REPRISE: At least the creative jobs can't be taken over by robots. Wait, what?

Note: The blog is taking some well-deserved rest for the next two weeks (that is code for I am pretty much out of decent ideas, and I doubt most folks are spending their holidays reading blogs anyway), and will be re-running some of best, or at least most interesting posts from 2013. Maybe you missed these the first time around or maybe you didn't really miss them, but either way they are presented for your consideration. Thanks to everyone who stopped by in 2013!

The below post was just one example of the topic I talked about the most in 2013 - the continual and increasing encroachment and pressure that technology and automation is having on the workplace - rendering more and more of us if not obsolete, at least significantly less relevant. The piece originally ran in April 2013.

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At least the creative jobs can't be taken over by robots. Wait, what?

I know I have beaten the 'robots are coming to take our jobs' angle pretty much to death here over the last few years, and I really want to move on to other things like what we can learn about leadership from Kobe Bryant and the Mamba Mentality, and why Jasper Johns is America's greatest artist, something about the automation of formerly human jobs keeps sucking me back in.

Check this excerpt from a recent piece on Business Insider titled How Facebook Is Replacing Ad Agencies With Robots, about some of the behind-the-scenes machinations that result in those often eerily smart advertisements you see on your Facebook timeline and newsfeed:

Facebook is working furiously to find more ways to make ads work better inside its ecosystem. Many of those ads, however, are untouched by ad agency art directors or "creative" staffers of any kind. And a vast number, from Facebook's larger e-commerce advertisers — think Amazon or Fab.com — are generated automatically by computers. 

If you're an e-commerce site selling shoes, you want to serve ads that target people who have previously displayed an interest in, say, red high-heels. Rather than serve an ad for your brand — "Buy shoes here!" — it's better to serve an ad featuring a pair of red heels specifically like the one the user was browsing for.

The ads are monitored for performance, so any subjective notions of "taste" or "beauty" or "style" or whatever go out the window — the client just wants the best-performing ads. There's no need for a guy with trendy glasses who lives in a loft in Williamsburg, N.Y., to mull over the concepts for hours before the ad is served.

It might be easy to miss in that description, but the key to the entire 'no humans necessary' ad creation and display process is a technology that is called 're-targeting' - Facebook (via some partners it works with), knows what products and services you have shown interest in out on the web, and then the algorithms try to 'match' your browsing trail with what the advertiser hopes will be a relevant ad. Since the volume of people and data and browsing history is so immense that a person or people couldn't actually create all the possible ads the process might need, the algorithms do all the work. 

So if you stopped at that Rasheed Wallace 'Ball Don't Lie' shirt on the online T-shirt site this morning, don't be surprised if you see an ad for similar on your Facebook feed tonight. 

Not a big deal you might be thinking, it's the web after all, and algorithms and machines run it all anyway. 

The big deal if you are a creative type person in advertising or media planning is this - if these kinds of re-targeted and machine generated ads show some solid ROI, more and more of the ad budget for big brands will follow. Budget that could be used for TV spots, print campaigns, or even more innovative games and contests on social networks, (that still, for now, have to be hatched and launched by actual humans). If machine-generated ads drive more revenue, (or drive revenue more efficiently), than traditional and expensive creative, then we'll see that impact in staffing. 

Traditional ads often run in media where it can be notoriously difficult to determine success - how valuable and how much revenue for a brand like Budweiser can be attributed to an obscenely expensive Super Bowl ad?

But these computer generated Facebook ads? The system can see in real-time how they are performing, which versions of a given campaign are more effective, and they can learn and adapt in reaction to this data. They are smart, so to speak. Almost everything about them from an ad standpoint is 'better' than the creative ad in a magazine or on TV.

Except for the fact that hardly any people are needed to create them. Depending on your point of view of course.

Be nice to the robots.

