Friday, November 27, 2020

"Robots in warehouses: job killers or indispensable?"/ "The burgeoning market for artificial intelligence"/ A Christmas present for an autistic man


Nov. 30, 2016 "Robots in warehouses: job killers or indispensable?": Today I found this article by Chris Atchinson in the Globe and Mail:


The days of warehouses bustling with workers to pick boxes and fill orders could soon be a thing of the past if robotic automation continues to gain momentum.

Robots are already rapidly delivering efficiencies as organizations across North America reinvigorate their logistics facilities with fast-moving machines.

Not surprisingly, these non-sentient additions are also generating a high degree of anxiety among some workers who fear for their jobs as robots accelerate their march into the workplace. Not without cause: 58 per cent of chief executive officers from 140 global companies planned to decrease their employee head count over the next five years as a result of robotics, according to a 2014 leadership survey by consultancy PricewaterhouseCoopers LLP.

And in Canada, between 1.5 million and 7.5 million jobs could be at risk of automation in the next 10 to 15 years, according to a report just released by the University of Toronto’s school of public policy and governance.

Need for efficiencies

But the flip side is businesses need these efficiencies to survive in an increasingly competitive landscape with an aging work force, experts say. However, Canadian companies lag competitors abroad in introducing warehousing automation, according to Marc Wulfraat, president of supply chain and logistics consulting firm MWPVL International Inc. in Montreal.

For those in the business of manufacturing robotic equipment, the transformation of the fulfilment system, if not the wider economy, is already here. And it may carry some benefits, says one provider.

“Technology provides … better jobs,” says Simon Drexler, director of industrial robotics for Kitchener, Ont.-based Clearpath Robotics Inc., whose industrial subsidiary Otto Motors designs and manufactures self-driving vehicles for warehouse, manufacturing and industrial environments across North America, and beyond.

“If you were an accountant when computers came out you would probably be terrified that you would lose your job, but what a computer allowed accountants to do was become data analysts.”

Transformation of warehousing

What we know for certain is that automation is transforming the warehousing industry, not to mention manufacturing facilities across the globe, as companies such as Amazon.com continue to embrace robotic assistance for jobs previously managed by humans.

Media reports indicate that e-retailing giant Amazon.com Inc. has cut costs by as much as $22-million in those fulfilment centres in which it deployed Kiva robots.

In a report, British market research firm Technavio estimates the market for logistics robots will reach $2.15-billion (U.S.) by 2020, with a compound annual growth rate of about 32 per cent over that period.

The PwC leadership survey indicates that 94 per cent of CEOs whose organizations had incorporated robotics into their operations found they helped boost productivity, while 64 per cent are counting on robots to help them innovate and increase revenue per employee.

Canadian companies

In Canada, retailers such as Hudson’s Bay Co. and grocery chain Sobeys Inc. have taken a lead role in the automation of their facilities, with the former investing more than $60-million to streamline operations at its distribution centres in a bid to compete with Amazon.com and others.

Indeed, in much of the world, the future is here when it comes to warehouse automation.

Drones, self-driving vehicles and even legged robots are handling tasks ranging from unloading trucks and picking orders, to gathering data and assisting with inventory management.

According to Mr. Drexler, organizations typically turn to robots to solve one of three problems: tackling labour shortages, gaining a cost advantage or improving efficiency.

Clearpath Robotics has been a clear beneficiary of that. The company, founded in 2009 by four University of Waterloo engineers, earned a place on Deloitte’s 2016 Technology Fast 50 ranking, posting three-year revenue growth of 662 per cent.

‘Smart factory’

“I really think we’re progressing toward the smart factory as a society,” says Mr. Drexler. “It’s about centralized operational data, about having interconnected devices feeding information into a centralized database, which gives the systems and processes utilizing the data as well as the people analyzing that data a better information pool about how operations are actually running in real time.

“Once you have that information, you’re able to make significantly better decisions about where you should be investing time in improvement initiatives to make your facility more efficient.”

But while robots are commonplace in facilities across Northern Europe, particularly Germany, Canada remains a relative laggard when it comes to automation, according to MWPVL’s Mr. Wulfraat.

