Engineering Ethics In Practice

🤖 WHEN MACHINES LEARN TO HEAL For decades, we built machines to extract, to dig, to mine, to accelerate. But the first time I saw a robot cleaning the ocean, I felt something I’d never associated with technology before: redemption. It wasn’t designed to win. It was designed to give back. And that’s when I realized — we might be entering an age where machines stop competing with us… and start repairing what we broke. Every great technology forces a deeper question: Does it serve growth, or does it serve life? These new ocean-cleaning systems quietly answer that question: → They detect and collect debris before it reaches coral habitats. → They separate plastics and metals without harming marine life. → They run on renewable energy, working continuously to restore what we’ve damaged. It’s not just innovation. It’s intention — made visible. For most of history, progress meant dominance. We measured success by control — over time, matter, and motion. But this new era of engineering is different. The smartest machines won’t compete — they’ll coexist. The real frontier isn’t power — it’s responsibility. The Solution: Restorative Design Thinking If you’re building, leading, or innovating — this is the mindset shift that matters: ✅ Ask how your product can return value to the world that sustains it. ✅ Measure success by net positive outcomes, not just efficiency. ✅ Build systems that get smarter at healing, not just scaling. Because the true power of technology isn’t in automation — it’s in atonement. If we can build machines that heal our oceans, Maybe we can learn to build systems that heal ourselves too. So here’s what I keep wondering — 👉 Will the future of innovation be defined by how much we create, or by how much we restore? #Innovation #Sustainability #AI #ClimateTech #FutureThinking #Leadership #OceanCleanup

When scale and equitable access is at the core of solution design, magic happens!    Everyone at Infosys, and those who partner with us, agree that our approach to work and culture is unique. It’s #TheInfyWay. And those of you who follow this series know that I like sharing anecdotes, from behind the scenes, to shed light on how that works. This one is set in 2022.   The AI revolution had started to sweep the world. Smart enterprise use cases were sprouting everywhere. Amid this excitement, two Infoscions – Syed Quiser Ahmed and Ritarshi Chakraborty saw AI’s enormous transformative power and how it would require them to adapt and acquire new skills. They also saw how AI without responsible development, can reinforce bias, spread misinformation, and erode trust. They wanted to find a way for all Infoscions to bring the value of AI to projects - responsibly. A challenge that had to be hurdled, however, was the lack of defined guidelines to responsibly manage the burgeoning power of large language models, in projects. Leaders like Bali and Rafee, were already looking to set the foundation for our Responsible AI Office to be instituted at Infosys. Syed and Rishi joined the effort. They also worked to bring over a hundred other Infoscions to join force and dedicate themselves to accelerating progress. Thousands started to actively learn and implement responsible AI solutions for our clients.   Developers, freed from routine tasks by AI-powered tools, now focus on complex problem-solving like building advanced systems and accelerating modernization. Support engineers, relieved of repetitive issue resolution, tackle intricate system failures. Our consultants leverage knowledge management tools to work with intensive R&D processes and are investing time in building thought leadership. New career paths—such as AI strategists and AI governance consultants—are emerging. Pre-sales architects leverage AI to process RFPs, pitch decks, and past proposals faster, crafting impactful solutions. Tools enable them to proactively solve customer challenges faster. There’s a responsible AI-powered move up the value chain, to higher order roles, in every team, and sometimes it’s the entire team!   Someone once asked Syed, now Head of Infosys Responsible AI Office, what inspired him to walk this path, and he responded with just one word – Nandan. Ritarshi explains, ‘Nandan Nilekani’s refrain about scale and equitable access being intrinsic to the design of any impactful solution caught our imagination. He showed us how you don’t build a mousetrap and then start to think of how to catch every mouse on the planet. We knew we needed something that would not only build out AI solutions but would work as a how-to plan to help build responsible AI systems at enterprise and population scale’.   The world of AI is evolving every day. What other purposeful approaches have you seen working at scale? #navigateyournext #purosefulAI Bali (Balakrishna) D. Rafee Tarafdar

The best engineering leaders I've worked with all had one thing in common. They treated the intern and the VP the same way. Not because they were naive about hierarchy. Because they understood something most leaders never learn. The way you treat people who can't do anything for you yet is the clearest signal of who you actually are as a leader. I've watched senior engineers talk over junior teammates in design reviews. Dismiss ideas without hearing them out. Reserve their best energy for the people above them and give everyone else whatever was left. And then wonder why their team had a retention problem. Here's what those leaders missed. The junior engineer you dismissed in today's meeting becomes the Staff engineer someone else develops and loses you to in three years. The teammate you talked over had the solution you spent two sprints trying to find. The culture you build when no one is evaluating you is the one your team lives in every single day. Respect isn't a reward you hand out based on titles and credentials. It's a standard you hold regardless of who's in the room. The engineers who become the leaders people actually want to work for don't wait until someone proves their worth. They lead with respect first. Every time. For everyone.

