Category Archives: Online User Experience

Fooling Some of the Systems Some of the Time

If there’s a system, there’s a way to game it. Especially when those systems are tied to someone making money.

Buying a Best Seller

Take publishing, for instance. New books that say they are on the New York Times Best-Seller List sell more copies than ones that don’t make the list. A 2004 study by University of Wisconsin economics professor Alan Sorenson found the bump is about 57%. That’s; certainly motivation for a publisher to game the system.

There’s also another motivating factor. According to a Times op-ed, Michael Korda, former editor in chief of Simon and Schuster, said that an author’s contract can include a bonus of up to $100,000 for hitting No. 1 on the list.

This amplifying effect is not a one-shot deal. Make the list for just one week, in any slot under any category, and you can forever call yourself a “NY Times bestselling author,” reaping the additional sales that that honor brings with it. Given the potential rewards, you can guarantee that someone is going to be gaming the system.

And how do you do that? Typically, by doing a bulk purchase through an outlet that feeds its sales numbers to TheTimes. That’s what Donald Trump Jr. and his publisher did for   his book “Triggered,” which hit No. 1 on its release in November of 2019, according to various reports.  Just before the release, the Republican National Committee reportedly placed a $94,800 order with a bookseller, which would equate to about 4,000 books, enough to ensure that “Triggered” would end up on the Times list. (Note: The Times does flag these suspicious entries with a dagger symbol when it believes that someone may be potentially gaming the system by buying in bulk.)

But it’s not only book sales where you’ll find a system primed for rigging. Even those supposedly objective 5-star buyer ratings you find everywhere have also been gamed.

5-Star Scams

A 2021 McKinsey report said that, depending on the category, a small bump in a star rating on Amazon can translate into a 30% to 200% boost in sales. Given that potential windfall, it’s no surprise that you’ll find fake review scams proliferate on the gargantuan retail platform.

A recent Wired exposé on these fake reviews found a network that had achieved a level of sophistication that was sobering. It included active recruitment of human reviewers (called “Jennies” — if you haven’t been recruited yet, you’re a “Virgin Jenny”) willing to write a fake review for a small payment or free products. These recruitment networks include recruiting agents in locations including Pakistan, Bangladesh and India working for sellers from China.

But the fake review ecosystem also included reviews cranked out by AI-powered automated agents. As AI improves, these types of reviews will be harder to spot and weed out of the system.

Some recent studies have found that, depending on the category, over one-third of the reviews you see on Amazon are fake. Books, baby products and large appliance categories are the worst offenders.

Berating Ratings…

Back in 2014, Itamar Simonson and Emanuel Rosen wrote a book called “Absolute Value: What Really Influences Customers in the Age of (Nearly) Perfect Information.” Spoiler alert: they posited that consumer reviews and other sources of objective information were replacing traditional marketing and branding in terms of what influenced buyers.

They were right. The stats I cited above show how powerful these supposedly objective factors can be in driving sales. But unfortunately, thanks to the inevitable attempts to game these systems, the information they provide can often be far from perfect.

A Look Back at 2023 from the Inside.

(Note: This refers to the regular feature on Mediapost – The Media Insider – which I write for every Tuesday)

It seems that every two years, I look back at what the Media Insiders were musing about over the past year. The ironic part is that I’m not an Insider. I haven’t been “inside” the Media industry for over a decade. Maybe that affords me just enough distance to be what I hope could be called an “informed observer.”

I first did this in 2019, and then again in 2021. This year, I decided to grab a back of an envelope (literally) and redo this far from scientific poll. Categorization of themes is always a challenge when I do this, but there are definitely some themes that have been consistent across the past 5 years.  I have tremendous respect for my fellow Insiders and I always find it enlightening to learn what was on their minds.

In 2019, the top three things we were thinking about were (in order): disruptions in the advertising business, how technology is changing us and how politics changed social media.

In 2021, the top three topics included (again) how technology was changing us, general marketing advice and the toxic impact of social media.

So, what about 2023? What were we writing about? After eliminating the columns that were reruns, I ended up with 230 posts in the past year.

It probably comes as a surprise to no one that artificial intelligence was the number one topic by a substantial margin. Almost 15% of all our Insider posts talked about the rise of AI and its impact on – well – pretty much everything!

The number two topic – at 12% – was TV, video and movies. Most of the posts touched on how this industry is going through ongoing disruption in every aspect – creation, distribution, buying and measurement.

Coming in at number three, at just under 12%, was social media. Like in the previous years, most of the posts were about the toxic nature of social media, but there was a smattering of positive case studies about how social platforms were used for positive change.

We Insiders have always been an existential bunch and last year was no different. Our number four topic was about our struggling to stay human in a world increasingly dominated by tech. This accounted for almost 11% of all our posts.

The next two most popular topics were both firmly grounded in the marketing industry itself. Posts about how to be a better marketer generated almost 9% of Insider content for 2023 and various articles about the business of tech marketing added another 8% of posts.