Why? He points to rapidly increasing labour costs that have forced manufacturers and distributors in Europe to continuously search for cost efficiencies – in many cases replacing human labourers with cheaper robots who don’t collect salaries, claim benefits or take sick leave.

Labour costs

“In Denmark there are people who make $75,000 per year … to drive a forklift in a production facility or warehouse,” he notes. “When the labour rates get that high then businesses look to automate.”

Mr. Wulfraat says that in North America, many organizations – particularly smaller ones – will often avoid multimillion-dollar investments in automation unless they can reasonably expect to recoup their investment in a few years or less.

In Canada, he says, the use of warehousing automation for smaller companies tends to be targeted to areas such as packaging, while capital investments on robotics tend to be capped at around $1-million or less.

Canadian companies usually can’t afford to automate to the same degree as their U.S. or European competitors because of smaller markets and limited economies of scale.

Demographics

But the tide is slowly beginning to turn even in the Great White North, according to Mr. Wulfraat, largely because of demographics.

“The work force is shrinking and companies are struggling to find labour to fill their facilities,” he points out.

That’s the precise reason why he feels that fears of robots fuelling a surge in unemployment are not imminent.

Consider this: The U.S. federal government projects a roughly 5-per-cent reduction in the country’s overall labour force participation rate by 2040, equivalent to about 20 million fewer workers, largely because of an aging population.

Statistics Canada’s projections are similar for the Canadian economy.

That’s why companies are wise to be proactive in their embrace of robotics, says Mr. Wulfraat, or risk being left behind when demographic pressures make finding labour even more challenging and costly.

“It takes time to integrate automation, it doesn’t happen overnight. If you’re the person who wakes up and realizes it’s 2030 and you can’t find people to run your warehouse and your competitors have already done this, pushing more volume out at a lower cost per case, that’s going to be a major differentiator.”




Harry the Hound
5 days ago

This time machines are not only mechanical but intelligent.
Our challenge is sociological. How does society benefit from machines without the devastation and impoverishment that occumpanied the previous industrial revolution?
Machines doing the drudgery will permit humans to be human leading to a new renaissance.
3 Reactions


jojo ba
3 days ago

The problem is that the replacement of the masses with robotic systems will only lead to the enrichment of the 1% and the change to the entire social system, across the globe, will never happen due to the mid set of that 1%.
1 Reaction


J_Lee
3 days ago

I doubt it. Investors in hudson's bay, for example, might still be in 1%, but they don't seem to be benefited from robotic automatiion: HBC's stock price is not doing that well after all.
2 Reactions


RonsterG
1 day ago

In reply to:

The problem is that the replacement of the masses with robotic systems will only lead to the enrichment of the 1% and the change to the entire social system, across the globe, will never happen due...

— jojo ba

Governments will have to design new income distribution and tax paradigms to fit the shift in the labour market. Ultimately if mechanization replaces the human workforce without a corresponding new avenue of employment opening up for the displaced masses, who's going to have the income to buy the products that the robots are manufacturing? 

You can only have continuous consumption with a continuous income stream. If the 1% benefits from the displacement of the human workforce then a greater share of the burden of supporting the needs of society as a whole will have to borne by those who are benefiting. 

In a utopian society this would free more people to pursue endeavours that are more soul fulfilling and geared towards enhancing the quality of life like arts and culture or to volunteering their time to meet the needs of society without the dependency on working for remuneration in order to survive. As I said utopian.


jojo ba
6 hours ago

The change would have to happen globally as Canada or the US could not exist under a new system on it's own. Given that governments cannot even agree on climate change how would they agree on a total change to the economic system. It could only happen under a new world order an unfortunately it will probably be more like the movie the Terminator than utopia.

Hide 4 replies

jojo ba
3 days ago


There is no field of work that is not going to be touched by AI and robotics. In the next decade you won't need an accountant or lawyer as the professions are covered by basic rules and precedence. Bank tellers are being phased out as will loans officers as banking moves online.

 Robots will be build and designed by robots and so on. Where does this all lead? As more jobs are replaced or automated there will be less disposable income to fuel the economy and more people requiring government assistance at a time when there is lower tax revenues. 

