Bare trust reporting is a new requirement by the CRA this year, but most Canadians are likely unaware of its existence — or penalties.

Did you co-sign your kid’s mortgage? There are new tax reporting rules to know - National | Globalnews.ca

After what&#x27;s become known in some quarters at the &quot;Kate Middleton photo scandal,&quot; questions loom over what this latest episode might mean more broadly for the Royal Family as it tries to find ways to bolster its relevance for the future.

ANALYSIS | The Kate photo scandal has tested the public's trust. How do the Royals get it back? | CBC News

If you&#x27;ve tried to use Google to research a product recently, you&#x27;ve probably encountered a whole lot of extremely similar ‘Best Of’ lists.

Can you still trust Google's search results?

Truts

truts

Here we go again. It was supposed to be the shining beacon of academic research, a tool that could sift through mountains of data, offer accurate citations, and provide credible sources to enhance scholarly work. Scholar GPT, the supposed breakthrough in AI-driven academic assistance, was meant to revolutionize the way we gather information. It was supposed to be a reliable resource that combined the power of cutting-edge technology with the expertise of years of research, right? WRONG. Once again, we are confronted with a harsh reality that we have all come to dread when it comes to AI: It can’t be trusted. In a shocking revelation, Scholar GPT—this supposed paragon of academic assistance. However, when I was using it I found it to be providing inaccurate information and statistics. The very thing it was supposed to excel at—accuracy—has turned out to be a total farce. This is not just a minor blip. This is a massive blow to the credibility of AI as a source of reliable academic content. Scholar GPT, which touts itself as being trained on the most valid and credible sources, was providing data that didn’t match up with reputable research and statistics And let’s not ignore the glaring fact that the platform claims to reference “credible” academic papers, yet several of these so-called references were completely fabricated or misquoted. At this point, anyone still believing that AI like CHATGPT, or in this case, Scholar GPT, is a trustworthy partner in academic research is either naive or seriously misinformed. I’m sorry, but when you trust a tool that generates fake statistics or pulls sources out of thin air, you are opening the door to disaster in your academic work. Sure, you might say, "But these AI models are constantly improving!" Really? Because the last time I checked, they’re still feeding you half-baked data that could ruin your credibility in a split second. It’s one thing for AI to make a mistake on trivial things, but when it comes to providing factual, verifiable information to the world of academia, there is no room for error. The repercussions of getting this wrong aren’t just some theoretical debate about technology—they can have real-world consequences. Imagine citing a non-existent study or quoting a statistic that’s completely fabricated—your academic integrity, your reputation, and your work could all go down the drain. How does AI expect to replace credible research when it doesn’t even know what reliability looks like? And don’t even get me started on how CHATGPT itself is still far from trustworthy. The promises of AI revolutionizing everything from writing to research have clearly been wildly overstated. Sure, it might be able to string together sentences that sound decent, but that’s about it. When it comes to fact-checking, cross-referencing, and providing legitimate citations, it falls flat on its face. Even after all the hype and supposed advancements, AI still struggles with the most basic and vital aspect of academic work: accuracy. It’s no longer just a matter of missing the mark on a few minor details—AI systems like Scholar GPT and CHATGPT are actively contributing to the spread of misinformation, and that is unacceptable. The reality is that we cannot afford to blindly rely on AI in fields that demand precision and scholarly integrity. So let’s all take a deep breath and stop pretending that these so-called "academic tools" are the holy grail of research. They’re not. They are not ready to replace the critical thinking, in-depth knowledge, and meticulous verification that true scholars have spent years honing. And, quite frankly, they may never be. Until AI can be trusted to consistently provide accurate, reliable, and verifiable information, it remains nothing more than a tool that could derail your academic efforts. If you’re still putting your faith in Scholar GPT or any other AI-driven platform for your academic work, I hate to break it to you—but you’re on shaky ground. The truth is, AI just isn’t ready for the world of academia yet. Here we go again. It was supposed to be the shining beacon of academic research, a tool that could sift through mountains of data, offer accurate citations, and provide credible sources to enhance scholarly work. Scholar GPT , the supposed breakthrough in AI-driven academic assistance, was meant to revolutionize the way we gather information. It was supposed to be a reliable resource that combined the power of cutting-edge technology with the expertise of years of research, right? Scholar GPT WRONG. WRONG. Once again, we are confronted with a harsh reality that we have all come to dread when it comes to AI: It can’t be trusted. It can’t be trusted. In a shocking revelation, Scholar GPT—this supposed paragon of academic assistance. However, when I was using it I found it to be providing inaccurate information and statistics. The very thing it was supposed to excel at—accuracy—has turned out to be a total farce. This is not just a minor blip. This is a massive blow to the credibility of AI as a source of reliable academic content. Scholar GPT, which touts itself as being trained on the most valid and credible sources, was providing data that didn’t match up with reputable research and statistics And let’s not ignore the glaring fact that the platform claims to reference “credible” academic papers, yet several of these so-called references were completely fabricated or misquoted. At this point, anyone still believing that AI like CHATGPT , or in this case, Scholar GPT, is a trustworthy partner in academic research is either naive or seriously misinformed. I’m sorry, but when you trust a tool that generates fake statistics or pulls sources out of thin air, you are opening the door to disaster in your academic work. CHATGPT Sure, you might say, "But these AI models are constantly improving!" Really? Because the last time I checked, they’re still feeding you half-baked data that could ruin your credibility in a split second. It’s one thing for AI to make a mistake on trivial things, but when it comes to providing factual, verifiable information to the world of academia, there is no room for error. no room for error. The repercussions of getting this wrong aren’t just some theoretical debate about technology—they can have real-world consequences. Imagine citing a non-existent study or quoting a statistic that’s completely fabricated—your academic integrity, your reputation, and your work could all go down the drain. How does AI expect to replace credible research when it doesn’t even know what reliability looks like? And don’t even get me started on how CHATGPT itself is still far from trustworthy. The promises of AI revolutionizing everything from writing to research have clearly been wildly overstated. Sure, it might be able to string together sentences that sound decent, but that’s about it. CHATGPT wildly overstated. When it comes to fact-checking, cross-referencing, and providing legitimate citations, it falls flat on its face. Even after all the hype and supposed advancements, AI still struggles with the most basic and vital aspect of academic work: accuracy. fact-checking, cross-referencing, and providing legitimate citations, It’s no longer just a matter of missing the mark on a few minor details—AI systems like Scholar GPT and CHATGPT are actively contributing to the spread of misinformation, and that is unacceptable. The reality is that we cannot afford to blindly rely on AI in fields that demand precision and scholarly integrity. we cannot afford to blindly rely on AI So let’s all take a deep breath and stop pretending that these so-called "academic tools" are the holy grail of research. They’re not. They are not ready to replace the critical thinking, in-depth knowledge, and meticulous verification that true scholars have spent years honing. And, quite frankly, they may never be. Until AI can be trusted to consistently provide accurate, reliable, and verifiable information, it remains nothing more than a tool that could derail your academic efforts. If you’re still putting your faith in Scholar GPT or any other AI-driven platform for your academic work, I hate to break it to you—but you’re on shaky ground. The truth is, AI just isn’t ready for the world of academia yet.

Scholar GPT Fails To Deliver – A Wake-Up Call For The Trustworthiness of AI in Academia