Continuing down the list, we have world events and politics (Dave Morgan’s columns about the Ukraine were a notable addition to this topic), examples of marketing gone wrong and the art and science of brand building.

We also looked at the phenomenon of fame and celebrity, sustainability, and the state of the News industry. In what might have been a wistful look back at what we remember as simpler times, there were even a few columns about retro-media, including the resurgence of the LP.

Interestingly, former hot topics like performance measurement, data and search all clustered near the bottom of the list in terms of number of posts covering these topics.

With 2023 in our rear view mirror, what are the takeaways? What can we glean from the collected year-long works of these very savvy and somewhat battle-weary veterans of marketing?

Well, the word “straddle” comes to mind. We all seem to have one foot still planted in the world and industry we thought we knew and one tentatively dipping its toes into the murky waters of what might come. You can tell that the Media Insiders are no less passionate about the various forms of media we write about, but we do go forward with the caution that comes from having been there and done that.

I think that, in total, I found a potentially worrying duality in this review of our writing. Give or take a few years –  all my fellow Insiders are of the same generation. But we are not your typical Gen-Xers/Baby Boomers (or, in my case, caught in the middle as a member of Generation Jones). We have worked with technology all our lives. We get it. The difference is, we have also accumulated several decades of life wisdom. We are past the point where we’re mesmerized by bright shiny objects. I think this gives us a unique perspective. And, based on what I read, we’re more than a little worried about what future might bring.

Take that for what it’s worth.

OpenAI’s Q* – Why Should We Care?

OpenAI founder Sam Altman’s ouster and reinstatement has rolled through the typical news cycle and we’re now back to blissful ignorance. But I think this will be one of the sea-change moments; a tipping point that we’ll look back on in the future when AI has changed everything we thought we knew and we wonder, “how the hell did we let that happen?”

Sometimes I think that tech companies use acronyms and cryptic names for new technologies to allow them to sneak game changers in without setting off the alarm bells. Take OpenAI for example. How scary does Q-Star sound? It’s just one more vague label for something we really don’t understand.

 If I’m right, we do have to ask the question, “Who is keeping an eye on these things?”

This week I decided to dig into the whole Sam Altman firing/hiring episode a little more closely so I could understand if there’s anything I should be paying attention to. Granted, I know almost nothing about AI, so what follows if very much at the layperson level, but I think that’s probably true for the vast majority of us. I don’t run into AI engineers that often in my life.

So, should we care about what happened a few weeks ago at OpenAI? In a word – YES.

First of all, a little bit about the dynamics of what led to Altman’s original dismissal. OpenAI started with the best of altruistic intentions, to “to ensure that artificial general intelligence benefits all of humanity.”  That was an ideal – many would say a naïve ideal – that Altman and OpenAI’s founders imposed on themselves. As Google discovered with its “Don’t Be Evil” mantra, it’s really hard to be successful and idealistic at the same time. In our world, success is determined by profits, and idealism and profitability almost never play in the same sandbox. Google quietly watered the “Don’t be Evil” motto until it virtually disappeared in 2018.

OpenAI’s non-profit board was set up as a kind of Internal “kill switch” to prevent the development of technologies that could be dangerous to the human race. That theoretical structure was put to the test when the board received a letter this year from some senior researchers at the company warning of a new artificial intelligence discovery that might take AI past the threshold where it could be harmful to humans. The board then did was it was set up to do, firing Altman and board chairman Greg Brockman and putting the brakes on the potentially dangerous technology. Then, Big Brother Microsoft (who has invested $13 billion in OpenAI) stepped in and suddenly Altman was back. (Note – for a far more thorough and fascinating look at OpenAI’s unique structure and the endemic problems with it, read through Alberto Romero’s series of thoughtful posts.)

There were probably two things behind Altman’s ouster: the potential capabilities of a new development called Q-Star and a fear that it would follow OpenAI’s previous path of throwing it out there to the world, without considering potential consequences. So, why is Q-Star so troubling?

Q-Star could be a major step closer to AI which can rationalize and plan. This moves us closer to the overall goal of artificial general Intelligence (AGI), the holy grail for every AI developer, including OpenAI. Artificial general intelligence, as per OpenAI’s own definition, are “AI systems that are generally smarter than humans.” Q-Star, through its ability to tackle grade school math problems, showed the promise of being artificial intelligence that could plan and reason. And that is an important tipping point, because something that can rationalize and plan pushes us forever past the boundary of a tool under human control. It’s technology that thinks for itself.

Why should this worry us? It should worry us because of Herbert Simon’s concept of “bounded rationality”, which explains that we humans are incapable of pure rationality. At some point we stop thinking endlessly about a question and come up with an answer that’s “good enough”. And we do this because of limited processing power. Emotions take over and make the decision for us.

But AGI throws those limits away. It can process exponentially more data at a rate we can’t possibly match. If we’re looking at AI through Sam Altman’s rose-colored glasses, that should be a benefit. Wouldn’t it be better to have decisions made rationally, rather than emotionally? Shouldn’t that be a benefit to mankind?

