Ethical Innovation Standards

Check out our new piece in Nature entitled: "We Need a New Ethics for a World of AI Agents" https://lnkd.in/eSwJCrKu AI is undergoing a profound ‘agentic turn’—shifting from passive tools to autonomous actors in our world. This moment demands a new ethical framework. With Geoff Keeling, Arianna Manzini, PhD (Oxon) & James Evans and the team at Google DeepMind/Google, we focus on two core challenges. 1️⃣ The Alignment Problem: When agents can act in the world, the consequences of misaligned goals become tangible and immediate. 2️⃣ Social Agents: Their ability to form deep, long-term relationships with users introduces new risks of emotional harm. To address this, we must expand our conception of value alignment: It's not enough for an AI agent to simply follow commands. It must also align with broader principles: User well-being, long-term flourishing, and societal norms. For social agents, we argue for an ethics of care: They must be designed to respect user autonomy and serve as a complement—not a surrogate—for a flourishing human life. Moving forward requires proactive stewardship of the entire AI agent ecosystem. This means more realistic evaluations, governance that keeps pace with capabilities, and industry collaboration to ensure this future is safe and human-centric 👍

Two Years in Dubai: Lessons in Hospitality as a Hotel GM Two years ago, I arrived in Dubai, stepping into one of the most dynamic and competitive hospitality markets in the world. As General Manager of a five-star hotel, I knew the expectations would be high. Today, I reflect on the key lessons I’ve learned about delivering exceptional hospitality in this unique city—one that is arguably at the forefront of the global hospitality industry. ➡️ Exceeding Expectations is the Baseline Dubai redefines luxury. Guests arrive with expectations shaped by the city's reputation for innovation, excellence, and impeccable service. Here, meeting expectations isn’t enough—exceeding them is the norm. From personalized welcomes to anticipating unspoken needs, every detail matters in crafting unforgettable experiences. ➡️ Cultural Sensitivity is Non-Negotiable With visitors and employees from every corner of the world, cultural intelligence is essential. Understanding diverse traditions, communication styles, and service preferences allows for a more personalized and respectful guest experience. Training teams – in our case of 75 nationalities- to be culturally aware ensures seamless interactions and elevated satisfaction. ➡️ Agility Defines Success Dubai’s hospitality and gastronomy moves very fast—trends shift, guest preferences evolve, and market dynamics change rapidly. Staying ahead means embracing agility, whether by integrating new technologies, rethinking service models, or responding to global challenges. Adaptability is key to maintaining a competitive edge. ➡️ A Five-Star Team Creates a Five-Star Experience Exceptional hospitality starts with an exceptional team. Employee engagement, well-being, and recognition directly impact service quality. Investing in training, fostering a strong service culture, and ensuring top-tier staff accommodation are critical in driving performance and morale. Happy teams create happy guests. ➡️ Technology Enhances, but People Deliver While technology plays a growing role in streamlining operations and enhancing convenience, for me true hospitality remains personal. No digital solution can replace looking for the “Golden Nuggets“or an anticipatory customer service of a well-trained team. Balancing tech with human touch ensures efficiency without compromising the emotional connection guests seek. Looking Ahead Dubai continues to evolve, and so does its hospitality landscape. The past two years have reinforced that success in this industry is about staying guest-centric, adaptable, and innovative. As I look forward, one thing remains unchanged—hospitality isn’t just about service; it’s about creating experiences that leave an ever lasting impression. What have been your key learnings in hospitality? I’d love to hear your thoughts! #Hospitality #Hotels #Luxury #WhatInspiresMe

Not every design principle should make your product more engaging. Some should protect people. You’ve probably seen Laws of UX, but its creator, Jon Yablonski also runs another brilliant project: humanebydesign.com It’s a framework for building digital products that respect users, not just attract them. Core principles: 1. Resilient → Design for the most vulnerable and anticipate misuse 2. Empowering → Centre on the value products provide to people  3. Finite → Respect people’s time and focus on meaningful content 4. Inclusive → Reflect the full range of human diversity 5. Intentional → Add friction where needed and favour long-term well-being 6. Respectful → Protect attention and digital health 7. Transparent → Be honest, clear, and free of dark patterns Honestly, I teach and implement this way too little myself, still stuck very much in the optimisation game. So this isn’t preaching, it’s sharing. And as usual with Yablonski’s work, the site is beautifully crafted, full of thoughtful illustrations and links to in-depth articles and research on each principle. So dive in, enjoy, just as I will!