Samsung, the world's second largest technology company by revenue, recently unveiled its plan to build the first AI-powered home appliances to have blockchain security-grade architecture. In other words, the tech giant is planning to leverage its Knox Matrix security framework  to create a ‘Trust Chain”, in a bid to secure connected devices in smart homes. This, like many other instances, is clear proof of the growing intersection between AI and blockchain technology,  which is often marked by the pronounced interest of tech companies in blockchain solutions. It reinforces the theory that AI needs blockchain and vice versa.  (Put simply, intelligence needs trust to thrive). In the words of Peter Kyle, UK’s Secretary of State For Science And Technology: AI has the potential to improve our public services, boost productivity and rebuild our economy.  But to take full advantage,  we need to build trust in these systems. Moreover, AI needs not just trust but it also needs decentralization to thrive. With decentralized AI, we can securely and efficiently distribute AI data against the background of centralized rules, thus enabling us to break free from centralized AI platforms commonly referred to as ‘AI data silos”. Dismantling AI Ecosystem's Bottlenecks AI must be built on trust and decentralization. The reasons are straightforward. In traditional AI systems, large corporations wield significant control over the distribution and accessibility of AI data. This centralized control is a bottleneck to AI development because it practically limits the potential of AI systems to learn from a diverse range of comprehensive datasets, thus hindering innovation in various industries where AI is used. Additionally, the lack of user control over their sensitive data has brought the issue of users’ privacy to the fore, making it one of their core underlying issues in AI development. Given the tendency of giant tech companies to cross the line by breaching users' privacy, the need for a collaborative AI ecosystem built on users’ privacy and ownership has become more apparent than ever. Furthermore, the centralized storage of AI data also poses a significant challenge to its accessibility. A decentralized AI data storage, however, opens up access to multiple stakeholders working in the AI industry,  improving the quality of AI data and the sophistication of its end users. A general example of the collaborative approach to data storage and accessibility is DePIN platforms which allow users to rent out their computing resources in return for tokenized rewards. These platforms incentivize users to individually participate in the distribution and cloud storage of heavy data loads on a decentralized network. Filecoin, Storj, Airweave, and Zetta AI, for example, reward users for contributing to a decentralized data economy, enabling the coordination of a global network of contributors—from developers to enterprises—to build, share, and be fairly rewarded for high-quality AI asset contributions while maintaining ownership, privacy, and control. Benefits of Decentralized AI Decentralized AI offers numerous advantages when compared to traditional data storage systems, which are often criticized for their centralization, limited accessibility, and breach of users’ privacy. Some of these benefits include : Data Quality As Jeff Dean rightly put it: The quality of your data determines the quality of your AI. Enabling AI models to learn from a wider comprehensive dataset can significantly improve the quality and output of AI data, thus creating more sophisticated AI data repositories for various stakeholders in the industry. Decentralized Ownership The beauty of decentralized AI is its ability to foster decentralized ownership of data while preserving users’ privacy and security. Centralization is a far cry from these attributes because it allows few platforms with significant resources to determine how AI data is stored and used. Collaboration and Incentive Decentralized AI fosters open collaboration among the various participants in a decentralized network by rewarding collaborative data sharing and participants’ contributions to AI model development. Tokenized rewards (i.e. tokens) are fairly distributed to users as incentives. Increased Transparency and Trust Decentralized AI fosters transparency, which involves recording all transactions and decision-making processes on a blockchain. Blockchain has the ability to ensure that AI data is traced and verified.  The traceability and transparency of AI data is crucial in building trust with users as it enables them to understand how their data is used.  This is a stark contrast to centralized platforms where users have little or no knowledge of how their data are used. Democratized AI development Famous AI advocate, Cathy O Neil, once said: Decentralized AI is a powerful tool for democratizing access to AI technology. By breaking down the barriers of centralization, we can empower individuals and communities to develop and deploy AI solutions that address their specific needs. The development of AI is dependent on the diversity of its learning models. It's vital to train AI systems from multiple rather than a single data set to enhance their performance and the quality of data across various industries. Latest Development: ZettaBlock Unveils KiteAI To Democratize AI Development ZettaBlock recently unveiled KiteAI, a transformative AI platform that opens access to non-public data for AI developers, with a focus on ensuring that contributors are fairly compensated. The team has concentrated on building enhanced data pipelines, especially for blockchain data, supporting key players like SUI, Eigenlayer, Chainlink Labs,etc. This platform has processed tens of terabytes of data, making it accessible to organizations for AI model development while safeguarding the privacy of the original data sources. Through advanced data attribution and privacy-preserving technology, ZettaBlock’s platform uniquely supports a collaborative economy. It ensures that contributors are recognized and rewarded as their data directly contributes to model performance and value. ZettaBlock is set to showcase elements of this technology at the upcoming Devcon, where attendees will gain insights into how the platform enables secure, equitable access to data for AI advancements. Conclusion: Building a responsible, efficient, and inclusive AI ecosystem is at the heart of decentralized AI. Moreso, it is a paradigm shift from centralized control of vital AI data hindering the further development of AI models. By encouraging decentralized data sharing and storage, it increases accessibility and foresters a collaborative approach to improving the quality of AI data. Most importantly, decentralized AI is poised to help AI to unlock its full potential and serve the various needs of individuals and organizations. Samsung, the world's second largest technology company by revenue, recently unveiled its plan to build the first AI-powered home appliances to have blockchain security-grade architecture. In other words, the tech giant is planning to leverage its Knox Matrix security framework  to create a ‘Trust Chain”, in a bid to secure connected devices in smart homes. This, like many other instances, is clear proof of the growing intersection between AI and blockchain technology,  which is often marked by the pronounced interest of tech companies in blockchain solutions. It reinforces the theory that AI needs blockchain and vice versa.  (Put simply, intelligence needs trust to thrive). In the words of Peter Kyle, UK’s Secretary of State For Science And Technology: AI has the potential to improve our public services, boost productivity and rebuild our economy.  But to take full advantage,  we need to build trust in these systems. AI has the potential to improve our public services, boost productivity and rebuild our economy.  But to take full advantage,  we need to build trust in these systems. Moreover, AI needs not just trust but it also needs decentralization to thrive. With decentralized AI, we can securely and efficiently distribute AI data against the background of centralized rules, thus enabling us to break free from centralized AI platforms commonly referred to as ‘AI data silos”. Dismantling AI Ecosystem's Bottlenecks AI must be built on trust and decentralization. The reasons are straightforward. In traditional AI systems, large corporations wield significant control over the distribution and accessibility of AI data. This centralized control is a bottleneck to AI development because it practically limits the potential of AI systems to learn from a diverse range of comprehensive datasets, thus hindering innovation in various industries where AI is used. This centralized control is a bottleneck to AI development because it practically limits the potential of AI systems to learn from a diverse range of comprehensive datasets, thus hindering innovation in various industries where AI is used. This centralized control is a bottleneck to AI development because it practically limits the potential of AI systems to learn from a diverse range of comprehensive datasets, thus hindering innovation in various industries where AI is used. Additionally, the lack of user control over their sensitive data has brought the issue of users’ privacy to the fore, making it one of their core underlying issues in AI development. Given the tendency of giant tech companies to cross the line by breaching users' privacy, the need for a collaborative AI ecosystem built on users’ privacy and ownership has become more apparent than ever. Furthermore, the centralized storage of AI data also poses a significant challenge to its accessibility. A decentralized AI data storage, however, opens up access to multiple stakeholders working in the AI industry,  improving the quality of AI data and the sophistication of its end users. A general example of the collaborative approach to data storage and accessibility is DePIN platforms which allow users to rent out their computing resources in return for tokenized rewards. These platforms incentivize users to individually participate in the distribution and cloud storage of heavy data loads on a decentralized network. Filecoin, Storj, Airweave, and Zetta AI, for example, reward users for contributing to a decentralized data economy, enabling the coordination of a global network of contributors—from developers to enterprises—to build, share, and be fairly rewarded for high-quality AI asset contributions while maintaining ownership, privacy, and control. Benefits of Decentralized AI Decentralized AI offers numerous advantages when compared to traditional data storage systems, which are often criticized for their centralization, limited accessibility, and breach of users’ privacy. Some of these benefits include : Data Quality As Jeff Dean rightly put it: The quality of your data determines the quality of your AI. The quality of your data determines the quality of your AI. Enabling AI models to learn from a wider comprehensive dataset can significantly improve the quality and output of AI data, thus creating more sophisticated AI data repositories for various stakeholders in the industry. Decentralized Ownership The beauty of decentralized AI is its ability to foster decentralized ownership of data while preserving users’ privacy and security. Centralization is a far cry from these attributes because it allows few platforms with significant resources to determine how AI data is stored and used. Collaboration and Incentive Decentralized AI fosters open collaboration among the various participants in a decentralized network by rewarding collaborative data sharing and participants’ contributions to AI model development. Tokenized rewards (i.e. tokens) are fairly distributed to users as incentives. Increased Transparency and Trust Decentralized AI fosters transparency, which involves recording all transactions and decision-making processes on a blockchain. Blockchain has the ability to ensure that AI data is traced and verified.  The traceability and transparency of AI data is crucial in building trust with users as it enables them to understand how their data is used.  This is a stark contrast to centralized platforms where users have little or no knowledge of how their data are used. Democratized AI development Famous AI advocate, Cathy O Neil, once said: Decentralized AI is a powerful tool for democratizing access to AI technology. By breaking down the barriers of centralization, we can empower individuals and communities to develop and deploy AI solutions that address their specific needs. Decentralized AI is a powerful tool for democratizing access to AI technology. By breaking down the barriers of centralization, we can empower individuals and communities to develop and deploy AI solutions that address their specific needs. The development of AI is dependent on the diversity of its learning models. It's vital to train AI systems from multiple rather than a single data set to enhance their performance and the quality of data across various industries. Latest Development: ZettaBlock Unveils KiteAI To Democratize AI Development Latest Development: ZettaBlock Unveils KiteAI To Democratize AI Development ZettaBlock recently unveiled KiteAI, a transformative AI platform that opens access to non-public data for AI developers, with a focus on ensuring that contributors are fairly compensated. The team has concentrated on building enhanced data pipelines, especially for blockchain data, supporting key players like SUI, Eigenlayer, Chainlink Labs,etc. This platform has processed tens of terabytes of data, making it accessible to organizations for AI model development while safeguarding the privacy of the original data sources. Through advanced data attribution and privacy-preserving technology, ZettaBlock’s platform uniquely supports a collaborative economy. It ensures that contributors are recognized and rewarded as their data directly contributes to model performance and value. ZettaBlock is set to showcase elements of this technology at the upcoming Devcon, where attendees will gain insights into how the platform enables secure, equitable access to data for AI advancements. Conclusion: Conclusion: Building a responsible, efficient, and inclusive AI ecosystem is at the heart of decentralized AI. Moreso, it is a paradigm shift from centralized control of vital AI data hindering the further development of AI models. By encouraging decentralized data sharing and storage, it increases accessibility and foresters a collaborative approach to improving the quality of AI data. Most importantly, decentralized AI is poised to help AI to unlock its full potential and serve the various needs of individuals and organizations.

