Spencer
Dinwiddie

Spencer Dinwiddie
NBA Athlete and Entrepreneur

The first line of my bio reads "NBA player," but I always tell people I’m a tech guy with a jumper. My fascination with emerging technology was the prime motivating factor for co-founding Calaxy, a new platform empowering Creators to connect with their fans and monetize their brands easier than ever before.

That fascination with new tech is also why I jumped at the opportunity to invest in Genies and explore the worlds of AI, blockchain, and virtual and augmented realities.

Recently I fell down a rabbit hole thinking about the advent potential of AI-generated avatars and conversational bots and how they might be able to help revolutionize fan interaction.

Before this technological era, a person couldn’t be in two places at once or appear to come back from the dead. But this technology — which seemed so novel and impossible to fathom — is now right at our fingertips.

The application of AI-generated avatars seems obvious, now. It could allow me — or anyone else that has so many demands on their time that they have to say no to things they’d like to be doing — to work in new ways. I could take video footage, photos of myself, words I’ve authored, and other content I’ve generated and use these materials to help train AI models in the hopes that they can extrapolate my personality and then appear and interact on my behalf, sort of like digital clones who works for me.

Surveys the

Anyone can see the benefits of this. People who want to interact with me but otherwise wouldn’t have that access are suddenly able to. And from my end, I’m able to say yes to things that otherwise wouldn’t have fit into my schedule.

It’s a game-changer.

And because AI models can evolve, digital representations of my personality could learn and grow over time.

This digital version of me would also be more knowledgeable about the world because it would be digesting information at a rate impossible for humans to keep up with. So it would pretty quickly become a smarter and wittier version of myself, if that’s something you can imagine.

But, AI-generated avatars could have some potentially terrifying results as well. With this tech, deep fakes are a real concern, especially as the line between what’s real and what isn’t gets blurrier and blurrier over time. And what happens if my AI-generated avatar is interacting with a fan and says something horrible? The backlash for those words or actions will land at my feet and impact my brand, not some AI-generated version of me. The avatar doesn’t have a reputation to worry about, but I do.

We need to figure out how to use this technology responsibly and ethically.”

AI Opportunity

There is some suggestion that blockchains and other immutable technologies could potentially help mitigate some of these concerns because they can ensure credibility and verify the authenticity of content, but we’re not going to be able to put the genie back in the bottle, no pun intended.

Another challenge is the lack of regulatory clarity. AI is advancing so quickly that it’s tough to keep up with the rules. We need to figure out how to use this technology responsibly and ethically. It’s a learning process, and we have to be careful not to cross any boundaries that we’ll regret later.

And let’s not forget the bigger picture. AI, if not properly controlled, could become a serious threat to humanity. We’ve all seen the Terminator movies and I’m not trying to be John Connor, so we’re going to need to be cautious and establish safeguards to prevent any unintended consequences. We don’t want to unleash something that we can’t handle.

We just have to remember that we’re still in the early stages of generative AI. If this were a basketball game, there’d be 20 seconds left on the shot clock of the first possession of the first quarter. There’s a ton of game left to play and we’re just scratching the surface of what this technology will ultimately do. It’s an exciting time, but we need to approach it with an open mind. We’ll learn as we go, and it’s important to keep evaluating, adapting, and having conversations about the best ways to use this technology…like enabling me to be swimming at the beach in Cannes and on-stage delivering a keynote address simultaneously.

Do you agree with this?
Do you disagree or have a completely different perspective?
We’d love to know

AI Goldmines and Landmines

Did Tom Brady Really Say That?

Tony Iliakostas
Adjunct professor of Entertainment Law and Intellectual Property at New York Law School

The innovation of generative AI opens the door wide open to sparking creativity and ideas. As it pertains to the sports industry, generative AI presents a plethora of great opportunities. However, there are more questions than answers concerning artificial intelligence and its place in the legal field.

and

Is AI a Goldmine or a Landmine For Athlete Brands?

Toby Daniels
Co Founder On_Discourse

This new age might be a goldmine for athletes, but they’ll have to avoid the landmines first.

AI’s potential role in enhancing personal branding in sports cannot be overstated.

Is AI a Goldmine

or a Landmine

For Athlete

Brands?

Toby Daniels
Co founder ON_Discourse

You're a sports fan in 2028.

You log into your fitness app and a chat pops up -- it’s an AI workout assistant that looks and talks like your favorite NBA star. You input your training goals for this week and get back a personalized diet and training plan based on your needs.

You pop on your VR headset and fire up Madden 2028 -- you scroll through a roster of thousands of hyper-realistic AI-generated players from throughout time and create your team. You head onto the field.


Later, you turn on SportsCenter and watch as Stephen A. Smith debates an AI-generated young Charles Barkley. They’re arguing over who’s wearing the sharper suit, which you can buy using your Apple Cash directly from your headset.

AI – with its seemingly endless ability to create, analyze, and mimic – is transforming industries at a breakneck pace. Athletes are uniquely positioned to capitalize on this tech to reimagine sports branding. 

Athletes, bound by the constraints of time and resources, now have the potential to leverage their likeness and scale their brands in innovative ways to engage fans.

AI also poses considerable risk. It’s uncharted territory with pitfalls that range from unauthorized deepfakes to AI-generated communication that fans find inauthentic.

This new age might be a goldmine for athletes, but they’ll have to avoid the landmines first.

AI’s potential role in enhancing personal branding in sports cannot be overstated.

Already, AI-driven analytics can synthesize vast amounts of data about fans' behaviors and preferences, allowing athletes to tailor their brands to better target individuals. 

Personalized fan experiences, from AI-curated content to virtual meet-and-greets, are poised to redefine the fan-athlete dynamic, creating a stronger and more direct connection. Generative AI models could be trained to replicate an athlete’s voice and tone. These models could then be used to create unique content in the style of the athlete, which could then be targeted at fans who are most interested in the topic. 

The economies of scale enabled by automation, including aspects of content creation, also enable athletes with smaller followings to boost their brands and reach more fans. This shifts the power dynamics within the sports industry, placing control back into the hands of the athletes.

But these tools are not without risk; there is also the potential for AI to erode the value of an athlete’s brand. Automated content, while efficient, lacks the genuine human touch and authenticity that fans often seek. The uniformity resulting from AI processes might also lead to diluted brand identity, reducing differentiation and competitive edge.

Equally, the potential for misuse is significant.”

Deepfakes, AI-manipulated images or videos that often appear authentic, present a risk even today. As the technology improves – and the ease of creating convincing synthetic media rapidly increases – public figures will have to reckon with the potential consequences of false narratives being planted by fake versions of themselves. The current legal framework, predominantly designed for a pre-AI era, struggles to tackle these novel challenges.