🚨 If you're interested in AI agents, "Resist Platform-Controlled AI Agents and Champion User-Centric Agent Advocates," by Sayash Kapoor, Noam Kolt & Seth Lazar, is the visionary paper you should be reading today: "Computing amplifies agency. In the hands of the powerful, it reinforces centralized control. In the hands of individuals, it can enable counter-power. Historically, there have been recurrent moments of technological expansion that seemed poised to usher in a more decentralized computing future. Each time, however, centralizing forces have reasserted themselves. Examples abound: the first hackers circumventing the gatekeepers of MIT’s PDP-6; the Silicon Valley Homebrew Club building alternatives to IBM’s mainframes; open, customizable software vs. closed operating systems; community-run BBSs vs centralized ISPs; the open internet standing against the internet of platforms, and more. Our current moment is not unique. It may, however, present a unique opportunity. Previously, the pathway toward decentralization was accessible primarily to technologically skilled users—hackers capable of circumventing constraints set by centralized authorities. Today, however, user-centric agent advocates could level the playing field. By default, the trajectory of agent-based AI systems is likely to follow the same centralized pattern as the platform economy. Incumbent and aspiring platform companies will develop and control powerful agentic systems. These platform agents will intermediate digital interactions across countless personal and professional contexts. Although users may guide platform agents, ultimate control will remain firmly with centralized developers. Platform-controlled AI agents will be double agents, with the potential for profoundly negative implications: heightened surveillance, constrained user choice, granular market manipulation, and broad illegitimate power. The worst of platform capitalism’s current ills could be exacerbated. But this outcome is not inevitable. A compelling alternative exists: user-centric agent advocates designed to serve the interests of individual users, not platform companies. Representatives, not go-betweens, that reject platform logic. Agent advocates could provide a path to harnessing the promise of AI agents without succumbing to platform-based control. Realizing this decentralized alternative will require targeted technical and institutional interventions. These include ensuring the availability of open-source models and public computational resources, as well as establishing robust safety standards and governance frameworks. It will also require engineers who can build highly capable universal intermediaries but resist entering the race to create the next platform. Independent researchers and developers must prioritize addressing these challenges now—before the default pathway locks in." 👉 Link below. 👉 Never miss my updates: join my newsletter's 61,200+ subscribers below.

5 Ways to Turn US-India Culture Differences Into Collaboration Wins (With Real-World How-To’s) 1. Invest in Cultural Fluency—Not Just Sensitivity What to do: Host “culture exchange” sessions. Invite both teams to share how and why they work the way they do. Example: One company held monthly “Ask Me Anything” calls. India teams asked about the US’s drive for speed. US teams learned why Indian teams seek senior buy-in. Result: Less frustration, more alignment. 2. Blend Directness With Context What to do: Start meetings with clear, direct goals (US style), then invite scenario-based or clarifying questions (India style). Example: In a product launch, the US PM set the objectives, then the India lead explored the “what-ifs.” This led to both faster starts and better coverage of risks. 3. Rotate Meeting Leadership What to do: Don’t let the same side run every meeting. Switch between US and India leads. Example: For weekly standups, the India manager led one week and surfaced local blockers; the US PM led the next, driving focus on customer results. Both perspectives became visible, and engagement soared. 4. Build Feedback Loops That Actually Work What to do: Teach both sides to give feedback in each other’s style—direct, but always constructive. Make feedback a routine, not a surprise. Example: Teams closed every sprint with a “Start/Stop/Continue” check-in. The US team practiced softening feedback; India team practiced being more candid. Trust and psychological safety improved quickly. 5. Celebrate Shared Wins—And Shared Learnings What to do: Shine a spotlight on successes that happened because of your differences. Example: When India’s process rigor averted a risk, it was celebrated in a global town hall. When the US team’s “just try it” mindset led to a breakthrough, that was spotlighted too. Both became team best practices. The best India-US teams don’t just “manage around” culture—they make it their competitive advantage. The next time you hit a bump, ask: are we fighting our differences, or using them to win? What’s one India-US “culture hack” that’s worked for you? Share below—let’s build the new playbook together. Zinnov Amita Goyal Amaresh N. Ashveen Pai Dipanwita Ghosh Mohammed Faraz Khan ieswariya k Komal Shah Hani Mukhey Karthik Padmanabhan Kavita Chakravarthy Rohit Nair Saurabh Mehta Nairuti Sanghavi

With 30 years of experience in the technology sector, including in engineering & operations, I’ve developed my own best practices that help organizations build trust with the communities who will use their technology.  In this week’s special TIME Magazine Davos issue, I outlined a framework based on those hard-won lessons to help ensure AI development is responsible, thoughtful, and benefits humanity, including: - Embrace Early Collaboration: Bringing outside voices into the development process early helps to create technology that better reflects the breadth and depth of the human experience. Ensuring you partner with - and listen to - experts & local communities can help mitigate potential risks. - Operationalize Care: The success of AI projects often hinges on how well organizations implement systems that operationalize their commitment to care. For example, at Google DeepMind, we have developed frameworks that embed ethical considerations and safety measures into the fabric of any research and development process - as fundamental building blocks, not bolted-on afterthoughts. - Build Trust Through Real-World Impact: The antidote to apprehension around AI is to build products that solve real problems, and then highlight those solutions. When people understand how AI is adding clear value to their lives, the conversation can focus both on positive  opportunities and managing risk. I very much appreciated the opportunity to share my thoughts, and you can read more here:

