As you probably guessed, Jack Welch has been on my mind, mainly because I was stuck having lunch with a retired executive who went on and on about what a great role model Welch is.

When I disagreed, with specific examples, he informed me that he expected my reaction because I was a woman.

Huh?

Wow. I’m really glad this guy is retired, because he sure doesn’t relate to today’s workers no matter their age.

Jack Welch said a lot of stupid things (IMO), but one of the worst was his attitude towards work/life balance.

“There’s no such thing as work-life balance. There are work-life choices, and you make them, and they have consequences.”

Another was his evangelizing Six Sigma as the solution to everything.

But nothing replaces high EQ, empathic, humane (not just human) bosses.

Not  processes, not technology, not AI, and definitely not robots.

No matter what big and little tech want, believe or tell us, people are analog and always will be. For that matter, the real world is analog and always will be.

So, for the foreseeable future, the management and leadership skills needed to grow strong, creative, highly productive workers will be found in those who understand the limits of digital and can move freely and successfully in an analog world filled with analog people.

They are the true gardeners.

Image credit: Jane Nearing

Back when Jack Welch implemented forced ranking throughout GE. was perched at the top of management gurus he

Also known as forced distribution and, derisively, as “rank and yank,” the practice was championed by former General Electric CEO Jack Welch, who insisted that GE identify and remove the bottom 10 percent of the workforce every year.

Hundreds of companies used it, including tech giants, but most (all?) have stopped. Some took longer than others, Microsoft got rid of it in 2015.

As I said in a post when Amazon finally dumped it in 2016,

Amazing how it’s only taken 30+ years for management to figure out that setting employee against employee does not foster teamwork.

Having to watch your back, knowing it’s “you or them,” doesn’t foster anything.

But even without a formal forced ranking policy, some managers still believe that pitting team members against each other is the fastest way to boost productivity.

However, it’s a great way to increase your experience hiring

Image credit: russel harris

Poking through  13+ years of posts I find information that’s as useful now as when it was written.

Golden Oldies is a collection of the most relevant and timeless posts during that time.

I wrote this in 2012 and reposted it in 2015. The idea behind it is one the most important and viable concepts a manager (supervisor, team lead, executive) will (can, should) learn during their career. It is the difference between good and great.

Read other Golden Oldies here.

As companies grow and managers build their organizations they frequently talk about “weeding out” low performing employees—Jack Welch was a ninja weeder.

If that thought has crossed your mind you might take a moment to think about James Russell Lowell’s comment, “A weed is no more than a flower in disguise.”

As with weeds, there are better ways to look at under-performing employees.

Seeing a weed as food changes everything, just as seeing people’s potential does.

95% of the time it’s management failures that create weeds and those failures run the gamut from benign neglect to malicious abuse and everything in-between.

Weeds can come from outside your company, inter-departmental transfers and even from peers in your own backyard.

What is amazing is how quickly a weed will change with a little TLC.

“Weeds can grow quickly and flower early, producing vast numbers of genetically diverse seed.”

People grow quickly, too, and often produce innovative ideas just because someone listened instead of shutting them down.

And while trust that your attitude won’t change takes longer to build, the productivity benefits happen fairly rapidly.

So before you even think about weeding look in the mirror and be sure that the person looking back is a gardener and not a weed producer.

Flickr image credit: barockschloss

I’ve written before that Alphabet has no scruples about how its various parts make money as long as they do.

YouTube is the most obvious proof.

It wasn’t until major brands pulled their ads that YouTube cleaned up a tiny bit of its act.

YouTube has previously been forced to make major changes because of advertiser backlash. In 2017, hundreds of brands pulled their advertising from YouTube after The Times reported their ads were appearing next to extremist videos. Dubbed the “YouTube Adpocalypse,” the mass boycott cost YouTube’s parent company, Google, an estimated $750 million, a note from analysts at Nomura Instinet said at the time.

When a “soft-core pedophile ring” was exposed last February YouTube disabled comments on most videos featuring kids, but only because big advertisers walked.

More recently, in spite of concerns over breeches of child privacy, brands have stayed steady and YouTube has done nothing to change.

Nor will it.

Because YOU don’t matter

YOU are a user.

Content providers are users.

As Forrester analyst Renee Murphy says,

“Users are the product, not the customer.”

Brands are the customer.

And the customer is always right.

Image credit: Joegoauk Goa

Poking through  13+ years of posts I find information that’s as useful now as when it was written.

Golden Oldies is a collection of the most relevant and timeless posts during that time.

