge of digital skills doubled between 2002 and 2016 and led to a wide array of jobs being digitized, including those of office clerks, customer service representatives and accounting workers. The middle is where there will be some of the most disruption, Muro says.

Some well-paying jobs in demand today arent off-limits from automation, either. A McKinsey Global Institute study concluded that some of the jobs most at risk involve data collecting and processing. Around a quarter of the activities of attorneys and physicians were deemed to be potentially automatable.

Large regions with jobs least susceptible to computerization, using the Oxford studys definitions, are high-tech centers, such as San Jose-Sunnyvale-Santa Clara, Calif., and Durham-Chapel Hill, N.C. Other metro areas with highly educated workforces such as Washington, D.C., and Boston similarly appear to have fewer jobs vulnerable to displacement. Regional economies relying heavily on education and health care may be less prone to automation because jobs requiring a high degree of human interaction are thought to be among the most resilient.

(Larger markers represent regions more susceptible to automation based on a University of Oxford study. View an interactive map here.)

Of course, widespread automation wont happen overnight. McKinsey projected that half the work activities across the economy today could be automated by 2055. An analysis by PricewaterhouseCoopers concluded that 38 percent of American jobs were at high risk of automation by the early 2030s. McKinsey studied prior cases of technological upheaval, finding that the time between initial commercial availability and peak adoption ranged between eight and 28 years.

The biggest unknown at this point is whether automation will eliminate more jobs than it creates. Automation itself isnt new, and prior advances in technology and industrialization havent brought about higher overall unemployment over the long term. But a growing number of academics are concluding that automation this time around could, in fact, wield noticeably more harmful effects on the workforce. One highly cited paper by economists Daron Acemoglu and Pascual Restrepo forecasts lower overall employment resulting from the introduction of more robots into the workplace.

Other researchers, notably ones at the Economic Policy Institute, argue that automation has not led and will not lead to higher joblessness. Experts appear to be divided almost evenly on this question: A 2014 Pew Research Center survey of experts found 48 percent agreeing that automation, robots and artificial intelligence will displace more jobs than they create by 2025.

While many unknowns remain, it wouldnt hurt for policymakers to start thinking about how to respond.

Some state workforce boards are looking at the issue. States already typically maintain labor market information divisions that project which occupations will be in demand in future years. Preparing farms and their workers for automation was the subject of a recent meeting of the California State Board of Food and Agriculture. While there arent yet many programs that specifically address automation, some states are engaged in activities that could help alleviate the impact of job losses. Apprenticeships are gaining a lot of attention and are expanding to health care, finance and other fields where they havent been common before. The model is being modified and theyre really trying to ramp it up, says Scott Sanders, executive director of the National Association of State Workforce Agencies.

For workers displaced by automation, community and technical colleges will play a crucial role in the pursuit of new careers. The federal government, however, has historically focused little on workforce training, spending much less than other wealthy nations do. We dont do training in America, we do education, says Anthony Carnevale, who directs the Georgetown University Center on Education and the Workforce. Our policy is: Go to college.

It was only a few short decades ago that computers began revolutionizing the American workplace. Regions and employers that were early adopters with skilled workforces are well ahead today, and its likely they will continue to be in the years to come.

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Is Automation Anxiety All a Hype? - Governing

NEW DELHI: Automation is bringing about changes in work choices like never before as some profiles get obsolete and new job roles make their way to cyber security, cloud and Big Data, among others, says a report.

According to a recent research by Simplilearn Career Data Labs, some of the job roles that may soon go off the radar include those of software test engineer, system engineer, data entry operator and the like.

New IT jobs that will be in demand are expected to be in segments like Big Data and data science, artificial intelligence (AI) and Internet of Things, cloud computing and cyber security, among others.

"The IT industry is seeing the impact of two major trends -- one, that of AI and machine learning. And second, that of legacy skill sets going out of date," Simplilearn Chief Business Officer Kashyap Dalal said.

Dalal further said that "while there is risk to jobs due to these trends, the good news is a huge number of new jobs are getting created as well in areas like cyber security, cloud, DevOps, Big Data, machine learning and AI. It is clearly a time of career pivot for IT professionals to make sure they are where the growth is".

Automation is gaining prominance in sectors like engineering, manufacturing, automobiles, IT and banking. With increasing adoption of automation, labour-intensive jobs are expected to take a hit.

According to a report by digital economy training company Simplilearn, roles such as data analyst and project manager will continue to generate interest, but the skills required to perform these roles will witness a shift.

The report noted that automation can never replace people. That said, to make themselves relevant, employees should evaluate the career choices of future and start bridging skill gaps to fit into the evolving business world.

Based on a survey of 7,000 IT professionals from key metros, the report said that over 50 per cent of IT professionals with work experience of 4-10 years have invested in courses and training programs to help them build new skills.

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Automation shaking up work choices, upskilling key - Economic Times

To help ensure the cybersecurity of self-driving cars, General Motors Co. has hired two well-known security researchers who hacked into a Jeep SUV.(Photo: Stan Honda / Getty Images)

To help ensure the cybersecurity of self-driving cars, General Motors Co. has hired two well-known security researchers who hacked into a Jeep SUV.

Charlie Miller and Chris Valasek have been hired by GM subsidiary Cruise Automation, an autonomous vehicle software tech startup GM bought last year, Cruise founder and CEO Kyle Vogt confirmed in a tweet Friday.

A GM spokeswoman said Monday that Miller and Valasek also would be integrated into GMs cybersecurity team led by Jeffrey Massimilla, chief product cybersecurity officer since 2014. They will work as software engineers.

Miller and Valasek will be focused on the many challenges related to securing the autonomous vehicle ecosystem, a GM spokeswoman said in an email. Our cybersecurity mantra recognizes that in order to prevent the worst, you need to engage the best. We believe we can build more secure systems by bringing on the people who excel at defeating them. Protecting the safety and security of our customers is of utmost importance.

The security researchers are known for their remote hack of a 2014 Jeep Cherokee that included disabling the SUVs engine functions and controlling interior features such as air conditioning, locks and the radio.

The hack was detailed in a 2015 Wired magazine article and led to Fiat Chrysler recalling 1.4 million vehicles that were shown to be vulnerable to computer hacking. Owners of Jeeps, Chryslers, Dodges and Rams with vulnerable entertainment systems were sent a flash drive to upgrade vehicle software.

Valasek most recently was security lead at Uber Technologies Inc., according to his personal website. The Pittsburgh resident said on the website that hes interested in automotive security research and reverse engineering, among other things. Miller most recently worked for Chinese ride-sharing company Didi Chuxing.

All automakers, including GM, have been ramping up cybersecurity efforts as self-driving vehicles inch closer to reality. Some, including Fiat Chrysler, have started to pay outside security experts bounties for their hacking information. Fiat Chrysler last year began to offer up to $1,500 bounties for information through a partnership with Bugcrowd Inc., a crowdsourced security-testing company.

