Overheard at ON_Discourse

The New Internet Will Look Very Familiar

Editor’s note: We’ve heard – and promoted – our fair share of sensational takes about the next internet, so it is with a special sense of duty that we offer this push-back. This perspective comes from a technology executive who was very interested in splashing cold water on the revolutionary framing of the future internet. Stay tuned for a counter-take.

When we talk about the next internet, there is an assumption that the new thing will be a revolution against the current internet. But It’s not always about reinvention. 

There is enough consumer data to suggest that people are not looking for a new internet as much as they are looking for more of what already exists. This is the data I’m talking about:

Screens still matter

The devices may change but consumers continue to watch some kind of screen for roughly 7 hours a day (TV + Phone).

The internet is for entertainment

70% of the bits that move through the internet are for entertainment (streaming TV, movies, sports, games, fitness).

Connectivity is steadily growing

Since 2019, the number of connected devices in the home has gone up 40%.

Let’s stop pretending that the future of the internet is going to look unrecognizable to the thing we’re using today. The internet consumer in 2025 is going to look like an internet superuser in 2019. 

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The Future of Media is Personal

A lot more content is coming

Overheard at ON_Discourse

From the editor: Is digital media doomed? The following perspective comes from a guest who was an executive at one of the biggest newsrooms in the world. It builds off another point we overheard about how news should be thought of as a service, not a product. This kind of thinking can transform news consumption into a personalized experience.

I pay for ESPN+. This subscription gets me access to countless streams that have no value to me at all. The only reason I pay is to access my team’s games. Are you telling me this kind of subscription model is a good thing? We are on the brink of a new kind of subscriber relationship that will be powered by AI and proprietary data.

We have to stop thinking about AI as if it is a replacement technology. AI is the ultimate enabler.

The first point is about the data. I have been paying ESPN directly for six years. They have collected data on my team & league affinities, watching preferences, and triggers. This data is not big enough to launch an ESPN LLM, but that does not matter; there are other ways to integrate smaller sets of proprietary data into another platform’s LLM. The bottom line is that ESPN can finally have access to the enabling technology that can ultimately deliver a true personalized experience. I don’t think we know yet how amazing this experience will be. It is going to be worth the money.

We have to stop thinking about AI as if it is a replacement technology. AI is the ultimate enabler. Media brands need to embrace the way this tech can foster novel content experiences. Doing so will revolutionize the relationships audiences have with their media brands. I am typically a pessimist when I think about the future of the internet, but this scenario gets me legitimately inspired.

READ MORE

Is Media Doomed?

The internet is mutating. Search queries are being replaced by prompts, and search results are turning into direct information. The web has always been perceived as an interconnected network of sites, but this new internet feels more like a magic mirror: prompt and you shall receive. Does this transition mean media is doomed?

AI Mediocrity is Coming

This is the era of exponential content

Bias is a moat against AI mediocrity

Develop a stronger point of view

News is a service, not a product

This mindset can unlock AI utility in newsrooms.

The future of media is personal

A lot more content is coming

Leverage your data

Available to read soon

Incumbents have an advantage

Available to read soon

AI is not the biggest threat to news

Available to read soon

News Is a Service, Not a Product

This mindset can unlock AI utility in newsrooms.

From the editor: Is digital media doomed? The following perspective comes from a guest who was an executive at one of the biggest newsrooms in the world. It reframes the way generative AI is often blamed for contaminating content with mediocre output. What if the focus was on the journalism and not the content?

Newsroom conversations about AI are confined by the wrong mindset. News is a service, not a product. In order to understand why this matters, let me break it down.

If news is a product, then the ultimate byproduct is the article. This mindset dictates how ads are bought, sold, and placed on the real-estate of the page. Additionally, the traffic to that page determines the ultimate value of the coverage for the bottom line. Publishers will spend resources designing the packaging and promotion of that content. Awards will be set up to honor the best designs. Careers will be made out of this whole arrangement. And while it works for many of the actors involved, it is missing one key element: the audience. For the most part, the youngest generation in the professional world are not finding any of this relevant.