AI Needs Two Things To Thrive: Trust And Decentralization

Hello developers, let's talk about donations for a minute. Imagine a "hypothetical" world where the top 50% earners around the world donated only but just $1 monthly out of their annual income. Surprisingly, this small gesture could rake in a staggering $42 BILLION - money that could empower small NGOs to bring that "small" change that could bring about transformative change to people's lives across the globe. Yes, in the “hypothetical” world where this happens, there would be enough to meaningfully improve lives, reduce inequality, and address urgent needs. But, how did I come up with that number? Let's do the math together now, shall we? Who are the top 50% of earners? You may be thinking, “I’m not exactly wealthy, just an average person.” Well, the statistics would rather say otherwise. You might be surprised to learn that a lot of people do qualify as top earners by global standards. If you earn approximately $23,380 annually, you are already above the bottom half of the global income distribution -- alongside approximately 3.5 Billion others. This also means that almost half of the world's population is positioned to make a tangible impact on the other bottom half, even with very small contributions. How did the $42 Billion come about? Since we have now established some of the facts: There are approximately 3.5 BILLION people who are above the bottom half of the global income distribution which makes them 50% of the top earners around the world.
The top 50% earners on planet earth earn approximately $23,380 annually which can be said to be $1,948 per month. If each of these 3.5 billion people contributed just $1 per month which by the way is 0.0513% ($1/$1948 = x %100) of their monthly income -- the collective impact would be massive: 3.5 billion people × $1 × 12 months = $42 billion annually The need for Trustless Donation Platforms Currently, the charitable landscape is marred by significant trust issues between donors and non-governmental organizations (NGOs). High-profile scandals, like the cases of Oxfam and Kids Company, where funds raised through donations were misused and there were serious ethical breaches. Events like these have led to increased skepticism amongst potential donors, who fear their contributions would not be utilized as intended. According to the report on a study done by the World Economic Forum, trust in NGOs has rapidly declined due to bad perceptions that these organizations have become overly focused on fundraising at the expense of their core missions, further alienating the public they aim to serve. This rapid decline in trust is also further compounded by a lack of accountability and most importantly transparency in traditional donation methods. Since donors usually feel disconnected from the impact of their contributions they have doubts about whether their contributions are being put to good use. Studies have shown that if there is no transparent and clear information on the operational and performance models of NGOs, the public's confidence in them will reduce which directly impacts their funding and sustainability. The rise of these challenges further calls for solutions, like  -- trustless donation platforms. These are platforms that use blockchain technology to create transparent and immutable records of donations, ensuring that funds are tracked accurately and transparently between donors and NGOs. One such innovative solution is Rootstock, a platform that enhances Bitcoin's capabilities by enabling smart contracts and decentralized applications. By eliminating the need for middle-men and allowing direct oversight through smart contracts, trustless donation platforms built on Rootstock can rebuild confidence among donors. What is Rootstock? Rootstock is the first and longest-lasting sidechain for Bitcoin that represents a significant evolution of blockchain technology. Rootstock or RSK integrates Bitcoin's proof-of-work consensus with the dynamic capabilities of smart contracts that were originally popularized by Ethereum. This enhances Bitcoin's functionality and also opens a new world of possibilities for developers. By introducing smart contract functionality to the Bitcoin network, Rootstock allows developers to create decentralized applications (dApps) that can autonomously execute complex agreements. They were able to achieve this by using a forked version of the Ethereum Virtual Machine (EVM), known as the Rootstock Virtual Machine (RVM). This is great because now developers can leverage existing Ethereum tools and resources, making it easier to build and deploy dApps on Rootstock while also simultaneously leveraging Bitcoin security. In addition, Rootstock adds a programmable layer to Bitcoin by allowing faster creation times -- approximately every 30 seconds compared to Bitcoin's 10 minutes. Now that block generation is faster the execution of smart contracts has become more efficient enabling a great ecosystem of applications that can now easily interact with Bitcoin's infrastructure. The integration of features like the Powpeg — a trustless bridge that allows for the transfer of Bitcoin to and from Rootstock—further solidifies its role as a critical layer in the broader blockchain landscape. Designing a Trustless Donation System Architecture To build or design a system for a trustless donation system we have to bear in mind that the key feature of the system is to foster transparency and accountability in donations. As previously mentioned, as philanthropy evolves, so do the need for solutions that addresses the inherent trust issues between donors and organizations becomes evident. Multi-signature Wallets The foundation of this architecture is the use of multi-signature (multi-sig) wallets that require private keys to authorize transactions. This approach ensures that security is enhanced by distributing control among several parties, thereby reducing the risk of fraud or mismanagement of funds. For example, in a 2-of-3 multisig setup, at least two out of three designated signatories must approve any transaction, ensuring that no single individual has unilateral control over the funds. This unique approach not only safeguards assets but also ensures trust among donors who can be assured that their contributions are being managed responsibly. Smart Contracts In addition to multisig wallets, smart contracts play a very important role in managing the funds donated. Using solidity, you can design contracts that automate certain aspects of fund distribution, including setting donation limits and setting up voting systems for the distribution of funds. This level of flexibility allows responsiveness to the preferences of the donors, allowing a more democratic approach to how funds are managed. Smart contracts can ensure that certain conditions are met before funds are released to enhance accountability. Real-time tracking Another key aspect of this architecture is real-time tracking of funds. Integrating with the RSK block explorer, donors can monitor the flow of their contribution transparently. This is to further enhance transparency and allow donors to hold the NGOs accountable. Two-way Peg Finally, the technical security provided by RSK's two-way peg mechanism ensures trustlessness when converting Bitcoin (BTC) to Rootstock Bitcoin (RBTC) and vice versa. This system allows users to transfer their Bitcoin assets to the RSK platform while maintaining the integrity and security of their original holdings. The two-way peg ensures that each BTC on RSK is equivalent to an RBTC, directly reinforcing trust in the conversion process and enabling seamless interactions within the donation ecosystem. Conclusion: Future Applications and Expansion The benefits of a trustless platform could extend beyond just technological advancements; they could represent a fundamental shift in how donations are perceived and managed in the charitable sector. One of the main features or advantages of a trustless platform is its ability to provide security and transparency. By leveraging a range of Bitcoin's security features and Rootstock's smart contract features, donors can be assured that their contributions are safeguarded against fraud and mismanagement. Looking ahead, there are many ways to expand the platform’s functionality. For example, adding multi-currency support could attract a broader range of donors from different regions, enabling them to contribute using their preferred cryptocurrencies. More so, RSK-based DeFi features could be integrated into the platform to allow for financial products that can allow ending or yield generation from donations. In summary, the future applications and expansion of a trustless donation platform hold immense promise. By leveraging the power of Rootstock and Bitcoin, we can create a more secure, transparent, and trustworthy environment for charitable giving. Resources Rootstock Built for Bitcoin
Blockchain for Good
Sidechain and RSK
Rootstock Fundamental
Does Social Trust Influence Charitable Giving for NGOs?
Why is Trust in NGOs failing – World Economic Forum
What is Multisig and How does it work
Smart Bitcoin Hello developers, let's talk about donations for a minute. Imagine a " hypothetical " world where the top 50% earners around the world donated only but just $1 monthly out of their annual income. Surprisingly, this small gesture could rake in a staggering $42 BILLION - money that could empower small NGOs to bring that "small" change that could bring about transformative change to people's lives across the globe. Yes, in the “ hypothetical” world where this happens, there would be enough to meaningfully improve lives, reduce inequality, and address urgent needs. But, how did I come up with that number? Let's do the math together now, shall we? hypothetical hypothetical” Who are the top 50% of earners? You may be thinking, “I’m not exactly wealthy, just an average person.” Well, the statistics would rather say otherwise. You might be surprised to learn that a lot of people do qualify as top earners by global standards. If you earn approximately $23,380 annually , you are already above the bottom half of the global income distribution -- alongside approximately 3.5 Billion others. If you earn approximately $23,380 annually 3.5 Billion This also means that almost half of the world's population is positioned to make a tangible impact on the other bottom half, even with very small contributions. How did the $42 Billion come about? Since we have now established some of the facts: There are approximately 3.5 BILLION people who are above the bottom half of the global income distribution which makes them 50% of the top earners around the world. The top 50% earners on planet earth earn approximately $23,380 annually which can be said to be $1,948 per month. There are approximately 3.5 BILLION people who are above the bottom half of the global income distribution which makes them 50% of the top earners around the world. The top 50% earners on planet earth earn approximately $23,380 annually which can be said to be $1,948 per month. If each of these 3.5 billion people contributed just $1 per month which by the way is 0.0513% ($1/$1948 = x %100) of their monthly income -- the collective impact would be massive: 3.5 billion people × $1 × 12 months = $42 billion annually 3.5 billion people $1 12 months $42 billion annually The need for Trustless Donation Platforms Currently, the charitable landscape is marred by significant trust issues between donors and non-governmental organizations (NGOs). High-profile scandals, like the cases of Oxfam and Kids Company , where funds raised through donations were misused and there were serious ethical breaches. Events like these have led to increased skepticism amongst potential donors, who fear their contributions would not be utilized as intended. According to the report on a study done by the World Economic Forum , trust in NGOs has rapidly declined due to bad perceptions that these organizations have become overly focused on fundraising at the expense of their core missions, further alienating the public they aim to serve. Oxfam Kids Company a study done by the World Economic Forum This rapid decline in trust is also further compounded by a lack of accountability and most importantly transparency in traditional donation methods. Since donors usually feel disconnected from the impact of their contributions they have doubts about whether their contributions are being put to good use. Studies have shown that if there is no transparent and clear information on the operational and performance models of NGOs, the public's confidence in them will reduce which directly impacts their funding and sustainability. The rise of these challenges further calls for solutions, like  -- trustless donation platforms . These are platforms that use blockchain technology to create transparent and immutable records of donations, ensuring that funds are tracked accurately and transparently between donors and NGOs. One such innovative solution is Rootstock , a platform that enhances Bitcoin's capabilities by enabling smart contracts and decentralized applications. By eliminating the need for middle-men and allowing direct oversight through smart contracts, trustless donation platforms built on Rootstock can rebuild confidence among donors. trustless donation platforms Rootstock What is Rootstock? Rootstock is the first and longest-lasting sidechain for Bitcoin that represents a significant evolution of blockchain technology. Rootstock or RSK integrates Bitcoin's proof-of-work consensus with the dynamic capabilities of smart contracts that were originally popularized by Ethereum. This enhances Bitcoin's functionality and also opens a new world of possibilities for developers. Rootstock is the first and longest-lasting sidechain for Bitcoin By introducing smart contract functionality to the Bitcoin network, Rootstock allows developers to create decentralized applications (dApps) that can autonomously execute complex agreements. They were able to achieve this by using a forked version of the Ethereum Virtual Machine (EVM), known as the Rootstock Virtual Machine (RVM) . This is great because now developers can leverage existing Ethereum tools and resources, making it easier to build and deploy dApps on Rootstock while also simultaneously leveraging Bitcoin security. Rootstock Virtual Machine (RVM) In addition, Rootstock adds a programmable layer to Bitcoin by allowing faster creation times -- approximately every 30 seconds compared to Bitcoin's 10 minutes. Now that block generation is faster the execution of smart contracts has become more efficient enabling a great ecosystem of applications that can now easily interact with Bitcoin's infrastructure. The integration of features like the Powpeg — a trustless bridge that allows for the transfer of Bitcoin to and from Rootstock—further solidifies its role as a critical layer in the broader blockchain landscape. Rootstock adds a programmable layer to Bitcoin by allowing faster creation times -- approximately every 30 seconds compared to Bitcoin's 10 minutes. Designing a Trustless Donation System Architecture To build or design a system for a trustless donation system we have to bear in mind that the key feature of the system is to foster transparency and accountability in donations. As previously mentioned, as philanthropy evolves, so do the need for solutions that addresses the inherent trust issues between donors and organizations becomes evident. trustless Multi-signature Wallets The foundation of this architecture is the use of multi-signature (multi-sig) wallets that require private keys to authorize transactions. This approach ensures that security is enhanced by distributing control among several parties, thereby reducing the risk of fraud or mismanagement of funds. For example, in a 2-of-3 multisig setup, at least two out of three designated signatories must approve any transaction, ensuring that no single individual has unilateral control over the funds. This unique approach not only safeguards assets but also ensures trust among donors who can be assured that their contributions are being managed responsibly. multi-signature (multi-sig) wallets Smart Contracts In addition to multisig wallets, smart contracts play a very important role in managing the funds donated. Using solidity, you can design contracts that automate certain aspects of fund distribution, including setting donation limits and setting up voting systems for the distribution of funds. This level of flexibility allows responsiveness to the preferences of the donors, allowing a more democratic approach to how funds are managed. Smart contracts can ensure that certain conditions are met before funds are released to enhance accountability. Real-time tracking Another key aspect of this architecture is real-time tracking of funds . Integrating with the RSK block explorer, donors can monitor the flow of their contribution transparently. This is to further enhance transparency and allow donors to hold the NGOs accountable. real-time tracking of funds Two-way Peg Finally, the technical security provided by RSK's two-way peg mechanism ensures trustlessness when converting Bitcoin (BTC) to Rootstock Bitcoin (RBTC) and vice versa. This system allows users to transfer their Bitcoin assets to the RSK platform while maintaining the integrity and security of their original holdings. The two-way peg ensures that each BTC on RSK is equivalent to an RBTC, directly reinforcing trust in the conversion process and enabling seamless interactions within the donation ecosystem. Conclusion: Future Applications and Expansion The benefits of a trustless platform could extend beyond just technological advancements; they could represent a fundamental shift in how donations are perceived and managed in the charitable sector. One of the main features or advantages of a trustless platform is its ability to provide security and transparency. By leveraging a range of Bitcoin's security features and Rootstock's smart contract features, donors can be assured that their contributions are safeguarded against fraud and mismanagement. Looking ahead, there are many ways to expand the platform’s functionality. For example, adding multi-currency support could attract a broader range of donors from different regions, enabling them to contribute using their preferred cryptocurrencies. More so, RSK-based DeFi features could be integrated into the platform to allow for financial products that can allow ending or yield generation from donations. In summary, the future applications and expansion of a trustless donation platform hold immense promise. By leveraging the power of Rootstock and Bitcoin, we can create a more secure, transparent, and trustworthy environment for charitable giving. Resources Rootstock Built for Bitcoin Blockchain for Good Sidechain and RSK Rootstock Fundamental Does Social Trust Influence Charitable Giving for NGOs? Why is Trust in NGOs failing – World Economic Forum What is Multisig and How does it work Smart Bitcoin Rootstock Built for Bitcoin Rootstock Built for Bitcoin Blockchain for Good Blockchain for Good Sidechain and RSK Sidechain and RSK Rootstock Fundamental Rootstock Fundamental Does Social Trust Influence Charitable Giving for NGOs? Does Social Trust Influence Charitable Giving for NGOs? Why is Trust in NGOs failing – World Economic Forum Why is Trust in NGOs failing – World Economic Forum What is Multisig and How does it work What is Multisig and How does it work Smart Bitcoin Smart Bitcoin

