Category Archives: Crystal Ball

Five for Friday: AI sans Musk, Leadership + culture, and black swans

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Well, after a few busy weeks that wreaked a little havoc in my writing time, this week we’ll start with the pending downfall of mankind due to the rise of the machines.  Wait, no, that’s not what this is about … that was a few weeks ago.  But look at this article about how a couple of robots came to be the newest hires at a Wisconsin factory in search of reliable workers. It’s just the title of the article this time.  Also, there was that story about how Facebook pulled the plug on some AI that developed its own language that humans couldn’t understand, and while nothing wrong with being excited about all the opportunities that AI will bring for the future, at the same time we need to look at its consequences from all perspectives while Salesforce set out to create “AI for everyone”—to make machine learning affordable for companies who’ve been priced out of the market for experts. They’ve promised to “democratize” AI.  While we’re at it, all that big data has to be stored somewhere.  Look at how it’s impacting one small Oregon town.  Then there’s the rise of AI forcing Microsoft and Google to become chip makers and the business of artificial intelligence.  Oh, and Microsoft replaced Mobile with AI as one of its top priorities in their most recent annual report.

Think that AI isn’t really touching your life?  Check this out from Venture Beat.

I was a little surprised when I read this article from Business Insider about what three of the potential black swans are that will likely trigger a global recession in 2018 as I didn’t see any of the others I’ve seen a lot of news about of late, but I think they do a great job of laying it out.  What with the current potential instability from governmental posturing, it’s likely that the global economy will be impacted sooner rather than later, but these are some more to keep an eye on.  That said, it’s logical that we should see a major market correction based on historical data and trends.  What’s odd is how changes in the trading systems have likely artificially inflated the markets as well.

You may have heard the news about how some hackers stole a whole bunch of money from the Ethereum platform, but did you hear the story about how a bunch of other hackers stole it back?

Both Gates and Zuckerberg are sounding alarms about jobs.  Should we listen?

Being a week full of cheer and merry-making (I mean, it wasn’t a week full of bad news, just odd news, which seems to be our current era), let’s move to some leadership-focused articles.  Strategy+business has had a few good ones of late, from one about how improving company culture is not about free snacks, to another about how leaders can improve their thinking agility, to this article about what the body tells us about leadership. Along with that is an article I think every leader or hiring manager should read about why emotional intelligence is so important to consider when hiring (this is a key area I focus on with every candidate I interview) and somewhat unrelated but still “fitting” in the category is this article from HBR about the personality traits of good negotiators.

Any time I feel like I’ve had a circuitous route to the world of tech, I come across another article about how those of us with humanities backgrounds are in high demand in the tech world.  Why?  It seems to boil down to ideas explored in this article: making stuff vs. making stuff people want.

Right, so I know I’m avoiding the elephant in the room with the Google memo that came out, but I’ll leave you with this orthogonal piece instead: not only has Kalanick been removed from his job as CEO at Uber, now Benchmark Capital (an early investor) is accusing him of fraud in an attempt to have him removed from the board of the company as well.

I realize I was just bragging a bit about the liberal arts cohort to which I belong, but we can’t deny the importance of science in the world around us.  This TED talk from Naomi Oreskes gives a historical view of why we should trust scientists.  Check it out.

 

 

Preview of Gartner’s 10 Strategic Tech Trends for 2017 + more

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While the “official” tech trends for 2017 won’t be announced until the Gartner Symposium next week, I was able to track down a preview which I’ll share later – we’ll see how accurate they are.  But first, some of the news from this week:

Bill Gates has some thoughts on how he thinks the public and private sectors needs to interact with one another when it comes to innovation and as well where he thinks we need to be focusing our efforts to innovate.

ING, a major Dutch lender, has plans to replace 5,800 jobs with machines as part of what they calling a “digital transformation.” A few years back, it was posited that the banking industry was ripe for “computerization,” and now ING and others (including Commerzbank in Germany) are making good on those predictions.  Along with that is this article from HBR on three ways work can be automated and this other one on how technology will replace us all.  Oh, and it’s obviously not just happening in banking today – take a look at the latest eBay acquisition.

As I’ve noted before, Facebook decided to fire its human news editors and The Intersect has done some initial tracking and analysis to prove that since that change, Facebook has repeatedly trended fake news.  No real surprise there, given the level of maturity of AI and how far machine learning needs to come, but still a fair warning for those who rely on social media or entertainment mediums for their news.

Speaking of AI, Deepmind, a world leader in artificial intelligence research and its application for positive impact, has a post this week about some recent work they did around creating a differentiable neural computer.  Their hope was to create a learning machine that could organize information into connected facts and then use those facts to solve problems, which they were able to do.  Then there’s this article on how vector space mathematics helps machines spot sarcasm.  Next thing you know we’ll have Deep Thought at our command. But don’t worry, it hopefully won’t destroy the world.

I honestly don’t even know how to correlate this next article to anything fantastical in the world simply because it seems so incredulous – I tried to make a correlation to The Hitchhiker’s Guide to the Galaxy or Men In Black, but I’ll just leave this here: apparently the tech industry is becoming ever more consumed as to whether our existence is actually an algorithm.  Follow on to that the desire of two tech billionaires to destroy the universe.  While we’re talking about destroying the universe, take a moment to read this summary of The McFuture podcast’s interview with Jeremy Rifkin, as well as this piece on the future of cities.

Given all the news about cutting cords the past few weeks, Business Insider decided to outline how we can expect to see wireless technology evolve over the next ten years.

Wondering where the top talent in the tech industry will land next?  Fast Company has a good overview of past trends and what we can expect for 2017.

Apparently, at Gartner’s recent event in Cape Town, Stephen Prentice gave a preview of the expected trends for 2017.  As you recall, between 3D printing and machine learning, there was a robust list of predictions last year (which I revisited a few weeks ago).  While the preview of 2017’s trends features some of the same entries, there are a few new ones as well:

Conversational systems

Prentice says that conversational AI systems will form part of the so-called “Digital Mesh” – along with the next two entries on the list.

Prentice noted that there are expected to be at least 25 conversational AI systems by 2018, citing examples already such as Siri, Cortana and Amazon‘s Echo.

“These are generation one systems… They don’t always sort of seem to understand properly, what we say. But like all technology, it’s going to improve and it’s going to improve very rapidly,” Prentice explained. He adds that we could see these systems not only comprehending what we say, but what we mean.