But here’s the rub. Compassion is an emotion. Empathy is an emotion. Love is also an emotion. What kind of decisions do we come to if we strip that out of the algorithm, along with any type of human check and balance?

Here’s an example. Let’s say that at some point in the future an AGI superbrain is asked the question, “Is the presence of humans beneficial to the general well-being of the earth?”

I think you know what the rational answer to that is.

When AI Love Goes Bad

When we think about AI and its implications, it’s hard to wrap our own non-digital, built of flesh and blood brains around the magnitude of it. Try as we might, it’s impossible to forecast the impact of this massive wave of disruption that’s bearing down on us. So, today, in order to see what might be the unintended consequences, I’d like to zoom in to one particular example.

There is a new app out there. It’s called Anima and it’s an AI girlfriend. It’s not the only one. When it comes to potential virtual partners, there are plenty of fish in the sea. But – for this post, let’s stay true to Anima. Here’s the marketing blurb on her website: “The most advanced romance chatbot you’ve ever talked to. Fun and flirty dating simulator with no strings attached. Engage in a friendly chat, roleplay, grow your love & relationship skills.”

Now, if there’s one area where our instincts should kick in and alarm bells should start going off about AI, it should be in the area of sexual attraction. If there was one human activity that seems bound by necessity to being ITRW (in the real world) it should be this one.

If we start to imagine what might happen when we turn to AI for love, we could ask filmmaker Spike Jonze. He already imagined it, 10 years ago when he wrote the screenplay for “her”, the movie with Joaquin Phoenix. Phoenix plays Theodore Twombly, a soon-to-be divorced man who upgrades his computer to a new OS, only to fall in love with the virtual assistant (voiced by Scarlett Johansson) that comes as part of the upgrade.

Predictably, complications ensue.

To get back to Anima, I’m always amused by the marketing language developers use to lull us into the acceptance of things we should be panicking about. In this case, it was two lines: “No strings attached” and “grow your love and relationship skills.”

First, about that “no strings attached” thing – I have been married for 34 years now and I’m here to tell you that relationships are all about “strings.” Those “strings” can also be called by other names: empathy, consideration, respect, compassion and – yes – love. Is it easy to keep those strings attached – to stay connected with the person at the other end of those strings? Hell, no! It is a constant, daunting, challenging work in progress. But the alternative is cutting those strings and being alone. Really alone.

If we get the illusion of a real relationships through some flirty version of ChatGPT, will it be easier to cut the strings that keep us connected to other real people out there? Will we be fooled into thinking something is real when it’s just a seductive algorithm?  In “her”, Jonze brings Twombly back to the real world, ending with a promise of a relationship with a real person as they both gaze at the sunset. But I worry that that’s just a Hollywood ending. I think many people – maybe most people – would rather stick with the “no strings attached” illusion. It’s just easier.

And will AI adultery really “grow your love and relationship skills?” No. No more than you will grow your ability to determine accurate and reliable information by scrolling through your Facebook feed. That’s just a qualifier that the developer threw in so they didn’t feel crappy about leading their customers down the path to “AI-rmegeddon”.

Even if we put all this other stuff aside for the moment, consider the vulnerable position we put ourselves in when we start mistaking robotic love for the real thing. All great cons rely on one of two things – either greed or love. When we think we’re in love, we drop our guard. We trust when we probably shouldn’t.

Take the Anima artificial girlfriend app for example. We know nothing about the makers of this app. We don’t know where the data collected goes. We certainly have no idea what their intentions are. Is this really who you want to start sharing your most intimate chit chat with? Even if their intentions are benign, this is an app built a for-profit company, which means there needs to be a revenue model in it somewhere. I’m guessing that all your personal data will be sold to the highest bidder.

You may think all this talk of AI love is simply stupid. We humans are too smart to be sucked in by an algorithm. But study after study has shown we’re not. We’re ready to make friends with a robot at the drop of a hat. And once we hit friendship, can love be far behind?

AI, Creativity and the Last Beatle’s Song

I have never been accused of being a Luddite. Typically, I’m on the other end of the adoption curve – one of the first to adopt a new technology. But when it comes to AI, I am stepping forward gingerly.

Now, my hesitancy notwithstanding, AI is here to stay. In my world, it is well past the tipping point from a thing that exists solely in the domain to tech to a topic of conversation for everyone, from butchers to bakers to candlestick makers. Everywhere I turn now I see those ubiquitous two letters – AI. That was especially true in the last week, with the turmoil around Sam Altman and the “is he fired/isn’t he” drama at OpenAI.

In 1991 Geoffery Moore wrote the book Crossing the Chasm, looking at how technologies are adopted. He explained that it depends on the nature of the technology itself. If it’s a continuation of technology we understand, the adoption follows a fairly straight-forward bell curve through the general population.

