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The Growing Role of Stablecoins in Online Transactions and Digital Services

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The Growing Role of Stablecoins in Online Transactions and Digital Services


When people compare top casinos worldwide, many notice that online casinos now turn to stablecoins, making each best-rated casino payment smoother than ever. The same measured shift is happening far beyond gaming. Stablecoins have quickly become the go-to money solution in creator platforms and global marketplaces alike, serving as quick, low-cost alternative currencies that remain stable over time. Tied directly to strong assets – typically the U.S. dollar – these tokens eliminate sudden swings which cause alarm among shoppers and store owners alike.

Both parties to any transaction can focus on what matters: providing service rather than guessing tomorrow’s rate. This article details why stablecoins are on the rise, how their systems function, and any remaining barriers. At its heart, this guide covers merchant benefits, user comfort, tech design, and regulatory rules in an accessible language suitable for everyday readers. By the end, businesses should better understand how to integrate stablecoins into existing payment systems, and observers will realize why tokens may soon feel just like credit cards did decades earlier.

Understanding Stablecoins Basics

Stablecoins are digital tokens designed to maintain stability instead of profit swings, linking each coin directly with an asset like dollars or euros in real life. Major stablecoins strive for 1:1 peg with these real world assets through reserves like cash, Treasuries or liquid assets – such as bank accounts holding money matching the reserve level; others lock away government bonds or short term notes for safe keeping; some projects use baskets of other cryptocurrencies in balancing value; but regardless of method employed the goal remains constant: keep price steady so buyers and sellers don’t worry as much about fluctuations between transactions!

Establishing a stablecoin requires creating and using an electronic wallet, which houses your private key that validates ownership of it. When someone wishes to pay, their digital wallet signs a message which moves onto a blockchain; confirmation times typically occur much more rapidly than traditional bank transfers, and fees vary depending on the blockchain network. Stablecoin transfers on networks like Solana, Tron, or Polygon often cost only fractions of a cent, while Ethereum fees can rise significantly during periods of heavy congestion. 

Why Stablecoins Appeal to Consumers

Consumers prefer easy math. A coin that equals one dollar helps shoppers know exactly what an album, shirt, or in-game skin will cost without worrying that prices might suddenly change as soon as a checkout page loads – something not possible with traditional crypto, where prices fluctuate drastically with every page load. Stablecoins eliminate this guessing game, so the focus remains squarely on the item rather than exchange rates and exchange rate fluctuations.

Speed matters too: cross-border credit card payments often involve several banks and incur unexpected fees; in contrast, stablecoin transfers can move globally in seconds or minutes through blockchain networks, allowing travelers to pay at a cafe abroad, gamers to tip streamers across continents quickly, freelancers receiving wages without waiting for wire times, and freelancers receiving pay without incurring wire times fees.

Privacy can play an integral part in blockchain use as well. While wallet addresses don’t directly reveal legal identities, blockchain analysis often can link activity back to real users. Blockchains remain public, but identifying users requires extra steps; for many, this light layer of protection feels safer than typing card details into multiple websites simultaneously, but with records being preserved forever on the chain, disputes may still be traced.

Merchant Benefits and Adoption Drivers

Merchants need to consider cost, risk, and reach. Stablecoins satisfy each of those three aspects for merchants; credit card processing typically costs two to four percent plus a fixed fee, while stablecoin gateways charge much lower fees that leave more profit in your till. Plus, savings grow even for small ticket goods where flat card fees have an outsized effect.

Traditional chargebacks have been greatly diminished as blockchain transfers tend to be irreversible once confirmed, meaning fraudsters cannot force reversals against them and therefore reduce bookkeeping headaches and insurance costs.

Global expansion follows. A seller in Ghana can accept stablecoin from an online gamer in Canada without needing to open U.S. bank accounts; currency swapping occurs later or never if purchasing supplies with that token. Through bypassing layers of correspondent banks, merchants can penetrate new markets that once seemed too small or complicated for service.

The Technology Behind Stablecoin Payments

At its core, most stablecoin activity takes place via established blockchains like Ethereum, Solana, or Polygon. Each chain processes transactions as individual blocks, which are then distributed across nodes around the globe based on consensus rules; no individual actor may rewrite history in such ways.

Smart contracts handle minting and burning efficiently. When users deposit dollars into an issuer account, an equal number of tokens are created; when users redeem, these disappear again. Auditors review reserve reports to make sure their backing remains healthy, while some issuers publish real-time banking partner data to provide accountants and curious holders an ongoing window into operations.