Augmented and virtual reality

The past 12 months have seen virtual reality and augmented reality make headlines, such as Oculus Rift and the Gear VR for the former and Pokemon Go for the latter. Prentice expects this to continue its growth.

“The mobile phone, given its location-based capabilities, its cameras, its inertial sensors and so on, is becoming a very powerful tool for augmented reality,” Prentice elaborates. He adds that distracted smartphone users are even getting guidance in the form of “traffic lights” installed in Sydney pavements.

As for virtual reality, Prentice notes that we’re seeing more powerful VR headsets, being used for everything from immersive experiences, molecular modeling, and healthcare therapy.

Digital twin

“Every physical object in this environment is going to have a digital equivalent. As we do things to the physical object, the data from that is being collected… and that’s being replicated in a digital equivalent,” Prentice explains. However, Prentice says that over time, things might flow in the other direction (i.e. manipulation of digital objects having a real-world effect).

Prentice gives the example of having one wind turbine in the real-world, but using the digital world to test the effect of having many wind turbines. He also cited NASA testing new technologies as one example of the digital twin concept.

Artificial intelligence and machine learning

“If you asked me for a personal point of view… which one stands out as the most significant, the most disruptive, I would have to say… it’s machine learning and advanced artificial intelligence,” Prentice elaborates.

“Over the last couple of years, and largely due to the impact of machine learning technologies, we’ve seen artificial intelligence give us capabilities, achieve things that, even a couple of years ago, we would’ve said were impossible,” he adds. He cites the example of DARPA’s autonomous vehicle challenge from just a decade ago, taking place in a desert and seeing many cars failing. And now the likes of Google and other companies are testing self-driving cars on public roads.

“The imminent expectation is that self-driving vehicles will be commonplace – not the majority – by the middle of the next decade.”

Prentice says that AI systems tasked with doing a specific thing are reaching a point where they can often be better than humans. But there are still reasons to use humans instead.

“In some cases, they’re (the AI system) is expensive. In some cases, it’s just a lot easier to have a person doing it. In some cases, there are regulatory reasons,” the Gartner analyst says.

Intelligent applications

When you combine AI and machine learning with applications, you get intelligent applications, Prentice explains.

These applications come in a variety of forms, such as robots, drones, chat bots/Siri/Cortana, smart sensors and smart appliances.

One specific example cited by Prentice includes a machine that visually analyses burger buns to improve quality.

Another example was the use of IBM’s Watson as a virtual advisor at Memorial Sloan Kettering, helping doctors determine treatment for cancer.

Intelligent things

“One of the challenges, in fact, is when we try to forecast the number of intelligent things being connected to the network, the reality is the vast majority of them have not yet been invented,” the Gartner representative noted. “They’re in categories that we don’t even think of.”

Some examples of intelligent things include intelligent MRI scanners and stethoscopes. The former could adjust settings based on the patient’s dimensions and details, while the latter is able to detect minor variations in vitals.

Adaptive security

This was one of the trends predicted for 2016, but Prentice says that this will continue to occur next year. He adds that adaptive security will entail the use of AI to help identify threats.

“Let’s be quite clear: the cyber threat is growing all the time. The more devices out there, the more weak points there are,” Prentice says.

“So this is an arms race, and it’s an arms race that, I have to say, the good guys are never going to win. Because the bad guys have access to exactly the same technology as the good guys and they don’t feel compelled to comply with the rules and regulations…”

However, it’s not all doom and gloom, as Prentice points to the auto industry’s recent focus on security as an example of manufacturers prioritizing the issue.

Blockchain and distributed ledger

“Blockchain is one of these things that’s at the peak of hype,” Prentice notes, before adding that it was providing a “decentralized, secure ledger of transactions”.

“It’s about adding trust, in an automated sense, into what is an otherwise untrustworthy environment,” he says, before stressing that it wasn’t “irrevocable”.

What about businesses wanting to use Blockchain technology? Prentice says you should be investigating the technology now.

“But at the same time, anything you do today… you should be expecting to replace in 18 months’ time.”

So if the technology is going to be changing that rapidly, why not investigate it later?

“That is an option, but we don’t believe that it’s a smart option. This is going to be an important technology, gaining some understanding into what it can do and how you might apply it, is going to be important,” Prentice explains.

Mesh app and service architecture

Gartner sees a future of “mesh type things, cloud-based servers… a lot of bots… small chunks of code… linking together in a variety of different ways”.

Prentice says that this type of architecture will allow for a different level of flexibility and faster development pace.

Digital technology platforms

When talking about digital technology platforms, Prentice said there were several main areas to take into account. These were internal systems (such as accounting systems, traditional IT), customer-facing systems (CRM, social media, websites) and the internet of things. And all of these systems will feed you or your company with intelligence.

Prentice also suggested a future where smart AI bots will become the customer. “My bot is going to be ordering products and services from your bot. So a lot of your customer relationship management is going to be turned on its head,” he added.

Prentice cautioned businesses against building an entire ecosystem of digital technology platforms on their own, calling on firms to find a “one-stop” solution instead.

Last this week is a TED talk by Jim Hemerling that speaks of five ways to lead in an era of constant change.  He contrasts the difference between how we view self-transformation versus organizational change – one we get excited about, the other we dread.

This Week in Google, Disney as a Service, Toward a constructive Technology Criticism + more

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Google unveiled its full line of products for the fall this week, with everything from a new phone (Pixel) to an Alexa competitor.  It looks as though Google Home will give Amazon’s Alexa a run for its money, however, the more interesting piece is the release of Pixel.  What with Samsung rushing to production on the Note and subsequent exploding phones (there’s even a hack that lets you turn Molotov into Notes in Grand Theft Auto V) and Google’s forays into the space in the past, it makes sense that Google would want to provide what appears to be the best mobile phone released this year without any crud wear from the manufacturer. I doubt it’ll have any impact as phone makers want some of the ever-spreading Android ecosystem, but it’d be interesting if Samsung took the route of Lenovo with Microsoft when Lenovo announced this week that they’d not make a windows 10 Phone.  All that said, Stratechery has a good dive into what’s behind the release of Pixel.  That said, the way Google (or, actually, Alphabet) wants us to leverage their technology means a continued erosion of privacy.

So what happened when a global software company scoured its salary data to determine if there was gender bias its compensation model?  Well, SAP did just that, and no surprise, they found that of the 1% of all employees that were underpaid, 70% of them were women.  So they fixed it, increasing the salaries of all underpaid employees, to a total additional cost of about $1 million annually.