Image rights, the linchpin of an athlete’s brand, face an unprecedented threat with the advent of AI. The ability of AI to create lifelike digital personas of athletes, and use them in a myriad of contexts, raises complex issues surrounding consent and ownership. An entirely new framework for licensing athlete likenesses – and for objecting to the use of unlicensed, AI-generated likenesses – is needed. 

The Threat to Brand Ownership and Authenticity

Need for Regulation

Contracts and the legal framework need to evolve to address the challenges posed by AI, protecting athletes' image rights and preventing misuse. Transparency and ethical considerations must guide the deployment of AI in sports branding, ensuring it enhances rather than detracts from the athlete’s brand value.

The emerging age of AI offers a wealth of opportunity and a chance to redefine the athlete-fan relationship. In the delicate balance between scaling and protecting an athlete’s brand, AI represents both a goldmine and a landmine. As we chart this new terrain, the challenge lies in unlocking the promise of AI while safeguarding against its perils.

Are these fears going to stifle creativity, innovation, and commercial growth? Humans have proven themselves eager to jump at hyped, if unproven tech, that promises financial gain. Just look at crypto! Will athletes fall into the same trap and pivot too quickly to using AI to redefine their personal brands? Maybe? Probably. 

Do you agree with this?
Do you disagree or have a completely different perspective?
We’d love to know

AI Goldmines and Landmines

An NBA Player Surveys the AI Opportunity

Spencer Dinwiddie
NBA Athlete and Entrepreneur

Recently I fell down a rabbit hole thinking about the advent potential of AI-generated avatars and conversational bots and how they might be able to help revolutionize fan interaction.

Before this technological era, a person couldn’t be in two places at once or appear to come back from the dead. But this technology — which seemed so novel and impossible to fathom — is now right at our fingertips.

and

Did Tom Brady Really Say That?

Tony Iliakostas
Adjunct professor of Entertainment Law and Intellectual Property at New York Law School

Athletes, bound by the constraints of time and resources, now have the potential to leverage their likeness and scale their brands in innovative ways to engage fan.

But AI also poses considerable risk. It’s uncharted territory with pitfalls that range from unauthorized deepfakes to AI-generated communication that fans find inauthentic.

Do You

Want to

Change

Your

MIND?

Dan Gardner
Co-Founder & Exec Chair, Code and Theory
Co-Founder, ON_Discourse

When was the last time you felt like you had your mind changed?”

When you engaged in a discussion with someone you respect and who has the experience to speak knowledgeably about a topic but had a completely different point of view than your own?

Imagine a space where you would find yourself thinking differently about the most important decisions you make.

As the founder and chairman of a creative and technology-driven consulting business with almost 2,000 employees, I think creating space to be challenged and to be able to challenge others' perspectives is essential to business success.

So why a member’s media company?

We believe “discourse” has become a bad word in media. In practice, it’s been used as a form of trolling or to express negativity around someone’s opinion, instead of embracing curiosity about a different opinion and understanding that can help make more informed decisions. A trusted space to publish and engage in conversation with those who value discourse is essential to what business leaders need.

We believe that the world of business and technology today is filled with fake experts, often confusing the narrative and, ultimately, decision-making. At ON_Discourse, we bring together practitioners to share perspectives about the work they do day in and day out. They share an understanding that only comes from being on the frontlines of technology. And these people also possess the humility to admit what they know and don’t know. 

We believe a members-only media company relieves us of the problem of prioritizing the wrong KPIs that often plague modern media companies. We don’t want to be focused on the volume of content, clickbait, or a NASCAR-style approach to ads on a page. This economic model allows us to focus on the value of our mission.

ON_Discourse launch event "A Symphony of Disruption" at Fotografiska in New York City

We will provide content that makes you question and helps inform action. We avoid predictable platitudes, the 100th similar take that’s already been written about the latest hot topic, self-help, or motivational essays. 

Whenever we publish something or host a live discussion, we ask ourselves how the content will provide decision-makers, with busy schedules and mission-critical projects, with information that they can use to go directly into meetings and negotiations feeling informed and a step ahead.

These are

our Values

  • Curiosity to go Deeper: We know that very few things are worthy of your time. We publish high-quality, high-impact work that elevates public discourse and provides our readers with unique insights. Volume is not our focus, value and quality are.
  • Diversity of Perspective: We champion intellectual honesty and the courage to acknowledge our own limitations in the pursuit of knowledge. We help our community challenge conventional thinking.
  • Empathy to Opposing Ideas: It's important that we're not pandering to our members and are open and honest in our approach to the subjects we cover. We should operate without fear or favor in analyzing and criticizing the issues we address. There can often be a "circle the wagons" approach in the technology space that we should avoid being part of. 
  • Disagreement is Encouraged: In order to offer true value, we need to be free of pressure from members or potential partners. We should be respectful and thoughtful in our approach. Challenge ideas, not people specifically. We expect that from our contributors as well.

We will deliver value through exclusive access to our digital content and exciting and engaging in-person events and experiences. We will bring together the best minds from the top levels of business and create opportunities for real discourse.

That’s the mission of ON_Discourse.

We’re excited to begin this journey with you.

You can explore our articles through our home page.
If you haven’t yet applied for membership you can do so here.

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Discourse

Sorry, Everybody Can't Be a Director

Dan Gardner
Co-Founder & Exec Chair,
Code and Theory
Co-Founder, ON_Discourse
or
The Shift from Knowledge
Work to Direction Work
Toby Daniels
Founder, ON_Discourse, former Chief Innovation Officer, Adweek, Founder and Chair, Social Media Week

INT. MODERN CONDO - MORNING

It’s 2027, but it looks like today. ANTHONY gets out of bed and sits in front of his COMPUTER–

This is no ordinary computer; there is no interface, no folders, no zoom calls, and no meetings needed. He’s staring at his one sole text field called ‘the prompt box.’ He says to himself –

“Get to work”

Anthony starts to submit directional commands.  Prompt after prompt. He gets a sense of fulfillment knowing the robot will do his every command. 

THEN the Camera pulls out of the window of the 

EXT. CONDO BUILDING

Moving further and further away, we reveal even MORE CONDO BUILDINGS. Inside, we see OTHER PEOPLE sitting in front of their computers with the prompt box.

The Camera flies back into

INT. MODERN CONDO

The camera flies all the way inside to a close-up of Anthony’s face. He turns to look into the next room. His wife PAM is sitting at her prompt box doing the exact same thing. It looks like she’s talking to herself.