Second-layer solutions increase speed and reduce fees by employing payment channels to facilitate quick transfers between two parties and only once settle the net sum on the blockchain. Rollups bundle transfers together to keep data compression under control so the base layer does not become overburdened with transfers; altogether these tools make stablecoin payments affordable enough for game add-ons or news articles with paywalls of under ten cents or below – as an example.

Regulatory Landscape and Compliance

Governments closely oversee money flows, including stablecoins. Many countries classify them as value-stored instruments subject to e-money or payment laws that enact capital reserves, routine audits, and strict know-your-customer checks designed to prevent digital tokens from turning into shadow banking systems.

U.S. legislation proposes forcing stablecoin firms to store reserves with insured banks or short-term Treasuries; Europe’s Markets in Crypto-Assets (MiCA) framework has introduced standardized disclosure and reserve requirements for stablecoin issuers across the EU, while smaller nations view an opportunity to promote innovation through clear licenses with favorable terms – it becomes an attempt at equitable oversight.

Compliance tools continue to evolve alongside crypto. Wallet providers now embed identity modules that collect documents upon signup; on-chain analytics firms screen transfers for possible connections to sanctions or stolen funds, making crypto more mainstream financially, as it becomes clearer to big brands who then add stablecoin checkout buttons alongside cards and PayPal.

Stablecoins in Subscription Models

Stablecoins provide predictability in subscription services and meal kits alike, and have become an indispensable payment method in Brazil, where currency swings could otherwise double their fees. A subscription model built upon stablecoins ensures its users enjoy predictable monthly bills – just imagine streaming services, cloud software, or meal kits charging users using tokens with fixed values like dollars each month rather than fluctuating fees!

Some blockchain-based subscription platforms are experimenting with smart-contract-powered recurring payments; users permit providers to draw one coin per cycle from their wallet, without incurring late-payment penalties or overdraft fines. Furthermore, there’s no credit check needed; all they require is having funds in their wallet balance. For young adults without banking accounts, this makes payments much simpler!

Businesses benefit from more precise cash-flow forecasts. Stablecoin receipts arrive instantly without card settlement delays that can last several days; accounting teams can match revenue with expenses within one asset and reconcile easily; over time, loyalty programs could exist on-chain to award reward tokens alongside subscription credits, further engaging users within an ecosystem.

Challenges and Limitations

Every tool has weaknesses; reserve risk is one such hazard to be wary of: should an issuer mismanage his/her backing assets, this peg may become loose, resulting in funds frozen or banks collapsing – although increased transparency and diversifying reserves help decrease this threat somewhat.

Technical mistakes present another danger. Smart contract bugs may lock tokens or allow hackers to drain accounts. While code audits and bug bounties provide some protection, no audit can detect all flaws; users should stay aware of official contract addresses in order to spot copycat scams.

Volatile network fees, while lower than card costs on average, can still spike during chain congestion. A peak moment on Ethereum can turn an inexpensive transfer into multiple dollars and disrupt business models designed around micropayments. Layer-two solutions help relieve some pressure; merchants should still plan backup plans.

Education gaps also impede adoption; many shoppers still associate crypto with speculation. Clear guides, friendly user interfaces, and strong customer support are necessary if stablecoins are to reach the same comfort levels as tap-and-go cards.

Case Studies Across Industries

Online gaming was at the forefront of this shift: players of massive multiplayer titles now purchase skins using dollar-pegged coins instead of regional price confusion; publishers can then enjoy instant funds and reduced fraud risk when pricing small items without fearing fee erosion.

E-commerce follows. A boutique in Vietnam that exports handmade shoes to Europe lists stablecoin prices alongside euros; because the firm imports leather from a supplier that also accepts tokens, their revenue remains within their chain, thus eliminating conversion losses and keeping revenue within.

Content producers also join. A popular podcast offers early episodes for one stablecoin per month; fans from 80 different nations subscribe without exchange hurdles; the host receives payment minutes after release and pays editors the following afternoon.

Humanitarian aid demonstrates its social impact. After a natural disaster strikes, nonprofits distribute stablecoin tokens via phone calls directly to volunteers; then stores accept these tokens in return for food, with QR codes posted outside stores for auditors to view in real-time and verify funds reach those on the front lines instead of disappearing through bureaucracy.

Future Innovations on the Horizon

Developers are working on programming finance systems where money only flows when predetermined rules are activated – for instance, concert tickets that return automatically if an artist cancels, or rent deposits that unlock when both tenant and landlord sign off on checkout conditions.

