Corporate Social Responsibility

$400M – that’s the price tag when sensitive #data ends up in the wrong hands. On May 11th, Coinbase – the largest US-based #crypto exchange (100M+ users, $330B in assets) – received a ransom demand for $20M. A threat actor claimed to have internal account documentation and customer data. Coinbase has refused to pay, instead boldly offering a $20M reward for information on the attackers. Coinbase’s May 14th SEC disclosure revealed the troubling root cause: overseas support agents were bribed to leak customer data, enabling targeted social-engineering attacks. While passwords and private keys appear safe, personal details – emails, phone numbers, addresses, government IDs, and account data – might have been compromised. The company is estimating a cost of $180M-$400M for remediation and voluntary customer reimbursements relating to the incident. This breach underscores a critical truth: insider access to sensitive data remains a massive, underestimated threat. Coinbase’s detection tools worked – identifying unauthorized access and firing the responsible individuals months earlier – but the data had already escaped. Identity management, DLP, and proactive data monitoring have never mattered more. AI agents add powerful new capabilities but also complicate the risk picture. If you’re a #founder building solutions around identity, insider risk, or data protection, I’d love to connect.

After $1B invested over 15 years, the Gates-backed Alliance for a Green Revolution in Africa (AGRA) promised agricultural prosperity. Instead, AGRA delivered ecological damage, farmer debt, and increased hunger, leaving target countries worse off than before the program began. AGRA began in 2006 with bold targets to double yields and incomes for 30M smallholder farmers while cutting food insecurity in half by 2020. Evaluations reveal what farmers already knew—AGRA failed to meet even its reduced goal of reaching just 9M farmers instead of the original 30M. The productivity gains fell dramatically short—only an 18% yield increase over 12 years against AGRA's promised 100%. Many regions saw growth equal to or worse than pre-AGRA rates. This structural failure hides behind selectively presented data and isolated success stories. Hunger increased by 30-31% across AGRA's 13 focus countries. The very metric AGRA was designed to improve has significantly worsened, exposing critical flaws in their entire approach to agricultural development. AGRA's single-crop farming model caused biodiversity loss by pushing farmers toward maize at the expense of hardy local varieties. Traditional climate-resilient crops declined measurably, with millet production dropping 24% between 2006-2018. Research in Zambia and Tanzania shows farmers trapped in debt after taking loans for fertilizer and hybrid seeds when harvests didn't deliver promised yields. This financial burden from input-dependency affects multiple generations of farming families. Beyond economic impacts, AGRA's chemical-intensive approach has accelerated soil degradation across target regions. Synthetic inputs disrupt soil microbial communities, compromising fertility and essential ecosystem functions like water storage and carbon sequestration. Specific soil contaminants associated with AGRA's model include PCBs, PBDEs, perfluoro carboxylic acids, benzene, and bisphenol A—compounds with documented adverse effects on ecological and human health. While AGRA now acknowledges soil degradation (65% of Sahel land affected), its solutions remain tied to chemical-intensive farming. New programs like ESMS and RE-GAIN show recognition of problems yet still fail to address their root causes. African civil society organizations increasingly call for redirecting funding from AGRA toward agroecological systems that align with both ecological imperatives and the lived realities of farming communities rather than imposing external technological dependencies. AGRA fundamentally misdiagnosed the problems facing African agriculture. After 15 years and $1B, hunger increased by 30%, yields barely improved, soils degraded, and farmers accumulated debt. Real solutions must restore ecological health while providing farmers with a pathway to prosperity.