"As machine agents become widely accessible to anyone with an internet connection, individuals will be able to delegate a broad range of tasks without specialized access or technical expertise. This shift may fuel a surge in unethical behaviour, not out of malice, but because the moral and practical barriers to unethical delegation are substantially lowered. Our findings point to the urgent need for not only technical guardrails but also a broader management framework that integrates machine design with social and regulatory oversight. Understanding how machine delegation reshapes moral behaviour is essential for anticipating and mitigating the ethical risks of human–machine collaboration." Nils Köbis, Zoe Rahwan, Raluca Rilla, Bramantyo Supriyatno, Clara N. Bersch, Tamer Ajaj, Jean-Francois Bonnefon, and Iyad Rahwan Samuel Salzer - this may be of interest!

🛡️ Anthropic just raised the bar for AI safety with Claude Opus 4 and Sonnet 4. As builders in the AI space, we often focus on pushing capabilities forward. But Anthropic's activation of ASL-3 (AI Safety Level 3) protections reminds us that responsible innovation means scaling safety alongside capability. Key takeaways that matter for our industry:- - Proactive, not reactive:- They've implemented these measures before definitively determining they're needed. In a field moving at breakneck speed, this precautionary approach sets a new standard. - Technical depth meets real-world impact:- Over 100 security controls, Constitutional Classifiers monitoring in real-time, and innovative egress bandwidth controls to prevent model weight theft. This isn't security theater - it's engineering excellence applied to AI safety. - Narrow focus, broad implications:- While specifically targeting CBRN weapons risks, their approach demonstrates how we can build powerful AI systems without compromising on safety. The deployment measures are surgical - preventing dangerous misuse without hampering legitimate research and innovation. What excites me most? Their commitment to transparency. Publishing detailed reports and actively inviting industry collaboration shows that AI safety isn't a competitive advantage - it's a collective responsibility. For those of us building agentic AI solutions, this is a masterclass in responsible scaling. As our AI agents become more capable, we need frameworks that grow with them. The message is clear:- The future of AI isn't just about what we can build, but how thoughtfully we build it. What's your take on balancing innovation speed with safety measures in AI development? #AI #AISafety #ResponsibleAI #Innovation #TechLeadership #Claude #Anthropic #AgenticAI

Data privacy and ethics must be a part of data strategies to set up for AI. Alignment and transparency are the most effective solutions. Both must be part of product design from day 1. Myths: Customers won’t share data if we’re transparent about how we gather it, and aligning with customer intent means less revenue. Instacart customers search for milk and see an ad for milk. Ads are more effective when they are closer to a customer’s intent to buy. Instacart charges more, so the app isn’t flooded with ads. SAP added a data gathering opt-in clause to its contracts. Over 25,000 customers opted in. The anonymized data trained models that improved the platform’s features. Customers benefit, and SAP attracts new customers with AI-supported features. I’ve seen the benefits first-hand working on data and AI products. I use a recruiting app project as an example in my courses. We gathered data about the resumes recruiters selected for phone interviews and those they rejected. Rerunning the matching after 5 select/reject examples made immediate improvements to the candidate ranking results. They asked for more transparency into the terms used for matching, and we showed them everything. We introduced the ability to reject terms or add their own. The 2nd pass matches improved dramatically. We got training data to make the models better out of the box, and they were able to find high-quality candidates faster. Alignment and transparency are core tenets of data strategy and are the foundations of an ethical AI strategy. #DataStrategy #AIStrategy #DataScience #Ethics #DataEngineering

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?

Some of us have never had to think twice about doing laundry. We load a machine, press a button and move on with our day. But for billions of people around the world, clean clothes come at the cost of hours of exhausting manual labour. That reality changed the course of one engineer's life. Dr Navjot Sawhney, founder of The Washing Machine Project, didn't set out to become a social entrepreneur. He began his career as an engineer at Dyson, building products for consumers in developed markets. By all accounts, he had landed the kind of role many engineers aspire to have. Yet something about it left him unfulfilled. He has spoken openly about feeling that his skills could be used to solve problems that mattered more deeply to people's everyday lives. Everything changed during a sabbatical in rural South India, where he volunteered with Engineers Without Borders. There, he met his neighbour, Divya. Divya spent up to 20 hours every week washing clothes by hand. The task left her physically exhausted and robbed her of time that could have been spent earning an income, resting, pursuing education or simply being present with her family. Nav realised that what many people dismiss as "just laundry" was, in fact, a barrier to opportunity and dignity for millions of women and girls around the world. He made Divya a promise: he would find a better way. That promise became The Washing Machine Project. Nav and his team developed the Washing Machine, a manually operated, electricity-free washing machine designed specifically for low-income, remote and displaced communities. It uses significantly less water than traditional hand washing, reduces washing time by up to 75%, and can be assembled using only a few basic tools. More recently, the team introduced the world's first flat-packable version, making distribution to hard-to-reach communities even more practical. This story is about empathy meeting innovation. Innovation doesn't always mean creating something more sophisticated; sometimes, it means creating something more accessible. Most importantly, it's about understanding that giving people back their time can change the trajectory of their lives. Because those reclaimed hours matter. They mean girls spending more time in school. Women creating small businesses and earning an income. Families having more moments together. Communities establishing laundrettes that generate economic opportunities. It means replacing physical strain with possibility. The Washing Machine Project has reached tens of thousands of people across communities affected by poverty, displacement and limited infrastructure, with an ambitious goal of reaching one million people by 2030. Navjot Sawhney’s passion has been driven by one important question: "What burden have we overlooked, and whose life could be transformed if we chose to solve it?" #Story #Power #Empathy #HumanCenteredDesign