Overheard at ON_Discourse

It is me taking you out and making you tell me something you don’t want to tell.


This is because news is not a product; we got that wrong. News is a service.

As someone just said at this table, the role of the journalist is not to produce articles. “It is me taking you out and making you tell me something you don’t want to tell.” The format of the information is irrelevant to the audience; the point of thinking this as a service is translating the relevant information into a context that serves that audience member. The act of journalism is hard to automate, but AI can help in converting facts into formats that do a better job of delivering value.

AI should be exciting to newsrooms.This technology can translate complex findings into personalized packages at scale. We are at the precipice of a new era of media and all we have to do is understand what we’re doing here and why. The article is not the point.

READ MORE

Is Media Doomed?

The internet is mutating. Search queries are being replaced by prompts, and search results are turning into direct information. The web has always been perceived as an interconnected network of sites, but this new internet feels more like a magic mirror: prompt and you shall receive. Does this transition mean media is doomed?

AI Mediocrity is Coming

This is the era of exponential content

Bias is a moat against AI mediocrity

Develop a stronger point of view

News is a service, not a product

This mindset can unlock AI utility in newsrooms.

The future of media is personal

A lot more content is coming

Leverage your data

Available to read soon

Incumbents have an advantage

Available to read soon

AI is not the biggest threat to news

Available to read soon

AI Mediocrity is Coming

This is the era of exponential content

Overheard at ON_Discourse

Overheard at ON_Discourse

From the editor: Is digital media doomed? The disruptive forces of generative AI are not only changing end-user experiences, they are changing the economic model of all media. The following perspectives come from a dialogue between two executives from global newsrooms.

So far, most newsrooms are generally using AI on the production side. This seems to be the most common expectation for how AI is going to infiltrate digital media. It should come as no surprise that the results so far have been a humiliating disaster. Nevertheless, the public scrutiny that came from these failures will not slow this trend. More AI-generated content is coming to newsrooms and out into your own personal content feeds. The problem is: the more content it generates, the more mediocre it will get.

AI is exponential. Exponents are tricky. AI has proven that it’s really good at creating more content — not good content — just more. But at a certain point there is too much to be processed, even by AI. What happens next?

This will not be a problem for many popular media formats and subjects. Audiences know how to accept “good-enough” content in the right context. Overall I think we’re fine with mediocrity. Media brands run by organizations that are focused solely on short-term earnings cycles will bank on this trend. 

READ MORE

Is Media Doomed?

The internet is mutating. Search queries are being replaced by prompts, and search results are turning into direct information. The web has always been perceived as an interconnected network of sites, but this new internet feels more like a magic mirror: prompt and you shall receive. Does this transition mean media is doomed?

AI Mediocrity is Coming

This is the era of exponential content

Bias is a moat against AI mediocrity

Develop a stronger point of view

News is a service, not a product

This mindset can unlock AI utility in newsrooms.

The future of media is personal

A lot more content is coming

Leverage your data

Available to read soon

Incumbents have an advantage

Available to read soon

AI is not the biggest threat to news

Available to read soon

Bias is a moat against AI
Mediocrity

Develop a stronger point of view

Overheard at ON_Discourse

Overheard at ON_Discourse

From the editor: AI-generated content is a cost-saving tool that serves no other purpose. One theme that popped up in our events was the power of a point of view. One of our guests welcomed the rise of mediocre content as a way for legacy brands to stay relevant in a saturated media environment. Can a stronger bias save legacy brands from extinction?

The solution to AI-generated content is a strong point of view. We need to bring bias back to newsrooms.

All of the brands that are experimenting with AI-generated content are dying. Sports Illustrated and the Gannett newspaper titles carry legacy brand value with older generational segments, driving short term marginal revenue. At the end of the day, they will eventually go the way of Life Magazine. In that way, it makes business-sense for the leaders to cut costs on content production. But those brands are dying and they don’t matter to this discussion. Let’s talk about the next generation of media.