Ever wonder how countries like China or Russia are able to control the internet?  Quartz explores that question in detail for you, using the Arab Spring to demonstrate.

Bloomberg thinks that Jack Dorsey is losing control over at Twitter, and they make a good case.  After a year of trying to reimagine the product, little growth has been achieved.  On the flip side of that, says Vox, are Wall Street’s unrealistic expectations for Twitter.

HBR gives us a brief history of augmented reality this week, and for those of you who’ve ignored post after post about it because I’m boring, give them a read.

I wrote of Mark Zuckerberg’s recent trip to Nigeria, but Backchannel has the story behind it and what both he and Nigeria got out of the visit – Nigeria got much more than they could’ve dreamed.

There’s an amazing essay this week from Aeon about the United States Founding Fathers and how today we tend to treat them as though they were holy relics versus the revolutionaries they were.

Redef has an in-depth look at how Disney is closer than ever to achieving Walt Disney’s 60-year-old vision, turning itself into Disney as a Service.  There have been hiccups on the road, for sure, but Disney is closer than ever to being a company that sells entertainment ecosystems.

Most newspapers in the country seem to have been behind the times and scared of technology and its impact on the medium.  The New York Times, on the other hand, has embraced it and is thriving for it.

Being first to market with an idea typically costs more and also give you first-mover advantage.  The problem is that others get to see your successes and failures and capitalize on them.  Sometimes you have enough momentum and early adopters who are loyal to win the market, other times, especially if you are arrogant by nature, you can get your legs cut out from under you.  Uber has had some pretty staggering losses to date and still seems to be the dominant force.  It also has any number of companies, like Lyft and Juno nipping at its heels. Oh, and the Freakonomics podcast this week is about how Uber is an economist’s dream.   Three guesses as to why …

A few articles this week about startups and Silicon Valley; the first is one about how non-tech companies are getting tech-frenzied by San Francisco.  Another is about how Silicon Valley punishes innovators who don’t embrace the liberal agenda by a buddy of mine, another on the easy way versus the best way to build a startup, and the last captures why startup hubs outside of Silicon Valley are built to last.  Oh, and you know one thing Silicon Valley hasn’t been able to disrupt?  Craigslist.

John McAfee was in the news this week, although not for anything as flamboyant as you’d think – he was at a local Home Depot and saw that some hackers had exploited a security flaw on a fridge to get the touch screen to display pornographic material.  There are challenges with new technology like that often, and even more so with old tech and the doors left open for cyber attackers.

We’ve seen a lot of technology disruption in the past twenty years, this week Vox argues that we’ll see a whole lot less over the next twenty and why.

Another trip of articles on Artificial Intelligence: first from Wired on how to steal and AI, second from Forbes on how Baidu is benchmarking hardware for deep learning, and last from Venture Beat from a panel on how AI can help out the C-suite.

If we’re going to discuss AI, then we should discuss Data as well, and TechCrunch does so this week in an insightful way.

So last week Elon Musk laid out his plan to colonize Mars, and perhaps you think you’d like to go.  Well, The Verge went to the trouble of outlining both the level of training that might be needed and whether or not, truly, “anyone can go” as long as they are will to face a “really high” risk of fatality.

Theranos was in the news again this week, laying off 40% of its staff.  Read the letter from Elizabeth Holmes explaining why and take from it what you will.  To me, we saw the beginning of the end weeks ago, so this shouldn’t come as a surprise to anyone.

Even as we see more and more of a move towards using Artificial Intelligence and Machine Learning to help our world evolve, The Guardian this last week made the point that we’ll need human input in this world driven by algorithms, and outlines from their point of view as to why.

If you hadn’t heard, most information security folks are telling people to delete their Yahoo mail accounts this week after it came to light that Yahoo has been searching user emails with impunity.

Finally this week is a 30,000 plus word scholarly article assessing the current state of technology coverage and criticism in the media and elsewhere, and some ideas of how to move that discourse forward.  I share it not because I expect you to read it word for word, but take a moment to glance through the executive summary and then the ideas the author has towards how to salvage criticism of technology and the strategies for doing so constructively.  My hope is this will help you cut the wheat from the chaff when reading the many articles that come across our desktops every day when it comes to technology.

Oddly, both my nine and five-year-old this week came home talking to me about how they got to code this week.  I’m not surprised by the nine-year-old, as she went to a computer science camp this summer (and had a blast making her own games), but the five-year-old had me pleasantly surprised.  I later learned that what her school called “coding” wasn’t exactly, but it brought to mind again that we need to be encouraging our children, including young ones, to learn to code.  This TED talk with MIT professor Mitch Resnick talks about the benefits of doing so.

“Active” listening, the”Hidden Curriculum” of Work, the Lost Infrastructure of Social Media + more

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We’ve all heard that as leaders and managers, we have to focus on active listening when we interact with our people.  In the past, that’s been defined as not talking as others speak while making empathetic noises that convey understanding and then synthesizing what was said and repeating it back.  I’ve done this many times, and have always felt like that made me good at listening.  Lately, though, I’ve been having a lot of conversations with people about their personal mission statements, about what drives them and helping them connect that back to the core values and strategy of their company.  I find myself coming out of these conversations invigorated, even inspired by the dialogue and while I did follow that pattern I laid out above, I also did a few things differently, naturally, that are emphasized in this article from HBR on what great listeners actually do.  I found myself asking questions to promote discovery (these were, after all, self-discovery conversations), found myself naturally building the other individual’s confidence and self-esteem because the entire focus was to focus on things they loved to do and how it tied back to their job, I did find myself making suggestions and synthesizing our conversation to allow for a different understanding of the problem we were solving, and I made plenty of suggestions.  Then I had another conversation where I just engaged in classis active listening this week and it seemed almost fake to me, too canned.  Take a moment and read the article and then think about some of the most exciting conversations you’ve had of late.  I think you’ll find that your best conversations have been the ones when you’ve challenged the speaker as you’ve listened.

Would a week have passed without Uber being in the news?  This week, though, it’s for their autonomous car fleet that just debuted in Pittsburg.  Now, they are “supervised” by humans, and they are just in test phase, but they are out there.  Along with that is a great thought piece about we are shifting from a driver to a car culture and the impact of that on Uber and others.

