Category Archives: Technology

The AI Apocalypse is Here

3 Reasons You Should Celebrate!

The AI Apocalypse is Here

GUEST POST from Robyn Bolton

Whelp, the apocalypse is upon us. Again.

This time the end of the world is brought to you by AI.

How else do you explain the unending stream of headlines declaring that AI will eliminate jobsdestroy the education system, and rip the heart and soul out of culture and the arts? What more proof do you need of our imminent demise than that AI is as intelligent as a Wharton MBA?

We are doomed!

(Deep breath)

Did you get the panic out of your system? Feel better?

Good.

Because AI is also creating incredible opportunities for you, as a leader and innovator, to break through the inertia of the status quo, drive meaningful change, and create enormous value.

Here are just three of the ways AI will help you achieve your innovation goals:

1. Surface and question assumptions

Every company has assumptions that have been held and believed for so long that they hardened into fact. Questioning these assumptions is akin to heresy and done only by people without regard for job security or their professional reputation.

My favorite example of an assumption comes from the NYC public school district whose spokesperson explained the decision to ban ChatGPT by saying, “While the tool may be able to provide quick and easy answers to questions, it does not build critical-thinking and problem-solving skills, which are essential for academic and lifelong success,”

Buried just under the surface of this statement is the assumption that current teaching methods, specifically essays, do build critical thinking and problem-solving skills.

But is that true?

Or have we gotten so used to believing that essays demonstrate critical thinking and problem-solving that we’ve become blind to the fact that most students (yes, even, and maybe especially, the best students) follow the recipe that produces an essay that mirrors teachers’ expectations?

Before ChatGPT, only the bravest teachers questioned the value of essays as a barometer of critical thinking and problem-solving. After ChatGPT, scores of teachers took to Tik Tok and other social media platforms to share how they’re embracing the tool, using it alongside traditional tools like essays, to help their students build skills “essential for academic and lifelong success.”

2. EQ, not IQ, drives success

When all you need to do is type a question into a chatbot, and the world’s knowledge is synthesized and fed back to you in a conversational tone (or any tone you prefer), it’s easier to be the smartest person in the room.

Yes, there will always be a need for deep subject-matter experts, academics, and researchers who can push our knowledge beyond its current frontiers. But most people in most companies don’t need that depth of expertise.

Instead, you need to know enough to evaluate the options in front of you, make intelligent decisions, and communicate those decisions to others in a way that (ideally) inspires them to follow.

It’s that last step that creates an incredible opportunity for you. If facts and knowledge were all people needed to act, we would all be fit, healthy, and have absolutely no bad habits.

For example, the first question I asked ChatGPT was, “Why is it hard for big companies to innovate?” When it finished typing its 7-point answer, I nodded and thought, “Yep, that’s exactly right.”

The same thing happened when I asked the next question, “What should big companies do to be more innovative?”  I burst out laughing when the answer started with “It depends” and then nodded at the rest of its extremely accurate response.

It would be easy (and not entirely untrue) to say that this is the beginning of the end of consultants, but ChatGPT didn’t write anything that wasn’t already written in thousands of articles, books, and research papers.

Change doesn’t happen just because you know the answer. Change happens when you believe the answer and trust the people leading and walking alongside you on the journey.

3. Eliminate the Suck

Years ago, I spoke with Michael. B Jordan, Pixar’s Head of R&D, and he said something I’ll never forget – “Pain is temporary. Suck is forever.”

He meant this, of course, in the context of making a movie. There are periods of pain in movie-making – long days and nights, times when vast swaths of work get thrown out, moments of brutal and public feedback – but that pain is temporary. The movie you make is forever. And if it sucks, it sucks forever,

Sometimes the work we do is painful but temporary. Sometimes doing the work sucks, and we will need to keep doing it forever. Expense reports. Weekly update emails. Timesheets. These things suck. But they must be done.

Let AI do them and free yourself up to do things that don’t suck. Imagine the conversations you could have, ideas you could try, experiments you could run, and people you could meet if you no longer have to do things that suck.

Change is coming. And that’s good news.

Change can be scary, and it can be difficult. There will be people who lose more than they gain. But, overall, we will gain far more than we lose because of this new technology.

If you have any more doubts, I double-checked with an expert.

“ChatGPT is not a sign of the apocalypse. It is a tool created by humans to assist with language-based tasks. While artificial intelligence and other advanced technologies can bring about significant changes in the way we live and work, they do not necessarily signal the end of the world.”

ChatGPT in response to “Is ChatGPT a sign of the apocalypse?”

Image credit: Pixabay

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The Coming Innovation Slowdown

The Coming Innovation Slowdown

GUEST POST from Greg Satell

Take a moment to think about what the world must have looked like to J.P. Morgan a century ago, in 1919. He was not only an immensely powerful financier with access to the great industrialists of the day, but also an early adopter of new technologies. One of the first electric generators was installed at his home.

The disruptive technologies of the day, electricity and internal combustion, were already almost 40 years old, but had little measurable economic impact. Life largely went on as it always had. That would quickly change over the next decade when those technologies would drive a 50-year boom in productivity unlike anything the world had ever seen before.