The only thing that make sense is that a portion of society is preparing for a time when there will be substantially fewer people to service their needs. Maybe there is a portion of the population that believes in a future where there are only 500 million living a Utopian lifestyle serviced by robots. They themselves may become cyborgs to all eternal youth.
1 Reaction


Straight talk
2 days ago


In Australian mining industry giant earth-movers are fully automated. It is efficient, safe, and economic. Unwittingly, self-destruction of human society is built in to human psyche. That is not intelligence.

Nov. 26, 2016 "The burgeoning market for artificial intelligence": Today I found this article by Ajay Agrawal in the Globe and Mail:


For most people, it is not easy to picture the buying and selling of cognitive capabilities that have traditionally been embedded in humans – things like judgment and decision-making. 

Yet, thanks to recent advances in machine learning, we face the very real possibility of precisely such a ‘market for intelligence’. Given the potential of this market to transform the entire global economy, we must all begin preparing – now – for its emergence.

To be clear, machine intelligence is still in its infancy, and while some of the current applications are remarkable, none are transformational. For example, the recommendation engines employed by companies such as Amazon and Netflix – which learn our preferences and recommend which books we should buy or which movies we should watch – are a common application of machine learning. 

Although they may increase the sales of books and movies – and may even enhance social welfare to some extent, by increasing matches between consumers and products – they do not represent a transformation to the economy.

Similarly, in the healthcare sector, applications of machine intelligence that identify and classify tumours from medical imaging data – with a higher degree of accuracy than the best human technicians – will surely enhance the productivity of doctors; but they will not transform the broader economy.

I suspect the reason why the driverless car has had such an effect on people is because it shows them something truly transformational: most people imagined a bigger gap between the machine’s recommendation system and the cognitive requirements of a human driver.

They are shocked to learn that, in fact, this new machine does not actually need human input at all.

How will advances in machine intelligence transition from providing simple productivity enhancements in individual, narrow markets, to transforming the overall economy? Will such a transition happen gradually or suddenly?

To the extent that the last technology shock – the Internet – offers guidance on this question, the answer is both.


In the case of the Internet, the development of the technology and associated infrastructure occurred gradually, but the transformative impact on the global economy occurred relatively suddenly.

The economic transformation began abruptly in 1995. In 1991, the High Performance Computing Act passed; in 1992, Network Solutions took control of the domain name system and the Internet Society was founded; in 1993, the Mosaic Browser was launched for Unix and Windows OS; and in 1994, the cookie was invented at Netscape and the World Wide Web Consortium was founded.

Then, in 1995, Bill Gates wrote his famous ‘Internet tidal wave’ e-mail, Microsoft launched Windows 95 and Netscape went public with a market capitalization of $3-billion – without displaying a nickel of profit.

So, when will machine intelligence experience its own ‘1995’?

As with any early-stage, general-purpose technology, there is much speculation and debate. For example, last fall, Tesla CEO Elon Musk remarked: “AI is much more advanced than people realize.” To which deep-learning pioneer Yann LeCun responded via Twitter: “No, it’s not. Quite the opposite in fact.”

Within this fog of uncertainty, futuristic depictions abound. Not only are fiction writers featuring AI in stories like Transcendence, Her and Ex Machina, but governments – notably Japan, Germany, China and the United States – are featuring machine intelligence in their industrial strategies.

In the midst of all the speculation, real companies and investors are making real capital allocation decisions – today. In 2014, Google acquired the pre-revenue AI startup Deep Mind for approximately $500-million and created AlphaGo – which this year famously beat the world’s top human player at the ancient Chinese game, Go, demonstrating what appeared to be ‘machine intuition’.

In March 2016, General Motors acquired AI startup Cruise for more than $1-billion to help turn regular vehicles into self-driving cars, and the following month, Salesforce acquired AI startup MetaMind to automate and personalize marketing and customer support.

Companies such as these are betting on how the future will unfold, and their bets are endogenous, in that they will influence the rate and direction of technological development – as well as where and how it occurs.

The downfall of once-mighty corporations like Barnes & Noble and Blockbuster provide ample warning for those contemplating a ‘wait-and-see’ strategy with respect to AI.

It is incumbent upon investors, governments and firms in every sector to have a thesis regarding how their industry will be transformed when the necessary technological and regulatory pieces snap into place, and the world is suddenly confronted with a functioning market for intelligence.

