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MetaMask co-founder Dan Finlay’s thoughts on the future of money Human needs are tangible goods, and cash is merely the means for exchanging tangible goods. A perfectly efficient economy, then, wouldn’t need cash as we currently understand it. , co-founder, believes that healthy economies hinge upon establishing networks of trust — ones in which people rely on each other to meet those tangible needs. He believes that the power of blockchain rests in its “unprecendented degrees of automation,” in which a person can add others to their secure, shared pools of resources with ease. Rather than dealing with lengthy loan applications and financial contracts, individuals can grant “transitive trust” via blockchains which allow trusted others to safely access one’s own tangible resources. Dan Finlay MetaMask People are compelled to keep their promises (to deliver on “loans” etc.) because of the social collateral they stand to lose if they free-ride or fail. In exchange for donating tangible resources to others, investors stand to profit from resource discounts the borrower offers for that initial transitive trust. Click to watch the full length interview. Dan Finlay gives the following example: a medical student might approach friends and family for aid going through school in the form of books, housing or food during their residency. In exchange, the student might issue promises (i.e. medical utility tokens) for future medical care. A breach in the contract would limit the student’s ability to secure resource help in the future. Trust and economic ability is born and dies alongside the keeping and breaking of promises in this decentralized marketplace. If this vision interests you, for more of Dan Finlay’s thoughts! watch the long-form interview I am building out the egalitarian infrastructure of the decentralized web with . ERA If you enjoyed this article, it would mean a lot if you gave it a clap, shared it, and connected with me on Twitter ! You can also subscribe to my YouTube channel!

Social Collateral and the Economy

ON THE CARE OF HEALTH.

Louise Penny, “The more things change, the more they stay the same. While the technology had changed, the job had not.” A Better Man In the recent Medical Futurist article , the author raises an interesting point that the key to improving health literacy lies in the un-digital design thinking. It makes one wonder: if digital health professionals are the masterminds behind the current digital health reality, then who we can task with the un-digital design thinking. I believe that the un-digital design thinking should be done in collaboration with the patients. The Fight Against The Ever-Widening Health Gap Between Rich And Poor This is by no means a new idea, and there are established institutions that have been calling for patient input for years. For example, the encourages patients and healthcare professionals to collaborate for improved healthcare outcomes. Furthermore, in 2014, encouraged researchers to involve patients in the paper review process and to identify how the research paper was impacted by the input from the patients. Society for Participatory Medicine British Medical Journal To steer the digital health wagon, we need to establish the essence of digital health. Is it a health app, a self-check-in, a virtual doctor appointment Is it a digital pill or a glucose tracker? How do we involve patients in design thinking for a highly specialized area? Patients leading the way With new wearable devices, patients begin to take lead on their health journey and directly influence new features and updates. For example, Apple sent out a to Apple Watch users to learn more about the health features and third healthcare apps they use. Unfortunately, this is not always the case with other digital health solutions. survey For example, virtual visits with a doctor are becoming a norm, but the question is for whom? For your grandparents? Probably not. Did anyone ask them if the current digital health format is convenient for them or was it forced upon them? Maybe the process should have started with a question? Input on how to make the experience better? An instruction? A clarification and reassurance that the doctor will provide you with the best of care and advise on necessary next steps? “The technology you use impresses no one. The experience you create with it is everything.” — Sean Gerety The paradox that I find of the utmost interest is that digital health solutions work because of the underlying human connection. e-Prescribing, for example, allows a clinician to see whether the prescription has been picked up from a pharmacy. It gives a doctor an insight into medication adherence, but for a patient, it also means that the doctor would know if the prescription had not been picked up. With a paper prescription, a patient could have lied to the doctor and not worried about the clinician finding out the truth. Hence one can make an argument that improved medication adherence rates connected to e-Prescribing hinge on the human connection and unwillingness to disappoint an authoritative figure. Digital health will continue to change Digital health is here to remain and to develop even further. And this is an excellent thing. A virtual visit at 8 am? A watch that tells me to get up more? At-home ultrasound for expecting mothers? Yes, there is now a home ultrasound scanner. https://www.youtube.com/watch?v=mjuIDQI9Xrc Digital health has many advantages, and one downside: we get obsessed with new technology and enthralled with our dreams for a better future that we forget who we are doing this all for. Patients. Let’s not leave them stranded and give them a product dictated only by our dreams and assumptions. Collaboration, human connection - and the future will be yours, my friend.