We all have visual prejudices that have nothing to do with race, ethnicity, gender anything obvious. It’s important to know your own or you can’t hear past them. I worked hard to be aware of mine. I had no choice, because, back when I was a recruiter, I occasionally met my candidates. I vividly remember two of them, because if I had met them before I presented them and set up interviews I wouldn’t have, which would have cost me dearly, since both were hired (different companies). Why not? Because they both hit my visual prejudices.

Read other Golden Oldies here.

Discrimination comes in many forms.

All of them are grounded in stupidity, but it’s age and appearance that I want to focus on today.

Layoffs are always a time when age is in the limelight, but this time it’s working in reverse.

“The share of older Americans who have jobs has risen during the recession, while the share of younger Americans with jobs has plunged.”

It seems that at least parts of corporate America have learned to see past the obvious.

“…employees whom companies have invested in most and who have “demonstrated track records…tend to be more experienced and are often older.””

So some companies have discovered that years of experience have substantial value when it comes to the success of the company.

But what about appearance? How much is hearing influenced by how someone looks at first take?

What better venue in which to consider this than the original British version of American Idol where the contestants are mostly young, generally good-looking and always bust their tails to make an impression.

How well do you think a slightly frumpy-looking 47 year old woman would fare under the scathing tongue of Simon Fuller?

How much do you think talent would offset the obvious visual assumptions made by both the judges and the audience?

Watch the judges and audience reaction carefully before Susan Boyle performs and how quickly it changes when she starts singing (embedding is disabled on this video); check out some of the more than 50 thousand comments.

Think about what happens when a “Susan” comes to interview; how well do you hear past her (or his) appearance?

Then come back and share your thoughts with us.

PS For a fascinating look at Susan read this article in the NY Times.

Image credit: cwsillero on sxc.hu

Yesterday you met the founder of a tech company that voluntarily shut down because its app was being abused.

Google, however, is playing its standard game of privacy announcements that sound great, but…

Users can now opt-in to have their location data automatically deleted from Google every three or every 18 months, depending on their preference.

The catch, of course, is the timeframe. If you bother deleting your info daily or weekly, as do many people, especially from their kids phones, Google’s offer of three or 18 months isn’t very attractive.

That’s plenty of time for the data to migrate.

Win-win for Google.

Makes them sound as if they are doing something big for your privacy, without actually costing them anything.

Guess that’s the difference between a company with a real conscience and one with a good feel for PR.

Image credit: Joakim Jardenbergerg

Sounds like an oxymoron.

The world knows about tech’s love affair with, and misuse of, personal data. The continual ignoring, minimizing and excusing of hate speech, revenge porn, fake news, bullying, etc.

Then there is its totally irrational attitude/belief that people will be kind and good to each other online no matter what they are like in the real world.

Given the prevailing attitude, would a hot tech startup have a conscience?

So would a founder, a self-described “technology enthusiast,” create an AI app that went viral and then shut it down because of the way it was being used?

DeepNude was built on Pix2Pix, an open-source algorithm used for “image-to-image translation.” the app can create a naked image from any picture of a woman with just a couple of clicks. Revenge porn activists said the app was “absolutely terrifying.”

As to the above question, the answer is “yes.”

The DeepNude team was horrified, believing “the probability that people will misuse it is too high.”

“We don’t want to make money this way. Surely some copies of DeepNude will be shared on the web, but we don’t want to be the ones who sell it,” DeepNude wrote in a tweet. “The world is not yet ready for DeepNude.”

—deepnudeapp (@deepnudeapp) June 27, 2019

Pix2Pix was developed by a team of scientists, who now believe the industry needs to do better and not just release their work to the world at large.

“We have seen some wonderful uses of our work, by doctors, artists, cartographers, musicians, and more,” the MIT professor Phillip Isola, who helped create Pix2Pix, told Business Insider in an email. “We as a scientific community should engage in serious discussion on how best to move our field forward while putting reasonable safeguards in place to better ensure that we can benefit from the positive use-cases while mitigating abuse.”

One can only hope that the scientific community does, indeed, find a way to do good while avoiding the worst of the negative fallout from discoveries.

And hats off to the DeepNude team.

It’s really inspiring to see such a concrete example of doing the right thing, with no shilly-shallying or dancing around the decision.

But I do wonder what would have happened if either the developers or the scientists were beholden  to investors.

Image credit: deepnudeapp via Twitter

Poking through  13+ years of posts I find information that’s as useful now as when it was written.

Golden Oldies is a collection of the most relevant and timeless posts during that time.