It is very likely that we are at a similar point now. Despite significant advances in technology, productivity growth has been depressed for most of the last 50 years. Over the next ten years, however, we’re likely to see that change as nascent technologies hit their stride and create completely new industries. Here’s what you’ll need to know to compete in the new era.

1. Value Will Shift from Bits to Atoms

Over the past few decades, innovation has become almost synonymous with digital technology. Every 18 months or so, semiconductor manufacturers would bring out a new generation of processors that were twice as powerful as what came before. These, in turn, would allow entrepreneurs to imagine completely new possibilities.

However, while the digital revolution has given us snazzy new gadgets, the impact has been muted. Sure, we have hundreds of TV channels and we’re able to talk to our machines and get coherent answers back, but even at this late stage, information and communication technologies make up only about 6% of GDP in advanced countries.

At first, that sounds improbable. How could so much change produce so little effect? But think about going to a typical household in 1960, before the digital revolution took hold. You would likely see a TV, a phone, household appliances and a car in the garage. Now think of a typical household in 1910, with no electricity or running water. Even simple chores like cooking and cleaning took hours of backbreaking labor.

The truth is that much of our economy is still based on what we eat, wear and live in, which is why it’s important that the nascent technologies of today, such as synthetic biology and materials science, are rooted in the physical world. Over the next generation, we can expect innovation to shift from bits back to atoms.

2. Innovation Will Slow Down

We’ve come to take it for granted that things always accelerate because that’s what has happened for the past 30 years or so. So we’ve learned to deliberate less, to rapidly prototype and iterate and to “move fast and break things” because, during the digital revolution, that’s what you needed to do to compete effectively.

Yet microchips are a very old technology that we’ve come to understand very, very well. When a new generation of chips came off the line, they were faster and better, but worked the same way as earlier versions. That won’t be true with new computing architectures such as quantum and neuromorphic computing. We’ll have to learn how to use them first.

In other cases, such as genomics and artificial intelligence, there are serious ethical issues to consider. Under what conditions is it okay to permanently alter the germ line of a species. Who is accountable for the decisions and algorithm makes? On what basis should those decisions be made? To what extent do they need to be explainable and auditable?

Innovation is a process of discovery, engineering and transformation. At the moment, we find ourselves at the end of one transformational phase and about to enter a new one. It will take a decade or so to understand these new technologies enough to begin to accelerate again. We need to do so carefully. As we have seen over the past few years, when you move fast and break things, you run the risk of breaking something important.

3. Ecosystems Will Drive Technology

Let’s return to J.P. Morgan in 1919 and ask ourselves why electricity and internal combustion had so little impact up to that point. Automobiles and electric lights had been around a long time, but adoption takes time. It takes a while to build roads, to string wires and to train technicians to service new inventions reliably.

As economist Paul David pointed out in his classic paper, The Dynamo and the Computer, it takes time for people to learn how to use new technologies. Habits and routines need to change to take full advantage of new technologies. For example, in factories, the biggest benefit electricity provided was through enabling changes in workflow.

The biggest impacts come from secondary and tertiary technologies, such as home appliances in the case of electricity. Automobiles did more than provide transportation, but enables a shift from corner stores to supermarkets and, eventually, shopping malls. Refrigerated railroad cars revolutionized food distribution. Supply chains were transformed. Radios, and later TV, reshaped entertainment.

Nobody, not even someone like J.P. Morgan could have predicted all that in 1919, because it’s ecosystems, not inventions, that drive transformation and ecosystems are non-linear. We can’t simply extrapolate out from the present and get a clear future of what the future is going to look like.

4. You Need to Start Now

The changes that will take place over the next decade or so are likely to be just as transformative—and possibly even more so—than those that happened in the 1920s and 30s. We are on the brink of a new era of innovation that will see the creation of entirely new industries and business models.

Yet the technologies that will drive the 21st century are still mostly in the discovery and engineering phases, so they’re easy to miss. Once the transformation begins in earnest, however, it will likely be too late to adapt. In areas like genomics, materials science, quantum computing and artificial intelligence, if you get a few years behind, you may never catch up.

So the time to start exploring these new technologies is now and there are ample opportunities to do so. The Manufacturing USA Institutes are driving advancement in areas as diverse as bio-fabrication, additive manufacturing and composite materials. IBM has created its Q Network to help companies get up to speed on quantum computing and the Internet of Things Consortium is doing the same thing in that space.

Make no mistake, if you don’t explore, you won’t discover. If you don’t discover you won’t invent. And if you don’t invent, you will be disrupted eventually, it’s just a matter of time. It’s always better to prepare than to adapt and the time to start doing that is now.

— Article courtesy of the Digital Tonto blog
— Image credit: Pexels

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Rise of the Prompt Engineer

Rise of the Prompt Engineer

GUEST POST from Art Inteligencia

The world of tech is ever-evolving, and the rise of the prompt engineer is just the latest development. Prompt engineers are software developers who specialize in building natural language processing (NLP) systems, like voice assistants and chatbots, to enable users to interact with computer systems using spoken or written language. This burgeoning field is quickly becoming essential for businesses of all sizes, from startups to large enterprises, to remain competitive.