Wearable Devices Let Patients Take the Lead on their Health Journey

I’m 32 and spent $200k on biohacking. Became calmer, thinner, extroverted, healthier & happier.

Tengo 32 años y gasté $200k en biohacking. Se volvió más tranquilo, más delgado, extrovertido, más saludable y más feliz.

Five years ago, Frank Chen posed a question that has stuck with me every day since. The question was this, “If self-driving cars are 51% safer, are we not morally obligated to adopt them?”.  I’ve posed this question a ton of times over the past five years, and usually, a knee-jerk reaction leads to an interesting debate. What makes this question so great is the knife's edge – it’s not 99% safer, it’s not 70% safer, it’s 51% safer. only To put it into context. The National Highway Safety Administration has that in 2022, there were an estimated 42,795 traffic fatalities. 50% of 42,795 is 21,398 people, and 51% is 21,825 people. reported That means if self-driving cars are 51% safer, using them would save 427 people’s lives every year. That is about 1.5 Boeing 777 airplanes full of passengers. Is saving 427 lives a moral argument for adoption? In the five years I’ve been sharing this question, the answers are never simple. They’re always fraught with “what ifs.” But even if the answers lack clarity, I think the question is incredibly important. In part because it opens a broader — and equally important — debate on the moral imperative of AI adoption across many aspects of our lives and work. Because, after all, avoiding technology that could save lives may be just as ethically problematic as adopting technology too hastily, The Moral Imperative of AI Adoption I've always found the debate around autonomous vehicles to be a perfect microcosm for the broader discourse on AI. If we possess technology that's statistically safer than human-operated vehicles, isn't the moral choice obvious? Consider this: have shown that human drivers had a higher rate of crashes with a meaningful risk of injury than self-driving  (AI-powered) cars. Specifically, human drivers caused 0.24 injuries per million miles (IPMM) and 0.01 fatalities per million miles (FPMM), while self-driving cars caused 0.06 IPMM and 0 FPMM. studies And remember, these numbers aren't just statistics. They represent real lives that could be saved by embracing AI technology. But why stop at autonomous vehicles? The potential for AI to enhance safety, efficiency, and accuracy spans across fields like medicine, public health, food safety, agriculture, cybersecurity, crime prevention, and military science. If AI can diagnose diseases with greater accuracy than human doctors, predict crop failures before they devastate food supplies, or thwart cyber-attacks before they breach our data, don't we have a moral obligation to also utilize those technologies? Of course, these are dramatic examples, but the argument extends beyond life-and-death scenarios. AI's ability to improve our daily quality of life is equally compelling. Whether by simplifying mundane tasks or making information and services more accessible and equitable, AI can end drudgery and enhance our daily quality of life. The moral imperative to adopt AI isn't just about preventing harm or death; it's about whether we have an obligation to contribute to human well-being if we can. The Dilemma of Choice and Safety So, do we choose human-operated vehicles (or human-led processes) knowing they are less safe or efficient than their AI counterparts? Simply because they are more human? Faced with the choice between human-operated systems and AI-enhanced alternatives, my thought is the decision should obviously hinge on safety and efficiency rather than an allegiance to some murky idea of what is "human" or not. Embracing AI doesn't mean disregarding human value or input; rather, it's about acknowledging that what's human isn't inherently superior — and honestly, is often significantly inferior in specific contexts. Now please don’t get out the pitchforks, I’m not joining Team Robot Overlord. I get the anxiety a lot of people feel about the disruption AI is already causing to their jobs and the societal change that is undoubtedly headed our way. I just wonder whether the efficiencies of AI and the quality of life benefits might, in the long run, outweigh the impact of those disruptions. Some of our reluctance to adopt AI is informed by cognitive biases and fears. For a species famed for its adaptability, we humans don’t love change. Cognitive biases play a substantial role in our hesitance to embrace AI. Cognitive biases are psychological patterns that are a holdover from our early years as Homo Sapiens. They are the habits our minds fall into — cognitive shortcuts that can be useful when running from predators but definitely skew our modern perception and judgment. In this case, recognizing and addressing these biases is crucial in moving toward a more rational, ethical approach to AI adoption. Here are a few that I think could be in play, influencing our suspicion, trust, or acceptance of AI technologies. People tend to attribute human characteristics to AI or robots, influencing their trust and expectations. This can lead to unrealistic assumptions about AI systems' capabilities or the attribution of evil intentions. Anthropomorphism Bias: This bias leads individuals to overestimate the probability of events associated with memorable or vivid incidents. Sensationalized media reports about AI failures or successes can be blown out of proportion and disproportionately influence perceptions of AI reliability and safety. Availability Heuristic: What’s everyone else doing? People may seek out or interpret information in a way that confirms their preexisting beliefs or hypotheses about AI. This bias can hinder the objective evaluation of AI technologies and their potential benefits or risks. Confirmation Bias: People don’t want to miss out on beneficial technologies but can lack an understanding of the implications. This bias can