If AI content is mediocre and generic, their content should be specific and infused with a strong point of view. Bring bias back!

I care about the media brands that have long-term goals that require growing an audience. These brands should be paying attention to the AI-generated content trend as a way to differentiate themselves with their target audience. If AI content is mediocre and generic, their content should be specific and infused with a strong point of view. Bring bias back!

Media bias is unnecessarily controversial in the US. It is easier in many cases for a newsroom to favor an unbiased product than to acknowledge the sentiments that exist within the newsroom and among its audience. This dynamic creates a barrier between media brands and younger generations. It is widely known in consumer research that younger consumers in their 20s, 30s, early 40s wanted brands to stand for something. It is no surprise, then, that unbiased media is not relevant to the next generation. 

Let’s let go of outdated expectations about bias and lean into our differences. 

Overheard at ON_Discourse

That’s not good

An innovative idea that’s too ahead of its time

From the editor: This perspective emerged out of a virtual event after the launch of the Vision Pro. A member was broadcasting into our Zoom call as their ethereal Apple persona before crashing out of the session. This sparked a member debate about which device the Vision Pro more closely resembles. We follow Chatham House rules, so we do not attribute perspectives without authorization.

In 1993, Apple released the Newton, the world’s first personal digital assistant (PDA). It was ugly, buggy, and expensive, and it also included a non-functioning stylus that frequently got misplaced. Does any of this sound familiar to you?

The Newton deserves a lot of credit. It invented a new category of computing for mobile devices. Many of the initial ideas for personal note taking and contact management persist in our smartphones today. To put it another way, the Newton was analogous to the Velvet Underground: not popular, but influential. At the same time, its failures were comical.

I am not the only one to say this. Beeple recently made the same comparison. So what does this mean for Apple and the Vision Pro?

The Newton was analogous to the Velvet Underground: not popular, but influential.

Apple is now just another player in the VR void. And so they have to join Meta, Pico, and all the other brands in their search for a use-case that will make headset computing mainstream. Let me put it another way: the Vision Pro did not change the VR industry. I don’t care how much they try to use the word spatial, the Vision Pro is a conventional VR device that is just heavier and more expensive.

Apple’s brand is aspirational, luxurious, and innovative. These attributes were earned by the spectacular attention to detail, design, and product-market fit that define every other product in their ecosystem. The high standards that Apple has traditionally set for itself have usually come with hard decisions that ultimately serve the customer. Upon his return in 1997, one of the first things Steve Jobs did was kill the Newton product line. They went back to the drawing board and ultimately came back with the most successful piece of hardware in the history of digital technology

Does any of that sound familiar to you?

That is the wrong comparison

The Vision Pro is neither the iPhone or the Newton. You have to think bigger.

From the editor: We are noticing that this device is prompting very strong contrarian discourse. In this case, a member is expressing a direct pushback against the Newton comparison. We follow Chatham House rules, so we do not attribute perspectives without authorization.

Is the Vision Pro the next Newton or iPhone? I urge you not to take the bait and condense this product launch into a specious binary. The company that built and launched the Newton might share a name, but it has no relationship to the Apple that exists today. Let me put it bluntly: they might not have landed on a use-case yet, but Apple always wins.

It is possible that the experience of the Newton fundamentally changed how Apple operates because since that launch, Apple has never again been first to market with a product. This is because the first to market is statistically the worst option. The iPhone was not the first internet-powered mobile phone. The Apple Watch was not the first smart watch. And the Apple Vision Pro is not the first headset device. I think we can all agree that those products are doing quite well. The Apple Watch is outselling all other watches in the world and the iPhone, well, it also succeeded.

If we are going to do a comparison, then we have to look to more recent Apple history. The Apple Watch and Apple TV are closer analogues. Both of those products and platforms launched without landing on a clear value-proposition and therefore with a longer adoption curve. They have the capital, brand, customer base, and time to figure these things out.

I’ll say it again: Apple always wins.