The most interesting companies in HR Tech #1 - Glassdoor

Note: It's time for a new, semi-occasional series here at the blog, especially since 'Job Titles of the Future' seems to have hit a bit of a dry patch. This time I am going to stay a little closer to a topic I am at least slightly more familiar with, the landscape of HR Technology solution providers. With 'The most interesting companies' series, I aim to highlight some of the cool and well, interesting things that HR tech companies are doing, particularly in areas that you may not be familiar with. As with every semi-occasional series on the blog, it will last as long as I find it interesting to write. And one more thing, none of the posts in this series are sponsored and I am not being compensated in any way for featuring any specific company.

Onward...

For the first 'most interesting' company, I submit Glassdoor.

Sure, you know Glassdoor as the home of the most extensive and thorough data source for company reviews submitted by employees, and a go-to source for job seekers to learn more about potential employers. And of course you know about Glassdoor's well-regarded and widely publicized lists and rankings, the best known being their Top 50 Places to Work list that was released earlier this week.

But what you may not know is that beyond their position as the de-facto home on the internet for a significant portion of what constitutes most organizations 'employer brand', Glassdoor has steadily been building additional tools and capabilities for employers to participate in proactive employer brand management, candidate engagement, accompanied by recruiting insights and analytics that are making Glassdoor an increasingly important and influential HR tech provider.

And Glassdoor provides many of these advanced company analytics for free, and so far over 16,000 companies have created free employer accounts to take advantage of the data and the insights. (See images on the right for example).Click to enlarge

Traffic to Glassdoor.com is ridiculously large, and the unique, valuable, and not reproducible asset of the millions of candidate and employee data points that form the backbone of the site make for an incredibly powerful, and yes, interesting combination, and at some level, makes Glassdoor one of the few (maybe the only) threats to 500-lb recruiting solutions provider LinkedIn.

Bottom line, 'normal' people go to LinkedIn every once in a while, when want to start looking for a job and think they had better polish up their profile. But they go to Glassdoor once they actually are immersed in the process, researching companies, prepping for interviews, trying to assess if the salary offers they received are fair. That is a huge distinction and one that Glassdoor is leveraging more and more each year.

Recently, Glassdoor announced a $50M funding round and according to the press release the funding will "use the capital to expand its team, accelerate international expansion, and further invest in products for job seekers and employers on mobile and desktop."

Click to enlarge

Glassdoor is already an extremely well known and well positioned player in the recruiting and talent management space and with additional funding, new products, an increasing global footprint, and the insane amounts of data and insight that can be mined from its data on over 300,000 companies it stands to become one of the most interesting (yes, I used that word again), HR tech companies to watch in 2014.

Have a great weekend everyone!

Q&A: How Mobile Consumers are Changing HR Technology

Recently I did a quick Q&A with the good folks at Cornerstone OnDemand that centered on how the consumer, really the smartphone and tablet-toting consumer, and their demands and expectations are going to drive and influence developments in the HR Tech space going forward.

In a nutshell, I had three basic takes that are shaping these trends: (you can head over the the Cornerstone OnDemand blog for the full Q&A).

Ease of use - the App-ification of our lives demands that the technologies that will be the most adopted, and therefore the most effective at work, be as easy to access, understand, and immediately derive value from as apps like Yelp, Shazam, and Instagram. No smartphone app comes with a user manual. If you can't move from installation to use to value in minutes then you are going to turn off most of your users. And that is even before we start talking about designing for the smaller screens and tap-tap-tap interfaces, rather than the 27-inch monitor you have at the office.

Mobile is the platform - The most popular social networks are increasingly mobile-only, or mobile-dominated. Facebook, Twitter - they are all about mobile now. And the fast climb of mobile-only messaging apps like WhatsApps and SnapChat tell entrepreneurs that you don't need a web interface to scale into the many millions of users. To day, almost all HR technology aimed at mobile users have just been mobile versions of existing desktop and web applications. I think that is going to change. 

Switching costs will decline - What do you do with a smartphone app that you no longer enjoy or simply ceases to add value to your life? Easy - two taps and it is gone forever and you find something to replace it. As more and more HR and workplace solutions move to the cloud and more will become mobile-only apps, over time both 'vendor lock in' and these kinds of switching costs will be reduced. The very same technology approaches that have allowed the cloud vendors to disrupt the on-premise solutions of the past makes they themselves open to the same disruption.

