7 Proven Ways To Write Emails That Get Replies, Backed By Science

March 14, 2014 by Bernie Reeder in Work Smart

Effective email writing boils down to one thing: Mind reading. 
Really.
Sure, we’re all different, but in many instances our brains are prone to react to psychological triggers in a similar manner. Understanding these subtleties can help you hone in on creative ways to persuade others to take a desired course of action, like reply to more of your meticulously written emails.
Here are seven powerful psychological principles that can help you get busy people to respond to your emails, backed by template reply-rate data and examples from Yesware’s own sales team. 

1. Social Proof

Peer pressure is one of the oldest tricks in the book, and still one of the smartest. It accounts for why emails have higher open rates when sent to multiple people, and higher response rates when mentioning other stakeholders at the company. Because when it comes to making decisions –like whether or not to reply to someone’s email– we take cues from other people. 

 

What it means: If your prospect sees proof that his colleagues are receptive to your ideas, he’ll be more likely to jump on the bandwagon and give you the time of day. It’s one of the reasons this prospecting template from Yesware’s Paul Hlatky has been so effective at garnering replies:

 

2. Provide A Reason (Because I Said So)

A study performed by Harvard social psychologist Ellen Langer found that people were more willing to comply with a request (in this instance, cut in line) when people used the word “because.” Even when the reason was seemingly nonsensical (i.e. “Can I use the copy machine first because I need to make a copy?”), nearly all (93%) people complied. 

 

What it means: When you ask someone to do you a favor, you’ll be more successful if you provide a reason. Because (see what I did there?) yes, in today’s world of 24-7-365 communication and mile long to-do lists, answering an email from someone you don’t know is a favor. 

3. Throw In The Frog

You’ve been going back and forth with someone for weeks now, and then suddenly, they’re MIA. No reply. Won’t return your phone calls. Nothing. What’s your next move?
You throw in the frog.
In an experiment by O’Quinn and Aronoff, participants were assigned to “buyer” and “seller” roles and asked to negotiate the price of a painting. Half of the sellers received instructions to use the line “my final offer is $_, …and I’ll throw in a pet frog.” This led to relaxation, smiles, and increased compliance, with buyers agreeing to pay significantly more money than when the frog joke was not used.
What it means: When you make someone smile, they relax. Humor can help break down objections and win over an otherwise unreceptive audience. Here’s an example of how breaking the ice can earn you replies:

4. Choose Your Numbers Wisely

Let’s look at three quick tips that can increase your chances of getting your email opened and keeping their attention long enough to get a reply, all backed by science.

1. Include digits in the subject line. Numbers written out as numerals (i.e. 33 as opposed to thirty-three) have been shown to stop wandering eyes of online readers, making it more likely that your email will get noticed in an overcrowded inbox.
2. Use statistics and data. It makes you appear more credible.
3. Remember: Three is the magic number. Numerous studies have proven that the brain likes to be presented with three choices, whereas four choices may trigger skepticism and anything higher than that can lead to confusion. Try breaking your email into three (short) paragraphs, offer three options for meeting times, or describe your product using three adjectives.  

5. Keep It Short & Simple

Brevity is the soul of wit. So it should come as no surprise that it’s the soul of effective emails, too. Drawing from data culled from five years of emails in an executive recruiting firm, researchers found that shorter emails result in quicker response time, leading to higher overall productivity.
What it means: Don’t waste their time. Be considerate of your audience and use spacing, numbers, bulleted lists etc., to visually break up your message so that it’s easy to digest and take action on. MIT’s Marshall Van Alstyne argues that Twitter length  - roughly 140 characters – is ideal. Here’s what that looks like:

6. Use Their Name More Than Once

Remember that a person’s name is, to that person, the sweetest and most important sound in any language. -Dale Carnegie

Dale wasn’t kidding. “Few things light us up quite like seeing our own names in print or on the screen,” explain the folks at Copyblogger, citing recent research on brain activation. “Our names are intrinsically tied to our self-perception and make up a massive part of our identity. No surprise then, that we become more engaged and even more trusting of a message in which our name appears.”

What it means: Personalization is key. Try catching their eye by placing their name in the subject line — i.e. “Hi Jim, it’s Bernie from Yesware.” Asking for a reply that requires more than a simple yes/no? Throw in a simple “Thanks for your time, Jim” to close out your email. 

7. Be Specific 

Being vague isn’t going to help you clinch that important meeting. According to research by psychologist Robert Sutton, people are more responsive and willing to help if they’ve been given clear directions on how to contribute. Research coming out of Carnegie Mellon also found that people are more likely to respond to email requests that are easy to answer, as opposed to complex messages that require more time and mental energy to address.

What it means: Ending your emails with open ended statements — i.e. “Let me know what works best for you” or “how is your schedule this week?” — does more harm than good. Rather than take the time and energy to make the decision for both of you, they instead opt for “no decision” and you get no reply to your email.