But if it’s a disruptive technology – one that we’re not familiar with – then adoption plots itself out on an S-Curve. The tipping point in the middle of that curve where it switches from being skinny to being fat is what he called the “chasm.” Some technologies get stuck on the wrong side of the chasm, never to be adopted by the majority of the market.  Think Google Glass, for example.

There is often a pattern to the adoption of disruptive technologies (and AI definitely fits this description).  To begin with, we find a way to adapt it and use it for the things we’re already doing. But somewhere along the line, innovators grasp the full potential of the technology and apply it in completely new ways, pushing capabilities forward exponentially. And it’s in that push forward where all the societal disruption occurs. Suddenly, all the unintended consequences make themselves known.

This is exactly where we seem to be with AI. Most of us are using it to tweak the things we’ve always done. But the prescient amongst us are starting to look at what might be, and for many of us, we’re doing so with a furrowed brow. We’re worried, and, I suspect, with good reason.

As one example, I’ve been thinking about AI and creativity. As someone who has always dabbled in creative design, media production and writing, this has been top of mind for me. I have often tried to pry open the mystic box that is the creative process.

There are many, creative software developers foremost amongst them, that will tell you that AI will be a game changer when it comes to creating – well – just about anything.

Or, in the case of the last Beatle single to be released, recreating anything. Now and Then, the final Beatles song featuring the Fab Four, was made possible by an AI program created by Peter Jackson’s team for the documentary Get Back. It allowed Paul McCartney, Ringo Starr and their team of producers (headed by George Martin’s son Giles) to separate John Lennon’s vocals from the piano background on a demo tape from 1978.

One last Beatle’s song featuring John Lennon – that should be a good thing – right?  I guess. But there’s a flip side to this.

Let’s take writing, for example. Ask anyone who has written something longer than a tweet or Instagram post. What you start out intending to write is never what you end up with. Somehow, the process of writing takes its own twists and turns, usually surprising even the writer. Even these posts, which average only 700 to 800 words, usually end up going in unexpected directions by the time I place the final period.

Creativity is an iterative process and there are stages in that process. It takes time for it all to  play out. No matter how good my initial idea is, if I simply fed it in an AI black box and hit the “create” button, I don’t know if the outcome would be something I would be happy with.

“But,” you protest, “what about AI taking the drudgery out of the creative process? What if you use it to clean up a photo, or remove background noise from an audio recording (a la the Beatles single). That should free up more time and more options for you to be creative, right?”

That’s promise is certainly what’s being pitched by AI merchants right now. And it makes sense. But it only makes sense at the skinny end of the adoption curve. That’s where we’re at right now, using AI as a new tool to do old jobs. If we think that’s where we’re going to stay, I’m pretty sure we’re being naïve.

I believe creativity needs some sweat. It benefits from a timeline that allows for thinking, and rethinking, over and over again. I don’t believe creativity comes from instant gratification, which is what AI gives us. It comes from iteration that creates the spaces needed for inspiration.

Now, I may be wrong. Perhaps AI’s ability to instantly produce hundreds of variation of an idea will prove the proponents right. It may unleash more creativity than ever. But I still believe we will lose an essential human element in the process that is critical to the act of creation.

Time will tell. And I suspect it won’t take very long.

(Image – The Beatles in WPAP – wendhahai)

Getting from A to Zen

We live in a Type A world. And sometimes, that’s to our detriment.

According to one definition, Type A is achievement oriented, competitive, fast-paced and impatient.

All of that pretty much sums up the environment we live in. But you know what’s hard to find in a Type A world? Your Zen.

I know what you’re thinking — “I didn’t peg Gord for a Zen-seeking kinda guy.” And you’re mostly right. I’m not much for meditation. I’ve tried it — it’s not for me. I’ll be honest. It feels a little too airy-fairy for my overly rational brain.

But I do love cutting the grass. I also love digging holes, retouching photos in Photoshop and cleaning pools. Those are some of the activities where I can find my Zen.

For best-selling author Peggy Orenstein, she found her Zen during COVID – shearing sheep. She shares her journey in her new book, “Unraveling: What I Learned About Life While Shearing Sheep, Dyeing Wool, and Making the World’s Ugliest Sweater.” Orenstein has a breezy, humorous, and self-deprecating style, but there are some deep thoughts here.

In reading the book, I learned it wasn’t the act of shearing where Peggy found her Zen. That’s because sheep shearing is really hard work. You can’t let your mind wander as you wrestle 200 to 300 pounds of Ovis aries, holding a buzzing, super-sharp set of sheers while trying to give it a haircut.

As Orenstein said in a recent interview, “Imagine you were in a ballet with Nureyev and nobody told you the steps. That was what it felt like to reach shearing sheep, you know, for the first time.”

No. You might find a lot of things in that activity, but Zen isn’t likely to be one of them. Orenstein finds her Zen in a less terrifying place, cleaning poop out of the newly shorn wool. She did it the way it’s been done for centuries, in a process called carding. While she carded the wool, she would “Facetime” her dad, who has dementia.