Central banks enter the scene with digital currency pilots. Their networks may interlink with private stablecoins to allow users to trade one for one across bridges – for instance, allowing a traveler arriving in Tokyo to quickly convert a dollar-pegged token to one backed by Japanese currency to use instantly on subway gates or for shopping purposes.

Interoperability layers will enable chains to communicate more fluently. At present, moving coins from Ethereum to Solana involves cumbersome bridges; new standards promise frictionless hops that maintain security standards; eventually, merchants will support multiple chains without additional code development costs.

Integrating stablecoins into everyday tasks of IoT opens new avenues. Smart meters could pay power producers every minute with stablecoins instead of cash outflow, better aligning cash outflow with actual consumption. Cars could settle tolls instantly rather than leaving queues of paperwork behind; each step further embedding these secure coins in daily tasks and pushing stablecoins further into everyday use.

Practical Tips for Businesses Embracing Stablecoins

Choose an issuer with a solid history; look for monthly reserve reports, third-party audits, and diverse banking partners as indicators of credibility. A solid issuer history reduces counterparty risk.

Second, select a blockchain tailored specifically to the customer base. Ethereum boasts the largest network; however, newer chains may provide lower fees. Some payment gateways support multiple chains so shoppers can select their most cost-efficient route.

Thirdly, choose an efficient form of custody. While hardware wallets might appeal to tech-savvy founders, custodial services provide turnkey solutions and backup procedures with clear role separation, which can protect against single-point failure.

Fourthly, update policies. Refunds, taxes, and accounting rules of stablecoins may differ significantly from fiat currency transactions. Record spot rates at receipt time; train staff on how to treat on-chain IDs as transaction numbers in bank transactions. Ensure compliance with local regulators by installing know-your-customer checks as needed.

Start small. Enable stablecoins on one product line or limited region at first and collect feedback, iron out user experience issues, and expand gradually – similar to how early e-commerce firms integrated card payments as standard practice over time.

Disclaimer: This is a paid post and should not be treated as news/advice.  



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Franklin Templeton says Wall Street fears blockchain because it threatens its profits

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Franklin Templeton says Wall Street fears blockchain because it threatens its profits

The future of asset management is shifting on-chain, but the transition is exposing a major structural conflict over traditional corporate revenue.

Speaking on a panel at the Proof of Talk summit in Paris, Jenny Johnson, CEO of Franklin Templeton, a $1.74 trillion asset manager, openly addressed the industry hesitation to deploy decentralized networks. According to Johnson, major financial firms are dragging their feet because public blockchain architecture directly challenges their existing profitability.

“This technology threatens a huge number of business models that exist today in traditional finance,” Johnson stated bluntly. “If you see any kind of hesitation, it’s because there is a threat to the business model. Think about the toll-takers in a transaction.”

She explained that if a blockchain can handle settlement instantly via a smart contract, large banks can no longer collect transaction fees as third-party intermediaries.

While crypto-native networks favor open architecture, traditional financial systems are beginning to migrate to public networks due to the significant transaction efficiencies. To demonstrate the cost savings, Johnson cited Franklin Templeton’s history running its tokenized money market fund, Benji, on public networks.

“It was so dramatically cheaper,” Johnson explained, breaking down the internal data. “It cost us about $1.30 a transaction for 50,000 transactions on the old system. And it cost us about $1.13 to run on the Stellar blockchain.”

Johnson’s mention of Benji comes just hours after the Wall Street giant announced it is expanding its digital asset strategy through a new partnership with MoonPay that will allow institutional investors to move between stablecoins and the asset manager’s tokenized money market fund through an onchain workflow.

“In everyday life, anybody—individual, medium, or large enterprise—we want to have a trusted party,” Johnson noted. “We don’t want to keep our assets in our private wallets, in our safes at home. We want to delegate this peace of mind to a third party. And that’s why custodians or banks still have a future.”

The shift of institutional wealth into digital assets will depend entirely on building standard, low-cost compliance rails for legacy investment funds. While Blockstream CEO Adam Back pointed out that bitcoin allows users to maintain true fiscal privacy without an institutional partner, Johnson concluded that standard investors will continue to demand a heavily regulated custody layer.



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Global fashion retailer closing all stores after 33 years

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Global fashion retailer closing all stores after 33 years


Another well-known retail name is set to disappear from high streets as ongoing financial pressure and intensifying competition continue to reshape the retail industry.

For more than three decades, the company has built its reputation as a destination for discounted designer and branded fashion. Despite its established name, loyal customer base, and value-focused business model, the retailer has been unable to overcome the challenges facing many traditional clothing chains.