Speaking of autonomous cars, Ford this week stated that they would have such cars ready to go to market in 2021 for automated ride-sharing companies.  They’ll be shipped without steering wheels or pedals (an upgrade to the Johnny Cab in Total Recall) and in this interview, Forbes digs in to how the head of autonomous vehicles at Ford plans to get that done.

An odd thing has been happening on Wall Street – as I’ve noted before, there’s been a drive to hire data scientists, but at Goldman Sachs, their technology division is made up of over 11,000 people, or as they brag, more engineers than Facebook.  It makes since, then, that Goldman would not just sponsor but also host All Star Code this summer on premise.  While the leaders at Goldman haven’t done a whole lot to improve the company’s reputation in the past decade, the people of Goldman are passionate about their communities (part of GS’s core values) and that’s evident in programs they support like ASC.

We’ve all heard stories of the dark net and Silk Road and the various nefarious transactions going on there, but have you heard the story of the dirty cops who tried to take advantage of it themselves?  Ars technica unpacks not just what they stole but also how they got caught.

Inc. this week has a great article on the history and evolution of Craigslist and how Craig Newmark, it’s founder, realized he sucked as a manager.

Strategy+business this week digs into the hidden curriculum of work – all those things that we have to learn/do in order to navigate our places of work that are outside of the job we were hired for, beyond the job description our people applied to.  As leaders, it’s incumbent on us to help our people understand that aspect, from the social and political environment to understanding (sometimes blindly) what is expected for one to advance in the organization.

Gartner has an interesting article this week where they state that 70% of enterprise file synchronizing and sharing companies will be gone by 2018.  Part of that makes sense as smaller companies who provide this service are absorbed by bigger firms.  Part of it will be due to innovation in the space.

For those of you who’ve felt that the past few summer blockbusters you’ve seen was written either a cat on a computer keyboard or AI, you’ll be interested to know the cats are still writing their magnum opus, AI has written its first screenplay.

Scientific American asked some of our leading thinkers about the future of humanity.  One of my favorite Q & As was Q: Will we ever figure out what dark matter is?  A:  Whether we can determine what dark matter is depends on what it turns out to be.

Alex Danco has the first two parts of how we make paradigm shifts in our world posted through Medium – it’s an interesting journey so far.  Check out Part 1 here and Part 2 here.

Last this week is another piece  from Medium about the lost infrastructure of social media – it’s a good look at then versus now and how what happened back then could be brought back to bear in the here and now.

TED has a blog post that can describe much better than I the importance of the talk this week – read it here and then watch for yourself.

A Dive into Artificial Intelligence + more

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Today’s is a bit of a different read as after I listened to This Week In Startups and a podcast on Artificial Intelligence I got curious as to what’s developed in the past couple of years and what the future looks like.  More on that later, though, first your weekly digest of what’s interesting (at least to me):

First, if you’ve not heard of it, the President of Brazil was impeached last week by her congress.  While it may seem trivial or inconsequential to some (we think back to Bill Clinton’s impeachment in the 90s), for the world it has serious implication, some of which are explored by Marketwatch.

Speaking of leadership and issues around it, HBR has a good article this week that asks the question “why do so many incompetent men become leaders?”  It’s interesting to note that the mythical image of a leader aligns with narcissism, psychopathy, histrionics, and Machiavellianism and how many male leaders that have embodied those traits.  Strategy+business also had two interesting articles this week, one on how to design a team to deliver powerful capabilities and another on the obsolescence of traditional organizational structures.

Last week I had a few articles about how Facebook has supposedly been squelching conservative news from people’s feeds. This week, the New York Times has an interesting take on the topic, including that there was a whole bunch of hub bub over nothing, for even if the editor’s at Facebook were biased against conservative news sources, the “Trending Topics” section was so small that it was inconsequential (it’s practically invisible in the mobile UI).  The issue more lies in the algorithms that determine what users see in their feeds.

Also on Facebook, here’s a look the Book’s attempt to bring millions of Indians to the internet and how it failed.  Oh, and I’d be remiss if I didn’t include a good summary of everything Google discussed at its i/o conference.

Since last year’s market peak, Apple has lost on quarter of a billion dollars of market capitalization, and even with the recent influx from Warren Buffet’s Berkshire Hathaway, the stock is still hovering at $94 per share, versus the market high of $132.  The Conversation this week posits that Apple has gone from being a disruptor to being the disrupted, with Apple losing momentum and direction on what the next “one more thing” may be.

If there’s one trend we’ve been seeing, it’s that personalized medicine is the next big thing when it comes to mobile health.  There’s an estimated $42 billion market waiting to be opened up and a mad dash to do so.  Techcrunch this week has a good read on how that blue ocean is going to be regulated and monitored by a partnership between the FDA and the FTC.   That said, there is and has been a flurry of activity when it comes to personal health apps.  In talking to friends of mine in the startup space, they say that all those regulations from the government get in the way.  It appears like the partnership between the FDA and the FTC is intended to make that ocean more accessible.  Speaking of startups, though, here’s an interesting article from someone I know from my days in Boulder that poses the question “do startups have a drinking problem?”

In a bit of a turn of events, it appears that emerging economies are turning out to be early tech adopters.  The World Economic Forum terms this as the Fourth Industrial Revolution and MIT Technology Review has a good overview of the how and the why.  The technology most driving this change?  The mobile phone, which shouldn’t be a shock to anyone.  Also from MIT is an article on how wireless, super-fast internet access is coming to our homes.

For those of you who have paid attention to Zappos and the organizational structure there, you’ll know a little something about Holocracy.  For those that don’t, Holocracy is a system of organizational governance in which authority and decision-making are distributed throughout a holarchy of self-organizing teams rather than being vested in a management hierarchy.  Well, it seems that system may not be living up to its hype.  In fact, it may be time to put a nail in that coffin.

As a bit of a segue into the world of Artificial Intelligence, there’s an interesting article this week about how companies are trying to be more human.  In a similar vein to our introduction to Viv last week, Google, Amazon, Microsoft, and even Facebook are augmenting their personal assistant efforts. While there may be some question around privacy, AI, and Personal assistants, bots are pushing ahead in this area as well.  Brands attempt to act like people as well, engaging with and talking to consumers on social media.  We see that extended in the TV show Community where, in order to open a franchise on campus, Subway enrolls as a student in the school. The next step, according to the author, is for Google to install an always-on device that listens and analyzes everything you say, allowing Google to become even more attached to your life.  And if that turns your stomach, you’ve not seen anything yet.