You should end every email with a pointed call to action. Buy or not buy? Meet or not meet? Interested or hold off? Here’s an example that’s worked particularly well for our team:

4 Email Templates to Keep in Touch

March 9, 2011 by Matthew Bellows in Sales, Work Smart

Some time ago I wrote about Four Winning Approaches to Writing a Cold Email. Hopefully that article helped you break through the hundreds of emails your prospect gets every day. It’s one of the most popular posts on the site, so it’s helping someone out there. But now you’ve got to keep in touch and build trust with this person. Here are three examples of “Keeping in Touch” emails, plus a “Getting Back in Touch” template. As a reminder, the four approaches are:

• Congratulations
• Praise
• Adding Value
• Off-Topic

In all cases, your email should be as specific, detailed and genuine as possible. “Specific” means you could get through the prospect’s personal spam filter. “Detailed” means that you are actually providing something useful – you’ve spent the time to think about the prospect’s situation and can propose actionable solutions. And “Genuine” means just that. No bullshit. Don’t try to be anyone’s best buddy. Just be yourself, be honest, and be clear.

The basic approach with these Keeping in Touch emails is to switch tactics. If you were Congratulating a prospect, switch to Adding Value or Off-Topic. If you started with Off-Topic, go to Adding Value. Mix up your approach to demonstrate your depth as a resource and a person.

Here’s a Congratulations email to follow an Adding Value opening:

Dear Ted,
Last week I sent you an article from The Economist on [changing industry dynamic] because it seemed to speak to your situation. This morning I find out your team has announced a whole new product line! Congratulations to you and your team on the launch. I know how hard it is to build something from scratch. In looking over the materials you posted, I had two questions:
1. [A genuine non-self-serving question about how it works]
2. [A question about how it could intersect with your company's product]
The reason I’m asking is that my company makes [XXX] and [YYY]. I’m always trying to find new applications and to learn new approaches for our work here.
Interested to hear your thoughts,
Freddy
Three quick notes on this template:

1. I  always use “you” and “yours” when talking about the prospect’s company. Personal pronouns personalize the email. When talking about the other company employees, I _always_ say “your team” because a) they are all on the same team and b) from the reader’s point of view, it’s a bit flattering to hear that someone outside the company might think that these unrelated departments are all part of “my team.”
2. This approach is easily adopted for press coverage, new customer announcements, new exec hires, etc. Keep the format, completely change the content in those situations. [contextly_sidebar id="1a3dc5b48e5e261ad55a374a271fc89b"]
3. It might be tempting to end with “Let’s schedule a call to discuss” or somesuch. Don’t do it. Let the person get back to you via email if they want. If they do, you are building communication. If they don’t, there are more templates below or highlighted in the sidebar here.

Here’s an Adding Value template to follow a Congratulations opening:

Hi Sarah,
Your news last week made an impression on me – I’ve found myself thinking about your company a fair amount since then. Here’s a Business Week article that thoughtfully describes some of the same opportunities that your announcement addressed [link]. Am I reading this right? [Question about how the article impacts Sarah's company]?
Hope you find it interesting!
Fred
Notes on this template:

1. Yes! It’s short! Congratulations emails run the risk of fawning/ass-kissing. The goal here is to Add Value, ask a question in case the prospect wants to engage, and then get out of the way.
2. Keep it relevant. The only way this approach will work is if you can connect the dots. If you are working too hard to cram the Congrats and the Value together – stop and find something else to say.

Here’s an Adding Value template to follow an Off-Topic opening:

Note: Remember that the Off-Topic approach is the riskiest one. It’s inspired by something timely and personal that the prospect puts out in a public forum. Now you have to pull back to prove your professional value while dispelling once and for all the fear that you are a stalker.
Hi William,
Hope those restaurant recommendations for Houston served you well. I’d love to hear if any of them worked out. I’ve been doing some thinking about your company, and I was wondering if you know [high-value contact of yours]. She’s the SVP at [potentially interesting customer/prospect for William]. I’d guess that with their [new office in China, interest in injection molding, etc.] and your accomplishments in the same, you guys might enjoy talking.
Want me to make an introduction?
Harry
Note: Salespeople don’t do enough trading of introductions. It’s an incredibly effective way to add value to a prospect’s professional life. It costs nothing. And, if you do it properly, it can be beneficial to both parties. There are very few people who won’t respond, at least with a “no thanks”, to this kind of email.

Finally, here’s a Getting Back in Touch template in case it’s been a while:

Dear Sam,
I hope this note finds you well. You guys have been busy since we last talked! I saw your announcement of [X] and [Y]. Congratulations! Things have been going well over here too – we released [new feature of relevant product] and have been getting great feedback from our customers.
Are you going to be [at industry event or in city of Sam's HQ] in two weeks? I’m heading out, and I’d love to ask you about [your announcement Y]. I have a thought about how it might dovetail with some of the R&D work we’re doing here. Let me know if you’ll be in town.
All the best,
Terry
Note: Compared to the templates above, this one goes right for the meeting. I’m imagining that you’ve been out of touch because the prospect isn’t hot, or the fit isn’t great. Oftentimes it’s better to just find out interest level for sure by asking about a meeting opportunity.
Recovering from a negative response to this email is easy. After the trip/conference, its “Sorry we missed each other. I had a great steak at Abe’s! Maybe next time.” and you are back in touch. And if your dangling of R&D previews works, you’ve got another meeting for your trip.