 $42 Billion and a Trustless Donation Platform

Building Trust in the Digital Economy With Blockchain Powered Digital Identity Verification

Trust-based Currencies on Blockchain: Trustlines Network, Circles UBI, and Karma

Blockchain-də etimad əsaslı valyutalar: Trustlines Network, Circles UBI və Karma

Валюты на аснове даверу на блокчейне: сетка Trustlines, Circles UBI і Karma

ব্লকচেইনে বিশ্বাস-ভিত্তিক মুদ্রা: ট্রাস্টলাইন নেটওয়ার্ক, সার্কেল ইউবিআই, এবং কর্ম

Monedas basadas en la confianza en la cadena de bloques: Trustlines Network, Circles UBI y Karma

Luottamukseen perustuvat valuutat Blockchainissa: Trustlines Network, Circles UBI ja Karma

מטבעות מבוססי אמון בבלוקצ'יין: Trustlines Network, Circles UBI ו-Karma

ブロックチェーン上の信頼に基づく通貨: Trustlines Network、Circles UBI、Karma

Waluty oparte na zaufaniu w Blockchain: Trustlines Network, Circles UBI i Karma

Meny založené na dôvere na blockchaine: Trustlines Network, Circles UBI a Karma

Trust-based Currencies paBlockchain: Trustlines Network, Circles UBI, uye Karma

Асъорҳои боваринок дар Blockchain: Шабакаи Trustlines, Circles UBI ва Karma

Tiền tệ dựa trên sự tin cậy trên Blockchain: Trustlines Network, Circles UBI và Karma