GM in early 2016 bought San Francisco-based startup Cruise Automation to help it with autonomous vehicle software development. The Cruise team has grown from about 40 people in California to more than 100, and GM plans to hire 1,100 over the next five years.

The Detroit automaker has said it is giving Vogt responsibility for operations and financial performance of GMs autonomous vehicle business.

GM and Cruise are testing more than 50 self-driving Chevrolet Bolt EVs in Metro Detroit, San Francisco and Scottsdale. The company recently built 130 more self-driving Bolt EVs that GM said in June would recently be deployed for testing in the three sites.

mburden@detroitnews.com

(313) 222-2319

Staff Writer Ian Thibodeau contributed.

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GM hires Jeep hackers to join Cruise Automation - Detroit News - The Detroit News

MANILA - The shift to automation can displace 40,000 low-skilled workers in the business process outsourcing industry, but will open up job opportunities for nearly 700,000 higher-skilled counterparts, an industry official said Tuesday.

Low-skilled workers include receptionists and clerks. Job demand will shift to medium and high-skilled jobs that offer higher compensation, said Alex Tined, program director of the IT and Business Process Association of the Philippines.

"We need to teach them the new jobs. The challenge now is to make sure that we have people to do the mid and high skill jobs," Tined said.

Tined said some 388,000 jobs would be added to the middle level and another 309,000 to the high skill level, bringing the industry workforce to 1.8 million by 2022 from the current 1.14 million.

The BPO industry is a key job generator and source of dollar earnings that help strengthen the peso.

Tined said the Philippines had fallen to third place among the world's top BPO destinations, as India and China lure companies with more advanced technologies.

China is a relative newcomer to the race, previously dominated by India and the Philippines.

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BPO automation may displace 40000, add 700000 jobs - ABS-CBN News

Driverless semi trucks are expected to hit the road in full force as soon as 2020. While this will make the industry more efficient, the question over what happens to 3.5 million truck driving jobs remains.

We hear about the potential impacts of work place automation when it comes to trucking, manufacturing, retail and more. Right now there are 1.64 robots to every 100 employees in the U.S. and that number will likely only climb over time. Korea has 4.78 robots per 100 workers, Japan has 3.14 per 100 workers, and Germany has 2.92 per 100.

As the number of robots per worker grows, the cost of implementation for robots in the workplace will shrink. Eventually, it will become cheaper for technology to do the work that humans are currently doing.

Some of the top industries potentially impacted include:

Insurance underwriter

Farm laborer

Construction laborer

Fast food

Trucking

Mail curriers

A global average of 57 percent of jobs will be at risk to work place automation as the future grows. Its scary stuff. So the question becomes, how do we prepare for a future where jobs arent necessarily threatened by immigration, but by technological progression?

The struggle will likely be felt by millions of Americans. Strong political leadership can help smooth out the transition. Tesla and SpaceX CEO Elon Musk recently spoke in front of the governors association, with the suggestion of legislating the upcoming artificial intelligence boom.

Its hard to look at a possible bright side when the scope of the jobs created by the automation process isnt immediately clear. There are entire industries now that revolve around technology that wasnt here 20 years ago (cell phones for example), and that trend will likely become more explosive. There will be new careers and new fields permeating the workforce as we enter into an even higher-tech world. Someone will need to make and maintain the technology used.

This list of the 21 hottest jobs of the future still holds several staples such as nurses and elementary school teachers, but it also includes software systems developers, research analysts, computer and information system managers, computer system analysts, software application developers and more. These are the fields that may be most spared by automation and also the jobs that will likely have a hand in shaping the future of the country and the world.

The people in industries most heavily impacted by automation will no doubt struggle. The more you understand about the potential risks you face now, the better. It will be a tough reality for people with 20-30 years experience in these industries.

If we do enter into a situation with millions out of work, how do we prop the economy back up? Thats where universal basic income comes into play. There are a lot of questions surrounding this debate that will need to be answered.

Will a universal basic income work?

Do we have the political will? Right now it seems the government is more interested in tackling an immigration problem.

How much would be given?

How much would it cost and who would pay for it?

What kind of exclusions would we make?

Could this lead to an explosion of creativity and entrepreneurship? Or would it kill productivity?

Can governments continue to afford this on a long term basis?

Avoiding the risk

The main factor for whether your job is at risk for automation is how routine your job is. Everyone in the American workforce will need to look at how vulnerable there industry and specific job is to automation. They might need to be looking at the emerging alternatives as well to determine how to create the most viable future for themselves.

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Photo credit: Getty Images

Matt Brennan is a marketing copywriter, occasional parenting writer, and journalist in the Chicago area. He is also the author of Write Right-Sell Now.

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How Will We Deal With Workplace Automation? - The Good Men Project (blog)

There are three main factors contributing to the increasing interest in intelligent automation (aka robotic automation) Avanademanaging director Sarah Adam-Gedge (pictured) told iTWire.

The digital transformation wave is continuing to break across most industries, organisations are getting better at handling their data, and they are hitting a productivity plateau after offshoring and industrialising processes, they need to find new ways to improve their competitiveness.

A related issue, she said, is that there are jobs that people are increasingly reluctant to do, as in the case of Woodside Petroleum's experimental use of a NASA Robonaut.

But despite those improvements in data management, data is still one of the biggest challenges to adoption, suggested Adam-Gedge. It is not enough to merely apply fresh technology to existing data, so the area is "very much a work in progress." Organisations should be thinking in terms of "big insights" rather than "big data.

Pegasystemsvice-president of robotics Francis Carden has a somewhat different view. He sees robotic automation as "tactically strategic" in the sense that it allows existing processes to be streamlined as a stopgap until they can be reengineered.

Customers are demanding "modern" interactions with organisations, and "you can't do that with all this legacy (software)", he told iTWire.

But what you can do is look for the frequently performed, time-consuming manual tasks required by legacy software and automate those. For example, a customer or employee onboarding process that involves multiple systems can be made much faster through the use of automation.

Such projects can be carried out very quickly as a stopgap, while new software is implemented on the Pegasystems platform. This approach is being used by the company's customers in the banking, financial services and healthcare sectors, Carden said, adding that Pegasystems' local customers include Telstra, Westpac and ANZ Bank.

Companies using dozens of applications won't be able to compete with those using newer and more streamlined systems, he suggested.

For example, a chatbot built using this sort of technology can work, but it doesn't learn in the way an AI-based bot does. However, such projects have very quick time to value and so are "truly as tactical as it gets".

Apart from any other considerations, legacy systems are becoming increasingly expensive to run, so organisations need to declare them end-of-life. But they need to bridge where they are to where they want to be.

"A large number of Pegasystems customers are doing robotics" and the technology is providing a pipeline of new customers, he said.