Artificial Intelligence.  I’ve shared a few articles about this space over the months but was listening to a podcast earlier this week about Vicarious and I thought it would be good to explore a bit the different types of AI together and end with a question:  what happens when we finally achieve artificial general intelligence and have massive computational power behind it.

So what is AI?  Many of us think of the Hollywood-ized version of AI when we think of it: everything from Teminator to Star Wars and a whole lot in between.  The reality is that AI is already everywhere, although not in those fanciful ways.  It ranges from your phone’s calculator to self-driving cars to something in the future that might change the world dramatically. AI refers to all of these things, which is confusing.  We use it all the time in our everyday lives but we likely don’t even realize it.  John McCarthy coined the term AI in 1956, and as he did he complained that once it works, it’s how things have always worked and we don’t acknowledge it as AI anymore.  Because of this, AI often sounds like a mythical future prediction more than a reality. At the same time, it makes it sound like a pop concept from the past that never came to fruition.

To clear it up a bit, I’m going to talk about Artificial Narrow Intelligence (what we have today) and Artificial General Intelligence (what companies like Vicarious are trying to achieve), and Artificial Super Intelligence.  Along the lines of clearing things up, it is good to note that AI doesn’t mean robots.  Robots are the shell that holds the AI, the ocntainer – think the latest Avengers movie with Ultron occupying Ironman armor. AI is the brain, and the robot is its body—if it even has a body. For example, the software and data behind Siri is AI, the woman’s voice we hear is a personification of that AI, and there’s no robot involved at all.

Secondly, you’ve probably heard the term “singularity” or “technological singularity.” This term has been used in math to describe an asymptote-like situation where normal rules no longer apply. It’s been used in physics to describe a phenomenon like an infinitely small, dense black hole or the point we were all squished into right before the Big Bang. Again, situations where the usual rules don’t apply. In 1993, Vernor Vinge wrote a famous essay in which he applied the term to the moment in the future when our technology’s intelligence exceeds our own—a moment for him when life as we know it will be forever changed and normal rules will no longer apply.

So back to those catergories of AI: Narrow, General, and Super:

Artificial Narrow Intelligence (ANI): Sometimes referred to as Weak AI, Artificial Narrow Intelligence is AI that specializes in one area. There’s AI that can beat the world chess champion in chess, but that’s the only thing it does. Ask it to figure out a better way to store data on a hard drive, and it’ll look at you blankly.

Artificial General Intelligence (AGI): Sometimes referred to as Strong AI, or Human-Level AI, Artificial General Intelligence refers to a computer that is as smart as a human across the board—a machine that can perform any intellectual task that a human being can. Creating AGI is a much harder task than creating ANI, and we’re yet to do it. Professor Linda Gottfredson describes intelligence as “a very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience.” AGI would be able to do all of those things as easily as you can.

Artificial Superintelligence (ASI): Oxford philosopher and leading AI thinker Nick Bostrom defines superintelligence as “an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills.” Artificial Superintelligence ranges from a computer that’s just a little smarter than a human to one that’s trillions of times smarter—across the board. ASI is the reason the topic of AI is such a spicy meatball and why the words “immortality” and “extinction” will both appear in these posts multiple times.  It also may be able provide the answer to the ultimate question of life, the universe, and everything.

Currently we are in a world of Artificial Narrow Intelligence.  Artificial Narrow Intelligence is machine intelligence that equals or exceeds human intelligence or efficiency at a specific thing. A few examples:

  • Cars are full of ANI systems, from the computer that figures out when the anti-lock brakes should kick in to the computer that tunes the parameters of the fuel injection systems. Google’s self-driving car, which is being tested now, will contain robust ANI systems that allow it to perceive and react to the world around it.
  • Your phone is a little ANI factory. When you navigate using your map app, receive tailored music recommendations from Pandora, check tomorrow’s weather, talk to Siri, or dozens of other everyday activities, you’re using ANI.
  • Your email spam filter is a classic type of ANI—it starts off loaded with intelligence about how to figure out what’s spam and what’s not, and then it learns and tailors its intelligence to you as it gets experience with your particular preferences. The Nest Thermostat does the same thing as it starts to figure out your typical routine and act accordingly.
  • You know the whole creepy thing that goes on when you search for a product on Amazon and then you see that as a “recommended for you” product on a different site, or when Facebook somehow knows who it makes sense for you to add as a friend? That’s a network of ANI systems, working together to inform each other about who you are and what you like and then using that information to decide what to show you. Same goes for Amazon’s “People who bought this also bought…” thing—that’s an ANI system whose job it is to gather info from the behavior of millions of customers and synthesize that info to cleverly upsell you so you’ll buy more things.
  • Google Translate is another classic ANI system—impressively good at one narrow task. Voice recognition is another, and there are a bunch of apps that use those two ANIs as a tag team, allowing you to speak a sentence in one language and have the phone spit out the same sentence in another.
  • When your plane lands, it’s not a human that decides which gate it should go to. Just like it’s not a human that determined the price of your ticket.
  • The world’s best Checkers, Chess, Scrabble, Backgammon, and Othello players are now all ANI systems.
  • Google search is one large ANI brain with incredibly sophisticated methods for ranking pages and figuring out what to show you in particular. Same goes for Facebook’s Newsfeed.

ANI systems as they are now aren’t especially scary. At worst, a glitchy or badly-programmed ANI can cause an isolated catastrophe like knocking out a power grid, causing a harmful nuclear power plant malfunction, or triggering a financial markets disaster (like the 2010 Flash Crash when an ANI program reacted the wrong way to an unexpected situation and caused the stock market to briefly plummet, taking $1 trillion of market value with it, only part of which was recovered when the mistake was corrected).

So what will it take to get us from ANI to AGI?  Well, that’s a tough one.  Nothing will make you appreciate human intelligence like learning about how unbelievably challenging it is to try to create a computer as smart as we are. Building skyscrapers, putting humans in space, figuring out the details of how the Big Bang went down—all far easier than understanding our own brain or how to make something as cool as it. As of now, the human brain is the most complex object in the known universe.