Six years since I wrote this and it’s only gotten worse. More time spent on social media, more time spent staring at a screen as the world goes by. But if people don’t reengage soon, the world they knew will no longer exist.

Read other Golden Oldies here.

I had just finished unloading my cart at Home Depot the other day when a woman pulled up with her two young sons; when I offered her my cart she shook her head and kept walking.

There was a time when she might have offered to take the cart, but those times seem a part of the past.

Instead, she kept walking, talked to her sons and answered her cell phone.

Is the world really shrinking or is it just a narrowing of interactions and less interest in what’s around us in real-time?

The more distracted we become, and the more emphasis we place on speed at the expense of depth, the less likely and able we are to care.

Everyone wants his parent’s, or friend’s, or partner’s undivided attention — even if many of us, especially children, are getting used to far less. Simone Weil wrote, “Attention is the rarest and purest form of generosity.”

Each step “forward” has made it easier, just a little, to avoid the emotional work of being present, to convey information rather than humanity.

As usual, I am out of step.

I take back the carts, function beautifully sans cell/smartphone, pay attention to the humans in my orbit and love real-world interactions.

Digging in the dirt, conversation and reading (mostly cozy mystery fiction) are my favorite “time wasters;” no Facebook, Twitter or Candy Crush (my sister’s addiction).

I prefer to be connected to a few in the real world than connected to dozens (hundreds?) in the cyber world.

In short, I want to continue to pay attention and be present for whatever time I have left on this planet, whether decades or days.

Flickr image credit: Enzo Varriale

Every day seems to bring more bad news from the AI front.

Google gives away tools for DIY AI, with no consideration for who uses them or for what.

One result is the proliferation of deepfakes.

Now scientists from Stanford University, the Max Planck Institute for Informatics, Princeton University, and Adobe Research are making faking it even simpler.

In the latest example of deepfake technology, researchers have shown off new software that uses machine learning to let users edit the text transcript of a video to add, delete, or change the words coming right out of somebody’s mouth.

The result is that almost anyone can make anyone say anything.

Just type in the new script.

Adobe, of course, plans to consumerize the tech, with a focus on how to generate the best revenue stream from it.

It’s not their problem how it will be used or by whom.

Yet another genii out of the box and out of control.

You can’t believe what you read; you can’t believe what you read or hear; it’s been ages since you could believe pictures, and now you won’t be able to believe videos you see.

All thanks to totally amoral tech.

Werner Vogels, Amazon’s chief technology officer, spelled out tech’s attitude in no uncertain terms.

It’s in society’s direction to actually decide which technology is applicable under which conditions.

“It’s a societal discourse and decision – and policy-making – that needs to happen to decide where you can apply technologies.”

Decisions and policies that happen long after the tech is deployed — if at all.

Welcome to the future.

Image credit: Marion Paul Baylado

I’ve written before that AI is biased for the same reason children grow up biased — they both learn from their parents.

In AI’s case its “parents” are the datasets used to train the algorithms.

The datasets are a collection of millions of bits of historical information focused on the particular subject being taught.

In other words, the AI learns to “think”, evaluate information and make judgments based on what has been done in the past.

And what was done in the past was heavily biased.

What does that mean to us?

In healthcare, AI will downgrade complaints from women and people of color, as doctors have always done.

And AI will really trash you if you are also fat. Seriously.

“We all have cultural biases, and health care providers are people, too,” DeJoy says. Studies have indicated that doctors across all specialties are more likely to consider an overweight patient uncooperative, less compliant and even less intelligent than a thinner counterpart.

AI is contributing significantly to the racial bias common in the courts and law enforcement.

Modern-day risk assessment tools are often driven by algorithms trained on historical crime data. (…) Now populations that have historically been disproportionately targeted by law enforcement—especially low-income and minority communities—are at risk of being slapped with high recidivism scores. As a result, the algorithm could amplify and perpetuate embedded biases and generate even more bias-tainted data to feed a vicious cycle.

Facial recognition also runs on biased AI.

Nearly 35 percent of images for darker-skinned women faced errors on facial recognition software, according to a study by Massachusetts Institute of Technology. Comparatively lighter-skinned males only faced an error rate of around 1 percent.

While healthcare, law and policing are furthest along, bias is oozing out of every nook and cranny that AI penetrates.

As usual, the problem was recognized after the genie was out of the box.

There’s a lot of talk about how to correct the problem, but how much will actually be done and when is questionable.

This is especially true since the bias in AI is the same as that of the people using it it’s unlikely they will consider it a problem.

Image credit: Mike MacKenzie