Future Of Work

🚨 BREAKING: Taiwan enacted its basic law on AI, which includes, among other innovative provisions, detailed AI governance principles and LABOR RIGHTS for humans who lose their jobs due to AI. Other countries should take note: According to the law's third article, the research and application of AI in Taiwan should adhere to the following principles (read them carefully!): 1. Sustainability: It should consider mental health, social equity, and environmental sustainability, reducing potential health risks or digital disparities, and enabling the public to adapt to the changes brought about by AI. 2. Human Autonomy: It should support human autonomy, respect fundamental human rights and cultural values such as the right to personality, allow for human oversight, and implement a people-centered approach that respects the rule of law, human rights, and democratic values. 3. Privacy Protection and Data Governance: It should respect the privacy and autonomy of personal data, adopt the principle of data minimization, and avoid the risk of data leakage. 4. Security: Cybersecurity measures should be established throughout the research and application of AI to prevent security threats and attacks, ensuring the robustness and security of the system. 5. Transparency and Explainability: AI outputs should be appropriately disclosed or labeled to facilitate risk assessment and understanding of their impact on relevant rights, thereby enhancing the trustworthiness of AI. 6. Fairness: AI research and application should avoid risks such as system bias and discrimination, and should not result in discrimination against specific groups. 7. Accountability: Traceability should be maintained, and different roles in AI research and application should bear corresponding responsibilities, including internal governance responsibilities and external social responsibilities. For those familiar with the EU AI Act, the way the principles above are framed is more direct and comprehensive than the European framework. As I wrote a few times before, the EU missed an opportunity to be more explicit and broad when protecting fundamental rights in the context of AI development and deployment (which could help set a stronger regulatory precedent). Another interesting provision is Article 12, focused on labor rights. It says that, in response to the development of AI, the government must address skill gaps and ensure workers' occupational safety, health, and labor rights, including providing employment assistance to those unemployed due to AI, based on their work abilities. To my knowledge, this is the first AI law that expressly foresees labor rights for those who lose their jobs due to AI. Well done, Taiwan! - 👉 To learn more about recent AI governance developments, join my newsletter's 90,000+ subscribers (below). 👉 To upskill and advance your career, join the 28th cohort of my AI Governance training in March (link below).

Some technologies don’t just solve problems — they give people their independence back. I rediscovered Liftware, and I was genuinely moved by what it can do. It looks simple: a smart handle connected to everyday utensils. But inside, it’s a powerful piece of engineering designed for people with hand tremors (Parkinson’s, essential tremor, and more). Here’s how it works: 🔹 Sensors detect tiny hand movements in real time 🔹 Micro-motors instantly counteract the tremor 🔹 The spoon or fork stays stable — even if the hand doesn’t The result? Up to 70% less shaking. And for many people, that means eating soup again… without help. This is technology at its best: invisible, intelligent, and deeply human. 💡 My take Most people don’t know this, but Liftware was developed by a small startup before being acquired by Google’s life sciences division (now Verily). What makes it remarkable is the engineering challenge: the device doesn’t try to stop the tremor — it predicts and cancels it. It’s basically a tiny real-time AI system… hidden inside a spoon. This is the future I love: not just smarter devices, but more compassionate ones. If you’ve seen other innovations that genuinely improve people’s lives, I’d love to discover them. What’s one piece of tech-for-good that inspired you recently? #techforgood #innovation #technology #healthtech #accessibility #assistivetechnology #futureofhealth #inclusiveDesign #AI #impact

India’s green economy is growing fast but LinkedIn data suggests green talent is growing even faster. The LinkedIn Hiring Rate (LHR) for green talent — defined as professionals with green skills, green job titles, or both — is now 59.7% higher than for the overall workforce. This means green-skilled professionals are significantly more likely to be hired than their peers, underscoring the growing demand for sustainability-focused roles. “The prioritisation of green talent by Indian companies is being fuelled by an interplay of policy reforms, rising consumer consciousness, and the need for deep business transformation,” says Neelima Burra, Chief Strategy, Transformation, and Marketing Officer at Luminous Power Technologies. “Government initiatives like the PM Suryaghar Yojna, National Solar Mission, and Smart City Mission, combined with the growing mandate for ESG reporting — are also pushing companies to recruit sustainability experts, carbon auditors, and ESG strategists to meet regulatory and investor expectations,” she adds further. Operational efficiency has emerged as the top skill across the top five industries increasingly hiring for green skills, as per LinkedIn data. In contrast, precision agriculture skills lead in farming, ranching, and forestry — highlighting how sector-specific green skills are evolving. “Operational efficiency offers the fastest route to tangible returns. It moves the conversation beyond regulatory compliance to net profitability, ensuring we can do more with less energy and fewer materials,” says Venu Nuguri Managing Director and CEO at Hitachi Energy. This surge in demand aligns with broader economic trends. Green jobs in India have grown over 10 times in the past five years, with Gen Z accounting for 63% of applicants, reports The Economic Times, citing a report by WeNaturalists. The projections are equally ambitious. India’s green economy will generate 7.29 million jobs by FY28 and 35 million by 2047, as the sector scales toward a $1 trillion valuation by 2030 and $15 trillion by 2070, suggests another report by The Economic Times, citing a report by NLB Services. The message is clear: green skills aren’t just good for the planet — they’re becoming essential for employability. As India accelerates its climate and economic goals, the workforce is already adapting. The question now is whether education, training, and policy can keep pace. Read the full report here: https://lnkd.in/g873CzHT #COP30 #GreenerTogether Source: The Economic Times: https://lnkd.in/d-3bShQP  The Economic Times: https://lnkd.in/dSUMFS58 