overshadow critical evaluation and lead to premature adoption. This bias is related to the Bandwagon Effect (e.g., The tendency to do or believe things because everyone else does - or influencers do. People might trust or distrust AI technologies simply because that seems to be the popular sentiment. FOMO: People prefer to maintain the current state, which leads to resistance against adopting something new like AI, regardless of potential benefits or proven superiority. This bias can slow innovation and the adoption of potentially life-enhancing technologies. Status Quo Bias: This bias makes the pain of losing something feel more potent than the pleasure of gaining something of equal value. For AI, this means the fear of job loss or loss of control overshadows the benefits of safety/efficiency/convenience. Loss Aversion: Overestimation of one's ability to control or understand something. For AI, this means overestimating or underestimating the risks associated with AI. Overconfidence Bias: Numbers are scary! People tend to be biased against algorithms, believing human decision-making is superior, even when evidence suggests otherwise. On the other hand, some might also have an unquestioning trust in AI decisions, ignoring the potential for errors or biases in AI systems. Algorithm Aversion/Trust: Economic Rationality Interesting, right? But the truth is, this is all academic. We may not even get to make this decision in the end.  Companies are already making it. A ton of corporations are barreling ahead with AI integration — mainly because the ROI often speaks louder than ethical debates. Take with its significant shift towards automation. The efficiency and economic benefits are tangible and measurable, and in the face of cold hard cash, moral and social criticisms suddenly feel more academic. Amazon as a prime example, Still, this isn't only about stone-hearted capitalism; it's about survival and adaptation. Businesses are tasked every day with the challenge of balancing technological adoption with ethical and ESG responsibilities. The impact of AI on employment and human well-being can't be an afterthought. For thousands, financial stability and career wellness hinge on these decisions. It’s something a lot of enterprises are grappling with. And here's where the moral imperative question becomes more nuanced. If AI can streamline operations, reduce costs, and even create new opportunities, then aren’t we also morally responsible for exploring these technologies? The trick will be to keep that ethical compass handy and ensure that as we embrace AI's efficiencies, we also safeguard against its potential to unfairly disrupt livelihoods. We are in a Transition Period Either way, we need to watch our footing. We are standing on the precipice of a new era, and one solid push could end us in a freefall. AI is no longer a futuristic fantasy; it's absolutely embedded in our daily lives and work. That’s exciting — and scary as hell. One of the most significant challenges we face is the accessibility or tech gap. AI has the potential to democratize technology, making powerful tools available to a broader audience. However, right now, AI's promise is primarily being seen by those who already have a certain level of access, so there is also the potential that AI will exacerbate existing inequalities rather than alleviate them. It’s a period of adjustment, so it will require patience, education, and proactive measures to ensure that the benefits of AI are widely distributed. We’ve got the potential to level the playing field so that AI's potential can be unlocked for everyone, not just the privileged few. The Conundrum of Cooperation Okay, so it is a paradox:  For AI to function optimally alongside humans, it must be superior to us in certain tasks.  But that VERY superiority threatens to displace human roles, fueling resistance and fear among us mortals. This paradox creates a tough "push-pull" for AI; that’s why we’re seeing such heated debate about morality. I believe the solution may be a suite of emerging design philosophies and technologies aimed at bridging the gap between AI and human cooperation in an ethical way. I’ll list them below. They are worth asking ChatGPT about: ensures that AI systems are developed with human needs and values at their core. Human-Centric AI Design (HCAI): demystifies AI decisions, making them understandable and transparent to humans. Explainable AI (XAI): guide the development and deployment of AI systems in a manner that respects human rights and values. Ethical AI Frameworks: learns from and adapts to human feedback, ensuring a synergistic relationship. Adaptive/Responsive AI: involves end-users in the AI development process, ensuring their needs and concerns are addressed. Participatory Design: emphasizes AI's role in enhancing human abilities rather than replacing them. Augmented Intelligence: builds confidence in AI systems through reliability, safety, and ethical assurances. Trustworthy AI: To Self-Drive Cars, or to Not Self-Drive Cars? In wrapping up, I’ll take a stand. I think adopting AI is a moral imperative. In my view, the potential to save lives, enhance our quality of life, and even address long-standing inequalities is too significant to ignore. However, this doesn't mean we should dive headfirst without consideration.  In my opinion, we need to approach AI with a blend of enthusiasm and caution—staying excited to explore its possibilities but mindful of the ethical, social, and economic impact. Thoughtful consideration, robust ethical frameworks, and stringent governance are the keys to unlocking AI's potential responsibly. I’m still open to debate on the subject. So, I’ll throw the question out to you. Reply here or on my and tell me why I’m wrong — or right. I invite your thoughts and comments on this complex issue. LinkedIn thread Are we ready to embrace AI with the moral seriousness it demands? Are you ready to take your next road trip in a self-driving car?