Its collapse highlights the mounting pressures facing brick-and-mortar retailers as e-commerce growth, rising operating costs, and changing consumer expectations transform how people shop. Consumers are increasingly prioritizing convenience, lower prices, and faster delivery, forcing many legacy brands to rethink their business models.

Founded in 1993, Leading Labels is a multi-brand fashion retailer and outlet chain across the UK and Ireland, offering discounted men’s and women’s apparel from brands including Calvin Klein, Wrangler, and Elle. After years of financial strain, the company has confirmed all remaining stores will close.

Leading Labels enters liquidation amid store closures

Leading Labels is closing its 15 remaining stores after entering liquidation, with clearance sales already underway across the chain as the business winds down operations.

The company appointed Jeremy Bleazard of XL Business Solutions Limited as liquidator on May 26. The appointment follows an earlier notice indicating that the company could be struck off the register and dissolved within two months from March 10 unless action is taken.

The Companies House filing history shows the company failed to submit its accounts due in November 2025, a sign that administrative and financial pressures may have been building before the retailer entered liquidation. Companies House serves as the UK’s official register of companies, maintaining public records of incorporated businesses and overseeing company dissolutions.

Full list of Leading Labels stores closing

Leading Labels currently operates 15 stores, all of which are expected to close as part of the liquidation process:

Leading Labels begins liquidation sales as it closes all 15 stores.Shutterstock

Why Leading Labels could no longer compete

Leading Labels faced many of the same challenges affecting apparel retailers across the industry, including weaker consumer spending, higher operating costs, and shifting shopping habits.

The retailer operated in a particularly challenging market segment. While discount fashion has historically appealed to value-conscious consumers, platforms such as Shein and Temu have dramatically altered expectations around price, product selection, and delivery speed, eliminating some of the advantages traditional outlet retailers once held.

The company’s off-price retail model also confronted growing competition from fast-growing e-commerce marketplaces that can rapidly introduce trend-driven products at ultra-low prices while operating with lower costs than many physical store chains.

At the same time, the retail landscape has undergone a dramatic transformation. The global e-commerce market was valued at $33.91 trillion in 2025 and is projected to reach $155.98 trillion by 2033, growing at a CAGR of 21.6%, according to Grand View Research.

As online shopping continues to expand globally, retailers are being forced to invest heavily in digital capabilities, supply chain efficiency, and customer experience to remain competitive.

Retail analysts at Forrester say long-term survival increasingly depends on a retailer’s ability to balance operational efficiency with digital innovation and a seamless customer experience. Many established brands that were slow to modernize now face mounting financial strain as consumers continue shifting more of their spending online.

Leading Labels’ liquidation reflects a broader trend across the retail sector, where many legacy fashion chains are finding it increasingly difficult to compete in a market driven by speed, convenience, and aggressive online pricing.

Retail store closures continue across the fashion industry

Leading Labels is far from alone. A growing number of fashion retailers have announced restructuring plans, insolvency proceedings, and store closures in recent years as industry-wide challenges persist.

Most recently, fashion retailer Quiz revealed plans to close all 37 of its remaining standalone stores by the end of June 2026 following its entry into administration earlier this year.

Here’s some of my previous coverage of retail closures:

The filing marked Quiz’s second administration in less than 12 months and its third insolvency in six years, prompting immediate clearance sales across all locations.

The challenges retailers are experiencing extend beyond individual brands. McKinsey & Company’s State of Fashion 2026 Report projects low-single-digit growth for the global fashion industry, citing ongoing macroeconomic uncertainty, tariff pressures, and value-conscious consumer behavior.

As economic pressures remain elevated and competition from online retailers intensifies, industry experts expect further consolidation, restructuring efforts, and store closures across the fashion sector in the coming years.

Related: Another retail chain closing all stores after 33 years in business

This story was originally published by TheStreet on Jun 2, 2026, where it first appeared in the Retail section. Add TheStreet as a Preferred Source by clicking here.



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Bold Symposium At Stanford Illuminates The Future Of AI For Mental Health

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Bold Symposium At Stanford Illuminates The Future Of AI For Mental Health


In today’s column, I analyze an important symposium on AI for mental health that took place at Stanford University on June 1, 2026, an event that was part of Stanford’s notable initiative known as AI4MH (AI for mental health).