Traditionally speaking, the banking system works with the help of a vast network of reliable intermediaries. Despite its challenges and shortcomings, we continue to rely on it to protect our funds and valuables – primarily in the virtual safe deposit box. This trust has been built over the centuries by the traditional banking system. Meanwhile, in the non-traditional landscape of cryptocurrency, the idea of a self-custody wallet has continued to gain traction even though bad actors are constantly in the news for hacking exchanges. While the crypto industry has undergone significant development, it is still very much plagued by scams and hacks that undermine efforts to build trust among millions of potential users. Crypto has an image problem, despite the promises of a self-custody revolution, and this is only aggravated by the instances of “overnight millionaires”. As a technological innovation, self-custody, which moves the management of assets into the hands of customers, represents a paradigm shift. It eliminates third-party involvement—a feature that can be a lifesaver as many platforms such as Terra, Celsius, and FTX, to mention a few, have crumbled causing significant losses to the tune of $40 billion as per CoinDesk. Building Trust Over Time It has taken several years of legal framing and enhancing the security measures of the conventional banking systems for people to develop trust in those systems. For instance when Silicon Valley Bank went bust, requisite measures to deal with customer losses were instituted without any delay. Crypto business, conversely, is a rather ill-defined and continuously developing market that still has no set rules to follow. Trust in this space has often been lost due to several failures as well as fraud-related cases. Consequently, self-custody appears to be the most viable innovation in such an environment. We can own assets outright and decrease the risk associated with third parties, which makes the process free from their intervention. The Role of Technology in Enhancing Security In the future, as this industry develops, we should also see these self-custody technologies reach the same high levels of trust and reliability as the present-day banking sector. Currently, CCData reveals that over one hundred providers can be identified all over the world to provide custodial solutions to retail and institutional investors looking to invest in crypto assets. The consolidation of the industry is foreseeable, as it is borne out by the experiences of sectors such as banking and the internet when transitions are initiated to tighten up security and instill greater trust in the industry. Distrust of centralized infrastructure is another problem that might appear unfathomable for retail users, but self-custody is imperative. The self-custody market remains to be developing, providing better and more consumer-friendly solutions that handle assets on the user‘s behalf. Additionally, self-custody is not only about transitioning between one technological paradigm and another – but a paradigm shift in thought. That is an indication of a shift towards self-organization and one’s faith in the financial systems. Unfortunately, self-custody will become one of the standards as crypto develops further for those who want their funds to be secure. Challenges Facing Web3 Wallet Management Currently, managing a Web3 wallet comes with the following challenges: Seed Phrases A Web3 wallet most importantly comprises the seed phrase recognized as a recovery phrase. It serves the purpose of becoming a unique identifier, allowing users to restore their wallets on various gadgets. It is a 12-24 random word phrase, and losing such a phrase will result in permanent loss of wallet and any of the funds stored in it. Unfortunately, there is no organized service to recover the phrase, and the total burden lies on the user. The problem lies in the question of how to safely store this seed phrase securely at the same time. It is too long and random that users cannot memorize it easily, and when they write it down or store it in an informatics device, there are some dangers involved. If the physical copy is lost, damaged, or stolen — or if a digital copy of the information is cracked — the user’s wallet could leak or could be locked away forever. Generating and Remembering Strong Passwords The majority of Web3 wallets also force users to set essential passwords to enhance the application’s protection. Such passwords must be used so that one is long and different from those used in the other accounts and contains symbols that cannot be subjected to hacking or brute force. However, this creates a significant challenge: how to achieve the best password creation to meet the standard of secularity while, at the same time be okay with the user to remember it. The reality is that there is no one server that a person can turn to get help, and as such, if the password is gone, so is the wallet. Worse still, fundamental password reset strategies such as receiving password reset links via email are not feasible in Web 3. As a result, the wallet remains closed for all eternity if the user forgets or loses the password to the wallet. This password is only with the user, so password insecurity is still an issue when managing Web3 wallets. Protecting Against Phishing Scams and Malware Crypto phishing scams are one of the most common types of scams actively used in the Web3 ecosystem. The attackers continue hiding behind the replica of any type of service or person, using techniques ranging from private keys to passwords from the user. As pointed out it has been noted that this kind of scam has evolved in a way that when the individual clicks on the links to the sites involved, these look almost like the real site, putting even the intelligent users at the mercy of the con-men. Malware is another huge problem because it is easy to spread an infected file or program into an organization's network. This can be acquired through downloads or by clicking on links in ads and will surreptitiously steal wallet details. For example, some malware may keep track of the clipboard of the user to replace the copied wallet address with a fake one, so as to guarantee that users deposit their cash into the wrong wallet. That is why pointing interest from the user and awareness of threats in the information space is needed to prevent these forms of attacks. Remaining Cautious of Unknown Links and Downloads Among the most used attack methods in Web3 is using links or downloads, which sound familiar or unknown to the user. If the user clicks on a fraudulent link, then the wallet becomes vulnerable to phishing sites, or the user's device is infected with malware. These are attacks with the intent of capturing the private key or otherwise phishing users into signing up for fraudulent transactions. Given the fact that Web3 is a decentralized network system, there is effectively no protection, and users are their self-defense line. This challenge is especially challenging because links can be disguised in several different ways, shapes, and forms. It comes from emails pretending to be from customer support or alert services on social media sites. One can compromise their account easily simply by downloading a well-known wallet plugin from untrusted sources. It makes every exchange that occurs through the platforms a potential risk that needs to be avoided. How GRVT Is Challenging The Notion of Private Key The GRVT Wallet simplifies the user experience through Web Authentication (WebAuthn), which allows users to create and access their wallet using a password and passkeys, avoiding the complexities associated with traditional crypto wallets. The integration of Dfns technology allows users to access their wallets via fingerprint or facial recognition, offering quick and secure authentication similar to traditional online banking. And it blends the user-friendliness of Web2 with the security of self-custody, protecting assets without the technical burdens. By leveraging off-chain, peer-to-peer networks with multi-party computation (MPC) and public key infrastructure, it is able to guarantee: No Single Point of Failure: GRVT Wallet supports multiple devices, creating multiple security layers to prevent breaches. Responsive Recovery: Recovery wallets and backup codes provide fail-safes if credentials are lost. Uninterrupted Transactions: Linking new devices doesn’t affect public key, allowing continuous transfers. Conclusion The question of why the conventional banking system continues to thrive despite its shortcomings and the revolutionary advantage of the self-custody system boils down to trust. Millions around the world still feel safe to keep their money and other valuables in the banks and the incidence of crypto scams and losses has increasingly overshadowed the prospects of a generational transition from modern banking to cryptocurrency and self-custody wallet. This problem is further aggravated by the technical complexities surrounding the use of a smart contract wallet, which requires a level of skill to operate. Nonetheless, the possibility for both systems to exist side-by-side in the future is worth considering. Traditionally speaking, the banking system works with the help of a vast network of reliable intermediaries. Despite its challenges and shortcomings, we continue to rely on it to protect our funds and valuables – primarily in the virtual safe deposit box. This trust has been built over the centuries by the traditional banking system. Meanwhile, in the non-traditional landscape of cryptocurrency, the idea of a self-custody wallet has continued to gain traction even though bad actors are constantly in the news for hacking exchanges. While the crypto industry has undergone significant development, it is still very much plagued by scams and hacks that undermine efforts to build trust among millions of potential users. Crypto has an image problem, despite the promises of a self-custody revolution, and this is only aggravated by the instances of “overnight millionaires”. As a technological innovation, self-custody, which moves the management of assets into the hands of customers, represents a paradigm shift. It eliminates third-party involvement—a feature that can be a lifesaver as many platforms such as Terra, Celsius, and FTX, to mention a few, have crumbled causing significant losses to the tune of $40 billion as per CoinDesk . Crypto CoinDesk Building Trust Over Time It has taken several years of legal framing and enhancing the security measures of the conventional banking systems for people to develop trust in those systems. For instance when Silicon Valley Bank went bust, requisite measures to deal with customer losses were instituted without any delay. Silicon Valley Bank Crypto business, conversely, is a rather ill-defined and continuously developing market that still has no set rules to follow. Trust in this space has often been lost due to several failures as well as fraud-related cases. Consequently, self-custody appears to be the most viable innovation in such an environment. We can own assets outright and decrease the risk associated with third parties, which makes the process free from their intervention. The Role of Technology in Enhancing Security In the future, as this industry develops, we should also see these self-custody technologies reach the same high levels of trust and reliability as the present-day banking sector. Currently, CCData reveals that over one hundred providers can be identified all over the world to provide custodial solutions to retail and institutional investors looking to invest in crypto assets. The consolidation of the industry is foreseeable, as it is borne out by the experiences of sectors such as banking and the internet when transitions are initiated to tighten up security and instill greater trust in the industry. Distrust of centralized infrastructure is another problem that might appear unfathomable for retail users, but self-custody is imperative. The self-custody market remains to be developing, providing better and more consumer-friendly solutions that handle assets on the user‘s behalf. Additionally, self-custody is not only about transitioning between one technological paradigm and another – but a paradigm shift in thought. That is an indication of a shift towards self-organization and one’s faith in the financial systems. Unfortunately, self-custody will become one of the standards as crypto develops further for those who want their funds to be secure. Challenges Facing Web3 Wallet Management Currently, managing a Web3 wallet comes with the following challenges: Seed Phrases A Web3 wallet most importantly comprises the seed phrase recognized as a recovery phrase. It serves the purpose of becoming a unique identifier, allowing users to restore their wallets on various gadgets. It is a 12-24 random word phrase, and losing such a phrase will result in permanent loss of wallet and any of the funds stored in it. Unfortunately, there is no organized service to recover the phrase, and the total burden lies on the user. The problem lies in the question of how to safely store this seed phrase securely at the same time. It is too long and random that users cannot memorize it easily, and when they write it down or store it in an informatics device, there are some dangers involved. If the physical copy is lost, damaged, or stolen — or if a digital copy of the information is cracked — the user’s wallet could leak or could be locked away forever. Generating and Remembering Strong Passwords The majority of Web3 wallets also force users to set essential passwords to enhance the application’s protection. Such passwords must be used so that one is long and different from those used in the other accounts and contains symbols that cannot be subjected to hacking or brute force. However, this creates a significant challenge: how to achieve the best password creation to meet the standard of secularity while, at the same time be okay with the user to remember it. The reality is that there is no one server that a person can turn to get help, and as such, if the password is gone, so is the wallet. Worse still, fundamental password reset strategies such as receiving password reset links via email are not feasible in Web 3. As a result, the wallet remains closed for all eternity if the user forgets or loses the password to the wallet. This password is only with the user, so password insecurity is still an issue when managing Web3 wallets. Protecting Against Phishing Scams and Malware Crypto phishing scams are one of the most common types of scams actively used in the Web3 ecosystem. The attackers continue hiding behind the replica of any type of service or person, using techniques ranging from private keys to passwords from the user. As pointed out it has been noted that this kind of scam has evolved in a way that when the individual clicks on the links to the sites involved, these look almost like the real site, putting even the intelligent users at the mercy of the con-men. Malware is another huge problem because it is easy to spread an infected file or program into an organization's network. This can be acquired through downloads or by clicking on links in ads and will surreptitiously steal wallet details. For example, some malware may keep track of the clipboard of the user to replace the copied wallet address with a fake one, so as to guarantee that users deposit their cash into the wrong wallet. That is why pointing interest from the user and awareness of threats in the information space is needed to prevent these forms of attacks. Remaining Cautious of Unknown Links and Downloads Among the most used attack methods in Web3 is using links or downloads, which sound familiar or unknown to the user. If the user clicks on a fraudulent link, then the wallet becomes vulnerable to phishing sites, or the user's device is infected with malware. These are attacks with the intent of capturing the private key or otherwise phishing users into signing up for fraudulent transactions. Given the fact that Web3 is a decentralized network system, there is effectively no protection, and users are their self-defense line. This challenge is especially challenging because links can be disguised in several different ways, shapes, and forms. It comes from emails pretending to be from customer support or alert services on social media sites. One can compromise their account easily simply by downloading a well-known wallet plugin from untrusted sources. It makes every exchange that occurs through the platforms a potential risk that needs to be avoided. How GRVT Is Challenging The Notion of Private Key How GRVT Is Challenging The Notion of Private Key The GRVT Wallet simplifies the user experience through Web Authentication (WebAuthn), which allows users to create and access their wallet using a password and passkeys, avoiding the complexities associated with traditional crypto wallets. The integration of Dfns technology allows users to access their wallets via fingerprint or facial recognition, offering quick and secure authentication similar to traditional online banking. And it blends the user-friendliness of Web2 with the security of self-custody, protecting assets without the technical burdens. By leveraging off-chain, peer-to-peer networks with multi-party computation (MPC) and public key infrastructure, it is able to guarantee: No Single Point of Failure: GRVT Wallet supports multiple devices, creating multiple security layers to prevent breaches. Responsive Recovery: Recovery wallets and backup codes provide fail-safes if credentials are lost. Uninterrupted Transactions: Linking new devices doesn’t affect public key, allowing continuous transfers. Conclusion The question of why the conventional banking system continues to thrive despite its shortcomings and the revolutionary advantage of the self-custody system boils down to trust. Millions around the world still feel safe to keep their money and other valuables in the banks and the incidence of crypto scams and losses has increasingly overshadowed the prospects of a generational transition from modern banking to cryptocurrency and self-custody wallet. This problem is further aggravated by the technical complexities surrounding the use of a smart contract wallet, which requires a level of skill to operate. Nonetheless, the possibility for both systems to exist side-by-side in the future is worth considering.