ANTHONY

Pam! Luckily we changed our majors in college back in 2023. We are now so prepared for this prompt box. Johnny and Michelle must be screwed!

Anthony commands his BARD and audio via voice application.

ANTHONY

Hey Bard, play today’s interesting business stories.

We hear a familiar voice… It sounds like SNOOP DOGG.

SNOOP DOGG

New study says…

But we quickly realize that this is not Snoop, but rather a DEEP FAKE –

SNOOP DOGG

…millions of jobs were saved by the early predictions of jobs shifting from  “knowledge workers” to “direction workers”

Another deep fake voice chimes in. This time it’s Al Pacino –

AL PACINO

Yes, It’s amazing how knowledge is not important anymore, but unfortunately, companies still can’t hire enough direction workers and it’s causing salaries to increase at a rapid pace

The rapid ascent of generative AI, automation, and technologies that boost creative output has caused speculation and fear that we’re on the precipice of a massive industry shift away from knowledge workers. The breakneck pace of change has young people wondering how to best prepare themselves for an unpredictable world – Should I study computer science? Is coding obsolete? – and employers grasping for how to hire for the skillsets of the future.

My answer is, Don't be so dramatic.

The rate of advancement in generative AI is so extreme that we are all trying to understand real-time the implications and guess what the ripple effects might be. It’s given everyone in every single industry collective whiplash. 

And it’s resulted in over-the-top projections and calls for overcorrections, like a total shift in how we approach educating the future workforce and hiring for skills necessary for success. But both traditional knowledge workers and “direction workers”-- those who direct and instruct the technologies of the future – will always be necessary. Creativity and success aren’t possible without both.

To clarify what I mean by “direction workers,” I’m referring to managers who not only lead teams but also primarily direct or instruct humans or technologies in various, often creative, outputs and tasks. If creative work is nearly wholly produced by generative AI, the story goes, those creative “doer” jobs will disappear in favor of jobs directing the tech.

Video Killed the Radio Star”

— The Buggles

But before we write off creativity and knowledge workers as superfluous, remember this is not our first industrial revolution — in fact, it’s one of many. So it’s essential to have some perspective on where we’ve been, where we are presently, and where we’re heading as a society. In every instance in the past where we saw dramatic changes in manufacturing, technology, and behaviors, one thing remained constant: passion, drive, creativity, and knowledge are the elements that drive innovation.

There are still thriving musical artists despite the advent of MTV. And music artists AND music videos are still thriving despite the advent of YouTube. Then there were still those artists, and record labels, despite the advent of MP3s, and so on, and so on.  Did job types reshuffle because of new processes,  business, and distribution models? Of course. But the industry didn’t vanish – it just evolved. Old jobs were gone, and new jobs were created.

Education is what remains after one has forgotten what one has learned in school.”

—Albert Einstein

It is not a new concept to suggest our educational system is outdated.  The emergence of AI may have shined a spotlight on this fact, but it sure isn’t the cause. We have basically had the same classroom teaching style for the last century, despite all that has changed around us.

The traditional education system has long emphasized memorization and rote learning, which is ineffective in a world where information is readily available at our fingertips. Students are often taught to regurgitate facts rather than develop critical thinking skills, problem-solving abilities, and adaptability — all of which are crucial no matter which discipline you choose. 

An updated education system should embrace interdisciplinary approaches, encouraging students to explore the intersections of different fields. This will enable them to connect the dots and develop a holistic understanding of complex issues, fostering innovation and adaptability regardless of where AI takes us. Hypothesizing on where AI is going in order to inform your educational choices today is ridiculous and should not be the point of education. 

A small reminder that if you’re 40-something years old or older, you somehow went through all of high school without a computer as a primary focus, and even in your college days, the computer offerings were likely rudimentary at best. And yet many have gone on to have long-standing careers focused on the web, mobile computing, and social media. How was that possible if they didn’t teach it in the ‘90s?

The greater danger for most of us lies not in setting our aim too high and falling short, but in setting our aim too low and achieving our mark.”

—Michaelangelo

Another issue with the push for AI and automation tech is that so many voices chiming in on this topic are overly fixated on the merits of staff reduction based on the output possible from artificial intelligence. Voices are asking, “Why does my business need ten people when I can have five people, or maybe better, just one person doing the job of the whole department?”

But if you and your competition are so intent on reduction, where does differentiation start? It doesn’t matter whether you majored in art or in engineering — we’re all aware that multiplication builds, while subtraction takes away. 

So if one company is multiplying and the other is subtracting, who may have the better outcome? What are companies adding to the discussion, the organization, and the culture at large, when they’re so focused on reduction? 

We are at a pivotal moment right now. That is undeniable. 

Everybody, across every level of an organization, is going to work with AI in the future, the same way the computer is essential today. Yes, some jobs will go away, while new ones are created. However, the types of careers that will emerge as a result of AI will differ from the ones that are being displaced. 

or
The Shift from Knowledge
Work to Direction Work
Toby Daniels
Founder, ON_Discourse, former Chief Innovation Officer, Adweek, Founder and Chair, Social Media Week

Nevertheless, occupations that rely on human skills such as problem-solving, creativity, and empathy are less susceptible to being replaced by machines in the immediate future. As AI continues to advance, these roles will also probably experience some impact. The encouraging aspect is that AI will augment, and potentially multiply the value and output of,  these occupations, propelling problem-solving, creativity, and empathy to unprecedented levels and generating fresh opportunities like never before.

If you take the implication of direction work to its most extreme conclusion, you can imagine the story above playing out where tens of millions of white-collar workers are all sitting in front of their computers, much like today. And, as the story goes, with these computers having just that one field. And the direction worker’s job is just to keep telling some artificial intelligence what to do: And now, computer, write this. Now, computer, create this – on and on. That’s a preposterous idea because there’s simply not enough direction that will be needed for that to happen. 