He doesn't recommend this approach for customer-facing systems. Established organisations face competition from new companies with low costs, that are "personable," and offer a good user experience (think in terms of some of the newer insurance companies). Robots don't change the experience enough, he said, so it is better to move to modern software more quickly.

People are realising that we are approaching a point where big improvements can be made quickly by replacing legacy software, Carden said. But for now, large numbers of applications have been deployed to fill the gaps in old-fashioned monolithic systems, and that provides plenty of opportunities to gain value through automation.

Robotics "has got to be part of something else", he said, "we're interested in customers who want strategic change".

Forrester has noted the way Pegasystems offers a range of business applications based on the same platform as its digital process automation suite which includes robotic process automation and other functions.

Growing awareness of machine learning will lead to increased attention being paid to data, said Adam-Gedge.

There are also organisational issues, so leadership skills are important. In particular, employees may be "culturally hesitant" about the introduction of automation, with concerns about whether such systems will eliminate jobs, and whether they will actually work in the specific circumstances.

An "HR bot" might be good for handling many routine inquiries such as questions about the annual leave policy, leaving staff to concentrate on issues around the employee experience, wellbeing and wellness.

Or a smart augmented reality system may improve the likelihood that field service staff will be able to fix faults immediately.

Carden seemed sceptical about suggestions that automation would merely free staff to do the more interesting tasks. Saving time will normally mean fewer staff, he said, unless there's a lot of work that's simply not being done at present. (Another possibility is that the improvement in productivity will lead to extra business, providing more work for the employees. But since that's unlikely to happen overnight, it seems probable that some will be retrenched and then other people hired as business picks up.)

Adam-Gedge also pointed to the way "machines are able to do things we never could do", such as using sensor data to drive predictive maintenance programmes that have the potential to save millions of dollars by extending the useful life of assets.

A recent survey of organisational leaders found that more than half of the respondents regard automation as a way of augmenting rather than replacing people, she noted.

But just because it is possible to do something, that doesn't mean you should. This is an "extraordinarily hot issue", she said. Technologists need to understand what is possible in regulatory as well as technical terms, and consider the position of stakeholders with regard to what they are trying to achieve with automation, and what is legal and ethical.

Organisations are spending more time considering such issues, said Adam-Gedge, and are "no longer just giving a set of requirements to a technologist".

Setting the right boundaries makes it possible to seek the benefits of automation while avoiding its bad side.

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Two steps to automation - iTWire

The US presidential election last year was a choice between two second world war acronyms: snafu (situation normal, all f***** up) and fubar (f***** up beyond all recognition).

American voters faced a choice between a candidate who personified the political status quo, and a candidate who promised the disruption of that status quo. With Hillary Clinton, there was the certainty that nothing much would change. With Donald Trump there was the chance of quite a lot of change, but the risk was that it would be change for the worse. Twelve months ago, it was dawning on me that there might just be enough voters willing to gamble on Trump, knowing full well that the outcome might be fubar.

Since Trumps election, I have tried to swim against liberal opinion. The more commentators proclaimed the advent of tyranny and the end of the republic, the more I tried to argue that the Trump administration belongs firmly in the tradition of American populism. The more journalists cried Watergate, the more I tried to show that Trump isnt Richard Nixon: with his dynastic approach and louche personality, he more closely resembles John F Kennedy.

My goal has not been to defend Trump, but rather to expose the inconsistencies of his critics. However, the time has arrived to break the bad news to those who voted for Trump.

You wanted change. You got it. But the result is a political system that I can now officially certify as fubar. This is not politics. This is fubatics.

Seven months ago, House Speaker Paul Ryan was proclaiming the opportunity of a lifetime for Republicans. Having achieved unified government control of the White House and both Houses of Congress their party was poised to enact a transformative legislative programme: repeal and replace Barack Obamas Affordable Care Act, comprehensive tax reform and a roll-back of economic regulation.

Yet,the Senate could not even agree on a skinny bill to repeal just parts of Obamacare. The same week, the Republicans abandoned all hope of passing the border adjustment tax, without which there can be no permanent cuts in corporate and income tax. As for deregulation, this was also the week when Steve Bannon, the chief presidential strategist, said he wanted to regulate Google and Facebook like public utilities.

Wait. Right now Google and Facebook are free. By contrast, I pay hundreds of dollars every month to the utilities.

Fubatics is to politics what comedy is to news. Ever since Americans began to get their politics from comedians such as Jon Stewart and Stephen Colbert, the danger was that the politicians would respond by providing their scriptwriters with material for gags. We have now reached that point.

Newly appointed White House communications director, Anthony Scaramucci, last week told a New Yorker journalist that his colleague, chief of staff Reince Priebus, was a f****** paranoid schizophrenic, a paranoiac ... I want to f****** kill all the leakers and I want to get the presidents agenda on track. He took to Twitter to imply that Priebus was guilty of a felony in leaking details about his finances. By Friday, Priebus was gone. The previous weeks casualty was press secretary Sean Spicer. Next on Trumps hit list: Attorney General Jeff Sessions. Unified government? These guys are unified the way the cast of Reservoir Dogs were unified. Or maybe Goodfellas.

Meanwhile, in Silicon Valley, the plan to render most Americans, and most humans, unemployed goes forward. If you dont live in northern California, you tend to assume that it will be decades before self-driving vehicles are the dominant mode of transport.

Nearly half the jobs in America are at risk of being automated over the next decade or two

Michael Gove, the British environment secretary, announced that the sale of new diesel and petrol cars would be banned in the UK by 2040 to encourage people to buy electric vehicles. This surely underestimates Tesla founder Elon Musk, not to mention the car makers chasing him in the race to bring e-cars to the mass market. Goves worries about diesel fumes remind me of The Times 1894 editorial warning that by the mid-20th century every street in London would be buried under horse manure. Despite evidence of the accelerating pace of technological change, we humans remain chronically bad at making realistic projections about our economic future. The American Trucking Association says the number of jobs for truck drivers will be 21 per cent higher in 2020 than in 2010. Yet self-driving vehicles are already on the road in several US states.

There are 3.5 million professional truck drivers in the US. It is the most common job in most states. But they sit where drivers of horse-drawn carriages once were: on the brink of unemployment. Nor are they alone. Nearly half the jobs in America are at risk of being automated over the next decade or two, according to Carl Frey and Michael Osborne of Oxford University. Looking at global employment, the McKinsey Global Institute has concluded that half of todays work activities could be automated by 2055, but this could happen up to 20 years earlier.

Trump voters thought it was globalisation that destroyed the good jobs in American manufacturing. In reality it was globalisation and technology. Now technology is getting ready to destroy the not-so-good jobs too.

As an economic historian, I cling to the hope that predictions of the impending redundancy of humanity, like similar predictions at earlier stages of industrialisation, will turn out to be wrong. As a reader of Dostoyevskys Notes from Underground, I also expect bloody-minded humanity to put up more of a fight against the automation of the world than Silicon Valley expects. This is why Google and Facebook are the new targets of Bannons populism.