4 Winning Approaches for Writing a Cold Email.

4 Winning Approaches for Writing a Cold Email

October 6, 2010 by Matthew Bellows in Email, Productivity, Sales Tips

Breaking through with a cold email for a hot prospect is tough… you’ve deleted enough of them to know. It would be much better to get an introduction from someone who knows your prospect already. But if that’s not possible, your cold sales email has two jobs:

1. Get through the prospect’s personal spam filters
2. Make enough of an impression to get to “The Crux” and “The Ask”

Getting through the personal spam filters is all about being specific in your subject line, immediately adding value, and not being too sales-y. For this purpose, I suggest a tight and directed subject line. These usually work for me:

• Congratulations subject lines – “Congrats on the product release/great quarter/NYT coverage/financing/new customer” (the more specific the better). If you are writing to the head of product development, product or feature messages are best. Want to meet with the VP of Sales? They all  like congratulations on a great quarter.
• Praise subject lines – “I’ve heard about your skills and wanted to get in touch” or “I’ve been following your efforts/blog/tweets/sales success for quite a while and wanted to reach out”. The key here is to be genuine, impressed, but not fawning. If you have no backbone, no one wants to hear your praise. On the other hand, if you are haughty, why are you writing?

The key here is to be genuine, impressed, but not fawning. If you have no backbone, no one wants to hear your praise.

• Adding value subject lines -  “Hi Ted! I found an article on [your industry/competition/field] and thought of you” I start out with using the prospect’s name so they know it’s not spam, and then immediately let them know that the message is relevant to their work life. Using the person’s name like that can work well in the other types of sale emails as well.
• Off topic but relevant subject lines – These are dangerous. You don’t want to sound like you are stalking. These also take a bit longer until you can get to business. However, if the person you want to talk with just posted a question about their upcoming ski vacation, and you are genuinely inspired, spend some time putting together your best recommendations (with links) and email it to them. Subject lines for that approach: “Recommendations for your ski trip: I’d say Utah” or “Saw your post about skiing – here are my suggestions.” If it’s relevant, timely and not too personal, this could work well.

Once you have an approach and a tight subject line, you’ve got to make an impression. Making enough of an impression is mostly about the value you can provide to the recipient in the first one-to-three lines of the email. For each of the approaches above, here’s a sample email opening:

• Congratulations – “Dear Ted, You and your team have really accomplished something. The feature/product/press mention yesterday is making a big impression among the people I talk to.  I wanted to reach out and say congratulations.” Don’t start these with the word “I”. This is a note about your prospect.
• Praise – “Dear Ted, We haven’t met in person but I’ve been impressed with your work/blog/leadership in [specific example] for some time. This isn’t a particularly easy environment to excel in. Amazing work.”
• Adding value – “The article appears in The Economist this week. I thought it did a good job of capturing the dynamics of [the situation]. Here’s the link:…” By citing the source at the top, it helps establish credibility for you and the email. Don’t bother with this approach if your source isn’t bulletproof. Bonus points: “Although the author misses [some specific aspect that only an industry vet like you would know] I thought this article was pretty insightful.”

Bonus points: “Although the author misses [some specific aspect that only an industry vet like you would know] I thought this article was pretty insightful.”

• Off-topic – With this approach, you need to spend some time thinking through this. Where have you been? You want to be sensitive about the places that you think the prospect would like. Do they have kids? No one wants to spend a lot of money, so put all your suggestions in terms of “value” even if they are five star.  Again, getting too personal is dangerous. It’s better not to, unless you can be subtle or it’s common knowledge. Here’s an opening that I’d use: “Dear Ted, I’ve been skiing since I was six, and I lived in Colorado for four years, but for a vacation like you posted about, I’d suggest Utah. Here are my three favorite resorts and hotels.” Notice that I’m using “I” here. Since these recommendations are coming from you personally, it’s better to take this approach than the grammatical gymnastics required to avoid it.

And now, “The Crux”. You have to leverage the good will you’ve created to get something in return. Here are a couple of approaches I like. They aren’t strictly related to the openings, so feel free to mix and match.

• Congratulations – “My company has been doing pretty well also. We recently announced [customer/competitor] as a client for our [product]. Maybe something like this could help you continue your impressive momentum?” I always say “my company” even if I don’t own the company, because it communicates my responsibility for the situation. I’m going to act like the owner. At the very least, I’m in charge of this relationship. That one little word “My” goes a very long way.

I always say “my company” even if I don’t own the company, because it communicates my responsibility for the situation.

• Praise – “I was wondering if I could ask you a couple of questions. My company is having some success with [product/service] but your insights on/experience with could really help us accelerate.”
• Adding value – “I’ve been thinking about this because my company is struggling with the same issue. Although we just launched [feature/product] and recently signed [customer/competitor], we’ve been working on [XXX] like the company profiled.” I like admitting that we’re struggling, that we’re working on something, that all is not awesome. It’s honest and it’s a state that everyone can relate to.
• Off topic – Get right to the point: “I hope you find this helpful, and you have a great vacation.” I wouldn’t follow this approach up with “The Asks” below. Close out the email while the prospect has a small amount of goodwill towards you. Then write back not sooner than ten business days with a “Hi Ted, I wrote you that note about Utah skiing a while ago. I thought of you again when talking with my product manager about [new feature/new product]…”

And finally, “The Ask”. If you haven’t sucked up too much, or been too stalkery, there’s no problem here. Just be specific. I say something like:

• “I’d like to follow up about this with a quick phone call. We can cover the important issues in 20 minutes. Can I call you next Tuesday at 8am EST?”