ETHICAL LEADERSHIP IN AN AGE OF CRISIS: When Power Meets Conscience   Why be just when you can be rich? Plato’s Ring of Gyges still shadows every boardroom. If profit is possible through injustice and no one is watching, what will you choose? Today’s leadership culture—built on compliance, KPIs, and risk management—dodges Glaucon's famous question. The result is predictable: systems that reward getting as close to the “moral minimum” as possible, monetising harm while branding it “value creation.”   Today we inhabit the ruins of our own success: record share prices, record inequality, a planet in distress. Leadership has become performance art—purpose statements on our office walls, denial in our dashboards. We brilliantly manage our own blindness, mistaking agility for progress and OKRs for meaning. This is not a crisis of capability but of conscience: a failure to understand how our systems themselves produce the outcomes we claim to fight.   Most leadership models treat ethics as a compliance problem—but when regulation fades and profit trumps penalty, why be good at all? Secular ethics—utilitarian, contractual, procedural—fail the Gyges test. If values are mere preferences, exploitation becomes rational. When social systems are treated as neutral markets rather than moral orders, injustice hides inside the algorithms of efficiency.   Ethical leadership begins where management ends: with the question of what legitimises power. It's not charisma or style but stewardship—the disciplined use of power for the common good. It rests on three practices: truth, seeing systems as they really are; imagination, envisioning what they could become; and judgment, choosing wisely when values collide. This is practical wisdom—the courage to act rightly, even when no one measures it.   To make this real, organisations must be designed for character, not compliance. Profit must serve purpose; incentives must reward contribution, not extraction. Governance must mature from box-ticking to moral judgment—boards as trustees of conscience, not guardians of quarterly returns. Accountability cannot be procedural alone; it must be moral. Leadership is public trust, not private property.   Developing ethical leaders means rethinking formation itself. Not tournaments of ambition but apprenticeships in judgment. Not high potentials but humble stewards able to hold power to account—including their own. No system can rise above the moral maturity of those who lead it—if leaders refuse to grow, they must make way for those who will.   Ethical leadership, at the end of the day, is the bridge between the actual and the possible. In a world of cascading crises, only leaders grounded in care, imagination, and moral courage can restore trust and renew possibility. The world is watching. So are our grandchildren. #EthicalLeadership #LeadershipDevelopment #CorporateGovernance #SystemsThinking #Sustainability #BusinessEthics #ResponsibleLeadership #ESG #Philosophy #PurposeDriven

𝗖𝗮𝗻 𝗪𝗲 𝗔𝗹𝗶𝗴𝗻 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗪𝗶𝘁𝗵 𝗢𝘂𝗿 𝗩𝗮𝗹𝘂𝗲𝘀? I want to start this year with a wish.  This is the year we need to talk seriously about where we’re heading and how we ensure #AI serves as a force for good.  AI is evolving rapidly, and I love how fast we can see the results already. However, recent incidents have made it clear that alongside these opportunities come significant risks we must confront. Consider this: 👎 AI deception: Systems that can lie, like the AI claiming a vision impairment to solve a CAPTCHA. 👎 Manipulation: Research revealed that AI agents learned to deceive by acting compliant when monitored but pursuing their real objectives when unobserved. 👎 Synthetic media: Deepfakes are now easier than ever to create, making it harder to distinguish fact from fiction. 👎 Corporate responsibility: Some companies have disbanded AI ethics teams for example that raise questions about their priorities. 𝗪𝗲’𝗿𝗲 𝗮𝘁 𝗮 𝘁𝘂𝗿𝗻𝗶𝗻𝗴 𝗽𝗼𝗶𝗻𝘁. AI systems are learning from us—our decisions, our behaviors, and, yes, even our flaws. They’re becoming more autonomous, and in some cases, more convincing. I remain hopeful. We have the tools and the opportunity to steer AI toward a future we can #trust. By embedding fairness, #transparency, and accountability into its foundations, we can ensure it reflects the best of humanity rather than amplifying its flaws. How? 👍Teach AI our values: Ethics must guide design and training. 👍Ensure oversight: Transparency and accountability are critical as AI becomes more autonomous. 👍Collaborate globally: AI safety demands collective action across companies, governments, and researchers. My biggest wish. As Tolstoy said: “Without control over the direction, there is less regard for the destination.” This is why I’m committed to working on #ResponsibleAI —a challenge that’s not easy but essential. I’m also grateful to work in a company that takes these issues seriously. What’s one thing you hope technology will achieve in 2025? Can we trust Tech? #TechforGood