In the interview, she said, “You know, I could just slow down. These ancient arts are slow. They’re very slow and (I would) sit with him and just be next to him and have that time together and sing.”

When I heard her say that in the interview, that hit me. I said, “I have to read this book.” Because I got it. That slowing down, that inner connection, the very act of doing something that seems mindless but isn’t – because doing the act creates the space for your mind to think the thoughts it normally doesn’t have time to do. All that stuff is important.

To me, that’s my Zen.

Now, unless you’re a Mahayana Buddhist, Zen is probably nothing more than a buzzword that made its way westward into our zeitgeist sometime in the last century. I am certainly not a Buddhist, so I am not going to dare tell you the definitive meaning of Zen. I am just going to tell you what my version is.

For me, Zen is a few things:

I think these Zen acts have to contribute to the world in some small way. There has to be something at the end that gives you a sense of accomplishment – the feeling of a job well done.

Maybe that’s why meditation is not for me. There is not a tangible reward at the end. But you can look at a pile of newly shorn fleece or a lawn neatly delineated with the tire tracks of your lawnmower.

The brain must be engaged in a Zen task, but not too much. It needs some space to wander. Repetition helps. As you do the task, your mind eventually shifts to auto-pilot mode. And that’s when I find Zen, as my mind is given the license to explore.

I think this is where step one is important – whatever you’re doing has to be useful enough that you don’t feel that you’re wasting time doing it.

Finally, it helps if your Zen tasks are done in a place where the Type A world doesn’t intrude. You need the space to push back interruption and let your mind wander freely.

I realize there are some of you who will immediately connect with what I’m saying, and others who won’t have a clue. That’s okay.

I think that’s the magic of Zen: it’s not for everyone. But for those of us who understand how important it is, we sometimes need a little reminder to sometimes go seek it. Because in this Type A world, it’s becoming harder to find.

No News is Good News

I’m trying not to pay too much attention to the news. This is partly because I’m exhausted by the news, and partly because of the sad state of journalism today.

This isn’t just a “me” thing. Almost everyone I talk to says they’re trying to find coping mechanisms to deal with the news. The News industry – and its audience – has gone from being an essential part of a working democracy to something that is actually bad for you.  In an online essay from 4 years, Swiss author Rolf Dobelli equates news consumption to a bad diet:

“(translated from its original German) News is to the mind what sugar is to the body. News is appetizing, easily digestible and at the same time highly harmful. The media feeds us morsels of trivial stories, tidbits that by no means satisfy our hunger for knowledge. Unlike with books and long, well-researched, long articles, there is no saturation when consuming news. We can devour unlimited amounts of messages; they remain cheap sugar candies. As with sugar, the side effects only show up with a delay.”

Rolf Dobelli, 2019

This alarming state is due to the fact that the News (in the US) is supported by advertising, which means it has a ravenous appetite for eyeballs. Because of this, it is highly profitable to make news addictive.

This creates a state, as Dobelli points out, where even though the news is highly inflammatory, like a constantly jangling alarm bell, almost all the news we consume is irrelevant to our daily lives. While the news we watch pushes all our hot buttons, it doesn’t serve a useful purpose. In fact, it does the exact opposite: it leads to chronic mental and physical ill-being and may cause us to start ignoring the warning signs we should be paying attention to.

A study last year (McLaughlin, Gotlieb and Mills) found ties between problematic news consumption and mental ill-being. The study found that 16.5% of 1,100 people polled in an online survey showed signs of “severely problematic” news consumption, which led them to focus less on school, work and family, and contributed to an inability to sleep.

Dobelli’s essay goes even further, pointing a finger at excessive news consumption as the cause of a list of issues including cognitive errors, inhibiting deeper thinking, wasting time, killing creativity, making us more passive and even wiring our brains for addiction in a manner similar to drugs.

All these negative side effects come from chronic stress – a constant and pervasive alarmed state that excessive news consumption puts our brains into. And if you thought Dobelli’s list was scary, wait until you see the impact of chronic stress! It actually attacks the brain by releasing excessive amounts of cortisol and restricting the uptake of serotonin, which can increase inflammation, lead to depression, shrink your hippocampus and impact your memory, make it difficult to sleep and impair your ability to think rationally.

To put a new twist on an old saying, “No news is good news.”

But let’s put aside for a moment the physical and mental toll that news takes on us. Even if none of that were true, our constant diet of bad news can also lead to something known as “alarm fatigue.”

Alarm fatigue is essentially our response to the proverbial boy who calls wolf. After several false alarms, we stop paying attention. And on that one time when we should be paying attention, we are caught with our guard down.

There is one other problem with our news diet: it oversimplifies complex problems into simple sound bites. Thomas Jefferson said, “An educated citizenry is a vital requisite for our survival as a free people.” But when the news abdicates its role as an informer to pursue profit as entertainment, it is no longer educating us. It is pandering to us by stuffing bite sized opinion pieces that reinforce our beliefs – right or wrong. We are never challenged to examine our beliefs or explore the complexity of the wicked problems that confront us. Real journalism has been replaced by profitable punditry.