The Vaults vs. Self-Custody: A Trust Revolution in Modern Finance

The Vaults vs Self-Custody: A Trust Revolution in Modern Finance

Сховішчы супраць самастойнай апекі: рэвалюцыя даверу ў сучасных фінансах

Трезорите срещу самопопечителство: Революция на доверието в съвременните финанси

Las bóvedas frente a la autocustodia: una revolución de la confianza en las finanzas modernas

Brankas vs. Penitipan Diri: Revolusi Kepercayaan dalam Keuangan Modern

金庫 vs. 自己管理：現代金融における信頼革命

Trezory vs. Vlastná úschova: Revolúcia dôvery v modernom financii

தி வால்ட்ஸ் எதிராக சுய-கஸ்டடி: நவீன நிதியத்தில் ஒரு நம்பிக்கைப் புரட்சி

Kasalar ve Öz-Muhafaza: Modern Finansta Bir Güven Devrimi

Các két sắt so với quyền tự lưu giữ: Một cuộc cách mạng về lòng tin trong tài chính hiện đại

Interaction, Repetition and Trust: Are These Opt-out?

… Which Still Doesn’t Look Very Good for Harris. So far, in my own little forecast for the 2024 U.S. presidential election, I've produced two predictions: ① One purely based on a weighted average of high-quality 2024 polling. ② The above, but corrected by the average of the 2016/20 polling error. (Please see this article for details on methodology.) From now on, I'm going to include a third one, assuming this year's polling error will only be half of the 2016/20 average error. Let me elaborate. It's most probably just as unrealistic to assume there'll be negligible systematic polling error in the swing states this year (①) as to assume it'll be as big as in 2016/20 (②). The truth will most probably lie somewhere in the middle. Pollsters have been busy identifying reasons for their previous misses and finding potential fixes. For instance, to tackle nonresponse bias and challenges in identifying likely voters, they increasingly rely on mixed modes to contact participants and have improved weighting based on the 2020 vote preferences of respondents. Hence, it's unlikely the polling error in 2024 will be as extensive as before. However, it's equally unlikely it'll all but disappear. While pollsters do have a good understanding of what probably caused polling errors in 2016/20, it's unclear if their adjustments will be effective. On top of that, there are efforts to make it harder for certain groups to vote, virtually all of which are carried out by Republicans (cf. https://www.democracydocket.com/). For instance, the RNC sued to remove thousands of registered voters in Arizona, Michigan, North Carolina, and Nevada. Also, there has been a deliberate reduction in polling places, often in predominantly black areas. Here, as well, the question is how effective these measures will be. But it's safe to assume there'll be people who participated in opinion polling with the intent to vote and then won't (be able to). Therefore, as already said, the truth will most probably lie somewhere in the middle. Ergo: a third prediction with half the polling error from the two previous election cycles. I've also adjusted one more thing in all predictions: as Pew Research explains, opinion polls' "real margin of error is often about double the one reported." Hence, I'm multiplying all standard deviations by 2 now. Alright, now—finally!—for my latest forecast. ① Here's the state of the race based on weighted high-quality polls only: ② When adjusted by the full average polling error from 2016/20: ③ And with just half the average polling error from 2016/20: Please feel free to head over to my Github—where I'll collect and archive everything—and have a look at the complete data and calculations in the latest Excel file: https://github.com/maxspeicher/2024-us-presidential-election I also post regular updates on Twitter (now 𝕏): https://twitter.com/maxspeicher … Which Still Doesn’t Look Very Good for Harris. … Which Still Doesn’t Look Very Good for Harris. So far, in my own little forecast for the 2024 U.S. presidential election, I've produced two predictions: own little forecast ① One purely based on a weighted average of high-quality 2024 polling. ① ② The above, but corrected by the average of the 2016/20 polling error. ② (Please see this article for details on methodology.) this article From now on, I'm going to include a third one, assuming this year's polling error will only be half of the 2016/20 average error. Let me elaborate. half It's most probably just as unrealistic to assume there'll be negligible systematic polling error in the swing states this year (①) as to assume it'll be as big as in 2016/20 (②). The truth will most probably lie somewhere in the middle. Pollsters have been busy identifying reasons for their previous misses and finding potential fixes. For instance, to tackle nonresponse bias and challenges in identifying likely voters, they increasingly rely on mixed modes to contact participants and have improved weighting based on the 2020 vote preferences of respondents. Hence, it's unlikely the polling error in 2024 will be as extensive as before. Pollsters have been busy However, it's equally unlikely it'll all but disappear. While pollsters do have a good understanding of what probably caused polling errors in 2016/20, it's unclear if their adjustments will be effective. On top of that, there are efforts to make it harder for certain groups to vote, virtually all of which are carried out by Republicans (cf. https://www.democracydocket.com/ ). probably https://www.democracydocket.com/ For instance, the RNC sued to remove thousands of registered voters in Arizona, Michigan, North Carolina, and Nevada. Also, there has been a deliberate reduction in polling places , often in predominantly black areas. Here, as well, the question is how effective these measures will be. But it's safe to assume there'll be people who participated in opinion polling with the intent to vote and then won't (be able to). RNC sued to remove reduction in polling places Therefore, as already said, the truth will most probably lie somewhere in the middle. Ergo: a third prediction with half the polling error from the two previous election cycles. I've also adjusted one more thing in all predictions: as Pew Research explains , opinion polls' "real margin of error is often about double the one reported." Hence, I'm multiplying all standard deviations by 2 now. Pew Research explains Alright, now—finally!—for my latest forecast. ① Here's the state of the race based on weighted high-quality polls only: ① ② When adjusted by the full average polling error from 2016/20: ② ③ And with just half the average polling error from 2016/20: ③ Please feel free to head over to my Github—where I'll collect and archive everything—and have a look at the complete data and calculations in the latest Excel file: https://github.com/maxspeicher/2024-us-presidential-election https://github.com/maxspeicher/2024-us-presidential-election I also post regular updates on Twitter (now 𝕏): https://twitter.com/maxspeicher https://twitter.com/maxspeicher

Polling Error or No Polling Error? The Truth Will Probably Lie Somewhere in the Middle