We’ve all heard about AI’s potential to boost productivity. But what truly matters to me is whether it’s making work better for the people who show up every day. At Cisco, our People Intelligence team, in collaboration with IT, has been exploring this very topic, and the findings are fascinating. Here are five key insights from our research that leaders should take seriously: 1. Leaders are key to adoption. At Cisco, employees are 2x more likely to use AI if their direct leader uses it. 2. Generic AI training doesn’t work. Role-specific, practical training accelerates AI use. 3. Confidence gaps exist among senior leaders. Directors at Cisco often feel less confident with AI than mid-level employees, underscoring the need for tailored support at all levels. 4. Employee autonomy fuels adoption. Hybrid work environments are powerful accelerators for AI adoption, while mandates can hinder it. Employees who voluntarily go to the office are more likely to use AI, while those who are required to work on-site have lower adoption. 5. AI use is linked to employee well-being, but the relationship is complex, with both benefits and trade-offs that require thoughtful navigation. This is just the beginning. Next, we’re looking at how AI is transforming the way teams operate. For now, one thing is clear, employees who use AI aren’t just more productive. They’re also more engaged, better aligned with company strategy, and empowered to focus on meaningful work. #AIAdoption #EmployeeExperience #FutureOfWork

Cloud Native technologies have long been at the heart of scalable applications. But now, with AI and Agentic Systems, the game is changing!   Unlike traditional AI automation, Agentic AI can make decisions, execute workflows, and adapt dynamically to system changes—without constant human oversight. This means self-healing, self-optimizing, and autonomous cloud-native infrastructure!  Here’s how Agentic AI can transform each layer of Cloud Native skills:  1. Linux & AI-Optimized OS   - AI-powered package managers automatically resolve compatibility issues.   - Agentic AI monitors system logs, predicts failures, and patches vulnerabilities autonomously.  2. Networking & AI-Driven Observability   - AI-driven network forensics using self-learning algorithms to detect anomalies.   - Agent-based routing optimizations, ensuring seamless traffic flow even in congestion.  3. Cloud Services & AI-Augmented Workflows   - Agentic AI predicts cloud workload demand and pre-allocates resources in AWS, Azure, and GCP.   - Autonomous cost optimization adjusts instance types, storage, and compute in real time.  4. Security & AI Cyberdefense Agents   - Self-learning AI security agents actively detect and mitigate cyber threats before they happen.   - Generative AI-powered penetration testing agents simulate evolving attack patterns.  5. Containers & Agentic AI Orchestration   - Autonomous Kubernetes controllers scale clusters before demand spikes.   - Agentic AI continuously optimizes pod scheduling, reducing cold starts and resource waste.  6. Infrastructure as Code + AI Copilots   - AI-driven infrastructure agents automatically refactor Terraform, Ansible, and Puppet scripts.   - Self-adaptive IaC, where AI updates configurations based on usage patterns and compliance policies.  7. Observability & AI-Driven Incident Response   - AI-powered anomaly detection in Grafana & Prometheus—flagging issues before failures.   - Agentic AI handles incident response, running diagnostics and executing pre-approved fixes.  8. CI/CD & Autonomous Pipelines   - Agentic AI writes, tests, and deploys code autonomously, reducing developer toil.   - Self-optimizing pipelines that rerun failed tests, debug, and retry deployment automatically.  The Future: Fully Autonomous Cloud Native Systems!  𝗗𝗲𝘃𝗢𝗽𝘀 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 → 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗼𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 → 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗰𝗹𝗼𝘂𝗱 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲. The result? Zero-touch, self-managing environments where AI agents handle failures, optimize costs, and secure systems in real time.  𝗪𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗲𝘅𝗰𝗶𝘁𝗶𝗻𝗴 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗰𝗹𝗼𝘂𝗱 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝘆𝗼𝘂’𝘃𝗲 𝘀𝗲𝗲𝗻 𝗿𝗲𝗰𝗲𝗻𝘁𝗹𝘆?