Buy Now, Pay Forever? The Shadowy Underbelly of BNPL The Buy Now, Pay Later (BNPL) sector has exploded in popularity, hailed as a convenient and accessible financial tool. Yet, beneath the hype lies a troubling reality: BNPL may be fostering a generation of debt-burdened millennials and Gen Zers. This article, BIS analysis of BNPL , delves into the hidden risks of BNPL, exposing its predatory practices and challenging the "fintech for good" narrative. Hidden Costs and Risks: 1/ Debt Trap for the Vulnerable: BNPL targets younger demographics, often with limited financial literacy and stable income. Easy access to credit without thorough underwriting creates a perfect storm for overspending and debt accumulation. 2/ Invisible Burden: Unlike traditional loans, BNPL purchases often escape credit bureau reporting, creating a hidden debt burden that can negatively impact future borrowing. 3/ Subsidized by Everyone: Merchants absorb high BNPL fees, ultimately inflating prices for all consumers, regardless of payment method. Regulatory Blindspot: The rapid growth of BNPL has outpaced regulation, allowing loopholes and lax oversight. This lack of control has fueled predatory practices and irresponsible lending. Time for Accountability: Regulators are finally waking up to the dangers of BNPL. It's crucial to implement stricter regulations to protect consumers, promote responsible lending, and ensure greater transparency within the industry. Moving Forward: BNPL needs a fundamental shift. Instead of prioritizing profit and VC inflows, the focus must be on consumer protection, financial literacy, and responsible lending practices. Only then can BNPL truly live up to its purported image of being "fintech for good." The BNPL boom isn't just about delayed payments, it's about financial vulnerability and predatory lending. We must move beyond the hype and hold this industry accountable to ensure financial empowerment, not exploitation, for the next generation. Spread the word: Share this article with your network and raise awareness about the hidden risks of BNPL. Did you know about the hidden risks before you clicked on “Yes” to use pay later on your favourite digital platforms while buying something (big or small). Leave a comment and let us all learn together. #buynowpaylater #Fintech #DigitalPayments #BNPL #lending

What would happen if healthcare was centered around neighborhood residents co-creating health instead of depending on providers to respond to our ill health?   This visual, which comes from Wong Sweet Fun at Yishun Health, shows three types of health promotion.   What we have today is on the bottom – someone gets sick, and we respond to it.   A better approach would enable early intervention due to neighbors checking in on each other.   The ideal approach would nurture social connectivity such that neighbors improved each other’s health through close connectivity and regular activities organized by them – a real community.   Going from what we have to what we should have requires a major change in how we think about healthcare. Instead of providers being center stage residents should be. Providers adopt an asset-based community development strategy centered on galvanizing residents to undertake communal health-creating activities on their own, strengthening social bonds and interfamily networks in the process. The goal is co-create health, transforming service providers into facilitating supporters rather than central actors—a reversal of roles—and reimaging care such that it is integrated across health, social, environmental and behavioral domains.   This approach focuses on identifying and enhancing assets within rather than looking for problems that outside entities must address. It works in a defined geographical area—a neighborhood—and leverages groups of people bonded by common interests, local institutions, nature, built infrastructure, a variety of relationships and networks, and the stories, culture, and heritage of residents. The main assets are the residents, each of whom can contribute their talents, skills, experience, and time. The residents own their own—and their neighbors’—health, not the service providers, with social interaction a way for them to discover their own capacities for contribution to others. All of this enhances belonging, cohesion, and a sense of importance and agency. And the more these residents work together to produce health on their own, the less the need for outside systems. The result is much lower cost - something our current system desperately needs. How possible is this approach in the US? Anyone know any good examples? What would shift incentives such that this approach became more common? #health #community #neighborhood #singapore #relationships #aging Placemaking Education Cormac Russell Frances Kraft Usha Srinivasan Jennifer Prophete Gordon Strause Michael Skoler Kara Revel Jarzynski Sam Pressler Tracy Hadden Loh PlacemakingX Kevin Ervin Kelley, AIA Lory Warren Noah Baskett Dr J.R. Baker Matt Abrams Reyn Archer MD Daron Babcock Anna Scott Ethan Kent John B. Carol Naughton