TL;DR: The evolution of trust, reputation and authority Trust No(One) Reputation has been the center of tribal human interaction, growing from word-of-mouth trust in small communities to algorithmically quantified scores in today's digital world. It's an invisible currency, shaping our social and professional lives and growing with the technology eating the world. The concept of reputation is not new in science fiction, but today trends with artificial intelligence, and the blockchain-based decentralized world we're currently building. One of the best thinkers in science fiction history: Isaac Asimov anticipated the importance of reputation in a hyper-connected future. His Foundation books revolve around predicting human behavior on a large scale with the idea of reputation management in governance and technology. Asimov's famous "psychohistory" relies on understanding and predicting the actions of huge groups of people based on their collective behaviors, mimicking the way reputational scores in digital systems work today. In software development, "fail-safe" systems with multiple redundancies rely heavily on trust. If a component fails, its partners bully it, lowering its votes on choosing a solution to a problem. Systems that coordinate to ensure reliability, like distributed databases or fault-tolerant microservices, use this voting concept. When a piece fails, another picks up the piece in the slack, keeping the system's reputation intact. The same happens with human trust networks, where the reliability of individuals or systems can buffer potential failures by relying on others to reinforce the gap. No chain is stronger than its weaker link. In the Black Mirror episode "Nosedive," reputation becomes an all-encompassing social credit score, dictating every aspect of a person’s life, from their social interactions to access to essential services. The more highly-rated someone is, the more power and privilege they are afforded. This TV chapter isn’t far from reality in some parts of the world today, where similar systems track and quantify people's reputations for various societal privileges. It is also a warning tale that explores the dystopian side of what happens when reputation becomes too pervasive and omnipresent. Another historical system built around reputation is the ELO chess rating. This system assigns players a numerical rating based on their performance, and updates based on wins or losses. It mirrors how reputation systems are built today, where success and failure adjust your standing, whether in chess, on social media, or within a decentralized network like Web3. The decentralized web may make reputational systems more granular, with users earning trust in different networks for specific skills, trades, or behaviors. Losing trust in one domain might not affect others, which adds resilience and complexity to managing personal reputation. Reputation in the Decentralized World The Web3 revolution, powered by the blockchain, decentralizes everything from finance to ownership and reputation systems. In this world, reputation doesn’t rely on a single governing authority, like a government or corporation. It’s shared and validated across multiple nodes and distributed through secure protocols. You gain or lose reputation based on interactions across various decentralized networks, from participation in decentralized finance to your contributions to open-source projects. Reputation is key in decentralized autonomous organizations where your position in the community impacts how much influence you hold. It's a world where your contributions, not your credentials, define you. Smart contracts may also build mechanisms for handling disputes or disagreements in reputation, offering transparency and requiring users to trust the underlying code and the people who built and deployed it. You can lose your reputation by failing to deliver on promises or being caught in malicious activities, as your on-chain actions are visible for everyone to scrutinize. Social Media and the Current State of Reputation Today’s social media platforms run on a form of reputational economy, quantified through likes, retweets, and followers. Except the system is broken. Social networks are opaque, easily manipulated, and often, lack the nuance needed to reflect true reputational value. A person can build a massive following based on charisma or polarizing opinions, with little regard for trustworthiness or expertise. A single misstep can lead you to be "canceled," a form of reputational collapse that occurs when public sentiment turns against you, often without due process or a chance for redemption. The problem with today’s reputation on platforms like Twitter or Instagram is that it’s too centralized and shallow. Algorithms designed to maximize engagement and screen time, not accuracy or trust, determine what rises to the top. Cancel culture amplifies this flaw, where reputational loss can be swift and brutal, often driven by mob mentality rather than any objective measure of wrongdoing. Trust in the Scientific Model and Experts Trust plays an essential role in reputation. In science and technology, people often need to trust experts because testing everything individually is impossible. You can't build your own Large Hadron Collider to verify the Higgs’ Boson in your backyard. You also can’t recreate experiments in gene editing unless you are a professional in the area. You trust the experts, institutions, and peer-reviewed systems with authority set up over centuries. The rise of misinformation is showing us that trust is fragile. The scientific model works since it’s based on evidence, reproducibility, and rigorous debate. In an age where everyone has a platform and misinformation spreads like wildfire, the expert reputation can be undermined with a few viral tweets or videos, and some people feel smarter preaching the earth is flat without trusting tons of evidence against it. The future challenge, especially in decentralized systems, is to build trust without relying on traditional gatekeepers. Systems like Web3 offer new ways to prove expertise—such as cryptographic proof of contributions—but they also open the door to new forms of manipulation and deceit. Keeping your reputation in such a world requires personal integrity and robust systems of validation that the community trusts. The evolution of trust, from the gold standard to trusting institutions without physical assets, reflects a profound shift in how societies and economies operate. The Future of Reputation and Humanity Reputation might develop into something even more complex, dynamic, and dispersed in the future. In a decentralized world, reputation systems might be attached to digital identities that span multiple domains—from work and social interaction to financial activities. Imagine a world where you build your reputation by pilling up micro-reputations across different blockchains and platforms, all visible and all contributing to your overall standing in society. Artificial intelligence may bring even greater difficulties for humans in maintaining its reputation. A.I. could automate reputation management, predicting reputational damage or gains based on real-time data analysis. But as with any algorithmic system, there’s the risk of reinforcing biases and unjust penalties. Quantum computing could enhance cryptographic protocols to secure reputational data, but it could also lead to new forms of hacking and identity manipulation. Humanity and the mechanisms that measure reputation and trust will both keep changing. The key will be finding a balance between transparency and privacy, and ensuring that reputational systems are fair, decentralized, and resilient enough to resist manipulation. Reputation is the new currency. Like any form of currency, its value will depend on the systems and frameworks you build around it, the trust we place in those systems, and the collective understanding of what it means to be trustworthy. TL;DR: The evolution of trust, reputation and authority TL;DR: The evolution of trust, reputation and authority Trust No(One) Reputation has been the center of tribal human interaction, growing from word-of-mouth trust in small communities to algorithmically quantified scores in today's digital world. It's an invisible currency, shaping our social and professional lives and growing with the technology eating the world. The concept of reputation is not new in science fiction, but today trends with artificial intelligence, and the blockchain-based decentralized world we're currently building. One of the best thinkers in science fiction history: Isaac Asimov anticipated the importance of reputation in a hyper-connected future. His Foundation books revolve around predicting human behavior on a large scale with the idea of reputation management in governance and technology. Foundation Asimov's famous "psychohistory" relies on understanding and predicting the actions of huge groups of people based on their collective behaviors, mimicking the way reputational scores in digital systems work today. In software development, "fail-safe" systems with multiple redundancies rely heavily on trust. If a component fails, its partners bully it, lowering its votes on choosing a solution to a problem. Systems that coordinate to ensure reliability, like distributed databases or fault-tolerant microservices, use this voting concept. When a piece fails, another picks up the piece in the slack, keeping the system's reputation intact. The same happens with human trust networks, where the reliability of individuals or systems can buffer potential failures by relying on others to reinforce the gap. No chain is stronger than its weaker link. In the Black Mirror episode "Nosedive," reputation becomes an all-encompassing social credit score, dictating every aspect of a person’s life, from their social interactions to access to essential services. Black Mirror The more highly-rated someone is, the more power and privilege they are afforded. This TV chapter isn’t far from reality in some parts of the world today, where similar systems track and quantify people's reputations for various societal privileges. It is also a warning tale that explores the dystopian side of what happens when reputation becomes too pervasive and omnipresent. Another historical system built around reputation is the ELO chess rating. This system assigns players a numerical rating based on their performance, and updates based on wins or losses. It mirrors how reputation systems are built today, where success and failure adjust your standing, whether in chess, on social media, or within a decentralized network like Web3. The decentralized web may make reputational systems more granular, with users earning trust in different networks for specific skills, trades, or behaviors. Losing trust in one domain might not affect others, which adds resilience and complexity to managing personal reputation. Reputation in the Decentralized World The Web3 revolution, powered by the blockchain, decentralizes everything from finance to ownership and reputation systems. In this world, reputation doesn’t rely on a single governing authority, like a government or corporation. It’s shared and validated across multiple nodes and distributed through secure protocols. You gain or lose reputation based on interactions across various decentralized networks, from participation in decentralized finance to your contributions to open-source projects. Reputation is key in decentralized autonomous organizations where your position in the community impacts how much influence you hold. It's a world where your contributions, not your credentials, define you. Smart contracts may also build mechanisms for handling disputes or disagreements in reputation, offering transparency and requiring users to trust the underlying code and the people who built and deployed it. You can lose your reputation by failing to deliver on promises or being caught in malicious activities, as your on-chain actions are visible for everyone to scrutinize. Social Media and the Current State of Reputation Today’s social media platforms run on a form of reputational economy, quantified through likes, retweets, and followers. Except the system is broken. Social networks are opaque, easily manipulated, and often, lack the nuance needed to reflect true reputational value. A person can build a massive following based on charisma or polarizing opinions, with little regard for trustworthiness or expertise. A single misstep can lead you to be "canceled," a form of reputational collapse that occurs when public sentiment turns against you, often without due process or a chance for redemption. The problem with today’s reputation on platforms like Twitter or Instagram is that it’s too centralized and shallow. Algorithms designed to maximize engagement and screen time, not accuracy or trust, determine what rises to the top. Cancel culture amplifies this flaw, where reputational loss can be swift and brutal, often driven by mob mentality rather than any objective measure of wrongdoing. Trust in the Scientific Model and Experts Trust plays an essential role in reputation. In science and technology, people often need to trust experts because testing everything individually is impossible. You can't build your own Large Hadron Collider to verify the Higgs’ Boson in your backyard. You also can’t recreate experiments in gene editing unless you are a professional in the area. You trust the experts, institutions, and peer-reviewed systems with authority set up over centuries. The rise of misinformation is showing us that trust is fragile. The scientific model works since it’s based on evidence, reproducibility, and rigorous debate. In an age where everyone has a platform and misinformation spreads like wildfire, the expert reputation can be undermined with a few viral tweets or videos, and some people feel smarter preaching the earth is flat without trusting tons of evidence against it. The future challenge, especially in decentralized systems, is to build trust without relying on traditional gatekeepers. Systems like Web3 offer new ways to prove expertise—such as cryptographic proof of contributions—but they also open the door to new forms of manipulation and deceit. Keeping your reputation in such a world requires personal integrity and robust systems of validation that the community trusts. The evolution of trust, from the gold standard to trusting institutions without physical assets, reflects a profound shift in how societies and economies operate. The Future of Reputation and Humanity Reputation might develop into something even more complex, dynamic, and dispersed in the future. In a decentralized world, reputation systems might be attached to digital identities that span multiple domains—from work and social interaction to financial activities. Imagine a world where you build your reputation by pilling up micro-reputations across different blockchains and platforms, all visible and all contributing to your overall standing in society. Artificial intelligence may bring even greater difficulties for humans in maintaining its reputation. A.I. could automate reputation management, predicting reputational damage or gains based on real-time data analysis. But as with any algorithmic system, there’s the risk of reinforcing biases and unjust penalties. Quantum computing could enhance cryptographic protocols to secure reputational data, but it could also lead to new forms of hacking and identity manipulation. Humanity and the mechanisms that measure reputation and trust will both keep changing. The key will be finding a balance between transparency and privacy, and ensuring that reputational systems are fair, decentralized, and resilient enough to resist manipulation. Reputation is the new currency. Like any form of currency, its value will depend on the systems and frameworks you build around it, the trust we place in those systems, and the collective understanding of what it means to be trustworthy.