While there is plenty of disagreement as to when AI will come to fruition, one thing is clear: decisions of significant consequence lie ahead.

Ajay Agrawal is the Peter Munk Professor of Entrepreneurship, Professor of Strategic Management and Academic Director of the Creative Destruction Lab at the Rotman School of Management.

A version of this article appeared in the Fall 2016 issue of Rotman Management, the magazine of the University of Toronto’s Rotman School of Management. Reprinted with permission.




My opinion: Both articles are intelligent and well-written.


This week's theme is about jobs and technology in the present and future:

"The digital economy will not power a recovery"/ "App gives employees control of scheduling" (Shyft)





"AI ethics: how far should companies go to retain employees?"/ "How to spot warning signs of disruptive innovation"






My week: 


Nov. 21, 2020 Naturalizer closing down;.

TORONTO — More than 130 Naturalizer stores in the United States and Canada will be closed by early 2021 as Caleres Inc. adopts a digital sales strategy for the shoe chain.

Calares says a large percentage of Naturalizer's sales already originate online, a trend in consumer shopping habits that has accelerated during the COVD pandemic.

Besides the 133 physical Naturalizer stores slated to close, Caleres expects to make changes to its back-office infrastructure to reflect the switch to digital.

https://ca.news.yahoo.com/shoe-retailer-caleres-close-133-215208394.html

My opinion: I wasn't really a big fan of that store.  I'm sure some of you guys are saying:

"I have to read the 'my week' part.  What if a store is closing down either it's in the news or a location at a mall?"

Nov. 23, 2020  "His bank raided his account to cover a payment made to scammers":



Justin Smith has been hit with a one-two punch of bad luck.

First, the Toronto man was duped by a job scam that made off with $3,000. Then his longtime bank, Tangerine, helped itself to money Smith had in his tax-free savings account to recoup what it had lost in the scam.

"You keep your money in the bank because you think it's safe," he said. "And they treat the money like it's theirs, and they just move it around to protect themselves. That's not fair."

Tangerine is an online subsidiary of Scotiabank that offers no-fee savings and chequing accounts.

Here's how the double episode of misfortune unfolded:

Smith, who works as a delivery person, had applied to work from home as a data entry clerk for the grocery chain Sobeys. He was offered the job, and was excited to receive an employment contract along with a cheque from his new employer for $3,495 to purchase a laptop, phone system, headphones and various other office equipment.

"It all looked totally authentic and real," he said.

Smith had checked out the names of the people who handled his hiring, and reviewed their profiles on LinkedIn to confirm they worked at Sobeys. So when he received an invoice from a firm called Tech Insight Services for the office equipment, and was instructed by the Sobeys hiring manager to make a $3,000 payment right away, he promptly sent an e-transfer.

"I only had $800 or so in my chequing account at the time, but after depositing the Sobeys cheque, I had over $4,000," he said.

What Smith didn't know was that the entire process was a sophisticated scam. The website where he'd applied, the supposed hiring managers, the cheque — all were fakes. His job application hadn't been sent to Sobeys at all. He had fallen into a snare set to swindle eager job seekers. The cheque even fooled Tangerine; the bank instantly deposited it to Smith's account.

Alarm bells didn't start ringing until the next day, when Smith's supposedly new employer told him he should send another $3,500 for a new desk.

"At this point, I became suspicious because no one spends that kind of money on a desk," he said. "I called up Tangerine and I said 'OK, I deposited a cheque yesterday, you guys let me send the money. I'm concerned that this cheque is going to bounce.'"

After being contacted by CBC's Go Public team, Tangerine said it will refund the $3,000 to Smith, and also pay $250 for a credit monitoring service for him.

In the article, there was a link to this story which I posted on my blog too:

He quit his job to take a new position — but the job offer was a scam | CBC News

His bank raided his account to cover a payment made to scammers (yahoo.com)

My opinion: I have to post this and inform everybody about this scam. 

1. Do not send money or e-transfer for supplies even if it's for work.

2. If you deposit the check into your account, there is a high chance it will bounce and be a fake check.  

3. As for work from home, most companies would mail you the computer and equipment.

My brother is in finance and he had a computer and equipment mailed to him so he can work from home.