I always ask for a phone call. You don’t need (or want) permission to send more product information. You want to take the next step in building a relationship, which is a spoken conversation. I always give a specific time and day.
It takes away the excuse of “now I have to suggest a time, etc. for this guy” Most people who are at all interested will check their calendar for that day. I try to suggest a time three to five days in advance, and at the beginning of the day – a time when they are in the car or out of a meeting. I strongly discourage any suggestion that you and your prospect spend time together beyond that call. You might both like skiing or baseball, but don’t go there until you are sure you won’t get turned down.
I n real life, you’d clear your calendar for an hour with person, but you can’t ever appear that desperate. The value of each of your prospects determines how much time you can spend on writing these emails, but for most B2B salespeople, it’s hard to spend too much time getting these openings right. No spelling mistakes. No grammatical errors. I read my messages out loud before I send them. I often ask a colleague to read them before I send.

And then – follow up… The best egg salesman in the USA says ‘I get 85% of my new business after four contacts.’

And then – follow up. Not soon. Remember, you are busy. But think of the person, and try to send them something that would help them in the next 12 to 15 days. The best egg salesman in the USA says “I get 85% of my new business after four contacts.”
Jack Daly says that on average “it takes nine touches to get someone’s attention.” So keep at it over the next couple of months. I’ll cover suggestions for those emails coming up next.

Are You Sacrificing Future Trust for Sales Today? The first lesson you learn in sales is how to qualify a lead. After all, speaking with someone who’s not legitimately interested in your product or service is a waste of your time — and theirs. But there’s something that’s even more important than making sure your prospect wants to buy what you’re pitching: ensuring that they’ll be happy with the purchase long after you’ve cashed their check. Just because you can smooth talk your way into a sale doesn’t mean you should.

 

TechCrunch

 

 

CrunchWeek: Net Neutrality, Big Late-Stage Raises, And Snapchat’s Latest Features

Posted May 16, 2014 by Jordan Crook (@jordanrcrook)

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The Zeus Is A 3D Printer, Scanner, And Teleportation Machine All In One

Net Neutrality, Uber and Airbnb Raise, and Snapchat's Update

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Net Neutrality, Uber and Airbnb Raise, and Snapchat’s Update

This week is all about CrunchWeek East, as we’re bringing this episode to you from AOL HQ in New York.
Anthony Ha, Jon Schieber and myself dive into the most recent madness in the industry. We discuss the new proposals around net neutrality law, major late-stage raises from companies like Uber, Airbnb, Pinterest, and others, as well as the latest Snapchat features that take the app from social network to messenger.
We hope you enjoy watching the show as much as we enjoy filming it.
Happy Friday, everyone!

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Google/YouTube Reportedly Prepping To Buy Twitch

Posted 16 hours ago by Greg Kumparak (@grg)

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EverPurse Raises Seed Round For A Different Kind Of Wearable

Yowza. So much for Sunday being a slow news day. About an hour after AT&T officially announces their plans to buy DirecTV, word of another billion-dollar acquisition has surfaced.
The story this time around: Google/YouTube reportedly want Twitch.tv, the increasingly/explosively popular service meant to let gamers watch others play games, live. The purported price tag? 1 billion.
According to Variety, it’s already a done deal, and they say the official announcement is looming.
The WSJ, meanwhile, says the talks are very early on – too early for a price to be set, even.
While the concept behind Twitch might seem crazy (I can’t even count the number of people I’ve heard ask “Why would you want to watch someone else play video games?”), the service has done nothing but rocket in popularity since launching back in 2011.
Turns out, people like to watch other people play games. With competitive games, like League of Legends, gamers watch to learn; with other, more casual games, like Minecraft, they watch just to be entertained.
Twitch.tv is actually something of an oddity, in that it’s an independent spin-off of another company.
A few years after launching Justin.tv (another video live streaming service, meant primarily to stream live video from your webcam) its founders noticed that the site’s gaming channels always managed to pull in particularly massive numbers. In 2011, they spun the site’s Gaming section into a site of its own — Twitch.tv. By 2014, Twitch had grown so huge that the parent company was rebranded as Twitch Interactive.
For those keeping track: Twitch has raised roughly $35M since becoming an independent company.

Fracasos y Exitos de experiencias de vida

Al final de cada año se debe revisar si los objetivos fijados fueron logrados, y cuando lo haces cada 5 años, luego cada 10 años y asi sucesivamente y luego concluyes que tienes mas "NO" que "SI", ¿Qué se hace?, se sigue viviendo el presente y se agarra uno a este mensaje para consolarse y dejar que la esperanza cambie nuestra suerte de vida. Y no deprimirse por el fracaso cosechado a lo largo de la vida vivida. Y por supuesto, si eres cristiano no vengarse de las personas que te hicieron el mal es la solucion, ya que Dios se encargara de ellos.