Reputation and Trust - Rely on Others

The concept of trust has always been a somewhat fragile construction, akin to the finest silk cloth yet as strong as a knight's armor. It is that invisible glue that holds societies together, enabling human cooperation to scale from the family level right through to cities, nations, and global systems. But this eternal concept stands at a crossroads in the digital era. Its nature changing. With that come new complexities. Is trust the shining armor that fortifies the future or the scarlet stain marring our efforts to connect in a digitized world? The Old Guard: Relational Trust as Legacy For centuries, trust was relational; it was about building face-to-face. People shook hands with someone and looked someone in the eyes, and there was something physical about the trust given and received. This type of trust (let's call it "analog trust") represents a haptic experience. It requires personal investment, deep familiarity, and an echo of vulnerability. But even in its seeming purity, this trust was far from flawless. It was manipulable, as it was often a question of personal charisma or the level of hierarchy within the organizational structure that established someone's trustworthiness. The village elder, the priest, the banker—trust was usually intertwined with authority and sometimes to the harm of those least able to question it. This relational trust had, however, one indisputable strength: it could be resilient. It could be repaired, built anew, and enriched through shared experiences across time. The Dawn of Tech-Powered Trust: Armor With Cracks When digital trust as technology moved in, a model flipped on its head from the analog trust. In this case, trust wasn't culled through repeated, intimate human interactions but via algorithms, encryption, and smart contracts. Blockchain, DeFi, and decentralized technologies are promising a world of trust without intermediaries, one where code (not personal connective tissue) will ensure that everything remains fair. The shiny armor of digital trust is unbreakable transparency, immutability, and decentralization. This shining armor of promise also hides a great deal of flaws behind its glittering veneer. Tech-ensured trust is founded on a very flawed premise that systems cannot be corrupted and that technology is impartial. And as we have very well learned through faulty algorithms, hacking scandals, and the breakdown of decentralized governance, those cracks in the armor can be just as catastrophic as breaches in the analog world. The facelessness of the digital trust concept (where trustworthiness is only an equation) makes the failure feel more disillusioned when the system breaks. There is no one to blame; it is the very nature of trust in that context that becomes paradoxical because it can scale yet very well become increasingly brittle. Trust: Superpower or Weakness? One might say that trust, in its analog or digital forms, represents a weakness. It is the realization that we cannot control everything and, therefore, must rely on others or systems. In trusting, one opens oneself up to risk. It can be in the form of relational betrayal or technological breakdown within decentralized systems. Is trust, then, a vulnerability? Or is it, in fact, strength? Trust, in a decentralized world, is a superpower. Not because it makes us invincible but because it builds collective resilience. That's the beauty of this distributed system: it distributes the one thing needed - trust. No single entity can betray us because no single entity holds power. And it's this diffusion of trust that can make the collective stronger, the very act of trusting a form of empowerment. Equally, in relational trust, we often find strength, not in the moments when trust is upheld but in times when trust is broken and repaired. The real value of trust comes not from its perfection but from its ability to endure and adapt. Whether analog or digital, trust does not stand still. It is constantly in fluctuation, testing our judgment as to how far we want to trust the goodness of systems and people while simultaneously creating opportunities to rebuild an even stronger bond after such a moment of failure. Hybrid Trust: A Third Way? But maybe the most interesting evolution in trust is right at the crossroads of these two worlds: analog and digital. Hybrid trust, a blend of relational and tech-powered trust, is already a reality. Consider social media platforms where the trust is both relational (it's your network of friends and followers) and, at the same time, tech-driven, with algorithms curating what you see. Or consider decentralized finance, where trust in code and technology is complemented by trust in community governance and collaborative decision-making. This hybrid model might be a foreshadowing of what the future might hold in terms of moderating analogs open to manipulation and digitals to complete failure. Trust might be more like a multilayered construct, adaptive through a multiplicity of contexts fusing the personal with the technical. Conclusion: Armor Radiant, the Scarlet Stain Trusting, be it relational or powered with technology, is neither pure shining armor nor a scarlet stain. It is both, in a duality, that epitomizes the complication of human interconnectedness in the digital age. Though the methodology of building trust will change (evolving from handshake agreements to cryptographic signatures), the essence remains the same. I mean a delicate balance between risk and reward, vulnerability and strength. In this, I find the imperfections and possibilities of trust as a guiding force. One that even now shapes our actions in ways we're only beginning to understand. The concept of trust has always been a somewhat fragile construction, akin to the finest silk cloth yet as strong as a knight's armor. It is that invisible glue that holds societies together, enabling human cooperation to scale from the family level right through to cities, nations, and global systems. But this eternal concept stands at a crossroads in the digital era. Its nature changing. With that come new complexities. Is trust the shining armor that fortifies the future or the scarlet stain marring our efforts to connect in a digitized world? The Old Guard: Relational Trust as Legacy For centuries, trust was relational; it was about building face-to-face. People shook hands with someone and looked someone in the eyes, and there was something physical about the trust given and received. This type of trust (let's call it "analog trust") represents a haptic experience. It requires personal investment, deep familiarity, and an echo of vulnerability. But even in its seeming purity, this trust was far from flawless. It was manipulable, as it was often a question of personal charisma or the level of hierarchy within the organizational structure that established someone's trustworthiness. The village elder, the priest, the banker—trust was usually intertwined with authority and sometimes to the harm of those least able to question it. This relational trust had, however, one indisputable strength: it could be resilient. It could be repaired, built anew, and enriched through shared experiences across time. The Dawn of Tech-Powered Trust: Armor With Cracks When digital trust as technology moved in, a model flipped on its head from the analog trust. In this case, trust wasn't culled through repeated, intimate human interactions but via algorithms, encryption, and smart contracts. Blockchain, DeFi, and decentralized technologies are promising a world of trust without intermediaries, one where code (not personal connective tissue) will ensure that everything remains fair. The shiny armor of digital trust is unbreakable transparency, immutability, and decentralization. This shining armor of promise also hides a great deal of flaws behind its glittering veneer. Tech-ensured trust is founded on a very flawed premise that systems cannot be corrupted and that technology is impartial. And as we have very well learned through faulty algorithms, hacking scandals, and the breakdown of decentralized governance, those cracks in the armor can be just as catastrophic as breaches in the analog world. The facelessness of the digital trust concept (where trustworthiness is only an equation) makes the failure feel more disillusioned when the system breaks. There is no one to blame; it is the very nature of trust in that context that becomes paradoxical because it can scale yet very well become increasingly brittle. Trust: Superpower or Weakness? One might say that trust, in its analog or digital forms, represents a weakness. It is the realization that we cannot control everything and, therefore, must rely on others or systems. In trusting, one opens oneself up to risk. It can be in the form of relational betrayal or technological breakdown within decentralized systems. Is trust, then, a vulnerability? Or is it, in fact, strength? Trust, in a decentralized world, is a superpower. Not because it makes us invincible but because it builds collective resilience. That's the beauty of this distributed system: it distributes the one thing needed - trust. No single entity can betray us because no single entity holds power. And it's this diffusion of trust that can make the collective stronger, the very act of trusting a form of empowerment. Equally, in relational trust, we often find strength, not in the moments when trust is upheld but in times when trust is broken and repaired. The real value of trust comes not from its perfection but from its ability to endure and adapt. Whether analog or digital, trust does not stand still. It is constantly in fluctuation, testing our judgment as to how far we want to trust the goodness of systems and people while simultaneously creating opportunities to rebuild an even stronger bond after such a moment of failure. Hybrid Trust: A Third Way? But maybe the most interesting evolution in trust is right at the crossroads of these two worlds: analog and digital. Hybrid trust, a blend of relational and tech-powered trust, is already a reality. Consider social media platforms where the trust is both relational (it's your network of friends and followers) and, at the same time, tech-driven, with algorithms curating what you see. Or consider decentralized finance, where trust in code and technology is complemented by trust in community governance and collaborative decision-making. This hybrid model might be a foreshadowing of what the future might hold in terms of moderating analogs open to manipulation and digitals to complete failure. Trust might be more like a multilayered construct, adaptive through a multiplicity of contexts fusing the personal with the technical. Conclusion: Armor Radiant, the Scarlet Stain Trusting, be it relational or powered with technology, is neither pure shining armor nor a scarlet stain. It is both, in a duality, that epitomizes the complication of human interconnectedness in the digital age. Though the methodology of building trust will change (evolving from handshake agreements to cryptographic signatures), the essence remains the same. I mean a delicate balance between risk and reward, vulnerability and strength. In this, I find the imperfections and possibilities of trust as a guiding force. One that even now shapes our actions in ways we're only beginning to understand.

Trust in the Digital Age: The Shiny Armor and the Scarlet Stain

La confianza en la era digital: la armadura brillante y la mancha escarlata

Konfiantza Aro Digitalean: Armadura distiratsua eta Orban Escarlata

डिजिटल युग में भरोसा: चमकदार कवच और लाल रंग का दाग

Վստահություն թվային դարաշրջանում. փայլուն զրահը և կարմիր բիծը

デジタル時代の信頼：光り輝く鎧と緋色の染み

ជឿជាក់លើយុគសម័យឌីជីថល៖ គ្រឿងសឹកភ្លឺចាំង និងស្នាមប្រឡាក់ពណ៌ក្រហម

Дижитал эринд итгэх: Гялалзсан хуяг ба час улаан толбо

ඩිජිටල් යුගය කෙරෙහි විශ්වාසය: දිලිසෙන සන්නාහය සහ තද රතු පාට පැල්ලම

Sanly zamana ynam: Parlak ýaraglar we gyrmyzy tegmiller

Magtiwala sa Digital Age: The Shiny Armor and the Scarlet stain

Dijital Çağda Güven: Parlak Zırh ve Kızıl Leke

Niềm tin trong thời đại số: Bộ giáp sáng bóng và vết bẩn đỏ thẫm

Stories, News & Mentions about TRUTS

Truts’s Stories on HackerNoon

Truts's News & Mentions