There is more of my insight/nonsense on these ideas over at the CSOD blog - many thanks to the Cornerstone team for asking me to share some of my thoughts.

Have a great weekend all!  

What does package delivery have in common with Top Music of 2013 lists?

Two exhibits, seemingly unrelated, (actually not seemingly, these are unrelated), but to me are both interesting in and of themselves and even more interesting when placed in a larger context, (and if you are willing to suspend disbelief a little bit).

Exhibit A - This is the one you already know all about, released not coincidentally on the eve of Cyber Monday, which is of course Amazon's plan to (someday) deploy unmanned drones to deliver small packages in less than 30 minutes.

Exhibit B - You might not of caught this one, I'm not really sure why I even read about it as I am not a user of the Shazam app and not really a big music person at all, but here it is from the Econsultancy site - Shazam, Big Data, and the Future of Year-end Lists. 

Since you know all about the Amazon stuff and everyone can get the pretty obvious implications to work and workers of such a plan, let's focus on the Shazam story a little. In case you are unfamiliar, Shazam is a smartphone app that you can use to recognize the name and artist of any song that is playing (as long as it is audible), in a process called 'tagging.' The user is then given the option to tap a link to purchase and download the song.

So in the course of the year the millions of Shazam users 'tag' millions of songs, and create a massive amount of data about music exposure, trends, and general buzz about artists and songs. Shazam is now (quite sensibly) using this data as input into it's 'Best of 2013' music recaps. 

The bigger implication of this? Check out the excellent take from the Econsultancy piece:

The beginning of January in music journalism is typically a barren wasteland of occasional punditry and arbitrary list-making. The bulk of these lists are written by experts using their own opinion and instinct.

Shazam has jettisoned this tradition in favour of data, maths and algorithms.

This is obviously a far more scientific approach than traditional methods, which removes subjective opinion and puts the list in the hand of Shazam’s 400m users. It is Shazam’s way of using huge amounts of data in order to predict future trends.

A more sensational writer would proclaim that big data is the death of music journalism. Obviously it’s not. What’s the point of publishing a list of the top artists to watch in 2014, curated by 400m users, if 400m users technically already know who to watch out for?

Amazon and its delivery partners someday maybe, would theoretically need far fewer drivers and driver helpers (and trucks and all the folks that work on keeping the trucks running), if they can successfully deploy an unmanned drone air armada to do at least some of their deliveries. And probably before the Amazon drones are a reality, unmanned and self-driving trucks and vans seem both closer to reality and availability, and disruptive to the job prospects in an industry already struggling to supply enough human labor. Not really surprising given how advances in technology have traditionally eliminated jobs and job categories in the past.

But the Shazam story is much different, and newer, and perhaps even more important since it isn't a theory or a prototype or just a nutty idea. Rather it's a simple example of how data, math, algorithms, and actual, regular people are being combined and mashed-up to disrupt something else entirely, the realm of the 'expert.'

Who needs some hipster music critic or tastemaker to grace us with his/her opinion about what the best songs or books or restaurants are when we have Shazam, Spotify, Amazon, Yelp and dozens of other sites and apps that create data that 'removes subjective opinion' and presents only findings that are backed by that data?

We don't need subject matter experts at all really, at least in these discrete fields, we only need one kind of subject matter expert, the data scientist/programmer type that can make sense of the data for any field at all really. After all, data is data, right?

It is really easy to see a future and understand one where truck drivers and other kinds of manual and medium-skilled roles are going to be increasingly threatened by technology.

It is much different, and up until now kind of unthinkable, to see a future when professional 'experts' are going to be needed less and less.

Here is the advice I give to my 12 year-old son, (I know he is not really listening, I just like hearing myself talk) - "Be the chef, not the guy trying to tell everyone else where they should eat." 