Think Before You Share: The Hidden Cybersecurity Risks of Social Media 🚨🔐 In an era where data is the new currency, every post, check-in, or status update can serve as an intelligence goldmine for cybercriminals. What seems like harmless sharing—your vacation photos, workplace updates, or even a "fun fact" about your first pet—can be weaponized against you. 🔥 How Oversharing Exposes You to Cyber Threats 🔹 Geo-Tagging & Real-Time Location Leaks Sharing your location makes you an easy target. Cybercriminals use this data to track routines, monitor absences, or even launch physical security threats such as home burglaries. 🔹 Social Engineering & Credential Harvesting Those "what’s your mother’s maiden name?" or "which city were you born in?" quiz posts are a hacker’s playground. Attackers scrape these responses to guess password security questions or craft highly convincing phishing emails. 🔹 Metadata & Digital Fingerprinting Every photo you upload contains EXIF metadata (including GPS coordinates and device details). Attackers can extract this information, identify locations, and even map out behavior patterns for targeted cyberattacks. 🔹 OSINT (Open-Source Intelligence) Reconnaissance Threat actors don’t need sophisticated hacking tools when your social media profile provides a full dossier on your life. They correlate job roles, connections, and public interactions to execute whaling attacks, corporate espionage, or deepfake impersonations. 🔹 Dark Web Data Correlation Your exposed social media details can be cross-referenced with breached databases. If your credentials have been compromised in past data leaks, attackers can launch credential stuffing attacks to hijack your accounts. 🔐 Cyber-Hygiene: Best Practices for Social Media Security ✅ Restrict Profile Visibility – Limit exposure by setting profiles to private and segmenting audiences for sensitive updates. ✅ Sanitize Metadata Before Uploading – Use tools to strip EXIF data from images before posting. ✅ Implement Multi-Factor Authentication (MFA) – Enforce adaptive authentication to prevent unauthorized account access. ✅ Zero-Trust Mindset – Assume any publicly shared data can be aggregated, exploited, or weaponized against you. ✅ Monitor for Breach Exposure – Regularly check if your credentials are compromised using breach notification services like Have I Been Pwned. 🔎 The Internet doesn’t forget. Every post contributes to your digital footprint—control it before someone else does. 💬 Have you ever reconsidered a social media post due to security concerns? Drop your thoughts below! 👇 #CyberSecurity #SocialMediaThreats #Infosec #PrivacyMatters #DataProtection #Phishing #CyberSecurity #ThreatIntelligence #ZeroTrust #CyberThreats #infosec #cybersecuritytips #cybersecurityawareness #informationsecurity #networking #networksecurity #cyberattacks #CyberRisk #CyberHygiene #CyberThreats #ITSecurity #InsiderThreats #informationtechnology #technicalsupport

🎉 Pleased to share our paper published in Nature Portfolio digital medicine. 🥳 We’ve developed a comprehensive framework called CREOLA (short for Clinical Review Of Large Language Models (LLMs) and AI). This framework is pioneered at TORTUS, taking a safety-first, science approach to LLMs in healthcare. 🔹 Key Components of the CREOLA Framework -Error Taxonomy -Clinical Safety Assessment -Iterative Experimental Structure 🔹 Error Taxonomy Hallucinations: instances of text in clinical documents unsupported by the transcript of the clinical encounter Omissions: Clinically important text in the encounter that was not included in the clinical documentation 🔹 Clinical Safety Assessment: Our innovation incorporates accepted clinical hazard identification principles (based on NHS DCB0129 standards) to evaluate the potential harm of errors: We categorise errors as either ‘major’ or ‘minor’, where major errors can have downstream impact on the diagnosis or the management of the patient if left uncorrected.  This is further assessed as a risk matrix comprising of: Risk severity (1 (minor) to 5 (catastrophic)) compared with Likelihood assessment (very low to very high) 🔹 Iterative Experimental Structure We share a methodical approach to compare different prompts, models, and workflows. Label errors, consolidate review, evaluate clinical safety (and then make further adjustments and re-evaluate if necessary). ----------Method-------------- To demonstrate how to apply CREOLA to any LLM / AVT, we used GPT-4 (early 2024) as a case study here. 🔹 We conduct one of the largest manual evaluations of LLM-generated clinical notes to date, analyzing 49,590 transcript sentences and 12,999 clinical note sentences across 18 experimental configurations. 🔹 Transcripts-clinical note pairs are broken down to a sentence level and annotated for errors by clinicians. ----------Results-------------- 🔹 Of 12,999 sentences in 450 clinical notes, 191 sentences had hallucinations (1.47%), of which 84 sentences (44%) were major. Of the 49,590 sentences from our consultation transcripts, 1712 sentences were omitted (3.45%), of which 286 (16.7%) of which were classified as major and 1426 (83.3%) as minor. 🔹 Hallucination types Fabrication (43%) - completely invented information Negation (30%) - contradicting clinical facts Contextual (17%) - mixing unrelated topics Causality (10%) - speculating on causes without evidence 🔹 Hallucinations, while less common than omissions, carry significantly more clinical risk. Negation hallucinations were the most concerning 🔹 we CAN reduce or even abolish hallucinations and omissions by making prompt or model changes. In one experiment with GPT4 - We reduced incidence of major hallucinations by 75%, major omissions by 58%, and minor omissions by 35% through prompt iteration Links in comments Ellie Asgari Nina Montaña Brown Magda Dubois Saleh Khalil Jasmine Balloch Dr Dom Pimenta M.D.