What’s interesting is that the hard parts of trying to build AGI (a computer as smart as humans in general, not just at one narrow specialty) are not intuitively what you’d think they are. Build a computer that can multiply two ten-digit numbers in a split second—incredibly easy. Build one that can look at a dog and answer whether it’s a dog or a cat—spectacularly difficult. Make AI that can beat any human in chess? Done. Make one that can read a paragraph from a six-year-old’s picture book and not just recognize the words but understand the meaning of them? Google is currently spending billions of dollars trying to do it. Hard things—like calculus, financial market strategy, and language translation—are mind-numbingly easy for a computer, while easy things—like vision, motion, movement, and perception—are insanely hard for it.

What you quickly realize when you think about this is that those things that seem easy to us are actually unbelievably complicated, and they only seem easy because those skills have been optimized in us (and most animals) by hundreds of millions of years of animal evolution. When you reach your hand up toward an object, the muscles, tendons, and bones in your shoulder, elbow, and wrist instantly perform a long series of physics operations, in conjunction with your eyes, to allow you to move your hand in a straight line through three dimensions. It seems effortless to you because you have perfected software in your brain for doing it. Same idea goes for why it’s not that malware is dumb for not being able to figure out the slanty word recognition test when you sign up for a new account on a site—it’s that your brain is super impressive for being able to.

One thing that definitely needs to happen for AGI to be a possibility is an increase in the power of computer hardware. If an AI system is going to be as intelligent as the brain, it’ll need to equal the brain’s raw computing capacity. The second key to creating AGI is to make it smart.  There pretty much are three ways to do this: plagiarize the human brain, leverage evolution through simulation, or to make the whole thing a computer’s problem, not ours.  For the middle one, we’d leverage a method called “genetic algorithms” which would work something like this: there would be a performance-and-evaluation process that would happen again and again (the same way biological creatures “perform” by living life and are “evaluated” by whether they manage to reproduce or not). A group of computers would try to do tasks, and the most successful ones would be bred with each other by having half of each of their programming merged together into a new computer. The less successful ones would be eliminated. Over many, many iterations, this natural selection process would produce better and better computers. The challenge would be creating an automated evaluation and breeding cycle so this evolution process could run on its own.

The downside of copying evolution is that evolution likes to take a billion years to do things and we want to do this in a few decades.

But we have a lot of advantages over evolution. First, evolution has no foresight and works randomly—it produces more unhelpful mutations than helpful ones, but we would control the process so it would only be driven by beneficial glitches and targeted tweaks. Secondly, evolution doesn’t aim for anything, including intelligence—sometimes an environment might even select against higher intelligence (since it uses a lot of energy). We, on the other hand, could specifically direct this evolutionary process toward increasing intelligence. Third, to select for intelligence, evolution has to innovate in a bunch of other ways to facilitate intelligence—like revamping the ways cells produce energy—when we can remove those extra burdens and use things like electricity. It’s no doubt we’d be much, much faster than evolution—but it’s still not clear whether we’ll be able to improve upon evolution enough to make this a viable strategy.

The thing is, all of this could happen now.  Rapid advancements in hardware and innovative experimentation with software are happening simultaneously, and AGI could creep up on us quickly and unexpectedly.

I’ll leave the question of ASI out there simply because we don’t know enough yet to even really conceptualize it – we need to get to AGI before we can truly understand what is possible with ASI.  Perhaps Roddenberry will have been right all along with his vision from the 60’s.  If you want to get up to speed on how to converse in AI, check out this resource from of all places the BBC, or check out this article from The Verge for more. Also, check out that podcast I mentioned to get some answers to what might be instore for us from AGI.

To end this week there are two TED talks on the AI: one from Nick Bostrom on what happens when our computers get smarter than we are and another from Jeremy Howard on the wonderful and terrifying implications of computers that can learn.

Why A Virtual Reality Web May Never Happen, As Hospitals Go Digital Human Stories Get Left Behind, In Praise of the Incomplete Leader, The Panama Papers + more

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I wrote a bit last week about Virtual Reality and how it is starting to impact our world.  Fastco Design has a quick read on why we may never see our existing web experience translate to that medium.  While demos exist of “what could be” today, no designers or developers are lining up to actually help create the experience.  The user experience of the web has been defined and solved, and while that UX may evolve over time, it has the same principles at its core.  As it stands today, the VR web is just transferring a very two-dimensional experience to a three-dimensional (even possibly four-dimensional) space.  It’s not immersive; it’s not what we might expect from a world with immersive 2-D experiences like Second Life and The Sims.  It seems like looking at those 2-D immersive experiences is getting in the way of a new UX for virtual reality.  That said, we know that’s what people expect, so let’s give it to them and then direct the crazy ones, the misfits, and the rebels who can re-imagine our world as a four-dimensional virtual one to focus on so they can break us out of the box that is our existing browsing experience.

Also from Fastco Designs is an article about how Kik thinks Chatbots will kill webpages.  Continuing the story of Tay, the “teen” AI/bot that Microsoft unveiled a few weeks ago just to pull down and how bots are seen as critical both in China and by the larger tech companies in the US, Kik, a messaging app, has a new platform which allows anyone to create a chatbot.  In Kik’s paradigm, the bots are “summoned” to provide contextual information and are created by the users themselves (or will people pay $.99 to buy a bot that someone else has created?).  The belief is that bots are going to solve the problems with the App ecosystem, but unfortunately it doesn’t’ look like Kik is set to use bots for what is most beneficial: machine learning.  Chatbots, apparently, are going to be everywhere.

One of the tougher nuts to crack of the past few years has been creating an interface for medical records that keeps up with the changers other industries are seeing, again from a UX standpoint.  I’ve known quite a few entrepreneurs who have tried to crack the “gamification” nut that seems to serve so many other thought-based industries well, however they’ve failed.   I think that is in part due to the high level of government regulations and requirements, but this article from STAT points to another issue: the interface used for tracking patient records gets in the way (in this case EPIC), and in fact reduces the most complex portion of a medical practitioner’s diagnosis, the emotional side, to information that is simply lost in translation.

Business Insider has a great piece this week on how we should forget about unicorns, and that investors are looking for “cockroach” startups now.  The premise is that unicorns are mythical creatures that are appearing to be more over-valued than not and have a huge amount of risk due to market fluctuations.  Cockroaches, on the other hand, are resilient. After all, the legend has it that only the cockroaches would survive a nuclear war.