Do you agree with this?
Do you disagree or have a completely different perspective?
We’d love to know

ON_AI

Media Companies Shouldn’t Reject Generative AI
Disclosing the use of AI in reporting: It’s Futile
Against AI Art
Good Artists Copy, Great AIs Steal
How Artists Turn AI Into Gold
A Brush with AI: The Copyright Fight For Digital Creativity
Will AI Enhance or Destroy the Business of Media – Event Recap
AI is Not a Public Utility
Big Tech Should Not Get Bigger
Should Bored Apes be in charge of AI?
Intellectual Property Law and AI: The Future of Athlete Branding
Did Tom Brady Really Say That?
An NBA Player Surveys the AI Opportunity
AI: A Goldmine or a Landmine For Athlete Brands?
Sorry, Everybody Can’t Be a Director
AI Doomerism is a Business Tactic
Startups Built on the ChatGPT API Are Taking a Huge Risk
The Open Source AI Revolution

AI

Doomerism

is a

Business

Tactic

Anthony DeRosa
Head of Content and Product,
ON_Discourse


Recent warnings from tech leaders that AI could lead to the extinction of humanity have raised eyebrows and reminded me of rhetoric that supports the US military-industrial complex. The apocalyptic scenarios put forth by AI industry titans like Sam Altman may be giving birth to an “AI-industrial complex,” driven by hyperbole rather than a rational evaluation of AI’s potential destructive power.

A Familiar Narrative

The parallels between the AI extinction talk and the fear-mongering that powers the military-industrial complex are striking. The military-industrial complex refers to the close relationship between the defense industry, the military, and the government. It suggests that these entities have a vested interest in perpetuating a state of war or the fear of external threats in order to maintain their power and profitability. By exaggerating or fabricating dangers, those in the military or defense industry can justify increased military spending, weapon development, and the expansion of military influence.

Similarly, fear-mongering about the risks of AI may amplify or embellish the potential danger of the technology. While it is important to acknowledge and address the ethical and safety concerns surrounding AI, over-the-top speculation can lead to exaggerated narratives that overshadow its potential benefits and hinder progress in the field. It can also shape public opinion and policy decisions, potentially resulting in restrictive regulations or unnecessary limitations on AI development.

The Emergence of an “AI-Industrial Complex”

The concept of an AI-industrial complex refers to the amalgamation of influential entities, including corporations, government agencies, and media outlets, that profit from fear and exaggeration surrounding AI’s potential dangers. This complex capitalizes on the public’s fascination with doomsday scenarios and, ironically, fuels the demand for AI-related products, services, and research by depicting these technologies as all-powerful.

The calls for regulation in the face of this supposedly extinction-level threat are hollow. Regulatory oversight often favors incumbents who can leverage their money and power to push for oversight that is more favorable to them, so it makes sense that many giants in the AI space are now calling for legislators to take a closer look. 

It’s imperative to question the motivations behind such rhetoric and consider whether it serves the best interests of society or simply acts as a vehicle for self-interest.

Discover more
Discourse

Fostering a Balanced Dialogue

The dangers of AI should not be disregarded, as responsible discussions around ethics, privacy, job displacement, and algorithmic bias are crucial. However, it is equally important to maintain a balanced dialogue that separates legitimate concerns from alarmist speculation. Painting all AI advancements with a broad brush of impending doom stifles innovation and instills unnecessary fear in the public.

To avoid falling into the trap of an
AI-industrial complex, we must encourage critical thinking, evidence-based analysis, and multidisciplinary collaborations. Thought leaders, policymakers, and the media should prioritize objective assessments of AI’s risks and benefits.

Drawing parallels between the AI extinction talk and the military-industrial complex should serve as a reminder to exercise caution and skepticism in the face of hyperbolic scenarios. In both cases, there is a potential for vested interests to exploit and manipulate public fear for their own gain. The military-industrial complex thrives on the perpetuation of fear to maintain its influence, while fear-mongering about AI risks can serve the interests of individuals or organizations seeking to control or shape the development of AI technologies and their regulation.

By drawing this parallel, we can recognize the potential for fear-based narratives to shape public opinion and policy decisions in both the military-industrial complex and the AI domain. It highlights the importance of critical thinking, transparency, and ethical considerations in navigating these complex issues.

Do you agree with this?
Do you disagree or have a completely different perspective?
We’d love to know

MORE
ON_AI

Media Companies Shouldn’t Reject Generative AI
Disclosing the use of AI in reporting: It’s Futile
Against AI Art
Good Artists Copy, Great AIs Steal
How Artists Turn AI Into Gold
A Brush with AI: The Copyright Fight For Digital Creativity
Will AI Enhance or Destroy the Business of Media – Event Recap
AI is Not a Public Utility
Big Tech Should Not Get Bigger
Should Bored Apes be in charge of AI?
Intellectual Property Law and AI: The Future of Athlete Branding
Did Tom Brady Really Say That?
An NBA Player Surveys the AI Opportunity
AI: A Goldmine or a Landmine For Athlete Brands?
Sorry, Everybody Can’t Be a Director
AI Doomerism is a Business Tactic
Startups Built on the ChatGPT API Are Taking a Huge Risk
The Open Source AI Revolution
AI is not a new revolution
Can LLMs be optimized like search results?
Good brands will integrate more friction into their CX
AI is too immature for your business
Expect fewer managers and direct reports
Your brand does not have enough data for AI
Can AI help consumers love your brand?
The prompt interface needs a redesign
Augmented Intelligence: from UX to HX
Will prompting replace browsing?
Hey Siri, you suck. Love, cars
Early in the AI era, smart devices are still dumb Maze of people at CES
AI will brainstorm your next re-org
Are the businesses even asking the right AI questions?
Michael Nuñez
Editorial director of VentureBeat
Disclosing the use of AI in reporting:
It's Futile

Across newsrooms, journalists are grappling with an unstoppable force — generative AI tools that are quickly reshaping how stories are reported, written, and edited.

In an editorial memo to our staff, I recently shared my vision for using generative AI as a creative partner, not as a replacement for human judgment. But much is at stake amid this enormous swell of innovation.

Tools like ChatGPT, Bing Chat, and Google Bard represent a massive paradigm shift for our profession. These large language models, trained on humanity’s cumulative knowledge, have the potential to dramatically expand journalists' storytelling abilities and productivity.

But as we embrace these innovations, we also face a dilemma: How do we balance the benefits of AI with the core values of journalism? How do we ensure that our stories are accurate, fair, and ethical, while also taking advantage of the speed and efficiency of AI? How do we preserve the human element of journalism—the empathy and judgment that make our stories meaningful and trustworthy—while also leveraging the power and potential of AI?

These are some of the questions that we at VentureBeat are wrestling with every single day. As one of the leading authorities in AI news coverage, we are at the forefront of exploring and experimenting with generative AI technologies in journalism. We are also committed to sharing our insights and best practices with our peers and our audience.

At VentureBeat, we’ve created several guardrails for the use of AI in the newsroom. We allow our editors and reporters to use tools like ChatGPT, Claude, and Bing Chat to suggest article topics, story angles, and facts — but journalists are required to verify all information through traditional research. We do not publish articles solely written by AI models.