Yet, as I watched my son play gleefully with a toy robot called Robosapien, the Action Man we gave him for Christmas forgotten, suddenly I felt a sense of kinship with that poor, discarded doll.

The goings-on in Washington are the comedy politics of a distracted age. But the more attention we give @realDonaldTrump on Twitter, the less we pay to the economic revolution all around us. The future belongs to robotics, not fubatics.

Niall Ferguson is a senior fellow of the Hoover Institution, Stanford

More here:

Trump's comedy politics is distracting humans from the age of automation and looming job losses - South China Morning Post

I love watching my son mastera LEGO set. Logic is the key ingredient in putting a set together, especially the super complexmodels that require many hours to assemble.

The LEGO company is smart. For the complex sets, the company breaks the whole into units, which are packaged to be built separately. The assembled sections are then added together to create the overall object.

The unit approach makes it much less overwhelming, while also making it easier to find the right pieces. It also helps kids realize success as each section is completed.

An added bonus is that the sections become a pathway to producing something different and creative. Many times my son has reused those units by putting togethermodules from a variety of sets to create something different and original,thereby expanding his enjoyment of the toy.

Marketing automation has a lot in common with building LEGOs. Complexmarketing automation campaigns designed and built unit by unit areeasier and more effective than anentire campaign implemented as a single unit.

[Read the full article on MarTech Today.]

Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.

Read more here:

LEGO logic rocks marketing automation - Marketing Land

I was amused reading the recent back and forth between Facebook's (NASDAQ:FB) Mark Zuckerberg and Tesla's (NASDAQ:TSLA) Elon Musk. It is funny when two heavy hitters, both of whom arguably should have a good understanding about a given piece of technology, fall on such opposite ends of the spectrum about its capabilities. Essentially it all started when someone asked Zuckerberg what he thought of Musk and his warnings about AI being an existential threat to humanity. He responded saying it was very irresponsible, to which Elon Musk replied on Twitter that Mark has limited knowledge about the subject. Is one of them wrong and the other right? Yes, I believe so, but more about that later. This exchange also got me thinking, is this belief the source of the lot of claims Musk has made about the capabilities and development of Tesla's Autopilot system? In this article, I will look into this a little more and show you some of the challenges faced in computer vision that illustrate the difficulties faced by a primarily vision-based fully autonomous driving system like Tesla's Autopilot 2.0.

It was just over six months back that Elon Musk promised customers would start seeing FSD features in Tesla's AP2 system over the next six months at the latest. However, customers haven't even seen their "Enhanced" Autopilot match the performance of the previous version of Autopilot let alone see any unique FSD features.

Now for anyone familiar with the technology, the fact that Tesla is facing a lot of challenges comes as no surprise. Unless Tesla makes significant strides beyond the current, state-of-the-art computer vision, I do not believe there is any way it can truly have a competent fully autonomous driving system under its current Autopilot 2.0 configuration. However, this is exactly what Tesla has been "promising" going as far as to hint that it would have details on a fully autonomous ride-sharing platform before the end of this year. By the way, that text hasn't changed since last year, so I guess we should now expect these details by end of 2018?

Source: Tesla

For a long time now, I had said Elon Musk and Tesla have been making knowingly misleading statements about the potential future capabilities of their system. However, as I hear his views more and more, I am starting to question if he really understands the technology and how it works. Before I go into this, let me take a step back and talk a bit about what has caused the recent revolution in the field of AI.

People have been using computers to automate a lot of work that humans have traditionally had to do manually. Indeed computers now encompass all aspects of human life. However, there were some problems that computer programmers found hard to write solutions for. One of the best examples of this is pattern recognition for example in the form of computer vision.

I can easily spot my wife in a large crowd of people, but if someone asks me how I do it, I will find it hard to describe what features I rely on to identify her. This is also one of the reasons witnesses find it hard to describe a potential suspect without the help of a sketch artist. It is generally hard to codify how the human brain interprets patterns from such visual data. This is where the idea of deep learning with large Convolutional Neural Networks comes in handy. The basic idea is that rather than trying to identify what features the system should look for, you instead just feed the system lots of data and have it learn the features that will help it identify similar objects.

The only problem here was that it took an excruciatingly long time to train a complex "Deep" network using large training datasets. With the advent of the use of GPU processing in training these systems, we are now able to use large amounts of data to train them in a reasonable amount of time. A job that would take weeks to months of running on a large CPU cluster earlier is now possible in a few hours to a few days, and this vastly expands the practical applications of these kinds of systems in pattern recognition. Over at FundamentalSpeculation, our price action based Momentum model is a result of harnessing this power of GPU processing in training.

However, at the end of the day, it is important to understand that pattern recognition is all that these systems are doing. It is not that they suddenly have a deeper understanding of what the objects in the picture represent. This is well illustrated for example by the work of Papernot, et al. in a recent paper where they used an adversarial system to trick a classifier that identifies road signs from MetaMind. This is an instance where there is an adversarial system being used specifically to target the classifier. But also consider edge cases where there is graffiti or a sticker or something similar on the sign and you realize there can be more benign instances where this can become a problem.

Source: Papernot, et al. The image on the left is an original image of a stop sign. The image on the right is a perturbed image that causes the classifier to mis-classify it as a yield sign even though it looks the same to the human eye.

To perform a real-world and properly-blinded evaluation, we attack a DNN hosted by MetaMind, an online deep learning API. We find that their DNN misclassifies 84.24% of the adversarial examples crafted with our substitute. -Papernot, et al.

The same concept also applies to achievements in the field of deep reinforcement learning. A lot of people including me celebrated when DeepMind's AlphaGo beat the world's best Go player earlier this year. However, even in this example, if the size of the board was any different than what the system was trained on, it would have failed miserably.

Humans have a tendency to see a machine perform a particular task and think of it as having a similar level of competency to a human capable of performing the same task. This generalization cannot be applied to the field of Machine Learning/AI. To be clear, I am not saying automation will not cause massive disruption to the economy. It has the potential to displace a lot of jobs. However, the idea that applications of "Narrow" AI that are becoming prevalent today are an existential risk and need to be regulated is silly. It is also the reason why "billions of autopilot miles" is a silly metric to gauge any potential advantage Tesla may have over its competition.

Driving a car is a very complex task. The reason the average human is reasonably good at it is because humans have "intelligence" which allows them to have a high level understanding of their environment and handle most of the edge cases fairly easily. This is fundamentally not true for AI systems we have today. When you think of these systems in terms of "automation" rather than "intelligence", you start to realize some of the hard challenges that need to be overcome. To top it all, Tesla's attempt to try to achieve this using a primarily vision-based system if anything puts it at a significant disadvantage to the rest of the competition.