Are We Morally Obligated to Adopt AI?

আমরা কি নৈতিকভাবে এআই গ্রহণ করতে বাধ্য?

Sind wir moralisch verpflichtet, KI einzuführen?

¿Estamos moralmente obligados a adoptar la IA?

Sommes-nous moralement obligés d’adopter l’IA ?

क्या हम नैतिक रूप से एआई को अपनाने के लिए बाध्य हैं?

私たちには AI を導入する道徳的義務があるのでしょうか?

우리는 AI를 채택해야 할 도덕적 의무가 있습니까?

Somos moralmente obrigados a adotar a IA?

Обязаны ли мы морально принять ИИ?

Ahlaki Olarak Yapay Zekayı Benimsetmek Zorunda mıyız?

Chúng ta có nghĩa vụ về mặt đạo đức phải áp dụng AI?

我们在道义上有义务采用人工智能吗？

On Dextaxation

While the COVID-19 pandemic has long faded into the rearview mirror, its lasting impact is still being felt on a widespread scale. For institutional investors, the global market volatility thrown up by an uneven post-pandemic recovery has thrown up fresh opportunities and risks throughout global markets. Although global growth has shown in the wake of the pandemic, an uneven recovery has been intensified by varying international responses to the health crisis, macroeconomic factors like historically high inflation, and the flare-up of geopolitical conflict in Europe and the Middle East. relative resilience In recent months, buoyed by exponential growth in the field of generative AI, the United States has been seen to outpace the likes of Europe and China. However, hopes of early Fed interest rate cuts in the US have been dashed due to lingering high inflation, and the prospect of a tumultuous and close-run presidential election in November may mean that no bloc is fully safe from uncertainty. What does this mean for institutional investors and discovering new opportunities in 2024? The answer may hinge on abandoning old reliances and building a more global outlook. Finding Value in Emerging Markets The impressive form of Sandglass Capital Management’s $262 million flagship fund last year underlined the quality of opportunities to be found in emerging markets (EMs). Returning a in 2023 through the purchase of high-risk government bonds in struggling nations like Sri Lanka, Ghana, Ukraine, and Greece, Sandglass’ returns through November were five times higher than the average in an index maintained by Hedge Fund Research. resounding 23% However, the performance of EMs is becoming increasingly convoluted, and hedge funds may be wise to look to the difficulties experienced throughout the Chinese economy as it struggles to keep up with market expectations. This has invariably pushed more institutions to look on a more widespread scale for opportunities within the world of investment opportunities throughout emerging markets. The view that emerging markets operate as a singular bloc like the European Union risks undermining the many key characteristics that differentiate across the landscape. While many share geopolitical risks and complex international relationships, they can be wildly different in their nature, and require plenty of exploration before institutions can act. Some of the many differences within emerging markets can include their respective roles as energy exporters or importers, and whether an economy is built on manufacturing or services. These can help to develop a more comprehensive understanding of markets and how they operate. For institutions with a more holistic overview of EM opportunities and risks, accessing a through real-time data centers can pave the way for stronger growth prospects as unpredictability continues to dampen the outlook across more traditional economies. full suite of global markets The Return of Risk 2024 is so far shaping up to become the year that risk appetite is returning to institutional investors. Much of this risk appears to revolve around exposure to global emerging