We’ve found that artificial intelligence can be regularly used in a few mission critical ways:

  • Story ideation: We often use tools like ChatGPT, Claude, and Bing Chat to brainstorm potential topics and angles for our stories, based on our areas of coverage and current trends. We also ask these tools to generate summaries, outlines, or questions for our stories, which help us structure our research and writing.
  • Headlines: We use tools like ChatGPT, Claude, and Bing Chat to generate attention-grabbing and informative headlines for our stories, based on the main takeaways and keywords. We also ask language models to suggest alternative headlines or variations, which help us optimize our headlines for SEO and social media.
  • Copyediting: We use tools like ChatGPT, Claude, and Bing Chat to proofread and edit first drafts of our articles, checking for grammar, spelling, style, and tone. We ask language models to rewrite sentences, paragraphs, or sections of our articles, to improve clarity, coherence, or creativity. Our human editors always review, edit and fact-check VentureBeat stories before publishing.
  • Research: We use AI to assist us with our research, by providing relevant facts, sources, quotes, or data for our stories. We also ask these tools to summarize or analyze information from various sources, such as web pages, reports, or social media.

By now, you might be wondering how we handle disclosures.

At VentureBeat, our policy is to disclose the use of AI only when it is relevant to the story or the reader’s understanding. Otherwise, we treat AI as any other tool that we use in our daily work, such as Microsoft Word, Google Search, or the grammar and word-choice suggestions made by Grammarly. We do not believe that singling out one tool over another adds any value for our readers. What matters are the core values of accuracy, objectivity, and ethical use of information that guide our craft — values that we uphold rigorously regardless of the technologies involved.

There is no one-size-fits-all solution for how to use AI in journalism. Each news organization has its own mission, vision, and standards that will guide its editorial decisions; each journalist has his or her own style, voice, and perspective that inform their storytelling; and each story has its own context, purpose, and audience that determine its format and tone.

But there are some principles that have been foundational to great journalism for centuries, and that will continue to be relevant in the age of AI. These principles can help us strike a balance between innovation and tradition and between automation and humanization.

or
Newsrooms Should Build
Their Own Generative AI
Matthieu Mingasson
Head of Design Transformation at Code and Theory

One principle is always reporting the truth. Our journalistic standards and values must be enhanced, not compromised by AI. 

That means that our stories must be factual, fair, and balanced. Any data used in a story — whether it’s surfaced by Google Search, GPT-4, or any other software available— must be verifiable. 

The use of large language models does raise some thorny questions about the data that powers the AI tools we’re using. As a journalist, I would, of course, like to know how the models are trained, what they can and cannot do, and what risks they pose.

We believe greater transparency into training datasets will be important as we forge ahead and confront this massive shift in the industry. Transparency in the datasets used to power LLMs will help us to understand how the models work, what assumptions they make, and what limitations they have. It will also help us monitor and audit the performance of models, to identify and correct any errors or biases, and ensure accountability and trust. We believe transparency in LLM research will be one of the defining issues of the year — and have covered it at length.

Another defining principle of how we use AI in the newsroom is accuracy.

We need to get the facts right. Without rigorously fact checking every detail, misinformation spreads. That means being careful and ethical about how and why we use AI in our reporting. Again, we do not rely on AI blindly or uncritically, but rather use it as a tool to augment our human skills and judgment.

For example, we recently wrote a story about how Amazon inadvertently revealed its plans to create an AI-powered chatbot for its online store. When we used ChatGPT to generate headlines for our story, it suggested inaccurate options that confused ChatGPT with a “hallucinated” (i.e. fabricated) conversational model that Amazon is trying to build in-house. It was just one of many examples we see on a daily basis that illustrates the need for human oversight and fact-checking when using such tools. Our final headline was written by a human: Amazon job listings hint at ChatGPT-like conversational AI for its online store.

There are many other instances where reliance on AI should be limited or avoided, such as in the interpretation of complex, nuanced information. While AI-generated summaries can help journalists quickly assess vast amounts of data, the technology may inadvertently omit critical details or misrepresent the original intent of the source material. In such cases, an experienced editor or reporter is necessary. We insist that all of our reporters review the source material for any story they write. We view this as part of the rigorous fact-checking required in modern-day journalism.

Our goal will never be to supplant or diminish our reporters or editors using AI — they’re the ones who make the stories happen. They are the heart and soul of our work. They go deep, challenge the status quo, and expose the truth. They give our readers the facts they need in order to make smarter decisions. Our journalists’ insight, perspective, and analysis is what makes them indispensable. We need them to use their judgment and bring that humanity to each of their stories in order to make us a leading source of news.

Finally, we are committed to accountability.

While AI can produce content at a massive scale, only humans can ensure quality. Articles produced by artificial intelligence are a draft, not finished work. Consumers rightly expect the media to get the details correct. We believe we will drive traffic and business with trust, not shortcuts. 

We treat text generated by AI as we have always treated news copy produced by humans. It is subject to rigorous editing and fact-checking before publication. We make corrections promptly and transparently when errors occur. If a story warrants disclosure of our methods to provide proper context, we will do so to maintain transparency. But the default is that we do not disclose the use of AI any more than we disclose the brand of word processing software upon which a story is written. What matters is the end result — a fair, unbiased, and truthful report. While others get lost in “AI-assisted” details, we continue to focus on breaking news.

While generative AI is an unstoppable force in many industries, how it transforms journalism over the next decade is up to those of us at the forefront — not legacy media, which will surely be slow to adopt. Those who embrace artificial intelligence wisely by supplementing reporters, not replacing them, will unlock new possibilities. Those who fall prey to AI’s hype risk dehumanizing and degrading their newsrooms.

The future of journalism lies in human empathy. Generative AI promises a productivity revolution, but journalists must steer that transformation in service of our profession’s higher purpose: delivering truthful, impactful stories that serve the public interest.

Our role has never been more crucial amid a flood of misinformation. Now we have an opportunity to shape AI to enhance, not erode, what makes journalism essential through this era of disruption. Doing so will require constant vigilance, ethical innovation, and a commitment to the values that undergird this work. The balance we strike will reverberate for decades. History watches our next move.

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Do you disagree or have a completely different perspective?
We’d love to know

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Startups

Built on the

ChatGPT API

Are Taking a

Huge Risk

Rachel Curry
Rachel Curry is a journalist based in Lancaster, Pennsylvania. Her work focuses on finance and technology on a global scale, as well as local issues impacting her community. You can connect with her on Twitter at @writingsofrach

Generative AI has emerged as a groundbreaking and captivating technology, capable of feats that have dominated press headlines and engaged a growing user base. Startups have raced to capitalize upon the fever-pitch surrounding ChatGPT and other generative AI models – and the recent release of OpenAI’s ChatGPT API has opened up the potential for countless niche products built on the back of the company’s super-powerful technology. But history shows longevity is uncertain – and risks plentiful – for companies too dependent on a closed-source API.