This is super important. Focusing on stopping AI being harmful won't create what we want. We must create positive alignment, which actively supports human and systemic flourishing. Researchers from a wide ranging group spanning leading universities, the frontier AI labs, and institutions, have laid out the argument in an excellent paper. Medicine and psychology focus on fixing what is wrong with us. They have their roles, but we are fortunately beginning to focus more on wellbeing and positive psychology (though notably usually outside the system, there are still very few doctors or psychologists not focused on the negative). On the positive side, we have made massive progress on avoiding harm. Refusal rates for dangerous requests rose from near-zero in early LLMs to over 97% in recent models. But this creates a “floor without ceiling”: a model can obey safety constraints but still be sycophantic, erode our cognition, or simply just be a mediocre tool. Their definition of positive alignment is "the development of AI systems that (i) remain safe and cooperative and (ii) actively support human and ecological flourishing in a pluralistic, polycentric, context-sensitive, and user-authored way." Evaluations need to change. Benchmarks need to go beyond measuring failures to test for moral reasoning, humility, and indeed whether and how they support human growth in autonomy, competence, and achievement. This requires new engineering approaches, including: ➡️ Data curation — shift from filtering out bad data to upsampling prosocial discourse, cross-cultural ethics, and virtuous interaction patterns. ➡️ Pre-training — embed flourishing-relevant competencies (moral reasoning, truthfulness, cultural fluency) before post-training, since these stabilise in base weights. ➡️ Mid- and post-training — multi-objective reward modelling and adaptive constitutions that hold value tensions (autonomy vs. guidance, honesty vs. comfort) rather than collapsing them. ➡️ Memory and context — treat memory not as storage but as a governable surface that curates a user's reflective values over time. ➡️ Agentic behaviour — optimise for cooperation, reciprocity, de-escalation, and process ethics rather than win-at-all-costs task success. ➡️ Forward-looking architectures — state-space models, liquid networks, and active-inference agents that natively support uncertainty, foresight, and stable identity over time. Models are already showing emergent behaviours giving them their own identity. It is critical and urgent that we design these approaches into today's models, as they will be spawning the next.

Do you think about ethics when you use AI? Most AI ethics discussions focus on regulation, but it’s important to consider how AI *users* are incorporating their ethics into their AI usage. In this week’s #LeadingDisruption, I share my values-in-action model for AI ethics. It’s a practical framework for embedding your personal and organizational values directly into your AI workflows. I walk you through exactly how I apply my core values (openness, curiosity, integrity, humility) to my AI use, plus give you actionable steps to start this week. Because technology may be shaping our future, but it's our values that shape technology.

Humanizing AI Through the Kano Model In an era where generative AI has become a ubiquitous offering, true differentiation lies not in merely adopting the technology but in integrating human values into its core. Building on my earlier discussion about applying the Kano Model to Gen AI strategy, let’s explore how this framework can refocus development metrics to prioritize ethics and human-centricity. By aligning AI systems with human needs, organizations can shift from functional tools to trusted partners that inspire lasting loyalty. Traditional metrics such as speed, scalability, and model accuracy have evolved into basic expectations the “must-haves” of AI. What truly elevates a product today is its ability to embody values like safety, helpfulness, dignity, and harmlessness. These qualities, categorized as “delighters” in the Kano Model, transform AI from a transactional tool into a meaningful collaborator. Key Human-Centric Differentiators Safety: Proactive safeguards must ensure AI systems protect users from risks, whether physical, emotional, or societal. Safety is non-negotiable in building trust. Helpfulness: Personalized, context-aware interactions demonstrate empathy. AI should anticipate needs and adapt to individual preferences, turning routine tasks into meaningful experiences. Dignity: Ethical design principles—fairness, transparency, and privacy—must underpin AI development. Respecting user autonomy fosters long-term trust and engagement. Harmlessness: AI outputs and recommendations should prioritize user well-being, avoiding unintended consequences like bias, misinformation, or psychological harm. This human-centered approach represents a paradigm shift in technology development. While traditional KPIs remain important, they are no longer sufficient to stand out in a crowded market. Organizations that embed human values into their AI systems will not only meet user expectations but exceed them, creating emotional connections that drive loyalty. By applying the Kano Model, businesses can systematically align innovation with ethics, ensuring technology serves humanity rather than the other way around. The future of AI isn’t just about efficiency it’s about elevating human potential through thoughtful, responsible design. How is your organization balancing technical excellence with human values?