markets, with March seeing the biggest rotation into EMs . since April 2017 According to , just under one-fifth of fund managers suggested that emerging market equities were set to become the biggest beneficiaries of US Federal Reserve rate cuts, ranking them behind only long-term growth prospects and value stocks in the survey. Bank of America polling The return of risk appetite throughout institutions is being driven by the expectation of a US economic recovery in 2024, but the uneven post-pandemic recovery still presents risks in the United States and beyond. In a recent survey charting the top global risks posed to economies in 2024, believed that extreme weather was the most likely to pose a material threat on a global scale during the year. However, pandemic recovery-related factors like a cost-of-living crisis and economic downturn accounted for a 75% combined share among respondents. 66% of the 1,490 respondents Other major concerns like an escalation of geopolitical conflict and generative AI misinformation or disinformation in an election year for many major economies also ranked high. For institutions seeking to level up their risk in emerging markets, sufficient due diligence must be conducted before building exposure. With headwinds continuing to loom, EMs carry a significant level of opportunity and danger for funds. Flocking to the Tropics One of the key areas in which hedge funds are looking for value appears to be within the tropics, as appetite for forex carry trades has seen turn their attention to the Brazilian real, Colombian peso, Mexican peso, and Indonesian rupiah with strong levels of upside. masses of market participants In cooler climates, a globalized FX drive can be found in the Hungarian florins’ newfound carry trade popularity, according to Bloomberg’s FX carry trade index, which measures the carry trade returns across various emerging markets. In Asia, global hedge funds have been , with institutions becoming infatuated with the nation’s growing depth and liquidity as a functional alternative to China’s ailing economy. seeking solace in India Recent players entering India’s markets include the Singapore-based hedge fund Dymon Asia Capital and Citadel Securities among various funds and brokers entering a frontier that had long been shunned by institutions due to taxation issues and the inability to hedge investments through short selling. Geopolitical Fragmentation Remains a Threat Although going global appears to be benefitting many risk-taking institutions already in 2024, leading asset manager BlackRock for the year that globalization is undergoing a ‘meaningful shift’ caused by geopolitical fragmentation and economic competition. warned in its outlook According to Trade Openness Index figures published by the BlackRock Investment Institute, trade integration since 2015 has begun falling at a rate that hasn’t been seen since the interwar period in the early 20th Century. This factor only adds to the level of complexity institutions are tasked with overcoming to flourish in the post-pandemic landscape. In a world that’s become increasingly unpredictable since the health crisis in 2020, market volatility is to be expected. For resourceful and risk-taking institutions backed by sufficient research, this presents a series of new opportunities throughout global markets. However, identifying and taking them will be a significant challenge in itself.

Why the Uneven Global Pandemic Recovery Will Lead More Institutions Into Global Markets Than Ever

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HINGE HEALTH

hingehealth.com

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Since 2015

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