Apple Flubbed the Vision Pro Launch

Overheard at ON_Discourse

Lost opportunity

The launch of the Vision Pro made me miss Steve Jobs

From the editor: The initial skepticism of the Vision Pro prompted many of our members to question Apple’s marketing strategy. Here is a collection of takes from a member at a recent virtual event who scrutinized the potential of this contentious product. We follow Chatham House rules, so we do not attribute perspectives without authorization.

Something struck me about the launch of the Apple Vision Pro. The whole process felt flat as if Apple was releasing a minor upgrade to an existing unit and not a revolutionary new piece of hardware. This was released more like the original Apple Watch, as if it were a fashion accessory that augmented the iPhone. It made me realize that this is the first major hardware release in the post-Jobs era. Does this explain the flat release? Is Apple any good at launching revolutionary products anymore? Does it matter?

Steve Jobs always marketed around clear and accessible customer use cases. When I saw “1000 songs in your pocket”, I immediately got the iPod (conceptually and commercially). The same can be said about the iPhone; this single device combined the iPod, phone, and mobile web. Additionally, the deliberately designed white phone contrasted mightily against the all-black devices that dominated the sector. Early adopters signaled their association with the Apple brand just by walking around. The little white brick made them look cool, which made other people want to buy one. The Vision Pro does not offer any of those benefits.

I’ve noticed that Apple has in-housed the marketing for the Vision Pro. This has resulted in unflattering 3D renders of the device with ineffective demonstrations of use cases. As a result, they haven’t made me want to buy one and I spend a lot of money on random shit I don’t need. 

The marketing was a flub, but this is still Apple and I fully expect future releases of the Vision Pro to go mainstream. Nevertheless, we are witnessing a fascinating new kind of computing experience get released without any imagination or spark. It’s disappointing and will result in a longer arc on the inevitable adoption curve.

XR will now forever be known as Spatial

This was no flub. Apple’s launch defined a new product category from scratch.

From the editor: We shared the critiques of Apple’s marketing with another member who has spent decades marketing with Apple. It turns out there are alternative ways to interpret Apple’s marketing strategy. We follow Chatham House rules, so we do not attribute perspectives without authorization.

Apple crushed the Vision Pro launch and I can prove it. The fact that we’re all using the word Spatial is the only evidence I need to prove that Apple is, once again, leading the conversation about new technology. No matter how big Apple gets and how premium its prices are, it will always be a challenger brand. In this case, Apple challenged and redefined the very nature of immersive video.

Apple deliberately avoided calling the Vision Pro an XR device, and as expected, the world followed. To call this device XR would follow the conventions set by the Meta Quest. Look at its marketing page: this device is built for video games. It is a toy. Apple had bigger intentions.

Apple positioned the Vision Pro around spatial experiences. This is a new concept that has yet to define a specific use case. Spatial tech can facilitate premium remote work experiences. It can catalyze exclusive new immersive video formats. It can also power a new kind of emotional content format: a sort of living memory. In its product launch, we saw Apple create an opportunity rather than box itself in as a video game player.

The idea that Apple hasn’t specified a use case is not the flaw you think it is; it is more of a flex. Apple has the resources, capital, and capability to launch this product and then figure it out. In your argument, you referred to the Apple Watch and how it was originally marketed as a fashion accessory. That is a fair point, but it is deliberately missing the coda. The initial product launch focused on fashion until health tech took over. Once that use case became clear to Apple, they marketed heavily around that. As a result, this Apple Watch is now the biggest-selling watch on the planet. To put it another way: Apple always figures it out.

In the end, Apple always wins.

Four Things Spatial Needs to Become Legitimate

Overheard at ON_Discourse

Free advice

The potential of spatial video is meaningless without scale

From the editor: Many of our members are excited by the Vision Pro. They are not deterred by the flawed form factor at all, and are instead focusing on the use-cases. One of our members recently laid out a roadmap for growth that has nothing to do with hardware fixes. This is a Chatham House recreation of a member’s perspective.