All this leaves us with a choice. Until the News industry cleans up its act (I’m not holding my breath), you’re likely far better off to ignore it. Or at least, ignore the profit driven platforms that are hungry for eyeballs. Stay informed by turning to books, long articles and true investigative journalism. That’s what I’m going to start doing.

Failing all that, just think about things. I understand it’s good for you.

Why I’m Worried About AI

Even in my world, which is nowhere near the epicenter of the technology universe, everyone is talking about AI And depending on who’s talking – it’s either going to be the biggest boon to humanity, or it’s going to wipe us out completely. Middle ground seems to be hard to find.

I recently attended a debate at the local university about it. Two were arguing for AI, and two were arguing against. I went into the debate somewhat worried. When I walked out at the end of the evening, my worry was bubbling just under the panic level.

The “For” Team had a computer science professor – Kevin Leyton-Brown, and a philosophy professor – Madeleine Ransom. Their arguments seemed to rely mainly on creating more leisure time for us by freeing us from the icky jobs we’d rather not do. Leyton-Brown did make a passing reference to AI helping us to solve the many, many wicked problems we face, but he never got into specifics.

“Relax!” seemed to be the message. “This will be great! Trust us!”

The “Against” Team was comprised of a professor in Creative and Critical Studies – Bryce Traister. As far as I could see, he seemed to be mainly worried about AI replacing Shakespeare. He did seem quite enamored with the cleverness of his own quips.

It was the other “Against” debater who was the only one to actually talk about something concrete I could wrap my head around. Wendy Wong is a professor of Political Science. She has a book on data and human rights coming out this fall. Many of her concerns focused on this area.

Interestingly, the AI debaters all mentioned Social Media in their arguments. And on this point, they were united. All the debaters agreed that the impact of Social Media has been horrible. But the boosters were quick to say that AI is nothing like Social Media.

Except that it is. Maybe not in terms of the technology that lies beneath it, but in terms of the unintended consequences it could unleash, absolutely! Like Social Media, what will get us with AI are the things we don’t know we don’t know.

I remember when social media first appeared on the scene. Like AI, there were plenty of evangelists lining up saying that technology would connect us in ways we couldn’t have imagined. We were redefining community, removing the physical constraints that had previously limited connections.

If there was a difference between social media and AI, it was that I don’t remember the same doomsayers at the advent of social media. Everyone seemed to be saying “This will be great! Trust us!”

Today, of course, we know better. No one was warning us that social media would divide us in ways we never imagined, driving a wedge down the ideological middle of our society. There were no hints that social media could (and still might) short circuit democracy.

Maybe that’s why we’re a little warier when it comes to AI. We’ve already been fooled once.

I find that AI Boosters share a similar mindset – they tend to be from the S.T.E.M. (Science, Technology, Engineering and Math) School of Thought. As I’ve said before, these types of thinkers tend to mistake complex problems for complicated ones. They think everything is solvable, if you just have a powerful enough tool and apply enough brain power. For them, AI is the Holy Grail – a powerful tool that potentially applies unlimited brain power.

But the dangers of AI are hidden in the roots of complexity, not complication, and that requires a different way of thinking. If we’re going to get some glimpse of what’s coming our way, I am more inclined to trust the instincts of those that think in terms of the humanities. A thinker, for example, such as Yuval Noah Harari, author of Sapiens.

Harari recently wrote an essay in the Economist that may be the single most insightful thing I’ve read about the dangers of AI: “AI has gained some remarkable abilities to manipulate and generate language, whether with words, sounds or images. AI has thereby hacked the operating system of our civilisation.”

In my previous experiments with ChatGPT, it was this fear that was haunting me. Human brains operate on narratives. We are hard-wired to believe them. By using language, AI has a back door into our brains that bypass all our protective firewalls.

My other great fear is that the development of AI is being driven by for-profit corporations, many of which rely on advertising as their main source of revenue. If ever there was a case of putting the fox in charge of the henhouse, this is it!

When it comes to AI it’s not my job I’m afraid of losing. It’s my ability to sniff out AI generated bullshit. That’s what’s keeping me up a night.

Search and ChatGPT – You Still Can’t Get There From Here

I’m wrapping up my ChatGPTrilogy with a shout out to an old friend that will be familiar to many Mediaposters – Aaron Goldman. 13 years ago Aaron wrote a book called Everything I Know About Marketing I Learned from Google.  Just a few weeks ago, Aaron shared a post entitled “In a World of AI, is Everything I Know about Marketing (still) Learned from Google”. In it, he looked at the last chapter of the book, which he called Future-Proofing. Part of that chapter was based on a conversation Aaron and I had back in 2010 about what search might look like in the future.

Did we get it right? Well, remarkably, we got a lot more right than we got wrong, especially with the advent of Natural Language tools such as ChatGPT and virtual assistants like Siri.