Five Skills to Look for When Hiring a Prompt Engineer

But with the rapid growth of the prompt engineer field, it can be difficult to hire the right candidate. To ensure you’re getting the best engineer for your project, there are a few key skills you should look for:

1. Technical Knowledge: A competent prompt engineer should have a deep understanding of the underlying technologies used to create NLP systems, such as machine learning, natural language processing, and speech recognition. They should also have experience developing complex algorithms and working with big data.

2. Problem-Solving: Prompt engineering is a highly creative field, so the ideal candidate should have the ability to think outside the box and come up with innovative solutions to problems.

3. Communication: A prompt engineer should be able to effectively communicate their ideas to both technical and non-technical audiences in both written and verbal formats.

4. Flexibility: With the ever-changing landscape of the tech world, prompt engineers should be comfortable working in an environment of constant change and innovation.

5. Time Management: Prompt engineers are often involved in multiple projects at once, so they should be able to manage their own time efficiently.

These are just a few of the skills to look for when hiring a prompt engineer. The right candidate will be able to combine these skills to create effective and user-friendly natural language processing systems that will help your business stay ahead of the competition.

But what if you want or need to build your own artificial intelligence queries without the assistance of a professional prompt engineer?

Four Secrets of Writing a Good AI Prompt

As AI technology continues to advance, it is important to understand how to write a good prompt for AI to ensure that it produces accurate and meaningful results. Here are some of the secrets to writing a good prompt for AI.

1. Start with a clear goal: Before you begin writing a prompt for AI, it is important to have a clear goal in mind. What are you trying to accomplish with the AI? What kind of outcome do you hope to achieve? Knowing the answers to these questions will help you write a prompt that is focused and effective.

2. Keep it simple: AI prompts should be as straightforward and simple as possible. Avoid using jargon or complicated language that could confuse the AI. Also, try to keep the prompt as short as possible so that it is easier for the AI to understand.

3. Be specific: To get the most accurate results from your AI, you should provide a specific prompt that clearly outlines what you are asking. You should also provide any relevant information, such as the data or information that the AI needs to work with.

4. Test your prompt: Before you use your AI prompt in a real-world situation, it is important to test it to make sure that it produces the results that you are expecting. This will help you identify any issues with the prompt or the AI itself and make the necessary adjustments.

By following these tips, you can ensure that your AI prompt is effective and produces the results that you are looking for. Writing a good prompt for AI is a skill that takes practice, but by following these secrets you can improve your results.

So, whether you look to write your own AI prompts or feel the need to hire a professional prompt engineer, now you are equipped to be successful either way!

Image credit: Pexels

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AI is a Powerful New Tool for Entrepreneurs

AI is a Powerful New Tool for Entrepreneurs

by Braden Kelley

In today’s digital, always connected world, Google too often stands as a gatekeeper between entrepreneurs and small businesses and financial success. Ranking well in the search engines requires time and expertise that many entrepreneurs and small business owners don’t have, because their focus must be on fine tuning the value proposition and operations of their business.

The day after Google was invented, the search engine marketing firm was probably created to make money off of hard working entrepreneurs and small businesses owners trying to make the most of their investment in a web site through search engine optimization (SEO), keyword advertising, and social media strategies.

According to IBISWorld the market size of the SEO & Internet Marketing Consulting industry is $75.0 Billion. Yes, that’s billion with a ‘b’.

Creating content for web sites is an even bigger market. According to Technavio the global content marketing size is estimated to INCREASE by $584.0 Billion between 2022 and 2027. This is the growth number. The market itself is MUCH larger.

The introduction of ChatGPT threatens to upend these markets, to the detriment of this group of businesses, but to the benefit to the nearly 200,000 dentists in the United States, more than 100,000 plumbers, million and a half real estate agents, and numerous other categories of small businesses.

Many of these content marketing businesses create a number of different types of content for the tens of millions of small businesses in the United States, from blog articles to tweets to Facebook pages and everything in-between. The content marketing agencies that small businesses hire recent college graduates or offshore resources in places like the Philippines, India, Pakistan, Ecuador, Romania, and lots of other locations around the world and bill their work to their clients at a much higher rate.

Outsourcing content creation has been a great way for small businesses to leverage external resources so they can focus on the business, but now may be the time to bring some of this content creation work back in house. Particularly where the content is pretty straightforward and informational for an average visitor to the web site.

With ChatGPT you can ask it to “write me an article on how to brush your teeth” or “write me ten tweets on teethbrushing” or “write me a facebook post on the most common reasons a toilet won’t flush.”

I asked it to do the last one for me and here is what it came up with:

Continue reading the rest of this article on CustomerThink (including the ChatGPT results)

Image credits: Pixabay

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Struggling to Innovate? Try This Instead

Struggling to Innovate? Try This Instead

GUEST POST from Robyn Bolton

Everyone is an innovator on January 1.

That’s the day when each of us resolves to do something new that creates value.

  • Start working out so I lose weight, look better, and feel healthier.
  • Stop smoking, so I live longer.
  • Turn off my computer and phone at 6:00 pm so I focus on family.

Only 20% of people are innovators on February 1. The rest of us gave up our resolutions and decided to keep doing the same things that create (good enough) value.

Your business is no different.

At the start of the fiscal year, you resolve to innovate!