So what does this mean for Tesla's Autopilot system? Firstly, a big part of my critique about its design is that it has minimal redundancy in its system. It is primarily a vision based system. However, this idea is sometimes challenged by stating that it has multiple cameras that offer redundancy. I don't mean to pick on my fellow contributor ValueAnalyst, but this was the most recent exchange in writing I remember having about this topic in a recent article I published about Audi's (OTCPK:AUDVF) new Level 3 system.

He is not alone in making this assumption. There was also a recent paper claiming why adversarial attacks like the one I talked about earlier do not apply to autonomous vehicles because there is redundancy in the various angles and scales at which the same object is observed and this defeats instances of mis-classification. What I find really funny is the rebuttal to this argument came from Musk's very own OpenAI.

We've created images that reliably fool neural network classifiers when viewed from varied scales and perspectives. This challenges a claim from last week that self-driving cars would be hard to trick maliciously since they capture images from multiple scales, angles, perspectives, and the like. - OpenAI Blog

Tesla's challenge though is even bigger. What we have been talking about so far is classification of well-defined categories of objects. Tesla's system however not only has to identify and classify these well-defined objects but also reliably identify any other potential object that is an obstacle in its drive path without false positives. This makes it a significantly harder problem. Again, I'm not saying the systems won't improve. However, the current state-of-the-art systems are not reliable enough to do this, and there is no reason to believe Tesla has surpassed the state of the art in this field. This makes Tesla's claim of achieving full autonomy in this short time frame all the more ridiculous.

None of this would matter that much if everyone understood that this as a field of research with future potential and not factor in its impact into current valuations. However, this is not the case. Again, I don't want to pick on any one person, but I'm drawn to Morgan Stanley's Adam Jonas. He is currently neutral on the stock after it reached his price target, but let's take a look at what got him to that price target. I remember watching one of his interviews on CNBC a few months back and having a hard time stopping myself from throwing stuff at the television to stop the insanity. What was really amazing about his performance was his confidence in talking about a topic he clearly has no understanding about. I highly recommend you watch his full interview.

We continue to believe over 100% of the upside from the current price to our $305 target can be accounted for by the value of Tesla Mobility, an on-demand and highly automated transportation service we anticipate to be launched at low volume in 2018. - Morgan Stanley

In a note he sent clients earlier that month, he tried to break down the prospects of the company by segments. He had assigned zero value to Tesla Energy because of its negative margins and he believed any prospects for this segment would be a rounding error in the grand scheme of things. He was significantly below the Street and management on the sales volume for the Model 3 while being higher than most on the average selling price of the Model 3 ($60,000). He spoke about some of his assumptions in an interview with Bloomberg at the time. He also is not all that very bullish on the sale of electric vehicles to individual customers. He gets to his valuation based on the assumption that Tesla will have a deployable autonomous driving system that can be used for ride-sharing within a Tesla Network.

"Well, we think the electric cars for private use really are ... for human driving pleasure for wealthier individuals. That's why it's so important that in the shared model where you're not driving 10,000 miles a year, but 50 or 100 in a fleet operation, then the economics of electrification you can get that pay back period under three years. That's the game changer - shared." - Adam Jonas, Morgan Stanley

So now what happens if this possibility evaporates? How much real demand would there be for a $35,000 electric vehicle if the possibility of generating revenue via participating in an autonomous ride-sharing network goes away? Forget even that, how many people are really interested in a midsize luxury sedan if the convenience of autonomous driving is taken away? Consider the volume of all Small/Midsize Luxury car sales in America last year shown below:

Source

The entire Small/Midsize Luxury segment sold a little over 800,000 vehicles across all manufactures and models in the US in 2016. Without the prospects of autonomous driving, this will be the target market for the Model 3. Further, as other manufacturers start to bring some of their more advanced driver assist and limited self-driving features to lower-range models, Tesla, relying primarily on its vision-based system, will have a hard time keeping up with the functionality offered by its competitors.

For a long time now, I have believed Elon Musk has been misleading TSLA shareholders and customers about the potential and development curve of Tesla's Autopilot system. While I still believe that, I am now starting to question whether he genuinely understands the capabilities and limitations of narrow AI systems. At the end of the day, neither option is good for Tesla shareholders. If and when the Model 3 starts to ship in large volumes, those future customers will have a lot of expectations for the autonomous driving technology promised to them and they may not be as forgiving as some of the early adopters have been so far.

Disclosure: I am/we are short TSLA.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Additional disclosure: The Content provided in this article should be used for informational and educational purposes only and is not intended to provide tax, legal, insurance, investment, or financial advice, and the content is not intended to be a substitute for professional advice. Always seek the advice of a relevant professional with any questions about any financial, legal or other decision you are seeking to make. Any views expressed by Laxman Vembar are his own and do not necessarily reflect the view, opinions and positions of FundamentalSpeculation.IO. Finally, you should not rely solely on the information provided by the models on FundamentalSpeculation.IO in making investment decisions, but you should consider this information in the context of all information available to you.

Link:

Automation != Intelligence - Seeking Alpha

In a monthly series, menu trend analyst Nancy Kruse and NRN senior food editor Bret Thorn debate current trends in the restaurant industry. For this installment, the two discuss robots in restaurants.

Nancy Kruse on the rise of robots:

When it comes to research, Im stubbornly low tech. Im embarrassed to admit, Bret, that I keep old-fashioned subject files full of clippings on hot topics, a practice that I returned to after an early, unsuccessful attempt to go paperless. (Dont judge me, but I also prefer real books to Kindles and traditional newspapers to iPads.) Based on the burgeoning size of my file on the subject, it is ironic, then, that robotics and their impact on the restaurant industry is a major hot-button issue of the moment. Just consider this random sample of articles:

In June, Entrepreneur magazine asked the rhetorical question When Will Robots Finally Take Over the Fast-Food Business? and proceeded to forecast that quick-service dining is inevitably headed to a largely automated future.

Operators who have jumped into robotics have predictably grabbed headlines, like Zume, a pizza joint in Northern California that uses robots to make its pies. Down the coast a few hundred miles, Pasadena, Calif.-based CaliBurger uses a robot to flip hamburgers, and airport-concessions titan HMS Host has tested a robot at one of its pubs to engage consumers with its food and drink offerings. As an aside on these last two, there seems to be an attempt to humanize the bots; the former is dubbed Flippy and the latter is called Pepper.

Its not surprising that early digital adopters like Dominos Pizza, which blazed a trail and boosted its business with its sophisticated ordering app, are actively experimenting with robots. After its initial trial run in New Zealand, Dominos DRU delivery robot was dubbed cheeky and endearing in a press release, another example of anthropomorphism that suggests the little guy dispenses one-liners and hugs along with its pizza.

The topper, though, is surely KFCs H.A.R.L.A.N.D., a robotic Colonel Sanders that accosted unsuspecting customers at selected drive-thru locations and used technology to make the drive-thru operators voice sound just like Sanders Kentucky drawl. As a promotional gambit, it may have been superior to some of his white-wigged, real-life impersonators, like the unnaturally tanned, B-list actor George Hamilton, who portrayed him in a TV commercial sometime back.