Featured Story

How Technology Is Destroying Jobs

• By David Rotman on June 12, 2013

• 752 comments

Also featured in:

MIT Technology Review Magazine
July/August 2013
More in this issue »

 

Why It Matters

Economic theory and government policy will have to be rethought if technology is indeed destroying jobs faster than it is creating new ones.

Given his calm and reasoned academic demeanor, it is easy to miss just how provocative Erik Brynjolfsson’s contention really is. ­Brynjolfsson, a professor at the MIT Sloan School of Management, and his collaborator and coauthor Andrew McAfee have been arguing for the last year and a half that impressive advances in computer technology—from improved industrial robotics to automated translation services—are largely behind the sluggish employment growth of the last 10 to 15 years. Even more ominous for workers, the MIT academics foresee dismal prospects for many types of jobs as these powerful new technologies are increasingly adopted not only in manufacturing, clerical, and retail work but in professions such as law, financial services, education, and medicine.

That robots, automation, and software can replace people might seem obvious to anyone who’s worked in automotive manufacturing or as a travel agent. But Brynjolfsson and McAfee’s claim is more troubling and controversial. They believe that rapid technological change has been destroying jobs faster than it is creating them, contributing to the stagnation of median income and the growth of inequality in the United States. And, they suspect, something similar is happening in other technologically advanced countries.
Perhaps the most damning piece of evidence, according to Brynjolfsson, is a chart that only an economist could love. In economics, productivity—the amount of economic value created for a given unit of input, such as an hour of labor—is a crucial indicator of growth and wealth creation. It is a measure of progress. On the chart Brynjolfsson likes to show, separate lines represent productivity and total employment in the United States. For years after World War II, the two lines closely tracked each other, with increases in jobs corresponding to increases in productivity. The pattern is clear: as businesses generated more value from their workers, the country as a whole became richer, which fueled more economic activity and created even more jobs. Then, beginning in 2000, the lines diverge; productivity continues to rise robustly, but employment suddenly wilts. By 2011, a significant gap appears between the two lines, showing economic growth with no parallel increase in job creation. Brynjolfsson and McAfee call it the “great decoupling.” And Brynjolfsson says he is confident that technology is behind both the healthy growth in productivity and the weak growth in jobs.
It’s a startling assertion because it threatens the faith that many economists place in technological progress. Brynjolfsson and McAfee still believe that technology boosts productivity and makes societies wealthier, but they think that it can also have a dark side: technological progress is eliminating the need for many types of jobs and leaving the typical worker worse off than before. ­Brynjolfsson can point to a second chart indicating that median income is failing to rise even as the gross domestic product soars. “It’s the great paradox of our era,” he says. “Productivity is at record levels, innovation has never been faster, and yet at the same time, we have a falling median income and we have fewer jobs. People are falling behind because technology is advancing so fast and our skills and organizations aren’t keeping up.”
Brynjolfsson and McAfee are not Luddites. Indeed, they are sometimes accused of being too optimistic about the extent and speed of recent digital advances. Brynjolfsson says they began writing Race Against the Machine, the 2011 book in which they laid out much of their argument, because they wanted to explain the economic benefits of these new technologies (Brynjolfsson spent much of the 1990s sniffing out evidence that information technology was boosting rates of productivity). But it became clear to them that the same technologies making many jobs safer, easier, and more productive were also reducing the demand for many types of human workers.

Anecdotal evidence that digital technologies threaten jobs is, of course, everywhere. Robots and advanced automation have been common in many types of manufacturing for decades. In the United States and China, the world’s manufacturing powerhouses, fewer people work in manufacturing today than in 1997, thanks at least in part to automation. Modern automotive plants, many of which were transformed by industrial robotics in the 1980s, routinely use machines that autonomously weld and paint body parts—tasks that were once handled by humans. Most recently, industrial robots like Rethink Robotics’ Baxter (see “The Blue-Collar Robot,” May/June 2013), more flexible and far cheaper than their predecessors, have been introduced to perform simple jobs for small manufacturers in a variety of sectors. The website of a Silicon Valley startup called Industrial Perception features a video of the robot it has designed for use in warehouses picking up and throwing boxes like a bored elephant. And such sensations as Google’s driverless car suggest what automation might be able to accomplish someday soon.
A less dramatic change, but one with a potentially far larger impact on employment, is taking place in clerical work and professional services. Technologies like the Web, artificial intelligence, big data, and improved analytics—all made possible by the ever increasing availability of cheap computing power and storage capacity—are automating many routine tasks. Countless traditional white-collar jobs, such as many in the post office and in customer service, have disappeared. W. Brian Arthur, a visiting researcher at the Xerox Palo Alto Research Center’s intelligence systems lab and a former economics professor at Stanford University, calls it the “autonomous economy.” It’s far more subtle than the idea of robots and automation doing human jobs, he says: it involves “digital processes talking to other digital processes and creating new processes,” enabling us to do many things with fewer people and making yet other human jobs obsolete.
It is this onslaught of digital processes, says Arthur, that primarily explains how productivity has grown without a significant increase in human labor. And, he says, “digital versions of human intelligence” are increasingly replacing even those jobs once thought to require people. “It will change every profession in ways we have barely seen yet,” he warns.
McAfee, associate director of the MIT Center for Digital Business at the Sloan School of Management, speaks rapidly and with a certain awe as he describes advances such as Google’s driverless car. Still, despite his obvious enthusiasm for the technologies, he doesn’t see the recently vanished jobs coming back. The pressure on employment and the resulting inequality will only get worse, he suggests, as digital technologies—fueled with “enough computing power, data, and geeks”—continue their exponential advances over the next several decades. “I would like to be wrong,” he says, “but when all these science-fiction technologies are deployed, what will we need all the people for?”
New Economy?
But are these new technologies really responsible for a decade of lackluster job growth? Many labor economists say the data are, at best, far from conclusive. Several other plausible explanations, including events related to global trade and the financial crises of the early and late 2000s, could account for the relative slowness of job creation since the turn of the century. “No one really knows,” says Richard Freeman, a labor economist at Harvard University. That’s because it’s very difficult to “extricate” the effects of technology from other macroeconomic effects, he says. But he’s skeptical that technology would change a wide range of business sectors fast enough to explain recent job numbers.