Avid readers know that I have been covering this crucial and groundbreaking Stanford AI4MH initiative on an ongoing basis; for example, see my coverage at the link here and the link here. This exciting initiative is under the auspices of the Stanford School of Medicine, Department of Psychiatry and Behavioral Sciences — details about AI4MH can be found at the link here. The stated purpose of AI4MH is to transform research, diagnosis, and treatment of psychiatric and behavioral disorders by creating and using responsible AI, including the creation of AI tools tailored towards psychiatric applications, facilitating their use within the department, fostering interdisciplinary collaborations, and providing cutting-edge knowledge.

In addition to AI4MH’s numerous webinars throughout the year, this bold AI4MH Symposium was the first of what I hope will be an annual conference series. The stellar event brought together a bevy of stakeholders, including researchers, scholars, practitioners, vendors, lawmakers, and the like, aiming to discuss where AI for mental health has been and where it is likely headed.

Let’s talk about it.

This analysis of AI breakthroughs is part of my ongoing Forbes column coverage on the latest in AI, including identifying and explaining various impactful AI complexities (see the link here).

AI And Mental Well-Being

As a quick background, I’ve been extensively covering and analyzing a myriad of facets regarding the advent of modern-era AI that generates mental health advice and performs AI-driven therapy. This rising use of AI has principally been spurred by the evolving advances and widespread adoption of generative AI and large language models (LLMs). For an extensive listing of my well over 150 analyses and postings on this evolving realm, see the link here and the link here.

There is little doubt that this is a rapidly developing field and that there are tremendous upsides to be had, but at the same time, regrettably, hidden risks and outright gotchas come into these endeavors, too. I frequently speak up about these pressing matters, including in an appearance on an episode of CBS’s 60 Minutes; see the link here.

AI Providing Mental Health Guidance

First, I’d like to share some overarching background about the AI for mental health domain. After doing so, I will dive into some selected highlights from the recent symposium.

Many millions of people are currently using generative AI as their ongoing advisor on mental health considerations (note that ChatGPT alone has over 900 million weekly active users, a notable proportion of which dip into mental health aspects; see my analysis at the link here). Surveys show that the top-ranked use of contemporary generative AI and LLMs is to consult with the AI on mental health facets; see my discussion at the link here.

This popular usage makes abundant sense. You can access most of the major generative AI systems for nearly free or at a super low cost, doing so anywhere and at any time. Thus, if you have any mental health qualms that you want to chat about, all you need to do is log in to AI and proceed forthwith on a 24/7 basis.

There are significant worries that AI can readily go off the rails or otherwise dispense unsuitable or even egregiously inappropriate mental health advice. Banner headlines keep arising as lawsuits concerning AI providing mental health advice or faltering in catching mental health crises come to public attention. AI makers are stridently devising and fielding AI safeguards in an effort to mitigate or prevent untoward AI actions.

Today’s generic LLMs, known as general-purpose AI (GPAI), such as ChatGPT, GPT-5, Claude, Gemini, Grok, CoPilot, and others, are not yet akin to the robust capabilities of human therapists. Meanwhile, specialized LLMs referred to as purpose-built AI (PBAI) are being built to provide robust mental health advice, though they are in the early stages of advancement and marketplace acceptance. See my detailed coverage at the link here.

Budding Laws On AI Mental Health

A beehive of activity is taking place regarding crafting new AI laws associated with regulating AI for mental health, principally arising on a state-by-state basis. See my extensive coverage of state-level AI mental health laws at the link here. Some policymakers and lawmakers ardently believe that AI and AI makers are being allowed to run amok, while others insist that innovation takes precedence and that new AI laws will adversely impede important progress.

It is too early to know whether these new AI laws will survive legal battles inevitably waged by AI makers and other contenders. Just because AI laws are enacted does not mean they are going to withstand legal scrutiny. All sorts of improper provisions and constitutionally contentious stipulations are undoubtedly buried within these shiny new AI laws.

Congress has repeatedly waded into establishing a comprehensive federal law that would encompass AI for mental health. So far, no dice. The efforts have ultimately faded from view. The big question will be to what degree a sweeping federal law would impact the numerous state-level AI laws. The odds are that many of the state-level laws would run afoul of a federal mandate, and a tsunami of legal cases would arise as a tussle between federal law and state law is undertaken. It surely will be a colossal legal mess.

Readers might recall that I proposed a 7-step AI-law-making process that I believe could substantively help regulators to devise new AI laws that are on target and balanced; see my depiction at the link here. This has an added benefit of reducing what I refer to as AI-law legal debt. This refers to AI laws that, though they look pristine, contain hidden debt that must ultimately be paid. Legal glitches and hitches will eventually be found when hurriedly devised AI laws are passed without suitable scrutiny and analysis.