  • Explore new offerings, customers, and business models
  • Experiment with new ways to get things done
  • Enter new markets

Then something goes wrong, and you divert some people (not everyone!) from innovating to fixing an operational problem.

Then the first quarter starts coming in below expectations, and you cut budgets to stay on track to deliver the bottom line.

Then something else happens, and something else, and something else, and soon it’s “February 1,” and, for excellent and logical reasons, you give up your resolution to innovate and focus all your resources on operating and hitting your KPIs.

Resolve to Revive.

Innovation is something NEW that creates value.

New is hard. It’s difficult to start something new, and it’s challenging to continue doing it when things inevitably go awry. Investing in something uncertain is risky, primarily when more “certain” investment opportunities exist. It’s why New Year’s resolutions and Innovation strategies don’t stick.

Revival is the creation of new value from OLD.

When you work on Revival, you go back to the old things, the things you explored, tried, implemented, or even launched years ago that didn’t work then but could create more value than anything you’re doing today.

Your business is filled with Revival opportunities.

How to Reveal Revivals

Ask, “What did we do before…?”

Everything we do now – research, development, marketing, sales, communication, M&A – was done before smartphones, laptops, desktops, and even mainframes. Often new technology makes our work easier or more efficient. But sometimes, it just creates work and bad habits.

If you are trying to make Zoom/Teams calls less exhausting and more productive, try to remember meetings before Zoom/Teams. They were conference calls. So, next time you need to meet, revive and schedule a phone conference (or a cameras-off Zoom/Teams call).

Find the failures

Most companies are highly skilled at hiding any evidence of failure. But the memories and stories live on in the people who worked on them. Talk to them, and you may discover a blockbuster idea that failed for reasons you can quickly address.

Like Post-It Notes.

While some parts of the Post-Its story are true – the adhesive was discovered by accident and first used to bookmark pages in a hymnal, most people don’t know that 10 YEARS passed between hymnal use and market success. In that decade, the project was shelved twice, failed in a test market, and given away as free samples before it became successful.

Resurrect the Dead

The decision to exit a market or discontinue a product is never easy or done lightly. And once management makes the decision, people operate under the assumption that the company should never consider returning. But that belief can sometimes be wrong.

Consider Yuengling, America’s oldest brewery and one of its old ice cream shops.

In 1829, David G. Yuengling founded Eagle Brewing in Pottsville, PA. The business did well until, you guessed it, Prohibition. In 1920, D.G. Yuengling & Sons (formerly Eagle Brewing) built a plant across the street from their brewery and began producing ice cream. When Prohibition ends, brewing restarts, and ice cream production continues. Until 1985, when a new generation takes the helm at Yuengling and, under the guise of operational efficiency and business optimization, shut down the ice cream business to focus on beer. TWENTY-NINE YEARS later, executives looking for growth opportunities remembered the ice cream business and re-launched the product to overwhelming customer demand.

Just because you need growth doesn’t mean you need New.

Innovation is something new that creates value. But it doesn’t have to be new to the world.

Tremendous value can be created and captured by doing old things in new ways, markets, or eras.

After all, everything old is new again.

Image credit: Pexels

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Globalization and Technology Have Failed Us

Globalization and Technology Have Failed Us

GUEST POST from Greg Satell

In November 1989, there were two watershed events that would change the course of world history. The fall of the Berlin Wall would end the Cold War and open up markets across the world. That very same month, Tim Berners-Lee would create the World Wide Web and usher in a new technological era of networked computing.

It was a time of great optimism. Books like Francis Fukayama’s The End of History predicted a capitalist, democratic utopia, while pundits gushed over the seemingly neverending parade of “killer apps,” from email and e-commerce to social media and the mobile web. The onward march of history seemed unstoppable.

Today, 30 years on, it’s time to take stock and the picture is somewhat bleak. Instead of a global technological utopia, there are a number of worrying signs ranging from income inequality to the rise of popular authoritarianism. The fact is that technology and globalization have failed us. It’s time to address some very real problems.

Where’s the Productivity?

Think back, if you’re old enough, to before this all started. Life before 1989 was certainly less modern prior to 1989, we didn’t have mobile phones or the Internet, but for the most part it was fairly similar to today. We rode in cars and airplanes, watched TV and movies, and enjoyed the benefits of home appliances and air conditioners.

Now try to imagine what life was like in 1900, before electricity and internal combustion gained wide adoption. Even doing a simple task like cooking a meal or cleaning the house took hours of backbreaking labor to haul wood and water. While going back to living in the 1980s would involve some inconvenience, we would struggle to survive before 1920.

The productivity numbers bear out this simple observation. The widespread adoption of electricity and internal combustion led to a 50-year boom in productivity between 1920 and 1970. The digital revolution, on the other hand, created only an 8-year blip between 1996 and 2004. Even today, with artificial intelligence on the rise, productivity remains depressed.

At this point, we have to conclude that despite all the happy talk and grand promises of “changing the world,” the digital revolution has been a huge disappointment. While Silicon Valley has minted billionaires at record rates, digital technology has not made most of us measurably better off economically.

Winners Taking All

The increase of globalization and the rise of digital commerce was supposed to be a democratizing force, increasing competition and breaking the institutional monopoly on power. Yet just the opposite seems to have happened, with a relatively small global elite grabbing more money and more power.