We all have high expectations of our leaders, and as well others have high expectations of us as leaders.  The belief is that we’re flawless, that we can do no wrong, and that we have it all figured out.   The reality is, no one does, and we’re all pushing ourselves to grow every day.  Being a lifelong learner goes hand in hand with being a good leader, and we have to realize that with a lifetime of learning comes a lifetime of growth.  HBR outlines four components in their framework of distributed leadership: sensemaking, relating, visioning, and inventing.  The article from HBR also provides a framework for evaluating where you are in relation to those skills and can be used to diagnose your team or organization as well.

It’s hard to think of the Harvard Business Review without thinking of Peter Drucker, the management guru of the latter 20th century.  Success had a piece back in 2010 that captured his career and how he created what is modern management theory that is as relevant today.  Looking back for that article was inspired by a brief collection of ten Drucker quotes I stumbled upon from Entrepreneur.   While you’re digesting that, take a moment to read what Forbes thinks are the lessons we can learn from Disney’s staggering CEO succession failure.

Along the lines of privacy, WhatsApp just turned on encryption for a billion people this week without even blinking an eye.  All the news of late has been about the face-off between Apple and the FBI, and while that has been getting a lot of news cycles, other tech firms have been quietly addressing security issues on their platforms, I guess while we’re all distracted.

The Panama Papers.  I’m sure every one of you has heard something in the news the last week about these.  There are numerous articles out there, but what fascinates me is how close to 400 journalists kept quiet about it for a full year before the story broke.  Take your pick on who you want to read: 6 things you need to know about the bombshell Panama Papers leak from Salon, The Panama Papers and SF’s housing crisis from 48hills, McAfee’s opinion that “a time bomb is hidden beneath the Panama Papers” from Business Insider, A Primer on the ‘Panama Papers’ Offshore Revelations from Bloomberg, or What you need to know about the #PanamaPapers investigation from PBS.

Joi Ito, head of the MIT Media Lab, has an excellent TED talk that speaks to how, in order to innovate, we have to be focused on building quickly and improving constantly.  This doesn’t apply just to software, but to hardware, manufacturing, bioengineering, and more.

Robots, Robots Everywhere, Global Stockmarket Meltdown, Having your Life Hacked + More

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Last weekend I finally got around to seeing the latest installment of the Terminator series and while it was a so-so film for the franchise, it seemed fitting timing given the number articles of late of how robots are taking over our lives of late.  While we’re not approaching the rise of the machines or anything akin to Asimov’s vision from I, Robot, there were two interesting reads this week, one about the robots coming to Wall Street and another about Ryan Calo, one of the minds behind robotics law in the United States.  To follow on to that is another article from the Times about a new breed of Trader out there: Coders with Ph.Ds.

Would you ever consider asking hackers to take apart your life as an experiment?  Kevin Roose did exactly that and it’s a scary but enlightening read.  Most of us don’t really pay attention to how fluid we are with our personal information with location based services and social media.  We need to be, as evidenced by just this bit from the story: they “began by compiling a dossier on me, using publicly available information like my email address, my employer, and my social media accounts. Most of this was information I’d made available on purpose, but some of it wasn’t. (They found my home address, for example, by enlarging and zooming in on a photo I’d posted to Twitter of my dog, which had the address listed in tiny type on the dog’s tag.)”  They pulled Roose’s mailing address from a social media photo of his dog.  Take a moment to think about all the different services out there that simply ask you for your name, date of birth, and address as their identity confirmation.  Then go re-read Roose’s article again.

strategy+business seems to be a weekly collection that I send out, and with good reason.  This week they had articles about Ten Principles of Organizational Culture, Three Secrets of Organizational Effectiveness, and how dysfunctional momentum impacts a company’s values to name a few, all worth a look.

The Next Web published a dive into what they view are the seven pillars of awesome game design. There are seven aspects of game design that need to be considered when you want to design and develop a successful game. They’ve highlighted some great video games that serve as examples of world, systems, content, game writing, level, user interface and audio design (said pillars).  Even if you aren’t into gaming, it’s interesting to look at those components and understand them from a conceptual standpoint and how they are used to pull players in.

Not to be chicken little, but I think it important that we keep abreast of what is happening in the global markets and some of the bear opinions out there.  One from MarketWatch digs into how the global stock market is wildly overvalued.  But it doesn’t stop there – luxury items as investments have had grossly excessive enthusiasm and other stating how they expect gold to rise to $2000 an ounce as we continue to see commodities and markets correct and then decline into recession territory.  Foreign Affairs dived into Eurasia’s coming anarchy and Citi also has some salient points as to why we might be moving into recession territory.  The good news is that this time around we’ve got eyes wide open going into this crunch so perhaps it can be averted.

Some other interesting articles from the week: Why the Future of Work Is at Home, Facebook Internet Drones Find Where the People Are, What’s Next in Computing?, Who’s reading my iMessages?, and Apple vs. FBI: Here’s everything you need to know (FAQ).

Decline of Oil, Oscar, Gut vs. Data + more

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This week the New York Times had a great article on the decline of oil prices and the ongoing paradox is the lack of increase in consumer spending that was expected with the reduction in prices at the pump.  There are bears out there that state that anything lower than $30 a barrel will be cataclysmic for the global economy, and now that we’re there … it looks like we’re facing a long-overdue correction.  Sure, there are a lot of economies that are teetering on the edge (and some that have been for years), however the drop in oil prices seems to be more making investors skittish versus having a meltdown as we’re hearing in some corners.  The global economy is still growing at the much slower rate that we’ve come to expect, and that may be the new normal.

As we approach what economists consider full-employment in the U.S., what’s not being talked about is the level of underemployment and those people who have chosen to leave the workforce outright and aren’t being counted anymore.  What’s truly interesting to me is not only the lack of savings accrued during the recovery, but also the number of people who are living paycheck to paycheck and how that is driving spending in our country.  I’m not an economist myself and there are other tells aside from the price of bent crude that signal a cooling economy – with sanctions being lifted on Iran we’re going to see a massive glut of oil on the markets and while that may impact some portions of the US from a production and investment standpoint, even that will be offset by OPEC and others.  What I do know is that we have people making “the sky is falling” statements and those statements being glamorized by others.  As Twain said, there are lies, damn lies, and statistics.  I think that could be updated to be “there are lies, damn lies, and then there’s the news cycle.”

Contrary to what you might expect, Netflix CEO Reed Hastings this week reinforced that we aren’t just going to rely on the data in the future, but we use the data to inform the call our gut makes for us.  We’ve seen and heard that elsewhere, and I think this goes along with the thought that you can, indeed, have too much data.  Paralysis can result from data, and we must never forget to listen to our guts.  Hastings goes on to talk about how to find your gut, and the full interview at DLD can be found here.