The AI4MH Symposium

AI4MH undertook a major symposium on June 1, 2026, entitled “Foundations, Frontiers, and the Real World: Shaping AI’s Role in Mental Health.” For the agenda of this significant event, see the link here. This event was co-organized by Stanford AI4MH and Stanford HAI, and the corporate sponsor was Wonder Sciences.

There were six segments comprising the core of the AI4MH Symposium:

  • (1) Opening Remarks
  • (2) Keynote Panel
  • (3) Academic Research: Foundation & Frontiers
  • (4) Industry & Translation: What It Takes to Deploy
  • (5) Policy & Ethics: Governing AI in Mental Health
  • (6) Closing Remarks

I will highlight next various selected points and insights. Please know that this half-day event was chock-full of useful information, and, due to the limited space available here, I’ll aim primarily to whet your appetite with selected aspects that caught my eye. I urge those who are keenly interested in the realm of AI for mental health to consider watching the official video recording of the AI4MH event; see the link here.

(2) Keynote Panel

The keynote panel consisted of:

  • Carolyn Rodriguez, MD, PhD (panel moderator), Professor of Psychiatry and Behavioral Sciences, Associate Dean for Academic Affairs, Stanford University School of Medicine; AI4MH Co-Director.
  • Ehsan Adeli, PhD (panelist), Assistant Professor of Psychiatry and Behavioral Sciences and, by courtesy, of Computer Science and of Biomedical Data Science; AI4MH Co-Director.
  • Brandon Staglin, MS (panelist), Co-Founder, Chief Advocacy & Engagement Officer of One Mind and Chair of the One Mind Lived Experience Council.
  • Vaile Wright, PhD (panelist), Senior Director for Health Care Innovation at the American Psychological Association.

During the keynote panel, one consideration that came up and that is not widely understood by the public at large is that the rising need for mental health services can’t be met by human therapists alone. The demand side for therapy is far in excess of the available supply of therapists. This means that many who need or desire therapy will be left in a lurch. What can be done about this?

A strident possibility is to lean into AI that is suitably devised for mental health support. Human therapists can leverage AI and accomplish more by using AI as a therapeutic tool with their clients. In addition, AI can potentially be used as a standalone mechanism for those who otherwise cannot readily access a human therapist. I have framed this as a transformation of the classic dyad of therapist-client into a new triad of therapist-AI-client, whereby AI is an integral component for psychotherapy; see the link here.

Another notable point that was made involves the prevailing myopic focus on text-based AI for mental health, which is the predominant mode currently, but will soon be eclipsed by multi-modal interactions. Multi-modal AI opens the door toward a much more robust means of engaging in mental health discernment and therapeutic practice. This is not some futuristic sci-fi aspect. It is getting nearer, and we must do more to prepare for and guide how multi-modal AI for mental health is going to emerge and be put into practice; see my discussion at the link here.

The importance of lived experience regarding mental health was brought to the fore when Brandon Staglin provided deeply personal remarks about his schizophrenia recovery during his youth. This was quite heart-wrenching and yet a fully inspirational telling since he ultimately turned that lived experience into a lifelong effort to spur mental health innovation and advocacy. Via One Mind, he continues as a vocal champion for lived experience-based guidance in devising the future of mental health systems.

(3) Academic Research: Foundation & Frontiers

The academic research panel consisted of:

  • Leanne Williams, PhD (moderator), Vincent V.C. Woo Professor and Professor of Psychiatry and Behavioral Sciences (Major Laboratories and Clinical Translational Neurosciences Incubator).
  • Alexis Hiniker, PhD (panelist), Associate Professor, University of Washington Information School Co-Director, Center for Digital Youth. Talk Title: “Friend or Frenemy? AI Chatbots and Teen Mental Health”.
  • H. Andrew Schwartz, PhD (panelist), Associate Professor of Computer Science & Psychology, Vanderbilt University. Talk Title: “Explaining GPT’s Schema of Depression: A Machine Behavior Analysis”.
  • Shannon Wiltsey Stirman, PhD (panelist), Professor of Psychiatry and Behavioral Sciences, Stanford University; AI4MH Associate Director; Stanford CREATE Center Director. Talk Title: “Using Large Language Models to Support Access and Implementation to Effective Mental Health Treatment”.

The panel on academic research noted the significance of carrying out bona fide scientific research when it comes to designing, fielding, and assessing the impacts of AI for mental health. Methodological soundness is a must. Studies that do not adhere to proper and accepted research approaches can give false impressions and be misleading.