Concentrix: I got a phone call from them, and I was told they will send the computer and equipment to me.

Here's my personal experience where I almost got scammed out of $4000 when I deposited a check for my "job":  

Tracy's blog: Scream 4/ Southgate Construction scam (badcb.blogspot.com)

Nov. 25, 2020 A Christmas present for an autistic man: I found this on my friend Heather's Facebook page and I shared this on my page and on this blog.  I was like: Awww.... there are a lot of comments about going on ebay where there are available The Land Before Time toys:  



Facebook



"The digital economy will not power a recovery"/ "App gives employees control of scheduling" (Shyft)

Nov. 30, 2016 "The digital economy will not power a recovery": Today I found this article by Andrew Jackson in the Globe and Mail.  I can't access it.  I will type this:

"To the extent that this is true, new technological marvels such as self-driving cars and robots will not revive growth, and a weak economy may actually be slowing technological progress.  What we need to spark a meaningful recovery is a big boost to the demand side of the economy in the form of higher wages and more public investment."  

Apr. 23, 2019: Today I found the article:

Economists and pundits are at odds over medium-term prospects for the global economy. Pessimists see stagnant growth, rising inequality and growing unemployment and underemployment, widely held to be responsible for the rise of right-wing populists such as U.S. president-elect Donald Trump.

Meanwhile, techno optimists such as Erik Brynjolfsson and Andrew McAfee, the authors of The Second Machine Age, argue that the digital economy will drive rapid productivity growth and underpin the gradual emergence of a post-scarcity economy capable of providing prosperity for all.

The current situation is paradoxical. The rise of the robots and artificial intelligence are widely seen to be driving a new technological revolution that is disrupting entire economic sectors and eliminating many jobs, increasingly including those of skilled workers.

Information technology has long since eliminated routine manufacturing and clerical jobs. 

More recently, 

retail trade has been rapidly shifting to online platforms, 

financial technology (fintech) is eliminating many well paid jobs in financial services,

 news media are downsizing rapidly as audiences and advertisers shift to Facebook and other social media, 

and analysts forecast the demise of entire occupations, such as truck and taxi drivers, because of the imminent rise of autonomous vehicles.

But measured growth in labour productivity or output per hour has been dismal over most of the past decade, and especially since the global financial crisis. As economist Robert Gordon once quipped, the impact of computers on productivity can be seen everywhere except in the statistics. 

He argues the impact of the digital economy is over-hyped compared with the transformative general-purpose technologies of the first and second industrial revolutions.

Even the optimists increasingly concede that rapid technological progress will not create enough new jobs to replace those being eliminated. 

As Economist editor Ryan Avent argues in his new book, The Wealth of Humans, the digital economy is creating a global labour surplus that drives down wages and job security in jobs that are not vulnerable to automation.

The digital economy delivers rich rewards to investors and the financial sector in the form of high corporate profits and high incomes to senior managers and core knowledge workers with advanced qualifications in successful firms. The proverbial top 1 per cent who directly benefit from the knowledge economy are accumulating stunning wealth.

The digital economy, along with globalization, has displaced many formerly middle-class workers into lower-wage and lower-skill jobs, increasing competition for those jobs at the low end of the skills spectrum that cannot easily be automated, and thus further driving down wages. 

Stagnant and falling wages for the bottom 90 per cent depress overall demand and, as Mr. Avent notes, cheap labour actually reduces the pressure on many low-wage employers to invest in capital and skills.

Along with major productivity gains in the disrupted sectors, we see an offsetting shift of employment to inherently low-productivity sectors such as personal services.

Another part of the overall growth and productivity problem is that business investment at the cutting edge of the new digital economy is mainly in knowledge creation and development instead of capital goods.

 Dominant companies such as Google and Apple have large market capitalizations and deliver high financial returns, but their material input needs and direct economic footprint are much smaller than dominant firms of the industrial age.

High corporate profits are sustained by high returns in finance and growing new economy sectors, but weak overall business investment in the material economy is the result of low overall economic demand because of rising inequality and the stagnation of wages. Thus, the productivity gains from the new economy are being hoarded by new-economy firms or paid out to shareholders, rather than reinvested in the economy.