The ChatGPT API-based startup arena includes companies like Baselit (a so-called copilot for data analytics), Landbot (a no-code customer service chatbot builder), and BarriAI (APIs that allow you to build ChatGPT apps on the fly).

Many API-dependent companies of the past have suffered after having access revoked or usage costs suddenly increased. Thread Creator, a startup that offered users the ability to manage Twitter threads, which was unable to function when the company lost access to the Twitter API in 2021. Then there’s CanvasPop, which no longer connects with Meta-owned Instagram to print pictures straight from the app. Elon Musk recently announced a price hike for many users of Twitter’s API.

Users of the startups’ services also face risk, which could lead to regulatory or legal requirements to a degree that founders are not able to pivot to meet. The valuations of many companies rest on the value of data collected from users rather than simply the quality or demand of the product itself.

The problems with ChatGPT startups are multifold. For founders, building a product on top of another company’s proprietary model leaves developers vulnerable. “You’re dependent on somebody else’s platform and infrastructure, and then you have to pass that cost onto your own customers,” says Theo Priestley, author of “The Future Starts Now,” and long-time futurist, 

If you use ChatGPT’s API, you pay based on a token system that reflects how “costly” it is to generate the text you need. This is important, considering that startups and developers using the API are held hostage if pricing shifts—which could trouble the overall competitiveness of industry pricing.

That issue melds with another, which is the replicability of ideas. “The ideas are ten a penny,” Priestley says.

What’s to stop another entrepreneur from taking a similar idea, improving it, and using it to launch something else—all while doing it cheaper? Alternatively, what’s to stop OpenAI from seeing demand for an API-dependent tool and simply replicating it as a feature for its own paying ChatGPT subscribers, effectively shuttering startups in that niche?

According to Dan Cunningham, CTO of AI-powered reputation management software Chatmeter, that market saturation is, in fact, possible to get past. “Startups have to ask themselves what value they are bringing, and where they can differentiate themselves,” Cunningham says. The emphasis here is on differentiation, or making ChatGPT API integration a slice of your offering, but not the whole pie. (Chatmeter has a new generative AI offering using the OpenAI Chat Completion API.)

[Generative AI chatbots] have become data hoovers very quickly and easily, and that’s worrying to me,” says Priestley.”

When startups rely too heavily on generated text as a substitute for human interaction, especially in cases where the AI’s influence isn’t readily disclosed, they run the risk of discomforting users and creating ethical concerns. California-based mental health nonprofit Koko rolled out a GPT-powered mental health support feature that it quickly shuttered due to ethical concerns. Koko co-founder Rob Morris wrote on Twitter about the shutdown. “We used a ‘co-pilot’ approach, with humans supervising the AI as needed,” he wrote. “Once people learned the messages were co-created by a machine, it didn’t work.”

Peter Relan, venture capitalist and founder of YouWeb Incubator, has experience investing in the generative AI space (including for Got It AI and MathGPT). “Failure is a distinct possibility,” Relan says, referring generally to investment in the generative AI space. He clarifies that there is broad-based investing going on at the seed stage, with investors hoping to find the winners in generative AI, much like the rest of the technology industry. However, with generative AI, the wheels are turning faster due to rapid advancement in the technology.

With all of these risks for founders, users, and investors, what are the alternatives to these kinds of API-based startups?

Aside from proprietary models using great training data sets, Relan says you can lean on open-source models or even fine-tuned LLMs for task-specific applications.

Relan says he sees that with his conversational AI startup Got It AI, which built its own model, ELMAR (Enterprise Language Model Architecture.) “It is a suite of on-premise guard-railed language models that can be fine-tuned to enterprise-specific tasks,” he says. He claims that this approach protects all parties involved while retaining the utility of generative AI. 

While we have yet to see the full breadth of alternatives, startups entirely dependent on ChatGPT APIs might have a short-lived outlook. However, that doesn’t mean generative AI innovation is a moot point. In fact, development in the space is essential, but it’s crucial to do so in a way that caters to longevity and value to all stakeholders.

Cunningham, of Chatmeter, believes startups that fine-tune models for their own purposes can succeed. “Smart startups will be looking to these technologies for future development, choosing the right model for their particular use case, and in many cases training these models on their own data and needs.”

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The future is experiential rather than transactional; immersive storytelling using innovative, sensory-based showrooms that connect with consumers through emotional narratives”

David Todd McCarty
David Todd McCarty has spent a career as a branding consultant, telling stories that attempt to explain human behavior in relation to commerce, from Dallas to Dubai, Moscow to Miami.

The Future

Of Retail

Imagine walking into the flagship showroom of your favorite brand, where your senses are immediately enveloped in a captivating manifestation of the brand’s identity—an immersive encounter that lingers in your memory long after you’ve departed. Here, you’re not focused on the product, but the experience itself. It’s a magical, elusive, and surprising journey.

You explore the sights, sounds, smells, textures, and tastes without worrying about size, color, availability, or fit. You’re on a journey to connect with yourself, and the eventual sale is merely the culmination of the brand experience. It becomes a cherished memento—a receipt capturing an unforgettable encounter.

In the meantime, you allow yourself to be guided by a mix of artificial intelligence-driven virtual reality and high-tech production, innovative technology, and authentic sensory explorations, a narrative that promises a more fulfilling life. All that is required is a deeper relationship with the brand so that you can become part of the story.

Is A Sensory

For years, the media has incessantly spoke of the decline of brick-and-mortar retail, resulting in the inevitable death of malls. Fortunately, to borrow a phrase from Mark Twain, reports of the mall’s demise have been greatly exaggerated. 

While online shopping has grown and evolved, it still accounts for less than 15% of total retail sales in the US. The over-expansion of retail in America was decades in the making, so even a significant collapse of our physical retail inventory could be explained as nothing more than a healthy, long-overdue correction. 

America is dramatically over-retailed compared to other markets. According to the CoStar Group, a leading supplier of data analytics to the commercial real estate industry, America currently has approximately 42 sf of retail per capita, whereas the United Kingdom, a much more densely populated market than the rest of Europe, comes in at a mere 22sf/pp.

A reckoning was inevitable.

Experience

So, what's next?