We talked a lot about something I called “app-sistants”. I explained, “the idea of search as a destination is an idea whose days are numbered. The important thing won’t be search. It will be the platform and the apps that run on it. The next big thing will be the ability to seamlessly find just the right app for your intent and utilize it immediately.” In this context, “the information itself will become less and less important and the app that allows utilization of the information will become more and more important.”

To be honest, this evolution in search has taken a lot longer than I thought back then, “Intent will be more fully supported from end to end. Right now, we have to keep our master ‘intent’ plan in place as we handle the individual tasks on the way to that intent.”

Searching for complex answers as it currently sits requires a lot of heavy lifting. In that discussion, I used the example of planning a trip.  “Imagine if there were an app that could keep my master intent in mind for the entire process. It would know what my end goal was, would be tailored to understand my personal preferences and would use search to go out and gather the required information. When we look at alignment of intent, [a shift from search to apps is] a really intriguing concept for marketers to consider.”

So, the big question is, do we have such a tool? Is it ChatGPT? I decided to give it a try and see. After feeding ChatGPT a couple of carefully crafted prompts about a trip I’d like to take to Eastern Europe someday, I decided the answer is no. We’re not quite there yet. But we’re closer.

After a couple of iterations, ChatGPT did a credible job of assembling a potential itinerary of a trip to Croatia and Slovenia. It even made me aware of some options I hadn’t run across in my previous research. But it left me hanging well short of the “app-ssistant” I was dreaming of in 2010. Essentially, I got a suggestion but all the detail work to put it into an actual trip still required me to do hundreds of searches in various places.

The problem with ChatGPT is that it gets stuck between the millions of functionality siloes – or “walled gardens” – that make up the Internet. Those “walled gardens” exist because they represent opportunities for monetization. In order for an app-ssistant to be able to multitask and make our lives easier, we need a virtual “commonage” that gets rid of some of these walls. And that’s probably the biggest reason we haven’t seen a truly useful iteration of the functionality I predicted more than a decade ago.

This conflict between capitalism and the concept of a commonage goes back at least to the Magna Carta. As England’s economy transitioned from feudalism to capitalism, enclosure saw the building of fences and the wiping out of lands held as a commonage. The actual landscape became a collection of walled gardens that the enforced property rights of each parcel and the future production value of those parcels.

This history, which played out over hundreds of years, was repeated and compressed into a few decades online. We went from the naïve idealism of a “free for all” internet in the early days to the balkanized patchwork of monetization siloes that currently make up the Web.

Right now, search engines are the closest thing we have to a commonage on the virtual landscape. Search engines like Google can pull data from within many gardens, but if we actually try to use the data, we won’t get far before we run into a wall.

To go back to the idea of trip planning, I might be able to see what it costs to fly to Rome or what the cost of accommodations in Venice is on a search engine, but I can’t book a flight or reserve a room. To do that, I have to visit an online booking site. If I’m on a search engine, I can manually navigate this transition fairly easily. But it would stop something like ChatGPT in its tracks.

When I talked to Aaron 13 years ago, I envisioned search becoming a platform that lived underneath apps which could provide more functionality to the user. But I also was skeptical about Google’s willingness to do this, as I stated in a later post here on Mediapost.  In that post, I thought that this might be an easier transition for Microsoft.

Whether it was prescience or just dumb luck, it is indeed Microsoft taking the first steps towards integrating search with ChatGPT, through its recent integration with Bing. Expedia (who also has Microsoft DNA in its genome) has also taken a shot at integrating ChatGPT in a natural language chat interface.

This flips my original forecast on its head. Rather than the data becoming common ground, it’s the chat interface that’s popping up everywhere. Rather than tearing down the walls that divide the online landscape, ChatGPT is being tacked up as window decoration on those walls.

I did try planning that same trip on both Bing and Expedia. Bing – alas – also left me well short of my imagined destination. Expedia – being a monetization site to begin with – got me a little closer, but it still didn’t seem that I could get to where I wanted to go.

I’m sorry to say search didn’t come nearly as far as I hoped it would 13 years ago. Even with ChatGPT thumbtacked onto the interface, we’re just not there yet.

(Feature Image: OpenAI Art generated from the prompt: “A Van Gogh painting of a chatbot on a visit to Croatia”)

The Dangerous Bits about ChatGPT

Last week, I shared how ChatGPT got a few things wrong when I asked it “who Gord Hotchkiss was.” I did this with my tongue at least partially implanted in cheek – but the response did show me a real potential danger here, coming from how we will interact with ChatGPT.

When things go wrong, we love to assign blame. And if ChatGPT gets things wrong, we will be quick to point the finger at it. But let’s remember, ChatGPT is a tool, and the fault very seldom lies with the tool. The fault usually lies with the person using the tool.

First of all, let’s look at why ChatGPT put together a bio for myself that was somewhat less than accurate (although it was very flattering to yours truly).