At CaliBurger, a robot named Flippy flips hamburgers.

While theres obviously a great deal of interest in the subject, I think its a little early to say exactly how robotics will impact our business in the long term. Of course, that hasnt stopped legions of prognosticators and doomsayers, most of whom maintain that this all spells the end for low-income workers, especially those in the back of the house. But early results suggest otherwise. The Entrepreneur story quoted a scary statistic from consultants at McKinsey & Company that estimated that a hefty 73% of foodservice activities have the potential to be automated. However, theres a distinct disconnect so far between potential and actuality, as the article goes on to describe how Panera Breads ambitious 2.0 initiative to implement mobile and kiosk ordering has actually resulted in more employees per location. It turns out that digital ordering increases both the volume of orders and their size, which necessitates extra labor to handle the flow. And while Zume Pizza executives say that the operation does employ fewer people than comparably-sized competitors, the chairman of CaliBurger believes that Flippy wont replace workers, but will free them up for less repetitive tasks that add value to the patron experience.

It strikes me that a couple of things are worth keeping in mind as the debate revs up, which it certainly will. First, in all the piles of papers written on the technology, none has suggested that robots can or will replace the creative talents of the chefs who cook up innovative dishes in the kitchen, negate the continuing importance of the face-to-face factor that is the foundation of hospitality in the dining room, or displace the talented concept developers including those behind Zume Pizza and CaliBurger, who keep the industry vital and vibrant.

Theres also a sense of dj vu all over again, as the robotics uproar harks back a time maybe 25 years ago, when we found ourselves enmeshed in a similar controversy.

Computers were coming into their own and bringing with them dire predictions about the outlook for the foodservice sales function. Sales reps for distributors and manufacturers were put on the endangered species list, the futurists insisted, and slated to be replaced by the customers computer keypad.

Its evident that no such thing transpired. The computer didnt replace human interactions; rather it made them faster and more accurate, facilitated the flow of information and enhanced problem solving. As a bonus, it also relieved weary reps from having to lug around a 30-pound order book.

KFC has a robotic Colonel Sanders named H.A.R.L.A.N.D. that appeared at select drive-thru locations and used technology to make the operator's voice sound just like Sanders.

My hunch is that well see a similar dynamic here, as robotics ultimately helps foodservice employees rather than hindering them, and reorganizes them, but doesnt replace them. Having already confessed my Luddite use of clipping files, Bret, this discussion is a bit above my pay grade. So would you care to wade into the debate? Im interested in your thoughts on the subject, and just for the record, I dont believe you have anything to fear when it comes to man vs. the machine. In my humble opinion, youre way too cheeky and endearing to ever be replaced by a robot.

Bret Thorn on the ongoing shift:

Nancy, I love technology. I love it! I love my Kindle that weighs less than a book, doesnt use paper and lets me look up the meanings of words just by touching them. I love my completely searchable computer files of old menu items that can tell me, for example, what chains used asparagus last spring. I like catching up on the news on my laptop or phone (I dont have an iPad; I love technology, but Im also cheap).

I dont have much use anymore for newspapers or magazines I dont miss their feel or smell or whatever people nostalgic for those things miss and although my desk is cluttered with cookbooks and other paraphernalia, theyre just there because I cant figure out who to give them away to.

I look forward to what new technology has to offer, in foodservice as much as in any other facet of life. Panera Bread and other chains have already seen success with people ordering and paying for their food online and then showing up to collect their order thats already waiting for them on a shelf. Its seamless and free of cumbersome interactions with humans.

I like humans, but on the transactional occasion that a limited-service restaurant experience generally is, I dont see a need for one to be between me and my sandwich.

And there are concepts like Eatsa, where guests order, customize and pay for everything via kiosk. Its then assembled behind closed doors (Eatsas founders indicate that theres some automation in the meal preparation, but they also insist that the details are secret) and appears in a window for the customer to collect, like magic.

Or like an automat from the 1950s.

At Eatsa, customers pick up their orders in a cubby.

People have been worried about robots taking our jobs since the term was coined, according to a National Public Radio story form 2011, in 1920 by Czech playwright Karel apec. According to science historian Howard Markel, the word was derived from rabota, an Old Church Slavonic term for forced labor, and apec used it in the play R.U.R. or Russums Universal Robots, to describe soulless people flesh-and-blood, not metallic who were mass-produced to do all of our work for us.

As robots almost always do in fiction, they eventually rebelled and killed most of the humans.

In 1952, Kurt Vonnegut Jr. wrote Player Piano, about a dystopian future in which humans are divided between scientists and such who have jobs, and everyone else, who has been essentially outsourced by machines.

Its an old, tired, but nonetheless terrifying plot that gets recycled with each generation, both in reality and in fiction.

I agree with you that restaurants will see more automation, and I also agree with you that the results will be that workers jobs will change. The Panera example that we both cited illustrates that beautifully.

As the chain becomes more efficient, more people are required to prepare the food, but also as technology shifts, as a Panera executive explained to me as their 2.0 system was being implemented, humans have to be available to help guests with the ordering kiosks.

Panera Bread's initiative to implement kiosk ordering has resulted in more employees per location.

Additionally, Panera has worked to make its service better, hiring people to deliver food to tables for those who dine in the restaurant.

I recall that a few years ago you coined a phrase high tech, high touch. The technology improves on clunky points of friction like ordering and payment, while human beings check in with customers to make sure theyre happy and to resolve any problems that come there way.

Another example is Pizza Hut, which is simultaneously improving its delivery algorithm to be more efficient, but also hiring 14,000 more drivers to carry out that more efficient delivery.

Pizza Hut is improving its delivery algorithm to be more efficient, but also hiring 14,000 more drivers to carry out that more efficient delivery.

Will self-driving cars eventually replace those drivers? Maybe, and that could well free up those drivers to fill some yet unforeseen role. I dont know what it would be, but here in the publishing world we have a whole team of people whose job is engagement or figuring out the best strategies to present our words in ways that will be efficient and enjoyable for our online readers

That wasnt a thing when I started this job 18 years ago, working for what at the time was a weekly news magazine.

Self-driving cars may eventually replace delivery people, freeing them up to fill some yet unforeseen role.

Ah, but what about the kitchen? Surely automation will cut labor there, you might say.

Perhaps, but it seems to me that just as human hospitality remains important in many front-of-the-house situations, culinary creativity is also at the heart of foodservice.

You probably have read about efforts by the IBM supercomputer Watson to develop menu items. Back in 2014 the machine that was able to win at Jeopardy and is reportedly being put to work to help cure cancer also was put to work in menu ideation at the Institute of Culinary Education in New York City.

The IBM supercomputer Watson has been put to work in menu ideation.