Discover more
Discourse

The evolution of the retail store has always been in a constant state of flux. We’ve seen the evolution from general stores to department stores, malls, big box concepts, and e-commerce. We now find ourselves navigating the fractured world of social media and subscription services. So, what’s next?

Human beings are social creatures, evolved to live in communities. We are drawn to shared experiences, often choosing to watch a performance, athletic event, motion picture, or exhibition with others, even though we can now experience these events with even greater production value in the privacy and security of our own homes. 

We are also sensory beings, suited to gathering input about the world around us through touch, taste, smell, sight, and sound. We desire experiences, not just possessions, and we are far more driven by our hearts than our heads. Traditional retail was designed around product distribution. Madison Avenue sold us the dream, and Main Street offered us the opportunity to see the product in person and try it out. But that’s changing. 

The future of retail will be brand showrooms, not distribution centers. As overnight and even same-day shipping has become ubiquitous, merchandise can be delivered to your door within days or even hours, using regional distribution centers, so there is no need for overstock, and no reason to lug things home from a central location. 

Stores will become experiential destinations, meticulously designed to invite you to try on a new lifestyle. The brand experience will combine high and low-tech, textures and scents with virtual reality, video, and sound. Tablet-wielding brand evangelists will guide you through the seamless process of completing the order, enabling contact-free payment and hassle-free delivery.

Beyond the inspiring technology and sensory displays, a significant expenditure will be devoted to brand ambassadors: highly-trained individuals capable of walking consumers through the brand experience, offering them a compelling emotional narrative and a satisfying sensory immersion. Think of actors putting on a show rather than mere salespeople. Cast members, not cashiers.

The fusion of immersive experience, cutting edge-tech and exceptional human interactions will set forth a new chapter in the evolution of retail.

Now imagine the best malls in the country, reinvented as awe-inspiring collections of flagship showrooms, featuring best-in-class brands. You plan your adventure using an app that schedules all your appointments and provides your digital dossier to the brand specialist in advance. Consequently, they receive you like the VIP customer you are, every time.

You depart these extraordinary spaces invigorated and satisfied, all your purchases sent to your home ahead of you, all your experiences captured in digital form to be shared with friends and family online, and all your likes and dislikes noted and cataloged for future reference.

Some might assume that traditional retail has run its course and is no longer practical when we can order anything in the world on our phones without leaving the house. But that ignores the vital human element, one that lies at the very core of human society. Time and again, we think we want the speed and efficiency of cold technology before realizing that we miss the unpredictable warmth of human culture and interaction. 

Do you agree with this?
Do you disagree or have a completely different perspective?
We’d love to know

Who Cares

Zaheer Goodman-Bhyat
Co-founder ON_Discourse and Purpose-driven Founder & Award-winning Storyteller @HighMagic.io

One of the major selling points of web3—at least among its most ardent proponents—is decentralization. Blockchain technology enables us to use smart contracts, build bankless assets, trade without friction, and much more. 

Here’s the problem with the way we’re trying to sell web3 to people who aren’t already interested: Who cares? Who really cares about abstract-sounding concepts like identity ownership, bankless assets, and smart contracts?

About Web3?

From the conversations I’ve had with folks on the periphery (or way outside) of web3 spaces, the answer is: not your average person. 

Let’s take decentralized finance as an example. The idea of bankless assets seems incredibly exciting to those of us on the inside of the discussion. Traditional banks fail consumers in many, many ways. Decentralized finance represents the future.

However, the majority of Americans are unable to cover a $1,000 emergency in cash. 

You’re not going to get the average person excited about the idea of bankless assets, because the average person has no assets. Decentralized finance sounds meaningless to a person living paycheck-to-paycheck. 

This is part of crypto’s current image problem. The far-reaching benefits of blockchain technology are exciting when you dig into the details, but the average person struggles to see how those benefits apply to their lives now when it matters to them.

or
What web3
Got Wrong
Mathew Sweezey
Mathew is the former
Co-Founder of the Salesforce Web3 Studio, HBR author, and a Web3 advisor and investor.

The idealism behind these common selling points is good, and it’s something we need to foster (especially in light of scams, cryptocurrency collapses, and other high-profile scandals).

Instead, we need to start leveraging that idealism into creating and pointing out useful tools—not just using web3 projects to do web2 stuff. The more relevant we can make web3 to the average user, the faster we’ll be able to onboard the next 100 million users.

Part of that onboarding is showcasing how the blockchain can make everyone’s lives easier, using examples that people who aren’t interested in speculative finance can understand and relate to.

Take a simple activity, like trying to sell something online.

Under the current model, you might want to list that item on multiple sites to increase the likelihood that someone sees and buys it: eBay, Amazon, Craigslist. In doing so, you face a few risks that most online sellers are all too familiar with.

If two people try to buy it at the same time from different sites, you’re going to have at least one angry shopper on your hands. And there’s a risk that the person who says they’re buying it doesn’t have the money for it. 

A smart contract eliminates those risks. You can list the item wherever you want and the smart contract ensures it can only be sold once. The smart contract checks the buyer’s wallet to make sure they have the assets to buy it. As soon as you scan the item at the UPS store or post office, the smart contract automatically validates the transaction and releases the funds. 

No need to interact with a middleman. No need to monitor all your listings to update information about how much stock you have. No need to worry about scams.

Something this simple is still an enormous benefit of blockchain technology. And you might notice that it includes all the same selling points: decentralization, bankless assets, smart contracts, and frictionless trade. 

Yet it’s an example that is far more likely to be relevant to the average person’s daily life. It’s more comprehensible than the idea of bankless assets on its own and showcases the concrete benefits of blockchain technology—not just the theoretical ones.

Crypto has an image problem, but one of the solutions is fairly simple: Meet people where they are. Show them how the blockchain can make their lives easier now and how it is relevant to their actual experiences. 

Do you agree with this?
Do you disagree or have a completely different perspective?
We’d love to know

What Web3

Got

Wrong

Mathew Sweezey
Mathew is the former Co-Founder of the Salesforce Web3 Studio, HBR author, and a Web3 advisor and investor.

The media cycles surrounding the 2017 ICO explosion and the 2021 NFT craze put the spotlight on web3 and made every CEO ask how their company could be in on the action. We’ve seen the world’s biggest brands, from Starbucks to Nike, invest heavily in web3. But even with the massive media hype and brand activations, web3 hasn’t caught on with the general consumer. 

So what will it take for these technologies to finally find traction? The first is a shift from Asset Class to Experience Layer, and the second is a shift from On-Chain to OmniWeb.  