This post was written by a human and narrated by an AI-generated voice. (powered by Wondercraft.ai).

0:00 / 0:00

The Vision pro is ugly and expensive and buggy and it is going to make the internet way more interesting. The biggest challenge that this product faces is not the shitty keyboard experience or the weight on your face, nor is it the weird battery pack; it is the lack of scale. The Vision Pro needs scale to meet its destiny. Here are four steps that can catapult this product into the mainstream.

1

Subsidize Cost / Reinforce Use-Case

Find a partner that can subsidize the ridiculous retail price. Apple already gets credit for pioneering this strategy to make the iPhone more accessible to customers. The Vision Pro can partner with entertainment providers (Netflix?) or remote work platforms (Zoom?) to make it easier to access this device. The right partner not only reduces the price but it also reinforces the use-cases for this device. Netflix as a partner could pair this device with a new premium spatial video offering that includes exclusive access to this new content. Additionally, if Zoom were a partner, you can imagine remote work getting a significant boost.

2

Elevate Remote Work into a Premium Experience

Speaking of remote work: the Meta Quest made a half-hearted attempt to capture remote work demand but failed. It is inconceivable that professional employees would want to work in a cartoonishly designed metaverse. 


Meta’s failure leaves an untapped white-space in the world of remote work. Zoom interfaces and Slack channels have not noticeably improved since the pandemic. As a result we are seeing more companies try to force employees back into the office. Despite all of this, remote work is not going away. The Vision Pro has the opportunity to enable premium collaborative experiences by converting a pen on a desk into a virtual object that can legibly draw on a digital whiteboard. Eventually the economics of this experience are going to drive mass adoption. As AI continues to rapidly diminish headcounts and management structure, employers will start to consider how much money an office, a desk, a chair costs compared to this device.

3

Leverage Mass Cultural Phenomena

The Vision Pro is driving a new kind of AV format that is undeniably riveting. Spatial video is not just a screen on your face; it is an emotional experience. The original Vision Pro includes a spatial video of Alicia Keys in the studio and it is an absolutely mesmerizing experience. The viewer is no longer a viewer, but a participant in an intimate setting with the musician. You are next to her at the piano, feeling her presence as you are hearing her perform. Alicia Keys is a magnificent star, but imagine this experience at a higher scale. If Alicia Keys has the star power of the sun, Taylor Swift is a galaxy. Her Eras Tour film already broke records in conventional theaters. What will her fans do if they can experience her presence with a fully immersive and personal movie theater experience? What if this experience is offered to die-hard football fans or NBA fans? How much would they pay for premium access to courtside seats from their own couch?

4

Tap into the Allure of Adult Content

This point should not be taken as an endorsement of porn, just an acknowledgement of its power to persuade the population to upgrade their personal tech. The emotional, sensory experience of spatial video is going to be irresistible to many consumers with expendable income. The moments in between intimate viewing are going to drive these users to get more value out of their device than their late-night ribaldry.

For the Vision Pro, scale is not necessarily focused on revenue alone; it’s about culture. Scale converts our collective creativity into new ways to use technology to shape culture. The iPhone is an example of this: there are over 2 million apps in the app store, yet the average iPhone owner frequently uses only 9 apps. You need scale to test out and identify what those final 9 apps could be. The iPhone, after all, is the standard bearer for the modern mobile experience. The Vision Pro has the potential to define the same thing for XR.

This product is going to change the way people consume media which will influence the way media is created. We should all be excited about this future. I have seen what the first Vision Pro can do – bugs and all – and I am still so fucking excited.

AI

is

not

a

new

revolution

Food for thought

It is tempting to think of AI as novel technology that emerged very recently

Overheard at ON_Discourse

From the editor: One of our most credentialed AI experts shared some essential perspectives for companies betting on AI. This speaker has a PhD in Brain and Cognitive Sciences, and has been working on machine learning models for over 15 years. As always, ON_Discourse operates under the Chatham House Rule—no attribution of perspectives without explicit consent.