Soon, Google will be able to Tweet for you

What's the worst thing for the average person trying to deal with the incredible growth of social networking?

I'd probably say it is the ridiculous amount of time and energy that adults spend wishing each other 'Happy Birthday!' on Facebook.

But for many other heavy users (and business and professional accounts) of social networking one of the main problems is simply keeping up with the flow of information, finding ways to sift and organize the constant streams of updates, and finding the time and energy to respond, engage, and interact in both a timely and relevant manner.

It is exhausting. A professional connection of yours is always posting about a new job on LinkedIn, someone you are hoping to curry favor with is updating their Facebook status with their latest vacation pics or athletics triumphs of their kids,  or some colleagues are mentioning your latest blog post or presentation on Twitter.

You should take the time to say 'Congratulations!' or to 'Like' the fact that little Joey scored 4 goals against a bunch of 6 year-olds, and to say 'Thanks!' to everyone that says something nice about your work on Twitter. You should do those things. 

But like I said it is exhausting. And time consuming. And kind of boring.

Enter your friends at Google who are seeking to patent a system/solution for the 'Automated generation of suggestions for personalized reactions in a social network.' 

From the text of the patent filing:

The popularity and use of social networks and other types of electronic communication has grown dramatically in recent years. With the increased use and popularity of social networks, the value of these networks has increased exponentially. However, this also means that the number of messages and information each user must process has increased exponentially. It is often difficult for users to keep up with and reply to all the messages they are receiving. Therefore, it is important for user to keep to most critical message based on their interests and more importantly, based on how other users reacted to that message.

Many users use online social networking for both professional and personal uses. Each of these different types of use has its own unstated protocol for behavior. It is extremely important for the users to act in an adequate manner depending upon which social network on which they are operating. For example, it may be very important to say "congratulations" to a friend when that friend announces that she/he has gotten a new job. This is a particular problem as many users subscribe to many social different social networks. With an ever increasing online connectivity and growing list of online contacts and given the amount of information users put online, it is possible for a person to miss such an update.

Ok, we get all that.  Too much data, too many contacts, missing updates and opportunities to engage. So what does Google propose to solve these challenges?

The present disclosure overcomes the deficiencies and limitations of the prior at least in part by providing a system and method for generating suggestions for personalized reactions or messages. The system according to the present disclosure includes a suggestion generation module. In one embodiment, the suggestion generation module includes a plurality of collector modules, a credentials module, a suggestion analyzer module, a user interface module and a decision tree. The plurality of collector modules are coupled to respective systems to collect information accessible by the user and important to the user from other systems such as e-mail systems, SMS/MMS systems, micro blogging systems, social networks or other systems. The credentials module cooperates with the plurality of collector modules to allow access to those other systems. The information from these collector modules is provided to the suggestion analyzer module. The suggestion analyzer module cooperates with the user interface module and the decision tree to generate suggested reactions or messages for the user to send. The suggested reactions or messages are presented by the user interface module to the user. The user interface module also displays the original message, other information about the original message such as others' responses, and action buttons for sending, discarding or ignoring the suggested message

Awesome. In case you missed the process flow buried in the dense verbiage here it is simply put:

Since Google knows so much about you (using data from 'e-mail systems, SMS/MMS systems, social networks, and other systems') it thinks that it could generate for you the kinds of personalized reactions you would be likely to post on social media and then post them on your behalf. It still would allow you or a corporate brand marketer to be in the approval process, a dialog or UI would be presented to the user and would ask for an approval before each tweet was sent.

Think about it. Instead of just a calendar pop-up or a Facebook notification telling you that 'So and so's birthday is today', the new Google social media robot would have your appropriately crafted reply all ready to go. Instead of scouring LinkedIn all day for the career ebbs and flows of people that you are interested in, just have the social media robot keep watch for you and let you know only when something that truly requires your attention surfaces. Note: This will hardly ever happen.

I dig it. I hope it gets made. That is what social networking really needs too.

More robots.

Note: The blog is on vacation the rest of the week. To all the folks in the USA, Happy Thanksgiving!