A shift from Asset Class to Experience Layer

Most consumers only understand web3 through a simple number, and that is generally the price of Bitcoin. Web3 has unleashed a new asset class on the world, which has driven all of its hype to date, and is one of its biggest barriers to mass adoption. 

Most consumers are afraid of crypto. It is hard, complex, and scary. Even when new applications make it easy to ‘on-ramp’ into crypto there is still the radical volatility of the asset class. Beyond these issues is the basic fact that most consumers don’t care about asset classes. 

The focus of web3 as an asset layer is also problematic for brands. Most brands are now holding off on creating web3 tokens (NFTs) due to the unknown regulatory environment. They simply don’t want to be creating assets as that will likely classify them as a financial institution, taking them away from their core business and opening them up to a massive new world of regulation. The tiny market that would even care about these assets doesn’t even come close to justifying the risk of additional regulation. 

A new asset class is good but comes with a large set of issues to drive mass adoption. To reach the masses we have to focus on what they care about. Consumers care about experiences. They want them to be faster, easier, and better. Web3 can do that!

Web3 can create a world where logging in is obsolete. A new study commissioned by Nordpass found the average person has over 100 passwords to remember across their digital lives! Yes, there are password management solutions like Nordpass or Onepassword to make this easier, but those are band-aids to the real problem. Identity is centralized and not extendable. Web3 can easily solve this by leveraging a tokenized identity layer where verified credentials are held by consumers. This could grant them instant access to services and could eliminate the need for logging in altogether, even eliminating the need for downloading the app in the first place. 

This is not a “password solution” but rather a new way of verification. Apps use passwords and usernames as a way of proving you are who you say you are. Tokens can do that. Tokens can prove you are who you say you are, and services can use them rather than making users create a new username and password. Those tokens can also carry data, eliminating the need for the app to store data. Rather the consumers bring their data with them. 

Beyond just being an easier way to log in, web3 can eliminate the need for apps and the creation of new profiles altogether as the tokens themselves can execute functions.

Imagine you have a car token given to you when you purchased the car. Now let’s say you want to do something with your car. From starting it to renting or selling it. Each of those would require at least one other application to be downloaded, a new profile to be set up, then have to manage all of those apps. This is how the web currently works, but in a tokenized (web3) world the tokens can be the applications themselves. 

Progressive brands like Karma have already done this for their high-end electric cars. Each car is given a token, and that token is added to your wallet. You then open the token and execute these functions from there directly. No need to download another app, or sign up for a new service. Want to sell the car? Click a button in the token, put in your terms, and then simply pick where you want to sell the car. All of your information from your terms to the car’s data and history is then sent to those marketplaces, and you interact with them through the token itself. Making selling a car easier, faster, and more trusted as the data is all verified.

The biggest barrier to this kind of implementation of web3 technology is the focus on web3 as a new asset class rather than an infrastructure to help provide better digital experiences.  We have expanded the aperture of how we think about tokens. Tokens are not just assets, they are also stores of data, and enable a new world of frictionless digital experiences to take place.

A shift from On-chain to “OmniWeb”

Web3, past being a speculative financial asset class, also has another big problem: the blockchain. The blockchain is a powerful database able to solve “double spend,” a potential risk to cryptocurrency in which a user might be able to spend the same digital currency twice. Through consensus mechanisms and the recording of transactions on a ledger, blockchain solves this flaw, enabling blockchain-based systems to be a transaction layer of assets and allowing for crypto to even exist. It’s a big deal! Despite this powerful feature, putting things on-chain comes with many issues that stifle the adoption of web3. 

Putting things on-chain makes transactions public. This is good for solving transparency in financial situations, but it’s bad for a lot of other general use cases. For example, brands don’t want their entire customer database visible to their competition. Additionally, blockchains are not as fast or scaleable as other databases. Blockchains are designed to be a transaction layer, and they are great at that. They are not great at storing a lot of information. So a slow, public, and expensive database has very limited use cases, and most brands and consumers find it too scary to engage. 

Web3 has to embrace a hybrid world where both on-chain and off-chain tokens work together. I call this “omniweb architecture,” where on-chain tokens can be extended via off-chain code and off-chain tokens can be leveraged by on-chain and off-chain applications.

Off-chain tokens, better known as “attestations” are exactly the same as the on-chain token – verifiable, decentralized, trusted, and programmable – however they come with the added benefit of no wallet being needed. They’re also private and are not seen by regulators as an asset. They can unlock the value of web3 with none of the hassles. 

For example, Taylor Swift could issue an off-chain token to all of her fans who follow her on Twitter, Spotify, and have been to a concert in the last year. Smart Token Labs is an Australian web3 startup that I currently advise and which is currently working on this technology. Their CMO Brent Annells believes that fans want new ways to connect. “Fans want to be rewarded for being fans but in a way they value. They don’t want to be paid or have a digital asset they can sell. They want access and to be recognized by the artists as fans,” he said.

Verified fandom allows fans and artists to unlock a new era of fan experience.”

With modern web3 technology, there is no digital wallet and no new login required for the fan to receive the credential, just an email. Now the fan can prove anywhere that they are a top fan of Taylor Swift and new experiences can be unlocked. For example, brands can give rewards to fans directly on their site, and ticket sales can now be gated to allow superfans to get first dibs. In both of these situations, the token, not backend databases, is the integration point. This makes new experiences easier and faster to create and allows consumers to derive greater value from their online data. 

Not all things require a blockchain, but all things can be better when leveraging web3 ideas and technology. Off-chain tokens are web3, and a great way to create new experiences that are frictionless while delivering on the core values of interoperability, decentralization, and ownership. For us to drive mass adoption we have to think past just on-chain and look towards an omniweb world.

Discover more
Discourse

So where do we go from here?

or
Who Cares
About web3?
Zaheer Goodman-Bhyat
Co-founder ON_Discourse
and Purpose-driven Founder
& Award-winning Storyteller @HighMagic.io

The entire current conversation about web3 is focused on the financial aspects of the technology, and mostly that is simply the token prices of Bitcoin. This limited view is too scary to consumers and brands. When we let web3 fade into the background and leverage it to create better experiences both of those fears go away, and a greater value can emerge. To do this we also have to reduce the complexity of the experience, which means embracing off-chain tokens to expand on these use cases and further reduce consumer friction.

By shifting the focus from web3 as an asset layer to an experience layer, and embracing a wider understanding of web3 technology beyond just the blockchain, we can deliver to consumers truly what they want: a better digital experience.

Do you agree with this?
Do you disagree or have a completely different perspective?
We’d love to know