AI is not magical. It is not new. And the recent surge in attention is not the result of an unexpected advancement in generative software.

The dominant media story about AI is that OpenAI achieved a major technological breakthrough sometime in 2022. This breakthrough unlocked new ways consumers can prompt with models to receive shockingly relevant generative output. In other words, before 2022, the generative systems were still largely theoretical. Nope.

The ability to prompt with generative models has been around for more than a decade. Prior to 2022, researchers in cognitive and brain sciences (not computer science, by the way) were interacting with models as seen on ChatGPT. They did not call this functionality artificial intelligence – it had always been called machine learning, a more accurate representation of the underlying tech.

So what happened? If the software didn’t change, why are we treating AI as a groundbreaking technological revolution? The short answers are that the hardware (the GPU chips) got faster and OpenAI put it all online. In other words: the hardware got faster and the UI made it accessible. 

Everything else that happened is hype.

AI researchers are constantly building models, trying something new, and incrementing the version number. Nevertheless, we have to put things into perspective before the hype takes over. This is the reality: no AI model can suddenly build a rocket from scratch or do anything it couldn’t do before. The headlines brag about it getting a 95 on one benchmark, and ignore the fact that the previous model got a 92. It is all a progression.

The headlines brag about it getting a 95 on one benchmark, and ignore the fact that the previous model got a 92.

The technology is undeniably amazing but the amount of hype around their improvements hasn’t been proportional. The only major innovation is how they made their AI models available to the masses. The technology that’s under the hood remains the same.
  
Companies looking to innovate shouldn’t bother with generative AI models. Innovation in areas like quantum computing, neuromorphic computing, and low-temperature semiconductors is much more likely to bring about the next wave of AI than hiring a bunch of Stanford Computer Science PhDs.

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

Your brand does
not have enough
data for AI

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

From the editor: One of our most credentialed AI experts shared some essential perspectives for companies betting on AI. This speaker has a PhD in Brain and Cognitive Sciences, and has been working on machine learning models for over 15 years. As always, ON_Discourse operates under the Chatham House Rule—no attribution of perspectives without explicit consent.

You need an
enormous amount

This is one of the AI era’s most
under-appreciated assumptions.

In the AI era, everyone seems to have convinced themselves that their company has the best data. You likely believe that not only is your data just the best, but it also happens to be just so unique that the resulting AI model is going to supercharge your whole business.

This is wrong, for two reasons:

  1. You have too little data. You need billions or even trillions of heterogeneous observations to be able to do anything interesting with AI. There are only a handful of companies today that possess that quantity.
  2. Your data is of poor quality. Even most large enterprises do not have a dataset rich enough to make a meaningful AI play. They rely on buying data from multiple sources or stealing it from internet users under the guise of fair use.

Many companies are opting for a shortcut into AI. Any company today can implement base GPT models. That works for experimentation, but it won’t drive revenue or improve efficiency. Why? AI is not trustworthy. You need to hire experienced teams to manage its bad behaviors.

For almost every single company, trying to build something bespoke that will move the needle is simply not worth the investment.

Your brand does
not have enough
data for AI

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

From the editor: One of our most credentialed AI experts shared some essential perspectives for companies betting on AI. This speaker has a PhD in Brain and Cognitive Sciences, and has been working on machine learning models for over 15 years. As always, ON_Discourse operates under the Chatham House Rule—no attribution of perspectives without explicit consent.

You need an
enormous amount

This is one of the AI era’s most
under-appreciated assumptions.

In the AI era, everyone seems to have convinced themselves that their company has the best data. You likely believe that not only is your data just the best, but it also happens to be just so unique that the resulting AI model is going to supercharge your whole business.

This is wrong, for two reasons:

  1. You have too little data. You need billions or even trillions of heterogeneous observations to be able to do anything interesting with AI. There are only a handful of companies today that possess that quantity.
  2. Your data is of poor quality. Even most large enterprises do not have a dataset rich enough to make a meaningful AI play. They rely on buying data from multiple sources or stealing it from internet users under the guise of fair use.