The use of RCTs (randomized controlled trials) is the gold standard for clinical research and ought to be a keystone in any serious work on this topic. I recently provided useful advice on how waitlist controls in the specific sphere of AI for mental health research should be suitably arranged; see the link here.

When I give talks about AI and mental health, I frequently mention that perhaps one-quarter to possibly one-third of those using generative AI are dipping into the AI for mental health advisement. During the panel remarks by Dr. Stirman, research findings as part of the Stanford CREATE Center were showcased, including that about 24%-33% of U.S. adults indeed are using LLMs for mental health. An added point was that this usage is not in direct avoidance of therapists or traditional care per se (which is a common myth perpetrated in the media).

CREATE is the Center for Responsible and Effective AI Technology Enhancement of PTSD Treatments at Stanford. For more about the innovative research underway at CREATE, you can visit their website at the link here. For some of my prior coverage about CREATE, see the link here and the link here.

(4) Industry & Translation: What It Takes to Deploy

The industry panel consisted of:

  • Russ B. Altman, MD, PhD (moderator), Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine, of Biomedical Data Science, Senior Fellow at the Stanford Institute for Human-Centered AI and Professor, by courtesy, of Computer Science.
  • Sara Johansen, MD (panelist), Product Policy Lead for Mental Health and Well-Being, OpenAI. Talk Title: “Mental Health & Well-Being, Support across the spectrum”.
  • Jina Suh, PhD, MS, MA (panelist), Principal Researcher, University of Washington, SafeMind Institute. Talk Title: “Beyond the Conversation: Designing the architecture around AI in mental health”.

One of the mantras that was repeatedly referred to during this session entails the aspect that AI for mental health meets people where they are. A person might need mental health assistance at 3 a.m. and not readily have a means to confer with their therapist at that late hour. AI stands ready on a 24/7 basis.

That being said, AI safeguards are sorely needed to keep AI on the right track at all times, night or day. Dr. Johansen described the role of model policies and product policies associated with AI for mental health. OpenAI recently introduced their Trusted Contacts feature, which I reviewed at the link here. AI makers are instituting a layered approach to mental health safeguards. Per the memorable words of Marcus Tullius Cicero: “The safety of the people shall be the highest law.”

(5) Policy & Ethics: Governing AI in Mental Health

The policy and ethics panel consisted of:

  • Michelle Mello, JD, PhD (moderator), Professor of Law at Stanford Law School and Professor of Health Policy at the Stanford University School of Medicine.
  • Assemblymember Mia Bonta (panelist), Member of the California State Assembly, 18th District.
  • Nicole Martinez-Martin, JD, PhD (panelist), Assistant Professor (Research) of Pediatrics (Biomedical Ethics) and, by courtesy, of Psychiatry and Behavioral Sciences (Child and Adolescent Psychiatry and Child Development). Talk Title: “Ethical Issues for Mental Health AI”
  • Jane P. Kim, PhD (panelist), Clinical Associate Professor of Psychiatry and Behavioral Sciences, Stanford University; AI4MH Associate Director. Talk Title: “Evaluating LLMs for Mental Health: Keeping humans in the loop”.

In the policy and ethics panel, Dr. Mello laid out the legal landscape associated with AI for mental health. One of the oft-noted and beguiling aspects concerns the FDA. Though many might assume that the FDA is right on top of the morass of AI apps that claim to provide mental health or well-being advisement, this is decidedly not the case. For my in-depth analysis of the FDA status in this realm, see the link here. And for what the FTC is doing, see my discussion at the link here.

The World Ahead

My above recap of the AI4MH Symposium represents a taste or sampling. I will be doing a series of in-depth pieces to cover some of the specific talks in further depth. Stay tuned.

A final thought for now.

AI has a dual-use effect. There are the downsides and the upsides. Just as AI can be potentially detrimental to mental health, it can also be a huge bolstering force for mental health. A determinative tradeoff must be mindfully managed. Generally, the goal is to prevent or mitigate the downsides and meanwhile make the upsides as widely and readily available as possible.

The realm of AI for mental health requires a wide array of well-thought-out perspectives, encompassing mental health professionals, behavioralists, psychologists, psychiatrists, AI researchers, AI developers, AI makers, legal experts, policymakers, lawmakers, and the public at large. It might be said that it takes a village to ensure that AI for mental health steers in the right direction. The stakes are high; namely, this is for the sake of humankind and the psyche of us all.

Let’s get this right.



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Prediction market traders bet bitcoin’s selloff has further to run

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Prediction market traders bet bitcoin's selloff has further to run


Prediction market traders are increasingly wagering that bitcoin’s correction is far from over, even after the cryptocurrency tumbled toward $65,000 this week amid mounting pressure from ETF outflows and weakening institutional demand.