Consider market consolidation. An analysis published in the Harvard Business Review showed that from airlines to hospitals to beer, market share is increasingly concentrated in just a handful of firms. As more expansive study of 900 industries conducted by The Economist found that two thirds have become more dominated by larger players.

Perhaps not surprisingly, we see the same trends in households as we do with businesses. The OECD reports that income inequality is at its highest level in over 50 years. Even in emerging markets, where millions have been lifted out of poverty, most of the benefits have gone to a small few.

The consequences of growing inequality are concrete and stark. Social mobility has been declining in America for decades, transforming the “land of opportunity” into what is increasingly a caste system. Anxiety and depression are rising to epidemic levels. Life expectancy for the white working class is actually declining, mostly due to “deaths of despair” due to drugs, alcohol and suicide. The overall picture is dim and seemingly getting worse.

The Failure Of Freedom

Probably the biggest source of optimism in the 1990s was the end of the Cold War. Capitalism was triumphant and many of the corrupt, authoritarian societies of the former Soviet Union began embracing democracy and markets. Expansion of NATO and the EU brought new hope to more than a hundred million people. China began to truly embrace markets as well.

I moved to Eastern Europe in the late 1990s and was able to observe this amazing transformation for myself. Living in Poland, it seemed like the entire country was advancing through a lens of time-lapse photography. Old, gray concrete building gave way to modern offices and apartment buildings. A prosperous middle class began to emerge.

Yet here as well things now seem to be going the other way. Anti-democratic regimes are winning elections across Europe while rising resentment against immigrant populations take hold throughout the western world. In America, we are increasingly mired in a growing constitutional crisis.

What is perhaps most surprising about the retreat of democracy is that it is happening not in the midst of some sort of global depression, but during a period of relative prosperity and low unemployment. Nevertheless, positive economic data cannot mask the basic truth that a significant portion of the population feels that the system doesn’t work for them.

It’s Time To Start Taking Responsibility For A Messy World

Looking back, it’s hard to see how an era that began with such promise turned out so badly. Yes, we’ve got cooler gadgets and streaming video. There have also been impressive gains in the developing world. Yet in so-called advanced economies, we seem to be worse off. It didn’t have to turn out this way. Our current predicament is the result of choices that we made.

Put simply, we have the problems we have today because they are the problems we have chosen not to solve. While the achievements of technology and globalization are real, they have also left far too many behind. We focused on simple metrics like GDP and shareholder value, but unfortunately the world is not so elegant. It’s a messy place and doesn’t yield so easily to reductionist measures and strategies.

There has, however, been some progress. The Business Roundtable, an influential group of almost 200 CEOs of America’s largest companies, in 2019 issued a statement that discarded the old notion that the sole purpose of a business is to provide value to shareholders. There are also a number of efforts underway to come up with broader measures of well being to replace GDP.

Yet we still need to learn an important lesson: technology alone will not save us. To solve complex challenges like inequality, climate change and the rise of authoritarianism we need to take a complex, network based approach. We need to build ecosystems of talent, technology and information. That won’t happen by itself, we have to make better choices.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Apple Watch Must Die

At least temporarily, because it’s proven bad for innovation

Apple Watch Must Die

by Braden Kelley

I came across an article in The Hill, titled ‘Apple flexes lobbying power as Apple Watch ban comes before Biden next week‘ that highlighted how Apple has been found guilty by the U.S. International Trade Commission (ITC) of infringing upon the intellectual property of startup AliveCor to provide its wearable electrocardiogram features in its Apple Watch.

Apple is now trying to get President Biden to veto the ruling (I didn’t know that was a thing) so that they can keep selling Apple Watches. In my opinion this is a matter for the courts and yet another example of how big tech (and big companies in general) far too often brazenly misappropriate the intellectual property of the little guys. So much so in Apple’s case that over the last 30+ years a popular term has emerged for it called ‘Sherlocking’.

According to the new Microsoft Bing (with ChatGPT):

Sherlocking is a term that refers to Apple’s practice of copying features from third-party apps and integrating them into its own software¹². The term originated from a search tool named Sherlock that Apple developed in the late 90s and later updated to include features from a similar app named Watson²³.

President Biden must let the courts do their job and not intervene if innovation is to thrive in America.

Apple has been found guilty by the ITC and should be forced to stop selling Apple Watches if that is what the court has decided. They should pay damages and redesign their product to design out the intellectual property theft. And, if they feel they are innocent, then they have an avenue of appeal and should exercise it.

But, bottom line, turning a blind eye to intellectual property theft is bad for innovation. We must encourage and protect entrepreneurship for innovation to thrive.

I’ll leave you with this clip from the movie Tucker to ponder on the way out:

And a trailer from probably the best movie on the subject of the struggle of the innovator against big business, based on the real life story of the inventor of the intermittent wiper – Dr. Robert Kearns, it’s called ‘Flash of Genius’:

Hopefully President Biden will stay out of it and let the courts decide based on the evidence.

Keep innovating!

SPECIAL UPDATE: On February 21, 2023 the Biden Administration elected NOT to veto the ITC ruling, leaving the courts to decide whether Apple is innocent or guilty.