Just out in Harvard Business Review, summary of the Hybrid Experiment results and lessons on how to make hybrid succeed. Experiment: randomize 1600 graduate employees in marketing, finance, accounting and engineering at Trip.com into 5-days a week in office, or 3-days a week in office and 2-days a week WFH. Analyzed 2 years of data. Two key results A) Hybrid and fully-in-office showed no differences in productivity, performance review grade, promotion, learning or innovation. B) Hybrid had a higher satisfaction rate, and 35% lower attrition. Quit-rate reductions were largest for female employees. Four managerial lessons 1) Hybrid needs a strong performance management system so managers don’t need to hover over employees at their desks to check their progress. Trip.com had an extensive performance review process every six months. 2) Coordinate in-office days at the team or company level. Schedule clarity prevents the frustration of coming to an empty office only to participate in Zoom calls. Trip.com coordinated WFH on Wednesday and Friday. 3) Having leadership buy-in is critical (as with most management practices). Trip.com’s CEO and C-suite all support the hybrid policy. 4) A/B test new policies (as well as products) if possible. Often new policies turn out to be unexpectedly profitable. Trip.com made millions of dollars more profits from hybrid by cutting expensive turnover.

A Return To Office mandate is a funny thing. A trade-off of lower workforce productivity, morale, retention, engagement, and trust in exchange for...managers feeling more in control. It's more a sign of insecurity and incompetence than sound decision-making. The fact that 80% of executives who have pushed for RTO mandates have later regretted their decision only makes the point further, and yet every few months more leaders line up to pad this statistic. In case your leaders have forgotten, return to office mandates are associated with: 🔻 16% lower intent to stay among the highest-performing employees (Gartner) 🔻 10% less trust, psychological safety, and relationship quality between workers and their managers (Great Place to Work) 🔻 22% of employees from marginalized groups becoming more likely to search for new jobs (Greenhouse) 🔻 No significant change in financial performance while guaranteeing damage to employee satisfaction (Ding and Ma, 2024) The thing is, we KNOW how to do hybrid work well at this point. 🎯 Allow teams to decide on in-person expectations, and hold people accountable to it—high flexibility; high accountability. 🎯 Make in-person time unique and valuable, with brainstorming, events, and culture-building activities—not video calls all day in the office. 🎯 Value outcomes, not appearances, of productivity—reward those who get their work done regardless of where they do it. 🎯 Train inclusive managers, not micromanagers—build in them the skills and confidence to lead with trust rather than fear and insecurity. Leaders that fly in the face of all this data to insist that workers return to office "OR ELSE" communicate one thing: they are the kinds of leaders that place their own egos and comfort above their shareholders and employees alike. Faced with the very real test of how to design the hybrid workforce of the future, these leaders chose to throw a tantrum in their bid to return to the past, and their organizations will suffer for it. The leaders that will thrive in this time? Those that are willing to do the work. Those that are willing to listen to their workforce, skill up to meet new needs, and claim their rewards in the form of the best talent, higher productivity, and the highest level of worker loyalty and trust. Will that be you?

Louder for the people at the back 🎤 Many organisations today seem to have shifted from being institutions that develop great talent to those that primarily seek ready-made talent. This trend overlooks the immense value of individuals who, despite lacking experience, possess a great attitude, commitment, and a team-oriented mindset. These qualities often outweigh the drawbacks of hiring experienced individuals with a fixed and toxic mindset. The best organisations attract talent with their best years ahead of them, focusing on potential rather than past achievements. Let’s be clear this is more about mindset and willingness to learn and unlearn as apposed to age. To realise the incredible potential return, organisations must commit to creating an environment where continuous development is possible. This requires a multi-faceted approach: 1. Robust Training Programmes: Employers should invest in comprehensive training programmes that equip employees with the necessary skills for their roles. This includes on-the-job training, mentorship programmes, online courses, and workshops. 2. Redefining Hiring Criteria: Organisations should revise their hiring criteria to focus more on candidates’ potential and willingness to learn rather than solely on prior experience or formal qualifications. Behavioural interviews, aptitude tests, and probationary periods can help assess a candidate's ability to learn and adapt. 3. Partnerships with Educational Institutions: Companies can collaborate with educational institutions to design curricula that align with industry needs. Apprenticeship programmes, internships, and cooperative education can bridge the gap between academic learning and practical job skills. 4. Lifelong Learning Culture: Encouraging a culture of lifelong learning within organisations is crucial. Employers should provide ongoing education opportunities and support for professional development. This includes continuous skills assessment and access to resources for upskilling and reskilling. 5. Inclusive Recruitment Practices: Employers should implement inclusive recruitment practices that remove biases and barriers. Blind recruitment, diversity quotas, and targeted outreach programmes can help ensure that diverse candidates are given a fair chance. By implementing these measures, organisations can develop a workforce that is adaptable, innovative, and resilient, ensuring sustainable success and growth.