On Kalshi, traders currently assign a 66% probability that bitcoin drops below $55,000 this year and a 50% probability of sub-$50,000 prices. They also give a 31% chance that prices could even dip below $40,000.

Polymarket traders are expressing a similar view. Contracts on the platform imply a roughly 67% chance bitcoin falls below $55,000 this year and a better-than-even chance it drops under $50,000.

On prediction platform Polymarket, traders now give bitcoin only a 30% chance of outperforming gold in 2026. Gold is down approximately 1.5% in the last month but is up 33% in the last year while BTC is down around 37%.

This comes amid dwindling institutional appetite for the leading cryptocurrency. According to data from SoSo Value, traders withdrew $2.4 billion from U.S.-listed BTC ETFs in May and $1 billion in the first two trading days of June, with the record-breaking outflow continuing.

Meanwhile, K33 Research argues that bitcoin is also losing a battle for investor attention against artificial intelligence-related stocks. As CoinDesk previously reported, in a report on Tuesday, the firm said many investors view the opportunity cost of holding bitcoin as too high while AI-linked companies continue to post outsized gains and major equity indexes push to record highs.

“Much of the market views the opportunity cost of holding BTC as too high while anything AI-related soars,” K33’s Vetle Lunde wrote.

While K33 still views bitcoin as undervalued relative to equities over the long term, prediction markets suggest traders are increasingly positioning for lower prices before any recovery arrives.

While traders increasingly bet on lower bitcoin prices, capital does not appear to be leaving crypto entirely. Instead, it is increasingly moving into digital dollars.

USDT and USDC have both gained market share during bitcoin’s slide to $66,000, CoinDesk previously reported, a sign that traders are raising cash and waiting for better opportunities rather than immediately buying the dip.



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LAB records 40% hike to hit record highs – Are buybacks driving demand?

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LAB records 40% hike to hit record highs - Are buybacks driving demand?


Buybacks, open positions, and shorts liquidations

As per the data, YES.

Yesterday, LAB’s official page on X (formerly Twitter) announced that a buyback program to address three main issues went live.

The data showed that protocol fees worth $3.401 million were used to buy back a total of 22.644 million LAB tokens. The team regarded the move as converting ecosystem revenue into market demand.

This program is expected to maintain steady buy pressure and hence, value growth. Additionally, it is anticipated to advance long-term resilience for ecosystem sustainability, as well as achieving balanced tokenomics. This would be done by distributing LAB tokens through incentives to the community to enhance healthy token circulation.

LAB
Source: Buyback.lab.pro

This buyback program has influenced a hike in trading activity. Open positions have increased significantly across different exchanges, particularly for small investors.

This was evident as Funding Rates on multiple exchanges turned green – A sign of buyer dominance. In fact, most of the Open Interest (OI) climbed by double digits. On Binance, for instance, it rose by 21.83% to $155 million.

Shorts liquidations in the last 24 hours surpassed $17 million across all exchanges. The largest liquidations occurred on Bybit, Binance, and OKX respectively.

LABLAB
Source: CoinGlass

On top of that, there seemed to be some token demand too. This was evident with the Long/Short Ratio exceeding 1, except on the KuCoin exchange.

This activity took place against the backdrop of massive Futures market demand that sparked a 16% rally recently.

LAB’s rally gains momentum

On the charts, LAB’s price went ahead and hit a record high of $20 following this day’s rally. The altcoin has seen high volatility lately, as shown by the Bollinger Bands (BB) expanding to maximum levels.

However, the Chaikin Money Flow (CMF) seemed to be ranging between 0.22 and 0.23. This value hinted at positive capital inflows, but it was minimal since the indicator was not rising.

At the time of writing, the altcoin’s rally was continuing to gain momentum with 12 straight green 4-hour candles. This momentum was seconded by the price being far from the mid-level of the BB.

LABLAB
Source: LAB/USDT on TradingView

Here, it’s worth noting the stall between $19 and $20 over the past three sessions. This may allude to a potential correction, one where LAB may return to around $16 or lower.

Simply put, the buyback program has so far elicited some confidence since it is addressing one of the market’s main concerns – Balanced LAB tokenomics.


Final Summary

  • LAB rallied by more than 40% in a day to hit a new record high of $20 following the debut of a buyback program. 
  • LAB’s 12 straight green candles hinted at buyer momentum, but an ongoing pause between $19 and $20 could suggest a looming correction. 



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