Employment trends have polarized the workforce and hollowed out the middle class.

David Autor, an economist at MIT who has extensively studied the connections between jobs and technology, also doubts that technology could account for such an abrupt change in total employment. “There was a great sag in employment beginning in 2000. Something did change,” he says. “But no one knows the cause.” Moreover, he doubts that productivity has, in fact, risen robustly in the United States in the past decade (economists can disagree about that statistic because there are different ways of measuring and weighing economic inputs and outputs). If he’s right, it raises the possibility that poor job growth could be simply a result of a sluggish economy. The sudden slowdown in job creation “is a big puzzle,” he says, “but there’s not a lot of evidence it’s linked to computers.”
To be sure, Autor says, computer technologies are changing the types of jobs available, and those changes “are not always for the good.” At least since the 1980s, he says, computers have increasingly taken over such tasks as bookkeeping, clerical work, and repetitive production jobs in manufacturing—all of which typically provided middle-class pay. At the same time, higher-paying jobs requiring creativity and problem-solving skills, often aided by computers, have proliferated. So have low-skill jobs: demand has increased for restaurant workers, janitors, home health aides, and others doing service work that is nearly impossible to automate. The result, says Autor, has been a “polarization” of the workforce and a “hollowing out” of the middle class—something that has been happening in numerous industrialized countries for the last several decades. But “that is very different from saying technology is affecting the total number of jobs,” he adds. “Jobs can change a lot without there being huge changes in employment rates.”
What’s more, even if today’s digital technologies are holding down job creation, history suggests that it is most likely a temporary, albeit painful, shock; as workers adjust their skills and entrepreneurs create opportunities based on the new technologies, the number of jobs will rebound. That, at least, has always been the pattern. The question, then, is whether today’s computing technologies will be different, creating long-term involuntary unemployment.
At least since the Industrial Revolution began in the 1700s, improvements in technology have changed the nature of work and destroyed some types of jobs in the process. In 1900, 41 percent of Americans worked in agriculture; by 2000, it was only 2 percent. Likewise, the proportion of Americans employed in manufacturing has dropped from 30 percent in the post–World War II years to around 10 percent today—partly because of increasing automation, especially during the 1980s.

While such changes can be painful for workers whose skills no longer match the needs of employers, Lawrence Katz, a Harvard economist, says that no historical pattern shows these shifts leading to a net decrease in jobs over an extended period. Katz has done extensive research on how technological advances have affected jobs over the last few centuries—describing, for example, how highly skilled artisans in the mid-19th century were displaced by lower-skilled workers in factories. While it can take decades for workers to acquire the expertise needed for new types of employment, he says, “we never have run out of jobs. There is no long-term trend of eliminating work for people. Over the long term, employment rates are fairly stable. People have always been able to create new jobs. People come up with new things to do.”
Still, Katz doesn’t dismiss the notion that there is something different about today’s digital technologies—something that could affect an even broader range of work. The question, he says, is whether economic history will serve as a useful guide. Will the job disruptions caused by technology be temporary as the workforce adapts, or will we see a science-fiction scenario in which automated processes and robots with superhuman skills take over a broad swath of human tasks? Though Katz expects the historical pattern to hold, it is “genuinely a question,” he says. “If technology disrupts enough, who knows what will happen?”
Dr. Watson
To get some insight into Katz’s question, it is worth looking at how today’s most advanced technologies are being deployed in industry. Though these technologies have undoubtedly taken over some human jobs, finding evidence of workers being displaced by machines on a large scale is not all that easy. One reason it is difficult to pinpoint the net impact on jobs is that automation is often used to make human workers more efficient, not necessarily to replace them. Rising productivity means businesses can do the same work with fewer employees, but it can also enable the businesses to expand production with their existing workers, and even to enter new markets.
Take the bright-orange Kiva robot, a boon to fledgling e-commerce companies. Created and sold by Kiva Systems, a startup that was founded in 2002 and bought by Amazon for $775 million in 2012, the robots are designed to scurry across large warehouses, fetching racks of ordered goods and delivering the products to humans who package the orders. In Kiva’s large demonstration warehouse and assembly facility at its headquarters outside Boston, fleets of robots move about with seemingly endless energy: some newly assembled machines perform tests to prove they’re ready to be shipped to customers around the world, while others wait to demonstrate to a visitor how they can almost instantly respond to an electronic order and bring the desired product to a worker’s station.
A warehouse equipped with Kiva robots can handle up to four times as many orders as a similar unautomated warehouse, where workers might spend as much as 70 percent of their time walking about to retrieve goods. (Coincidentally or not, Amazon bought Kiva soon after a press report revealed that workers at one of the retailer’s giant warehouses often walked more than 10 miles a day.)
Despite the labor-saving potential of the robots, Mick Mountz, Kiva’s founder and CEO, says he doubts the machines have put many people out of work or will do so in the future. For one thing, he says, most of Kiva’s customers are e-commerce retailers, some of them growing so rapidly they can’t hire people fast enough. By making distribution operations cheaper and more efficient, the robotic technology has helped many of these retailers survive and even expand. Before founding Kiva, Mountz worked at Webvan, an online grocery delivery company that was one of the 1990s dot-com era’s most infamous flameouts. He likes to show the numbers demonstrating that Webvan was doomed from the start; a $100 order cost the company $120 to ship. Mountz’s point is clear: something as mundane as the cost of materials handling can consign a new business to an early death. Automation can solve that problem.