Watson was fed a huge database of recipes, nutritional information and data on the molecular composition of ingredients. Then it was instructed to come up with flavor combinations from different culinary traditions say, Baltic combined with Korean and North African combining them in a way that chefs wouldnt have thought of. The chefs could specify the protein or other key ingredients they wanted to use and Watson would spit out combinations that might not have gone together traditionally, but that ought to work from a molecular perspective.

But all Watson could do was list ingredients. It was still up to chefs to develop dishes from them, and I think it will stay that way for many years to come.

Oh, and thanks for valuing my cheekiness and endearing qualities over DRUs, but lets wait and see what the next round of artificial intelligence looks like.

Nancy Kruse, president of the Kruse Company, is a menu trends analyst based in Atlanta and a regular contributor to Nations Restaurant News.

E-mail her [emailprotected]

Contact Bret Thorn [emailprotected]

Follow him on Twitter:@foodwriterdiary

Read the original post:

Will automation supplant the restaurant worker? - Nation's Restaurant News

Technology, be it the driver-less cars or the ubiquitous smartphone, is impacting every sphere of our life.

Technology-driven automation is omnipresent and pervading our lives like never before.

From robots and chatbots to virtual/augmented reality, machine learning, artificial intelligence (AI) and beyond, the physical space is littered with digital influence.

The impact of increased automation is already upon us and influencing our lives in all possible ways. Up till now technology adoption has never been so rapid, versatile and secular but the presence of connectivity has enabled this growth.

The focus of this narrative will be to explore how exactly human life gets affected because of these inevitable technology trends. There are six such changes that look imminent.

The newer technologies are enabling embryonic assessments in early stages, hence alleviating the need for morphological assessments where high degree of human skills was required. The issue is that morphological grading by humans leads to wide inter- and intra-operator variation. These long-standing difficulties may now be improved by using advances in AI. Thus, mathematical variables derived from time-lapse images of embryo development may now be used such that an algorithm can classify images of an embryos development automatically, and so remove the human variable from the crucial task of morphological assessment.

This was also highlighted in study presented on July 4, 2017 at the 33rd Annual Meeting of ESHRE in Geneva. Start-up Deep Genomics is leveragingAI to helpdecode the meaning of the genome and their learning software is developing the ability to try and predict the effects of a mutation based on its analyses ofhundreds of thousands of examples of other mutations even if theres not already a record of what those mutations do. Another example is the case of actress Angelina Jolie where she had a one recessive gene in her genome that was predicted using deep learning algorithms on her DNA sequence using the data from past studies, which predicted that she is susceptible to breast cancer. She underwent pre-emptive mastectomy to prevent herself from cancer. The confluence of medicine and technology will bring unprecedented transformations in human life.

Another biological victim of the digital automation will be ubiquitous handwriting skills. Already most of the content thats getting produced and published is digital. Handwriting skills have already suffered as most of the content gets digitally typed and then printed if at all needed in the physical format. Dematerialisation has already inflicted the damage on the physical copy. It is now rare to write something on paper except when its your own signature, which is also digitally available now. Handwriting is almost nostalgic now. More and more people are digitally publishing the content online with handwritten notes becoming virtually non-existent. When was the last time you wrote a handwritten letter or note to your friends? The growth of virtual assistants like Apple Siri, Google Assistant or Cortana that can translate the verbal instructions into written word will further deteriorate the physical handwriting practice whatever is left so far. This may impact the anatomy of hand including the fingers, which may become less flexible, and thinner to aid typing. Maybe in the future the meta-carpel and carpel joints undergo significant changes as they are no longer used for writing purposes.

The third biological influence will be on the eyes. The sheer amount of information flow thats happening is coming from social media apps, devices, digital displays or the web, which is exerting enormous strain on the eyes. Reading has exponentially multiplied, as is typical of information age where status quo is consistently challenged. The knowledge bust thats happening is fuelling the information fire. With faster and better technology, development and evolution is becoming possible in every sphere of our life, be it medicine, law, science, engineering, education, hence necessitating the constant need to upgrade and update. The concomitant impact of it will be largely borne by eyes. With so much to read and ingest, the shape of our eyes may get adapted over a period; they may become enlarged or may be more bulged. In fact, the underlying neuron system powering the vision may undergo subtle changes as well because of the way the things will be perceived and seen in the VR, AR-infected world.

Another impact is going to be on the neck and the backbone. With the advent of smartphone the average time we are spending on the device is about 180 minutes. Yes, thats correct: three hours per day. We are continuously stretching our necks for longer periods of time, which is therefore bent most of the time. Now most of things can be actioned, can be monitored or searched on phone, which is reducing physical movements all the time. For example, you can monitor your employees working remotely on your phone using the GPS and camera, thereby obviating the need for physically moving yourself. This is not only forcing your neck to constantly gobble up the data thats being ejected on your smartphone screens but also increasing your seating time, making you more sedentary than ever. Seating continuously for longer periods of time puts pressure on the spinal cord and the vertebrae. Hence all these lifestyle changes will have an anatomical impact on our spinal cord and neck in the time to come. As a result, the spine may become more rounded and short. It may be so that in future humans have few extra movements in neck due to some extra cervical spine joints.

With the problem of plenty, memory will be worst affected. As more and more information is produced collaboratively and co-operatively on social platforms lesser and lesser will be retained. Also, with advanced search algorithms by our side, who needs to worry about remembering something? Learning by rote will be extinct in future. This will impact the memorability of human beings as lesser effort will be given to remember anything. The incentives that existed in the past to learn mathematical tables or capitals of the countries have ceased to exist. Society is now rewarding people who have application skills, who can combine expertise in multiple subjects to yield insights and solve layered business problems. The demand for people who can blurt out facts has completely evaporated. The processing thats required to memorise things will weaken during time, leading to complete adaptation of the neurons and brain functions that govern memory.

With so much data floating around us and machine learning algorithms parsing them, AI is getting adaptive by the day. The rich data thats getting ingested is only leading to more informed choices and better decisions. The role of luck, or the unknown is getting subsumed by intelligent analytics or processed data that was earlier not available. The traditional belief structures rooted in religion of God are getting displaced by more data-centric approach or Dataism, as Yuval Harari calls it. So much structured and unstructured data is getting generatedbe it location data, emails, OCR processed reports, Facebook posts or likes, WhatsApp messages, tweets etc.which enables algorithms to do the data analysis and decipher the subterranean trends, patterns and phenomena underlying these data sets, paving the way for better understanding of society and things around us. As more and more evidentiary proofs are available for our actions, the needle of our belief will keep swerving away from the universality of God.

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How technology and automation will impact human evolution - YourStory.com

I love watching my son mastera LEGO set. Logic is the key ingredient in putting a set together, especially the super complexmodels that require many hours to assemble.

The LEGO company is smart. For the complex sets, the company breaks the whole into units, which are packaged to be built separately. The assembled sections are then added together to create the overall object.