Economists have long believed that technological change drives growth by increasing productivity, which raises overall demand in the economy through higher wages and higher business investment.

 But this virtuous process seems to have broken down in the case of the new digital economy.

To the extent that this is true, new technological marvels such as self-driving cars and robots will not revive growth, and a weak economy may actually be slowing technological progress. 

What we need to spark a meaningful recovery is a big boost to the demand side of the economy in the form of higher wages and more public investment.

Andrew Jackson is an adjunct research professor in the Institute of Political Economy at Carleton University in Ottawa and senior policy adviser to the Broadbent Institute.


https://www.theglobeandmail.com/report-on-business/economy/economic-insight/the-digital-economy-will-not-power-a-recovery/article33093633/

Jul. 30, 2016 "App gives employees control of scheduling" (Shyft): I found this article by Dina Bass in the Edmonton Journal :

Next week Starbucks barista Foster Cooley will be traveling. Normally he'd have to ask or text co-workers to fill in for him at his Chandler, Arizona, cafe and hope someone can take his shifts. Instead he's using an app to post his hours to baristas in the entire region.

Called Shyft, the app emerged from Seattle Techstars, an accelerator program that backs promising startups. With little marketing and no cooperation from major retailers, Shyft says it has signed up 12,000 workers at U.S. Starbucks stores, more than 7,500 at McDonald's and 3,500-plus at Old Navy. 

In the past three months, workers have exchanged the equivalent of 26,000 hours on the app, according to Shyft Chief Executive Officer Brett Patrontasch. If the app catches on more widely, it's sure to be unpopular in the corporate suite because it essentially wrests away control over scheduling.

"This gives shift workers the power to treat themselves like an economic unit and not be boxed in," says Heather Redman, a Seattle technology executive who was the first to sign on as an investor. "It is a little controversial and disruptive to have your workers have a whole ecosystem that you didn’t put in, but that’s the world we live in."

Founded last year, Shyft has attracted big-name investors, including former Seattle Seahawks player Russell Okung and ex-Mariner Edgar Martinez. Along with Redman, Madrona Venture Group and entrepreneur T.A. McCann, they agreed to pony up $1.5 million in new seed capital, the company said Wednesday. Patrontasch declined to discuss the company's business model.


Shift workers often face challenging work schedules—erratic hours, shifts in stores further from home, not enough work to meet their financial needs. Many companies use sophisticated scheduling software that has been criticized for spreading a worker's hours over too many days.

Last year New York State's Attorney General sent a letter to more than a dozen retailers asking about one particular shift-scheduling practice. A Seattle City Council member held a forum this week to discuss issues with shift scheduling, including too few hours and unpredictable schedules; the council and mayor are considering imposing rules.

 This month, a Starbucks barista gathered almost 13,000 signatures for a petition complaining that the company has been understaffing stores to save money and hurting workers who need more hours. 

Besides letting employees more easily offload shifts they can't make, Shyft helps those who need more hours to qualify for healthcare, Starbucks' college degree program or even just make the rent. The company also wants to enable geographic flexibility: A worker who wants to visit his grandmother out of state, say, could pick up shifts during the trip. 

Some companies require a manager to approve shift swaps so Shyft gives bosses a quick way to say yay or nay on a change. Workers trying to offload a tough shift—say Christmas or a significant other's birthday—can offer a monetary enticement. Some 10 percent of shifts on the system include such tips, Patrontasch says. 




My opinion: That's a good and useful app.

"AI ethics: how far should companies go to retain employees?"/ "How to spot warning signs of disruptive innovation"



Jun. 13, 2018 "AI ethics: how far should companies go to retain employees?": Today I found this article by Jay Kiew in the Globe and Mail:

Canada, we have a problem.


Our companies are struggling to retain their employees. According to a 2017 study by LinkedIn, Canada has the fourth-highest employee-turnover rate globally at 16 per cent (compared with the global average turnover rate of 11 per cent).



As companies struggle to predict how likely their employees are to leave, organizations are turning to data at the source: employees themselves. While organizations are legally allowed to monitor employees’ internet, e-mail and instant-messaging content, the extent of monitoring is now elevated with sentiment analysis using artificial intelligence.