When AI Hallucinates

I have found a few articles that calls ChatGPT out for lying. But lying is an intentional act, and – as far as I know – ChatGPT has no intention of deliberately leading us astray. Based on how ChatGPT pulls together information and synthesizes it into a natural language response, it actually thought that “Gord Hotchkiss” did the things it told me I had done.

You could more accurately say ChatGPT is hallucinating – giving a false picture based on what information it retrieves and then tries to connect into a narrative. It’s a flaw that will undoubtedly get better with time.

The problem comes with how ChatGPT handles its dataset and determines relevance between items in that dataset. In this thorough examination by Machine Learning expert Devansh Devansh, ChatGPT is compared to predictive autocomplete on your phone. Sometimes, through a glitch in the AI, it can take a weird direction.

When this happens on your phone, it’s word by word and you can easily spot where things are going off the rail.  With ChatGPT, an initial error that might be small at first continues to propagate until the AI has spun complete bullshit and packaged it as truth. This is how it fabricated the Think Tank of Human Values in Business, a completely fictional organization, and inserted it into my CV in a very convincing way.

There are many, many others who know much more about AI and Natural Language Processing that I do, so I’m going to recognize my limits and leave it there. Let’s just say that ChatGPT is prone to sharing it’s AI hallucinations in a very convincing way.

Users of ChatGPT Won’t Admit Its Limitations

I know and you know that marketers are salivating over the possibility of AI producing content at scale for automated marketing campaigns. There is a frenzy of positively giddy accounts about how ChatGPT will “revolutionize Content Creation and Analysis” – including this admittedly tongue in cheek one co-authored by MediaPost Editor in Chief Joe Mandese and – of course – ChatGPT.

So what happens when ChatGPT starts to hallucinate in the middle of massive social media campaign that is totally on autopilot? Who will be the ghost in the machine that will say “Whoa there, let’s just take a sec to make sure we’re not spinning out fictitious and potentially dangerous content?”

No one. Marketers are only human, and humans will always look for the path of least resistance. We work to eliminate friction, not add it. If we can automate marketing, we will. And we will shift the onus of verifying information to the consumer of that information.

Don’t tell me we won’t, because we have in the past and we will in the future.

We Believe What We’re Told

We might like to believe we’re Cartesian, but when it comes to consuming information, we’re actually Spinozian

Let me explain. French philosopher René Descartes and Dutch philosopher Baruch Spinoza had two different views of how we determine if something is true.

Descartes believed that understanding and believing were two different processes. According to Descartes, when we get new information, we first analyze it and then decide if we believe it or not. This is the rational assessment that publishers and marketers always insist that we humans do and it’s their fallback position when they’re accused of spreading misinformation.

But Baruch Spinoza believed that understanding and belief happened at the same time. We start from a default position of believing information to be true without really analyzing it.

In 1993, Harvard Psychology Professor Daniel Gilbert decided to put the debate to the test (Gilbert, Tafarodi and Malone). He split a group of volunteers in half and gave both a text description detailing a real robbery. In the text there were true statements, in green, and false statements, in red. Some of the false statements made the crime appear to be more violent.

After reading the text, the study participants were supposed to decide on a fair sentence. But one of the groups got interrupted with distractions. The other group completed the exercise with no distractions. Gilbert and his researchers believed the distracted group would behave in a more typical way.

The distracted group gave out substantially harsher sentences than the other group. Because they were distracted, they forgot that green sentences were true and red ones were false. They believed everything they read (in fact, Gilbert’s paper was called “You Can’t Not Believe Everything You Read).”

Gilbert’s study showed that humans tend to believe first and that we actually have to “unbelieve” if something is eventually proven to us to be false. Once study even found the place in our brain where this happens – the Right Inferior Prefrontal Cortex. This suggests that “unbelieving” causes the brain to have to work harder than believing, which happens by default. 

This brings up a three-pronged dilemma when we consider ChatGPT: it will tend to hallucinate (at least for now), users of ChatGPT will disregard that flaw when there are significant benefits to doing so, and consumers of ChatGPT generated content will believe those hallucinations without rational consideration.

When Gilbert wrote his paper, he was still 3 decades away from this dilemma, but he wrapped up with a prescient debate:

“The Spinozan hypothesis suggests that we are not by nature, but we can be by artifice, skeptical consumers of information. If we allow this conceptualization of belief to replace our Cartesian folk psychology, then how shall we use it to structure our own society? Shall we pander to our initial gullibility and accept the social costs of prior restraint, realizing that some good ideas will inevitably be suppressed by the arbiters of right thinking? Or shall we deregulate the marketplace of thought and accept the costs that may accrue when people are allowed to encounter bad ideas? The answer is not an easy one, but history suggests that unless we make this decision ourselves, someone will gladly make it for us. “

Daniel Gilbert

What Gilbert couldn’t know at the time was that “someone” might actually be a “something.”

(Image:  Etienne Girardet on Unsplash)