Source: Conversation with Bing, 2/18/2023
(1) Apple ‘Sherlocking’ Highlighted in Antitrust Probe—Google Also …. https://www.itechpost.com/articles/105413/20210422/apple-sherlocking-highlighted-antitrust-probe-google-questioned-over-firewall.htm Accessed 2/18/2023.
(2) What Does It Mean When Apple “Sherlocks” an App? – How-To Geek. https://www.howtogeek.com/297651/what-does-it-mean-when-a-company-sherlocks-an-app/ Accessed 2/18/2023.
(3) Sherlock (software) – Wikipedia. https://en.wikipedia.org/wiki/Sherlock_(software) Accessed 2/18/2023.
(4) All the things Apple Sherlocked at WWDC 2022 – TechCrunch. https://techcrunch.com/2022/06/13/all-the-things-apple-sherlocked-at-wwdc-2022/ Accessed 2/18/2023.

Image credit: Pexels

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The Reality Behind Netflix’s Amazing Success

The Reality Behind Netflix's Amazing Success

GUEST POST from Greg Satell

Today, it’s hard to think of Netflix as anything but an incredible success. Its business has grown at breakneck speed and now streams to 190 countries, yet it has also been consistently profitable, earning over $12 billion last year. With hit series like Orange is the New Black and Stranger Things, it broke the record for Emmy Nominations in 2018.

Most of all, the company has consistently disrupted the media business through its ability to relentlessly innovate. Its online subscription model upended the movie rental business and drove industry giant Blockbuster into bankruptcy. Later, it pioneered streaming video and introduced binge watching to the world.

Ordinarily, a big success like Netflix would offer valuable lessons for the rest of us. Unfortunately, its story has long been shrouded in myth and misinformation. That’s why Netflix Co-Founder Marc Randolph’s book, That Will Never Work, is so valuable. It not only sets the story straight, it offers valuable insight into how to create a successful business.

The Founding Myth

Anthropologists have long been fascinated by origin myths. The Greek gods battled and defeated the Titans to establish Olympus. Remus and Romulus were suckled by a she-wolf and then established Rome. Adam and Eve were seduced by a serpent, ate the forbidden fruit and were banished from the Garden of Eden.

The reason every culture invents origin myths is that they help make sense of a confusing world and reinforce the existing order. Before science, people were ill-equipped to explain things like disease and natural disasters. So, stories, even if the were apocryphal, gave people comfort that there was a rhyme and reason to things.

So it shouldn’t be surprising that an unlikely success such as Netflix has its own origin myth. As legend has it, Co-Founder Reed Hastings misplaced a movie he rented and was charged a $40 dollar late fee. Incensed, he set out to start a movie business that had no late fees. That simple insight led to a disruptive business model that upended the entire industry.

The truth is that late fees had nothing to do with the founding of Netflix. What really happened is that Reed Hastings and Marc Randolph, soon to be unemployed after the sale of their company, Pure Atria, were looking to ride the new e-commerce wave and become the “Amazon of” something. Netflix didn’t arise out of a moment of epiphany, but a process of elimination.

The Subscription Model Was an Afterthought

Netflix really got its start through a morning commute. As Pure Atria was winding down, Randolph and Hastings would drive together from Santa Crux on Highway 17 over the mountain into Silicon Valley. It was a long drive, which gave them lots of time to toss around e-commerce ideas that ranged from customized baseball bats to personalized shampoo.

The reason they eventually settled on movies was the introduction of DVD’s. In 1997, there were very few titles available, so stores didn’t stock them. They were also small and light and were easy to ship. Best of all, the movie studios recognized that they had made a mistake pricing movies on videotape too high and planned to offer DVD’s at a level consumers would buy them.

In the beginning, Netflix earned most of its money selling movies, not renting them. However, before long they realized that it was only a matter of time before Amazon and Walmart began selling DVD’s as well. Once that happened, it was unlikely that Netflix would be able to compete, and they would have to find a way to make the rental model work.

The subscription model began as an experiment. No one seemed to want to rent movies by mail, so they were desperate to find a different model and kept trying things until they hit on something that worked. It wasn’t part of a master plan, but the result of trial and error. “If you would have asked me on launch day to describe what Netflix would eventually look like,” Randolph wrote, “I would have never come up with a monthly subscription service.”

The Canada Principle

As Netflix began to grow it was constantly looking for ways to grow its business. One idea that continually came up was expanding to Canada. It’s just over the border, is largely English speaking, has a business-friendly regulatory environment and shares many cultural traits with the US. It just seemed like an obvious way to increase sales.

Yet they didn’t do it for two reasons. First, while Canada is very similar to the US, it is still another country, with its own currency, laws and other complicating factors. Also, while English is commonly spoken in most parts of Canada, in some regions French predominates. So, what looked simple at first had the potential to become maddeningly complex.

The second and more important reason was that it would have diluted their focus. Nobody has unlimited resources. You only have a certain number of people who can do a certain number of things. For every Canadian problem they had to solve, that was one problem that they weren’t solving in the much larger US business.

That became what Randolph called the “Canada Principle,” or the idea that you need to maximize your focus by limiting the number of opportunities that you pursue. It’s why they dropped DVD sales to focus on renting movies and then dropped a la carte rental to focus on the subscription business. That singularity of focus played a big part in Netflix’s success.