With details of the EU’s General Data Protection Regulation (GDPR) bombarding news feeds globally about privacy and data regulation, a multitude of questions arise. How much data should companies be able to capture about their employees? To what extent are employees aware of the monitoring?



Broadly speaking, how far should companies go to retain their employees and where do ethics in AI fit in?

Accessing employee insights through sentiment analysis



One of the predominant workplace communication tools is Slack, whose userbase has grown to 70,000 paying organizations and eight million daily active users, competing directly with Microsoft’s Skype for Business and Facebook’s Workplace.


Enter Vibe, a Slack plug-in that brands itself as a morale meter for teams. Vibe applies natural-language processing (NLP) algorithms to scan messages across individuals, teams and the company. It identifies five key emotions (happiness, irritation, disapproval, disappointment and stress) to generalize the mood in the workplace.

 By analyzing employee sentiment on public channels through keywords and emojis, Vibe can help companies identify employees who may be flight risks.


Vibe isn’t the only one though. Emotion-detection company Affectiva offers Emotion as a Service, which analyzes images, video and audio to provide facial and vocal emotion metrics. 

Veriato tracks workplace productivity and insider threats by monitoring internet and e-mail content.


With a wide range of sentiment analysis tools available, organizations can keep track of employee stress levels - and perhaps, by extension, their job satisfaction - through their use of positive or negative words.

If managers can track their employees a bit better, perhaps they can make a concerted effort to reach out and check in when necessary. After all, understanding employees better is the first step to improving employee retention.


It is important to note that sentiment analysis is not new. Personal journal reflection sites such as 750 Words, created in 2009, provide NLP insights for users who write daily as an introspection tool. The website’s software examines keywords and phrases to identify a writer’s mindset, feelings and concerns.


The insights from 750 Words are extremely valuable for users to take an outside view of their own thoughts. The application of sentiment analysis to user data is intentionally transparent; users seek to better understand themselves.


However, the difference between 750 Words, Vibe and Veriato lies in the privacy and intended use of the data they obtain. With applications such as Vibe and Veriato, users may not fully understand that their messages are being collected and analyzed – and employers recognize that there are risks to that.


In Deloitte’s Global Human Capital Trends for 2018, six out of ten respondents said “they were concerned with employee perceptions of how their data is being used.” If these new technologies are used recklessly, consequences such as backlash over data abuse or privacy concerns could take a PR spotlight.

Ethics in work force analytics



There is no denying that employers must better understand their employees in order to better support their work lives. However, when applying artificial intelligence to employee monitoring, work force analytics programmers should take three things into account: data collection and analysis; data use; and data security.



Data Collection and Analysis: AI programs are highly dependent on the type of data that is collected, how that data is cleaned and how algorithms are coded. That means the results and capabilities of any AI program are reliant on the programmers that code it.

 When using third-party software, companies should be conscious of possible biases that may have gone into a software’s development and place controls on the software’s scope of data collection and analysis. As standard practice, companies should ask for employee permission to collect and analyze data. 


Data Use: Discussing IBM’s use of data last year, IBM chief executive Ginny Rommetti promised transparency on when, where and how AI insights would be used. Transparency for employees is a great start to broader corporate policies ensuring proper use of data. 

Employees should be aware of what information is being tracked and how data is specifically being used to engage or retain them.


Data Security: In light of the recent Facebook-Cambridge Analytica data scandal, companies need to own accountability for securing personal data. Although that scandal surrounded the leak of user data, storing employee data is equally important. If third-parties are analyzing company data, companies must take additional measures to ensure sensitive personal data is not leaked.


The use of AI in work force analytics should not be discounted completely. However, ethics should play a key role in the development and use of AI in work force analytics, and companies should be held accountable for its implementation.

Looking ahead



In the conversation on employee retention, AI-enabled work force analytics may be more of a distraction than a benefit.


In fact, organizations may already have the answer: A 2015 LinkedIn survey notes that 45 per cent of employees globally left jobs because they were “concerned about the lack of opportunities for advancement.”