Something is shifting in healthcare—but most people don’t have a name for it yet. It’s not just prior auth headaches, claim denials, or doctors drowning in paperwork. Those have always existed. What’s new is how quietly and systematically patients are being sorted, deprioritized, or excluded—often before they even seek care. This is Actuarial Medicine. Healthcare decisions are no longer just about clinical need. They’re being reshaped—not through outright denials, but through system design, automation, and interface constraints that subtly dictate the flow of care at scale. 🧮 Your medical record doesn’t just track your health—it generates a risk score that determines which treatments, referrals, or authorizations are frictionless and which face silent resistance. 🔁 Claims don’t just get denied—they get algorithmically stalled, redirected, or deprioritized before a human ever reviews them. 👨💻 Physicians aren’t just encouraged to consider cost—their tools nudge them toward pre-approved, lower-cost pathways, making other options harder to access. The Impact ❌ A test that was routine last year is now “not medically necessary”—but the denial appears as a pre-checked system recommendation, not an explicit rejection. ⏳ A referral that used to take weeks now takes months—not because of medical necessity, but because of administrative triage embedded in scheduling algorithms. 💊 A patient’s medication is switched to a cheaper alternative—not through direct denial, but because the better option is buried behind extra documentation and system hurdles. For patients with chronic, rare, or complex conditions, these aren’t just bureaucratic slowdowns—they are engineered barriers to care. And when those patients stop seeking treatment? The system records it as cost savings, not harm. This isn’t just about efficiency. It’s a fundamental shift in how care is controlled. And the longer it stays hidden, the harder it is to challenge. So let’s call it what it is: Actuarial Medicine. Are you seeing this in your work or care journey? How do we push back? Let’s talk. 👇 #ActuarialMedicine #Healthcare #AIinMedicine #HealthPolicy #MedicalEthics #HealthTech #DigitalHealth #PatientAccess