While we all rely more and more on social media to keep connected in the world, it lies at the bottom of the public trust rankings at 2%.  David Chaum believes his PrivaTegrity will be able to secure multiple platforms and provide the layer of security needed to elevate infrastructure to the next level of integrity and how simple it is to accomplish.  Along with this article is a follow up to last week’s article on Blockchain, exploring what it is and isn’t a bit deeper and the risks that go along with it.

A good friend and colleague of mine shared a McKinsey article on changing Change Management that highlights how companies are using key performance indicators to reinforce or indicate the need for change.  It seems like a an easy connection to make, but many times people don’t realize how critical the digital tools we are developing for business insight aren’t just tools for managing our business, but perhaps the most powerful means for changing it.

Would you believe it if I told you that phone numbers will be a thing of the past by the end of 2016?  I have a hard time swallowing that one myself, however, in this blog post, David Marcus of Facebook posits exactly that.  Just like the flip phone is disappearing, old communication styles could be disappearing too. Now we can do so much more with our phones. We went from just making phone calls and sending basic text-only messages to having computers in our pockets.  With 800 million users, Facebook wants its Messenger app to be the go-to chat platform.  Time will tell whether this will come to pass, however it’s hard to see developing countries that rely on mobile platforms for so many different purposes (especially exchanging money) that this will come to pass this year much less in the next five unless global infrastructure changes radically in the near term.  Facebook may get it’s wish in 2016 being the year that makes Apps irrelevant however.  Interesting things are afoot at Menlo Park.

Last is an article about Oscar, a health insurance start up that is looking to completely disrupt the industry.  How?  By allowing its users to easily buy health-insurance coverage from the marketplaces created under the Affordable Care Act. The company uses technology and design to make its statements and services easy for anyone to understand.  They must be on to something with a $3 billion valuation.  Curious?  Learn more here.

Part of the point of these missives is to encourage growth, and this week Inc. has a great collection of sites that will help you push yourself and explore new topics, top of the list being TED (for Technology, Entertainment, and Design).  Along those lines is an article from Business Insider this week about the secret to not getting frustrated.

100 Podcasts That Will Make You …, Exploring Future Reality, Radical Candor + more

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This week is more of a digest approach versus a specific theme as there’s been a variety of topic in my queue to catch up on and share out.  First off, to follow up on my recommendation that you listen to some thought leader with consistency as a part of your personal board of directors, here’s a handy list of 100 vetted podcasts from Inc.  Start by finding one or two that strike your interest and build from there once you consistently listen, or explore the feeds of several and focus on specific topics that may be covered from varying viewpoints.  On a different track but in line with last weeks’ topic of mentoring, Fortune has a great article this week on how some entrepreneurs in the Bay area are using algorithms to “empower women to break the glass ceiling, together.”  They’ve created a service that pairs mentors with mentees based on online matchmaking.  What’s curious to me is to see how it correlates to the concept of having more of a board of directors versus a senior/junior relationship from a mentoring standpoint.  It does, again, broach the topic of how much algorithms know about us and how much we want them to know.

Next is assessing your curiosity profile from HBR.  It’s pretty obvious which questions lean towards whether you are curious, but still an interesting few minutes spent finding how you fit on the spectrum from unconventional to traditional thinking.  It ties into another article from HBR on learning agility.  For those wondering, I’m an unconventional thinker who is intellectually hungry and seek new relationships and experiences.  Where do you fall?  If you are on the curious side, I’d bet you’ll like this next collection of articles from the NYC Media Lab focused on exploring future reality.

An interesting question I find out there when I’m reading or exploring the interwebs is around whether there really is any new thought when it comes to management thinking, and whether it even matters.  This article digs into that question, talking about how context changes the question and how it is answered. Another fact we face is that often times we find ourselves meeting our colleagues for the first times in front of customers given how decentralized our workforce has become (no matter what Marissa Meyer’s desire may be).  Sometimes, however, we can work in the same campus and never meet our “competitors” from our own firms.  Strategy+Business digs into how we can address three major issues when trying to act as one company: streamlining work while maintaining brand identity and nurturing customer relationships, avoiding the bureaucracy that frequently goes hand in hand with complexity, and getting people to risk depending on one another.

We often talk about work-life balance and how much of a struggle that can be, and how grateful some of us are to work for firms that are vigorously passionate about that.  Not that it’s meant to make us work MORE, however there was an incredible dive into Japan’s 105-hour work week that I felt compelled to share because of one thought: that good enough isn’t nearly good enough when it comes to getting the job done.  It’s interesting to look at a culture where there is no “good enough” approach, how it impacts the family dynamic, how that country is stagnating possibly in part because of that ethos, and contemplating that perhaps, just maybe, in our own work we need to move the bar a little higher for what is “good enough.”  That’s not to say we should work more, as more work doesn’t mean better results.  It means we should always strive to improve and do better than we have before.

But what about the usual mix I share around leadership and management skills?  Well, glad you asked: this article about radical candor proposes that precisely that is the key to being a good boss while HBR explores the two sides of employee engagement.  Fun fact: each year, companies are spending nearly three-quarters of a billion dollars in an effort to improve employee engagement.  Follow on to that the “no duh” realization/article from Quartz that toxic coworkers are more expensive than superstar hires and we might be on to something here.  Along with that is how we can get millennials to want to work with us and the reality is, these are all mantras with which we are very familiar.

Last, with the debut of the new Star Wars movie this week, I wanted to leave you with an article from Vulture about whether Han Solo was legally justified in shooting Greedo first.  It’s a bit of a read, but an attorney digs through all sorts of Imperial legal code to get to an answer.  Yes, Imperial legal code has been written.

The Imagination Gap and 2015 Industry Perspectives

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This week will be brief (as I’ve been at a client’s site), however I found these two articles to be good ones to keep bookmarked for the flight home:

The Imagination Gap: Business leaders in at least 16 sectors are still not fully prepared for the digital transformation of their industries

2015 Industry Perspectives: Strategy&’s annual collection of industry perspectives addresses major trends, challenges, and opportunities for companies to consider in 2015 and beyond. Their experts developed their views from industry discussions, observations of shifting market dynamics, and skilled analysis of data in the sectors that Strategy& serves.