When it comes to retention, perhaps companies don’t need AI after all. They just need to pay closer attention to what their employees are already saying.

https://www.theglobeandmail.com/business/careers/leadership/article-ai-ethics-how-far-should-companies-go-to-retain-employees/

Jul. 8, 2018 "How to spot warning signs of disruptive innovation": Today I found this article by Merge Gupta-Sunderji in the Globe and Mail:

Merge Gupta-Sunderji is a leadership speaker, consultant, and founder of Turning Managers Into Leaders.


Is it possible for a small, young company to outperform an industry titan, for David to beat Goliath? Just ask Uber, Netflix and Airbnb.


Upstart Uber became one of the world’s largest taxi companies without owning a single taxi.

Netflix revolutionized the video market, essentially putting Blockbuster out of business. 

Airbnb has become an accommodation provider to be reckoned with, without acquiring real estate.



It’s called disruptive innovation. And senior leaders across North America lose sleep thinking about whether it could happen to their company and, perhaps more importantly, how they could prevent it.


Disruptive innovation is when a company, usually a startup, introduces new products or services, often technology-based, to gain advantage over established competitors.

 And in this context, the word “disruptive” does not mean to interrupt or cause disorder, but to replace. If you’re a behemoth in your industry, that should be cause for angst.



Historically, established corporate leaders don’t often see disruptive change as a hazard, usually because it starts when their own company’s profitability is robust and the competitive impact is minimal. However, by the time the threat is conspicuous, the disruptive force has already gained so much traction that any efforts to reverse the tide are futile. 

So what is really needed is an advance-warning system: specific actions leaders can take to assess whether their company and industry will come under attack, well before the threat becomes a reality. Here are three things you can do to ensure you don’t become collateral damage when your market niche is disrupted.

IDENTIFY POTENTIAL DISRUPTORS



First, keep a vigilant eye on your potential disruptors. Listen when your customers tell you their pain points and pay close attention to who is stepping in to alleviate the ache. Monitor online forums and social media.

 The companies that are addressing your customers’ complaints about your product or service are the ones that will pull ahead to disrupt your business. The biggest grievances with the traditional taxi model included long wait times, poor in-car service, payment hassles and a perceived lack of safety. 

Uber’s model directly addressed each of these concerns – and all at a lower price. The warning signs were all there, but nobody in the taxi industry knew, or cared, to pay attention.

DETERMINE YOUR COMPETITIVE ADVANTAGES



Second, be pro-active in determining where your organization’s advantages lie. For an example, consider higher education. Online universities have economies of scale. Because they use e-learning technologies, they can enroll, educate and grant degrees to far more students at a much lower cost than traditional universities, which matters if you are a student with a limited budget. 

But for those students who want an exclusive university on their résumé, or who are seeking the college social experience, an online university cannot meet their needs. So traditional bricks-and-mortar universities will do better to focus on these two aspects when looking to differentiate themselves from their online competitors.

EVALUATE YOUR DISRUPTORS’ BARRIERS



Third, look beyond the present. 

What barriers would your disruptors have to surmount for them to wipe out your existing differentiators? In other words, how easy is it for you to lose your current competitive advantage? 

Consider these five types of barriers to disruption, ranked from easy to very difficult to breach:

  1. Momentum: Customers stay with you only because they are used to the status quo. Not surprisingly, these clients will jump ship quickly.
  2. Tech implementation: Current technology only needs to be implemented for your customers to leave you.
  3. Ecosystem: The business environment would have to change for your potential disruptor to become a viable competitor.
  4. New technologies: New technology would have to be developed in order for disruption to occur.
  5. Business model: The disruptor would actually have to adopt your cost structure in order to compete with you. If this is true, your company is likely safe – at least for now.

Even if your competitive advantages fall into the fourth or fifth type, don’t think you are immune. For years, the worldwide accommodation business had high barriers to entry for competitors.

 But when Airbnb capitalized on the massive reach of the internet by connecting providers with potential customers, the world of overnight lodging was turned on its ear. 



No matter what industry you’re in, disruptive innovation can be a threat. But with intelligent watchfulness, it doesn’t have to be a source of anxiety.

https://www.theglobeandmail.com/business/careers/management/article-how-to-spot-the-warning-signs-of-disruptive-innovation/