Meanwhile, Kiva itself is hiring. Orange balloons—the same color as the robots—hover over multiple cubicles in its sprawling office, signaling that the occupants arrived within the last month. Most of these new employees are software engineers: while the robots are the company’s poster boys, its lesser-known innovations lie in the complex algorithms that guide the robots’ movements and determine where in the warehouse products are stored. These algorithms help make the system adaptable. It can learn, for example, that a certain product is seldom ordered, so it should be stored in a remote area.
Though advances like these suggest how some aspects of work could be subject to automation, they also illustrate that humans still excel at certain tasks—for example, packaging various items together. Many of the traditional problems in robotics—such as how to teach a machine to recognize an object as, say, a chair—remain largely intractable and are especially difficult to solve when the robots are free to move about a relatively unstructured environment like a factory or office.
Techniques using vast amounts of computational power have gone a long way toward helping robots understand their surroundings, but John Leonard, a professor of engineering at MIT and a member of its Computer Science and Artificial Intelligence Laboratory (CSAIL), says many familiar difficulties remain. “Part of me sees accelerating progress; the other part of me sees the same old problems,” he says. “I see how hard it is to do anything with robots. The big challenge is uncertainty.” In other words, people are still far better at dealing with changes in their environment and reacting to unexpected events.
For that reason, Leonard says, it is easier to see how robots could work with humans than on their own in many applications. “People and robots working together can happen much more quickly than robots simply replacing humans,” he says. “That’s not going to happen in my lifetime at a massive scale. The semiautonomous taxi will still have a driver.”
One of the friendlier, more flexible robots meant to work with humans is Rethink’s Baxter. The creation of Rodney Brooks, the company’s founder, Baxter needs minimal training to perform simple tasks like picking up objects and moving them to a box. It’s meant for use in relatively small manufacturing facilities where conventional industrial robots would cost too much and pose too much danger to workers. The idea, says Brooks, is to have the robots take care of dull, repetitive jobs that no one wants to do.
It’s hard not to instantly like Baxter, in part because it seems so eager to please. The “eyebrows” on its display rise quizzically when it’s puzzled; its arms submissively and gently retreat when bumped. Asked about the claim that such advanced industrial robots could eliminate jobs, Brooks answers simply that he doesn’t see it that way. Robots, he says, can be to factory workers as electric drills are to construction workers: “It makes them more productive and efficient, but it doesn’t take jobs.”
The machines created at Kiva and Rethink have been cleverly designed and built to work with people, taking over the tasks that the humans often don’t want to do or aren’t especially good at. They are specifically designed to enhance these workers’ productivity. And it’s hard to see how even these increasingly sophisticated robots will replace humans in most manufacturing and industrial jobs anytime soon. But clerical and some professional jobs could be more vulnerable. That’s because the marriage of artificial intelligence and big data is beginning to give machines a more humanlike ability to reason and to solve many new types of problems.

Even if the economy is only going through a transition, it is an extremely painful one for many.