Nobody Knows Anything

Randolph’s mantra throughout the book is that “nobody knows anything.” He borrowed the phrase from the writer William Goldman’s memoir Adventures in the Screen Trade. What Goldman meant was that nobody truly knows how a movie will do until it’s out. Some movies with the biggest budgets and greatest stars flop, while some of the unlikeliest indy films are hits.

For Randolph though, it’s more of a guiding business philosophy. “For every good idea,” he says, “there are a thousand bad ideas it is indistinguishable from.” The only real way to tell the difference is to go out and try them, see what works, discard the failures and build on the successes. You have to, in other words, dare to be crap.

Over the years, I’ve had the chance to get to know hundreds of great innovators and they all tell a different version of the same story. While they often became known for one big idea, they had tried thousands of others before they arrived at the one that worked. It was perseverance and a singularity of focus, not a sudden epiphany, that made the difference.

That’s why the myth of the $40 late fee, while seductive, can be so misleading. What made Netflix successful wasn’t just one big idea. In fact, just about every assumption they made when they started the company was wrong. Rather, it was what they learned along the way that made the difference. That’s the truth of how Netflix became a media powerhouse.

— Article courtesy of the Digital Tonto blog
— Image credit: Unsplash

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Frontier Airlines Ends Human-to-Human Customer Service

Frontier Airlines Ends Human-to-Human Customer Service

GUEST POST from Shep Hyken

In a bold move to cut costs, Frontier Airlines announced that it would no longer offer human-to-human customer support. As a customer service expert, I was surprised at this move. I have waited to see the fallout, if any, and thought the company might backpedal and reinstate traditional phone support. After almost two months, it hasn’t returned to conventional customer support. The dust has settled a bit, and people (passengers and employees) are adjusting to the decision.

The decision to go digital is different from the decision Northwest Airlines (which eventually merged with Delta) made in 1999 to introduce online check-in to its passengers. The idea behind that technology, and eventually the technology driving online reservations, was to give the customer a better and more convenient experience while at the same time increasing efficiency. The big difference in that decision versus Frontier’s was that there has always been (and still is) an option to connect to a live agent. If passengers didn’t want to use the self-service tools the airline provided, they could still talk to someone who could help them.

That does not appear to be the case with Frontier. There is no other option. The airline is relying on digital support. If you check the website for ways to contact them outside of their self-service options on the site or mobile app, you can use chat, email or file a formal written complaint. Chat is in the moment, and can deliver a good experience—even if it’s AI doing the chatting (and not a human). Email or a written complaint could take too long to resolve an immediate problem, such as rebooking a flight for any last-minute reason.

For some background, Frontier Airlines is a low-cost carrier based in Denver. It has plenty of competition, and when you combine that with rising expenses in almost every area of business and a tough economy, Frontier, just like any other company in almost any industry, is looking to cut costs. In a recent Forbes article, I shared the prediction that some companies will make the mistake of cutting expenses in the wrong places. Those “wrong places” are anywhere the customer will notice. Cutting off phone support to a live human, just one of Frontier’s cost-cutting strategies, is one of those places the customer may notice first.

If a customer wants to change or cancel a flight, make a lost-luggage claim and more, if they have the information they need on hand and the system is intuitive and easy to navigate, the experience could be better than waiting on hold for a live agent. Our customer service research found that 71% of customers are willing to use self-service options. That said, the phone is still the No. 1 channel customers prefer to use when they have a problem, question or complaint.

Frontier’s decision to stop human-to-human customer support has generated controversy and criticism from customers/passengers and employees. The company’s management defends its decision, stating that they need to cut costs to remain competitive. They claim you can eventually reach a human, but their passengers will first have to exhaust the digital options. While self-service automated customer support may help the airline cut costs and increase efficiency, it obviously frustrates customers and negatively impacts employees.

The big concern is that 100% digital or self-service support is still too new. We are still a long way from technology completely replacing the human-to-human interactions we’re used to in the customer service and support worlds. Efficiency is important, but so is the relationship you maintain with your customers and employees. It takes a balance. The best companies figure this out.

Consider this: Video did not kill the radio star. ATMs were predicted to eliminate the need for bank tellers. And for the foreseeable future, technology will not kill live, human-to-human interactions. Frontier customers looking to save money will be forced to adapt to its new way of customer service. Knowing this upfront will help. But also consider this, something I’ve been preaching for several years: The greatest technology in the world hasn’t replaced the ultimate relationship-building tool between a customer and a business, and that is the human touch.

This article was originally published on Forbes.com.

Image Credit: Pixabay

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Technology Pushing Us into a New Ethical Universe

Technology Pushing Us into a New Ethical Universe

GUEST POST from Greg Satell

We take it for granted that we’re supposed to act ethically and, usually, that seems pretty simple. Don’t lie, cheat or steal, don’t hurt anybody on purpose and act with good intentions. In some professions, like law or medicine, the issues are somewhat more complex, and practitioners are trained to make good decisions.

Yet ethics in the more classical sense isn’t so much about doing what you know is right, but thinking seriously about what the right thing is. Unlike the classic “ten commandments” type of morality, there are many situations that arise in which determining the right action to take is far from obvious.