Many companies are opting for a shortcut into AI. Any company today can implement base GPT models. That works for experimentation, but it won’t drive revenue or improve efficiency. Why? AI is not trustworthy. You need to hire experienced teams to manage its bad behaviors.

For almost every single company, trying to build something bespoke that will move the needle is simply not worth the investment.

Augmented

Intelligence:

from

UX to HX

Craig Elimeliah
Chief Creative Officer, Code and Theory

Editor’s note: ON_Discourse co-founder Dan Gardner argues that human behavior is the ultimate prompt. This article explores what this means for user interface design.

Augmented Intelligence (AI) is becoming an everyday reality, fundamentally transforming how we interact with our world. Its primary driver is human behavior, the main “prompt” for AI development and application.

This shift challenges us to reconsider the role of AI in our lives, focusing on how it shapes and responds to human actions and decisions. I believe this evolution will be marked by a transition from User Experience (UX) to Human Experience (HX), wherein technological innovation emphasizes, rather than obscures, humanity’s essence.

This is a critical moment. We are at the forefront of a design renaissance, wherein our focus is shifting from mere interfaces to meaningful interactions, from digital screens to the human psyche. Transitioning from UX to HX signals a shift from interface-driven design to a more empathetic, behavior-centric approach.

We are at the forefront of a design renaissance, wherein our focus is shifting from mere interfaces to meaningful interactions, from digital screens to the human psyche.

In this new age, technology will become more than a tool. We won’t just be using AI algorithms and automation, we will be building a symbiotic relationship that marries AI’s analytical strengths with human intuition and insights.

While such a synergy can accelerate and amplify our abilities, it also brings forth a critical challenge: ensuring that AI augments human creativity and intuition without overshadowing them. We must not overlook the ethical implications of an AI-driven HX. Personalization in AI, while beneficial, raises privacy concerns. We must grapple with these ethical challenges head-on, ensuring that AI’s incursion into our lives respects our privacy and adheres to ethical standards.

One of the assumptions in our AI-driven journey is the belief that AI can fully understand and replicate the depth of human emotions and behaviors. Here lies a potential pitfall. We must strike a balance between leveraging AI’s capabilities and preserving human intuition and ethics in design.

For HX to work, I envision AI transcending traditional data analysis to offer a nuanced understanding of human emotions and behaviors. Imagine a customer service chatbot that can detect frustration in a conversation and respond with empathy, or e-commerce AI that suggests products based on emotional cues.

This article is part of The Intelligently Artificial Issue, which combines two big stories in consumer tech: AI and CES.

Read more from the issue:

USER EXPERIENCE

Augmented Intelligence: from UX to HX

Will prompting replace browsing?

The car is the gateway drug to a voice-first acceleration

The prompt interface needs a redesign

RE-ORG

AI will brainstorm your next reorg

Expect fewer managers and direct-reports

AI is too immature for your business

AI is not a new revolution

BRAND

Should we ignore the hardware?

Can AI help consumers love your brand?

Your brand doesn't have enough data for AI

Can LLMs be optimized like search results?

Good brands will integrate more friction into their CX

In health care, AI could evolve to support doctors by providing data-driven insights while preserving the irreplaceable human element in diagnosis and patient care. In education, AI could adapt to students' emotional states, offering personalized encouragement and learning paths.

These scenarios underscore the shift towards ethical AI design, where algorithms must be crafted with diverse datasets and regularly audited to prevent biases, ensuring fairness and inclusivity. 

The AI era must also be characterized by transparency, with companies openly disclosing how their AI technology uses consumer data, thereby fostering trust. AI in smart homes, for example, should recognize and respect individuals' privacy preferences, ensuring that family boundaries are maintained.

As human behavior becomes the new prompt, it will become clear that the role of HX is not just to understand, but to respect and enhance human actions and emotions. The future will not be determined just by the sophistication of experiences that AI can create, but by how these experiences honor and elevate our humanity.