The unit approach makes it much less overwhelming, while also making it easier to find the right pieces. It also helps kids realize success as each section is completed.

An added bonus is that the sections become a pathway to producing something different and creative. Many times my son has reused those units by putting togethermodules from a variety of sets to create something different and original,thereby expanding his enjoyment of the toy.

Marketing automation has a lot in common with building LEGOs. Complexmarketing automation campaigns designed and built unit by unit areeasier and more effective than anentire campaign implemented as a single unit.

From a psychological standpoint, smaller modules are easier to focus on than one large overwhelming campaign. By breaking down a campaign into small units, it becomes much easier to tackle and the focused-brain can hone in on exactly what is needed, as Eric Ravenscraft wrote in Lifehacker.

Designing modules within the marketing automation platform can lead to reuse. Different subsets can be used in different campaigns.

The units (for example a campaign flow or contact filter) can either be copied and the new version slightly updated or they can simply be used as they are. This saves time when building new campaigns.

Testing is also simplerformodularly-designed campaigns. Spotting and fixing issues at a unit level is easier than at the overall campaign level when its not clear what is causing the problem.

Optimization of a modularly-built campaign allows for the pieces to be taken apart, streamlined and put back together. Conversely, if an entire campaign is intertwined and locked tightly together, enhancing the whole is a very complex task.

A modular design allows thecampaign to launch in-market faster than acampaign designed as a single unit.

Single unit campaigns require all the content, landing pages, and emails be built before kick-off . Modularly-designed campaigns only need the initial logic flow to go to market. Additionally, if the flows are the same across buying cycles (or modules) copying them will save time.

Make each component of your marketing automation campaign a separate module. For example, each form, landing page, segment, filter, data store, field merges, dynamic content, etc. should be developed separately.

Units in a modularly-designed campaign interconnect and communicate, necessitating the use ofconsistentdata points throughout. For example, if a filter excludes one demographic by eliminating a certain value, other filters using that demographic should use theexact same value (even if the same result could be achieved a different way).

To create a campaign like a LEGO set, start at the lowest component level. Design first the data components, then the field merges, dynamic content, and forms that interface with those data components. Lastly, build out the landing pages, emails, and, finally, the campaign logic flows that use those units.

Test each unit as a single entity before incorporating it into the overall campaign. Do the same thing when the module is copied for reuse. That way you flush out any issues when its a single unit and not when there are multiple versions of it that you must chase down.

For example, when creating a landing page with a form, test that by itself first. Ensure the UI looks as expected in all browsers. Confirm the form functions as designed and that the data collected from the form saves correctly.

Once validated, test the landing page from the link in the email. Now, if something is not working, its easy to isolate the issue and resolve it beforeit has been propagated to multiple units that all need fixing.

Design each buying cycle of a campaign as a separate module. Use linkage to send contacts from one buying cycle to the next.

This makes the campaign logic easier to read when you open it back up in the future. At the same time,smaller modules are easier to reuse.

More importantly, by modularizing the buying cycle, it makes it easier to work in all the nuances of the business logic and to launch into the market sooner.

Implementing marketing automation as LEGO sets empowersyou for success, SixthDivision founderBrad Martineau explained in a podcast extolling this LEGO method. With a clear vision of the overall business need and associated strategy broken into individual components, campaigns become less overwhelming to build and simplerto put into the market.

Some opinions expressed in this article may be those of a guest author and not necessarily MarTech Today. Staff authors are listed here.

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LEGO logic rocks marketing automation - MarTech Today

More efficient lighting and climate control is one of several cost-saving benefits a smart building can offer your customers.

Smart buildings are on the rise around the world as companies recognize the potential cost savings of automation.

With the advent of the Internet of Things (IoT), every building with an integrated security and access control system has the capability to also integrate the buildings energy use, water use, ventilation and more.

Here are five steps to ensure successful automation of a commercial facility.

The first step is to show your customers the potential savings by conducting a thorough cost analysis. When surveying, you should look at everything from air handlers and chillers, to irrigation and what types of lighting are currently in place.

Be sure to also include details like switching to LED lighting, and updating compressors and chillers, and show the total potential cost savings. Buildings waste a lot of energy.

Simply propping a door open can cause the automation system to go into overdrive, pumping out air and creating significant energy waste. The ROI on building automation can sometimes free up money for other projects, while enhancing technology, comfort and security.

Theres an ongoing shift in the decision-making authority from facility managers to the IT leadership. This can be problematic, as many CIOs are unfamiliar with the challenges of maintaining a facilitys physical security.

Facility managers can be equally frustrated by unfamiliar IoT technology. Helping to create or improve the relationship between the CIO and the facility manager is crucial.

Educating the CIO about physical security, and bridging the knowledge gaps for the facility manager with smart device technologies will be essential as the industry moves to a more IoT-centric mindset. Providers and integrators should present themselves as a coordination point.

As with any new technology, there will be those who are hesitant to embrace the change. For instance, the IT director may have concerns about putting all their eggs in one software basket.

When a building is fully automated and networked, a failure in one area can cause failure in others. There may also be network bandwidth limitations that will have to be addressed to handle the amount of data that will becollected and shared between the various components of an automated system.

Concerns can usually be alleviated through detailed communication and concrete information about how the buildings systems can live side-by-side and how integration can benefit the customer in the long run.

The most important thing is to ensure that everyone has an opportunity to voice those concerns at the beginning.

To ensure the long-term success of a project, its crucial that the technology specified is future-forward and will flex and grow as the institution does.

The transition to new technology is never seamless, but there are solutions that can simplify the process. Look for systems and devices that are open source in nature; meaning, they can work together or can be easily integrated with each other.

Choosing proprietary versus open systems and devices could limit overall functionality and long-term adaptability.

Transitioning to a fully optimized smart building may seem overwhelming at first. It can be helpful to outline a series of goals with timeline milestones set.

60 days: Set goals for improving efficiency. Compare energy costs across multiple locations to establish a baseline of use and areas of loss/waste.

Six months: Use the data from your test location to establish an initial ROI and look for areas to further improve.

12 months: Track energy use at all locations to measure energy savings and establish overall ROI.

24 months: Develop a long-term plan for energy savings, including how to integrate new facilities into the overall solution. Experienced players in the security space understand there are no shortcuts.

The adoption of IoT technologies and tools will initially grow at the pace at which industry experts can support it. Wait too long and the space will be disrupted by external forces driven by consumer demand.

Minu Youngkin is Marketing Manager at Allegion.

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5 Steps to Successful Smart Building Automation - Security Sales & Integration

BBC News

The automation-resistant skills we should nurture BBC News If these jobs can't be automated, and will continue to be necessary into the future, workers with emotional skills will be highly in demand in the coming decades. But, right now, the jobs that depend most on these skills are often badly compensated: a ...

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The automation-resistant skills we should nurture - BBC News