In a panel discussion some months ago, I said that anonymising personal data (PD) was a promising means of facilitating cross-border data flows, because once you can no longer identify an individual from the data, it should no longer fall within many countries' definition of PD, and would not be subject to export requirements. Someone asked if it was worth talking about anonymisation since it is reversible. I wasn't sure if it was a rhetorical question or philosophical question (if anonymisation is reversible, has there really been anonymisation?), or maybe we ascribed different meanings to the term, as do many jurisdictions. But in one of my LI posts I said that I would write more about it. This is what this post is about. When I use the term "anonymisation", I'm referring to the PDPC's definition of it i.e. the process of converting PD into data that cannot identify any particular individual, and can be reversible or irreversible. And to me, anonymisation is not like flipping a light switch such that you get light or no light, 1 or 0. There are factors that can affect re-identification of a person, e.g. - the number of direct and indirect identifiers in the dataset - what other data the organisation has access to (including publicly accessible info), which, when combined with the dataset, could re-identify the individual - what measures the organisation takes to reduce the possibility of re-identification e.g. restricting access to / disclosure of the dataset. So I think it is not so useful to think about anonymisation in binary terms. What I suggest we should think about is the possibility of re-identification. Think of a dimmer switch instead. When you see the cleartext dataset, that's when the light is on. When you start turning the dial down - the more direct and indirect identifiers you remove, the more safeguards you implement vis-a-vis the dataset - the dimmer the light gets, the possibility of re-identification is reduced. If you (a) remove all direct and indirect identifiers from a dataset, (b) encrypt it, and (c) only give need-to-know employees read access, I think the light's going to be pretty dim. It might no longer be PD, meaning that you can export it without being subject to export requirements. So yes, I think that anonymisation is a promising means of facilitating CBDF. Do note that you should also apply the "motivated intruder" test and consider if someone who has the motive to attempt re-identification, is reasonably competent, has access to appropriate resources e.g. internet, and uses investigative techniques, could re-identify the individual (see the ICO's excellent draft guidance https://lnkd.in/gmRfXj-W, and The Guardian's 2019 article https://lnkd.in/gZXfkHVC).

The Embedded Bias series by STAT sheds light on hidden biases — especially #racial and #gender biases — woven into the technologies and algorithms within our healthcare system. STAT, which is a media company that focuses on health, medicine and life sciences, dives deep into how these #biases affect patient care and outcomes. These critical insights show that bias in technology often reinforces the very health disparities we’re working to eliminate. The first part of this series exposes how racial biases in diagnostic tools can lead to inaccurate assessments for Black patients. The second reveals how gender biases in clinical trials have left women’s health concerns under-researched and under-treated. In later parts of the series, we see how bias in AI-driven healthcare solutions risks worsening disparities if not carefully checked. This investigation is a powerful reminder that transformative technology can still reflect and exacerbate existing societal inequities. If we’re not intentional about rooting out these biases, we risk further marginalizing communities already struggling to access quality care. https://bit.ly/3ZW14uD

The Business Case for Sustainability 🌎 Global economic and environmental conditions are reshaping the way businesses operate. Regulatory frameworks are becoming more stringent, consumer preferences are shifting toward responsible brands, and investors increasingly assess companies based on environmental, social, and governance (ESG) criteria. These factors have made sustainability a strategic priority rather than a compliance obligation. Companies that proactively integrate sustainability into their core operations enhance resilience, strengthen stakeholder relationships, and position themselves for long-term success. One of the most immediate advantages of sustainability is operational efficiency. Reducing waste, optimizing energy consumption, and improving supply chain management lead to significant cost savings. Regulatory agility further supports financial stability, ensuring compliance with evolving policies while mitigating legal and reputational risks. Businesses that stay ahead of regulatory trends maintain a competitive advantage and avoid disruptions linked to non-compliance. Market differentiation is another key benefit. Companies with strong sustainability commitments attract consumers who prioritize ethical and environmentally responsible products. Verified sustainability credentials build trust and enhance brand reputation, opening new revenue streams and fostering customer loyalty. Investors also recognize sustainability as a marker of strong governance and long-term value creation, improving access to capital and financial performance. Sustainability drives innovation by encouraging the development of new products, services, and business models that align with emerging trends. In an increasingly complex and uncertain global landscape, sustainability is a critical factor in future-proofing business operations. Climate risks, resource scarcity, and shifting stakeholder expectations require a forward-looking approach. Organizations that embed sustainability into strategic planning not only mitigate risks but also unlock new opportunities, ensuring adaptability and sustained growth in a rapidly evolving economy. This post is part of The Stakeholder Engagement Playbook, a bi-weekly series launched in partnership with The Sustainability Circle. #sustainability #sustainable #business #esg #climatechange #ROI