In the tony northern suburbs of New York City, IBM Research is pushing super-smart computing into the realms of such professions as medicine, finance, and customer service. IBM’s efforts have resulted in Watson, a computer system best known for beating human champions on the game show Jeopardy! in 2011. That version of Watson now sits in a corner of a large data center at the research facility in Yorktown Heights, marked with a glowing plaque commemorating its glory days. Meanwhile, researchers there are already testing new generations of Watson in medicine, where the technology could help physicians diagnose diseases like cancer, evaluate patients, and prescribe treatments.
IBM likes to call it cognitive computing. Essentially, Watson uses artificial-­intelligence techniques, advanced natural-language processing and analytics, and massive amounts of data drawn from sources specific to a given application (in the case of health care, that means medical journals, textbooks, and information collected from the physicians or hospitals using the system). Thanks to these innovative techniques and huge amounts of computing power, it can quickly come up with “advice”—for example, the most recent and relevant information to guide a doctor’s diagnosis and treatment decisions.
Despite the system’s remarkable ability to make sense of all that data, it’s still early days for Dr. Watson. While it has rudimentary abilities to “learn” from specific patterns and evaluate different possibilities, it is far from having the type of judgment and intuition a physician often needs. But IBM has also announced it will begin selling Watson’s services to customer-support call centers, which rarely require human judgment that’s quite so sophisticated. IBM says companies will rent an updated version of Watson for use as a “customer service agent” that responds to questions from consumers; it has already signed on several banks. Automation is nothing new in call centers, of course, but Watson’s improved capacity for natural-language processing and its ability to tap into a large amount of data suggest that this system could speak plainly with callers, offering them specific advice on even technical and complex questions. It’s easy to see it replacing many human holdouts in its new field.
Digital Losers
The contention that automation and digital technologies are partly responsible for today’s lack of jobs has obviously touched a raw nerve for many worried about their own employment. But this is only one consequence of what ­Brynjolfsson and McAfee see as a broader trend. The rapid acceleration of technological progress, they say, has greatly widened the gap between economic winners and losers—the income inequalities that many economists have worried about for decades. Digital technologies tend to favor “superstars,” they point out. For example, someone who creates a computer program to automate tax preparation might earn millions or billions of dollars while eliminating the need for countless accountants.
New technologies are “encroaching into human skills in a way that is completely unprecedented,” McAfee says, and many middle-class jobs are right in the bull’s-eye; even relatively high-skill work in education, medicine, and law is affected. “The middle seems to be going away,” he adds. “The top and bottom are clearly getting farther apart.” While technology might be only one factor, says McAfee, it has been an “underappreciated” one, and it is likely to become increasingly significant.

Not everyone agrees with Brynjolfsson and McAfee’s conclusions—particularly the contention that the impact of recent technological change could be different from anything seen before. But it’s hard to ignore their warning that technology is widening the income gap between the tech-savvy and everyone else. And even if the economy is only going through a transition similar to those it’s endured before, it is an extremely painful one for many workers, and that will have to be addressed somehow. Harvard’s Katz has shown that the United States prospered in the early 1900s in part because secondary education became accessible to many people at a time when employment in agriculture was drying up. The result, at least through the 1980s, was an increase in educated workers who found jobs in the industrial sectors, boosting incomes and reducing inequality. Katz’s lesson: painful long-term consequences for the labor force do not follow inevitably from technological changes.
Brynjolfsson himself says he’s not ready to conclude that economic progress and employment have diverged for good. “I don’t know whether we can recover, but I hope we can,” he says. But that, he suggests, will depend on recognizing the problem and taking steps such as investing more in the training and education of workers.
“We were lucky and steadily rising productivity raised all boats for much of the 20th century,” he says. “Many people, especially economists, jumped to the conclusion that was just the way the world worked. I used to say that if we took care of productivity, everything else would take care of itself; it was the single most important economic statistic. But that’s no longer true.” He adds, “It’s one of the dirty secrets of economics: technology progress does grow the economy and create wealth, but there is no economic law that says everyone will benefit.” In other words, in the race against the machine, some are likely to win while many others lose.

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Credits: Noma Bar (Illustration); Data from Bureau of Labor Statistics (Productivity, Output, GDP Per Capita); International Federation of Robotics; CIA World Factbook (GDP by Sector), Bureau of Labor Statistics (Job Growth, Manufacturing Employment); D. Autor and D. Dorn, U.S. Census, American Community Survey, and Department of Labor (Change in Employment and Wages by Skill, Routine Jobs)

Tagged: Computing, Biomedicine, Business, Communications, Energy, Web, robotics, AI, economy, jobs, automation, middle class

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FLUID: IBM's Watson Supercomputer. Talk and answer questions.

IBM's Watson supercomputer will soon be your personal shopper

BY Mariella Moon @mariella_moon April 24th 2014, at 4:44:00 am 26

Watson had been a doctor, a geneticist, a game show contestant and even a chef in the past. But now IBM's supercomputer has a new career: personal shopping. IBM has partnered with digital commerce firm Fluid to develop a cloud-based app called Expert Personal Shopper (XPS), which uses Watson's brains to answer buyers' highly specific questions. In short, the computer with many hats now plays the role of a sales associate when you're shopping online. IBM and Fluid are currently working with several consumer brands, but The North Face will be the first to feature the technology on its website. When the outdoor clothing and equipment company launches XPS, you can ask it questions like you would an assistant at a mall. If you needed a recommendation on the best equipment to use for a five-day cross-country trip, or need to know the best tent to use if you're hiking with family, including kids, then Watson's got your back. It's unclear when XPS will launch exactly, but IBM has granted Fluid a $100 million investment to speed up the digital shopping assistant's development -- all parties involved are planning to develop it further for mobile applications and devices.