Today, as our technology becomes vastly more powerful and complex, ethical issues are increasingly rising to the fore. Over the next decade we will have to build some consensus on issues like what accountability a machine should have and to what extent we should alter the nature of life. The answers are far from clear-cut, but we desperately need to find them.

The Responsibility of Agency

For decades intellectuals have pondered an ethical dilemma known as the trolley problem. Imagine you see a trolley barreling down the tracks that is about to run over five people. The only way to save them is to pull a lever to switch the trolley to a different set of tracks, but if you do that, one person standing there will be killed. What should you do?

For the most part, the trolley problem has been a subject for freshman philosophy classes and avant garde cocktail parties, without any real bearing on actual decisions. However, with the rise of technologies like self-driving cars, decisions such as whether to protect the life of a passenger or a pedestrian will need to be explicitly encoded into the systems we create.

That’s just the start. It’s become increasingly clear that data bias can vastly distort decisions about everything from whether we are admitted to a school, get a job or even go to jail. Still, we’ve yet to achieve any real clarity about who should be held accountable for decisions an algorithm makes.

As we move forward, we need to give serious thought to the responsibility of agency. Who’s responsible for the decisions a machine makes? What should guide those decisions? What recourse should those affected by a machine’s decision have? These are no longer theoretical debates, but practical problems that need to be solved.

Evaluating Tradeoffs

“Now I am become Death, the destroyer of worlds,” said J. Robert Oppenheimer, quoting the Bhagavad Gita. upon witnessing the world’s first nuclear explosion as it shook the plains of New Mexico. It was clear that we had crossed a Rubicon. There was no turning back and Oppenheimer, as the leader of the project, felt an enormous sense of responsibility.

Yet the specter of nuclear Armageddon was only part of the story. In the decades that followed, nuclear medicine saved thousands, if not millions of lives. Mildly radioactive isotopes, which allow us to track molecules as they travel through a biological system, have also been a boon for medical research.

The truth is that every significant advancement has the potential for both harm and good. Consider CRISPR, the gene editing technology that vastly accelerates our ability to alter DNA. It has the potential to cure terrible diseases such as cancer and Multiple Sclerosis, but also raises troubling issues such as biohacking and designer babies.

In the case of nuclear technology many scientists, including Oppenheimer, became activists. They actively engaged with the wider public, including politicians, intellectuals and the media to raise awareness about the very real dangers of nuclear technology and work towards practical solutions.

Today, we need similar engagement between people who create technology and the public square to explore the implications of technologies like AI and CRISPR, but it has scarcely begun. That’s a real problem.

Building A Consensus Based on Transparency

It’s easy to paint pictures of technology going haywire. However, when you take a closer look, the problem isn’t so much with technological advancement, but ourselves. For example, the recent scandals involving Facebook were not about issues inherent to social media websites, but had more to do with an appalling breach of trust and lack of transparency. The company has paid dearly for it and those costs will most likely continue to pile up.

It doesn’t have to be that way. Consider the case of Paul Berg, a pioneer in the creation of recombinant DNA, for which he won the Nobel Prize. Unlike Zuckerberg, he recognized the gravity of the Pandora’s box he had opened and convened the Asilomar Conference to discuss the dangers, which resulted in the Berg Letter that called for a moratorium on the riskiest experiments until the implications were better understood.

In her book, A Crack in Creation, Jennifer Doudna, who made the pivotal discovery for CRISPR gene editing, points out that a key aspect of the Asilomar conference was that it included not only scientists, but also lawyers, government officials and media. It was the dialogue between a diverse set of stakeholders, and the sense of transparency it produced, that helped the field advance.

The philosopher Martin Heidegger argued that technological advancement is a process of revealing and building. We can’t control what we reveal through exploration and discovery, but we can—and should—be wise about what we build. If you just “move fast and break things,” don’t be surprised if you break something important.

Meeting New Standards

In Homo Deus, Yuval Noah Harari writes that the best reason to learn history is “not in order to predict, but to free yourself of the past and imagine alternative destinies.” As we have already seen, when we rush into technologies like nuclear power, we create problems like Chernobyl and Fukushima and reduce technology’s potential.

The issues we will have to grasp over the next few decades will be far more complex and consequential than anything we have faced before. Nuclear technology, while horrifying in its potential for destruction, requires a tremendous amount of scientific expertise to produce it. Even today, it remains confined to governments and large institutions.

New technologies, such as artificial intelligence and gene editing are far more accessible. Anybody with a modicum of expertise can go online and download powerful algorithms for free. High school kids can order CRISPR kits for a few hundred dollars and modify genes. We need to employ far better judgment than organizations like Facebook and Google have shown in the recent past.

Some seem to grasp this. Most of the major tech companies have joined with the ACLU, UNICEF and other stakeholders to form the Partnership On AI to create a forum that can develop sensible standards for artificial intelligence. Salesforce recently hired a Chief Ethical and Human Use Officer. Jennifer Doudna has begun a similar process for CRISPR at the Innovative Genomics Institute.

These are important developments, but they are little more than first steps. We need a more public dialogue about the technologies we are building to achieve some kind of consensus of what the risks are and what we as a society are willing to accept. If not, the consequences, financial and otherwise, may be catastrophic.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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