Should you try Google’s famous “20% time” experiment to encourage innovation? We tried this at Duolingo years ago. It didn’t work. It wasn’t enough time for people to start meaningful projects, and very few people took advantage of it because the framework was pretty vague. I knew there had to be other ways to drive innovation at the company. So, here are 3 other initiatives we’ve tried, what we’ve learned from each, and what we're going to try next. 💡 Innovation Awards: Annual recognition for those who move the needle with boundary-pushing projects. The upside: These awards make our commitment to innovation clear, and offer a well-deserved incentive to those who have done remarkable work. The downside: It’s given to individuals, but we want to incentivize team work. What’s more, it’s not necessarily a framework for coming up with the next big thing. 💻 Hackathon: This is a good framework, and lots of companies do it. Everyone (not just engineers) can take two days to collaborate on and present anything that excites them, as long as it advances our mission or addresses a key business need. The upside: Some of our biggest features grew out of hackathon projects, from the Duolingo English Test (born at our first hackathon in 2013) to our avatar builder. The downside: Other than the time/resource constraint, projects rarely align with our current priorities. The ones that take off hit the elusive combo of right time + a problem that no other team could tackle. 💥 Special Projects: Knowing that ideal equation, we started a new program for fostering innovation, playfully dubbed DARPA (Duolingo Advanced Research Project Agency). The idea: anyone can pitch an idea at any time. If they get consensus on it and if it’s not in the purview of another team, a cross-functional group is formed to bring the project to fruition. The most creative work tends to happen when a problem is not in the clear purview of a particular team; this program creates a path for bringing these kinds of interdisciplinary ideas to life. Our Duo and Lily mascot suits (featured often on our social accounts) came from this, as did our Duo plushie and the merch store. (And if this photo doesn't show why we needed to innovate for new suits, I don't know what will!) The biggest challenge: figuring out how to transition ownership of a successful project after the strike team’s work is done. 👀 What’s next? We’re working on a program that proactively identifies big picture, unassigned problems that we haven’t figured out yet and then incentivizes people to create proposals for solving them. How that will work is still to be determined, but we know there is a lot of fertile ground for it to take root. How does your company create an environment of creativity that encourages true innovation? I'm interested to hear what's worked for you, so please feel free to share in the comments! #duolingo #innovation #hackathon #creativity #bigideas

Smart helmets incorporating AI technology represent a significant advancement in safety, connectivity, and overall functionality. What do you think about this one? These helmets leverage artificial intelligence to enhance various aspects of the user experience. 1. Head Protection: Impact Detection: AI can be employed to detect and analyze the severity of impacts, providing real-time information about potential head injuries. Emergency Response: Smart helmets can automatically send distress signals or call for help in the event of a significant impact. 2. Augmented Reality Displays: Helmet-Mounted Displays: AR technology integrated into helmets can offer real-time information, such as navigation, speed, and relevant data, directly in the user's line of sight. Enhanced Situational Awareness: AI algorithms can analyze the surroundings and provide augmented information, like highlighting potential hazards. 3. Communication and Connectivity: Hands-Free Communication: AI-driven voice recognition enables hands-free communication, allowing users to make calls, send messages, or access information without removing the helmet. Intercom Systems: Smart helmets can facilitate communication between riders, improving group coordination during activities like motorcycling or cycling. 4. Gesture Recognition: Intuitive Controls: AI-powered gesture recognition enables users to control the features of the helmet through simple hand gestures, promoting a seamless and intuitive user experience. 5. Biometric Monitoring: Vital Signs Monitoring: Integrated biometric sensors can monitor vital signs such as heart rate and temperature, providing insights into the user's health and well-being. Fatigue Detection: AI algorithms can analyze data to detect signs of fatigue, alerting the user to take breaks when needed. 6. Navigation Assistance: Turn-by-Turn Navigation: Helmets equipped with AI can provide turn-by-turn navigation guidance, enhancing safety and convenience during travel. Route Optimization: AI algorithms can suggest optimal routes based on real-time traffic conditions. 7. Adaptive Lighting: Dynamic LED Lighting: Helmets with AI-controlled LED lighting can adapt to ambient conditions, improving visibility and safety, especially in low-light environments. 8. Automatic Tinting: Adaptive Visors: AI can control visors that automatically adjust tint based on changing light conditions, offering optimal visibility to the user. 9. Collaboration with IoT Devices: Integration with IoT: Smart helmets can seamlessly connect with other IoT devices, such as smartphones, smartwatches, or vehicle systems, creating an interconnected ecosystem. 10. Security Features: Facial Recognition: AI-driven facial recognition can enhance security by allowing authorized users access to specific features or functionalities. #innovation #helmet #ai via @ justhelmet