AI's Influence on Workplace Ethics

AI’s Impact on Work Can’t Be Left to Chance: We're at major inflection point. The choices leaders make about AI today could reshape not just companies, but society itself. This isn’t about efficiency or productivity alone, it’s about whether millions of people will have meaningful work, dignity & the ability to participate in the economy. In a Time Magazine editorial last month, Salesforce CEO Marc Benioff described AI as a “colleague who never sleeps,” a partner which should be designed to augment human capability. He insisted that “we must keep humans at the center of this revolution,” framing AI as a force to expand what people can see & do. His message: AI should augment, not replace, human workers. Yet, literally days later, he literally fired 4,000 customer service reps, saying AI now handles half of their tasks, so the company didn’t need “these heads" In calling his employees “heads,” he dehumanized them. It shows how even leaders who say the right things about AI can quickly pivot to using it as a blunt tool for efficiency, with enormous human consequences. Geoffrey Hinton, Nobel Prize winning computer scientist & Godfather of AI, told the FT this weekend he believes “most people will end up poorer” due to AI. He said guaranteed basic income can never equal the incomes workers lose when AI takes their jobs. And GBI cannot address the loss of dignity that comes from being excluded from meaningful work. People get a sense of self-worth from their jobs.” Hinton fears Wall Street is prodding corporate CEOs to gut their workforces & fears society itself will collapse were it to happen. “Who would buy the goods & services AI produces? Companies could cut costs, but the economy would shrink & long-term growth would vanish.” So we’re faced with a choice: AI as a multiplier: a technology that frees people from drudgery, opens opportunity & amplifies human strengths. Or AI as a reducer: a technology deployed mainly to cut costs, eliminating the very work that gives people identity, expertise & purchasing power: the foundation of a functioning economy. We cannot let Silicon Valley executives decide our fate. This moment calls for all of us to step up & direct how AI is shaped. Here a five ways we can ensure AI is used for good: Leaders can commit to designing AI deployments that augment human potential, not replace it. Organizations can retrain & upskill people rather than discard them. Individuals can speak out, support ethical companies & demand transparency in how AI is used. Teams can embed ethics & human-centered decision-making into AI projects from day one. Investors can prioritize companies that invest in people as well as AI, recognizing that sustainable demand & economic growth rely on workers with income & dignity. Geoffrey Hinton’s final warning captures the stakes: “We don’t know what is going to happen. It may be amazingly good & it may be amazingly bad.” Moral: We can't take the risk of rolling the dice on this.

✳ Bridging Ethics and Operations in AI Systems✳ Governance for AI systems needs to balance operational goals with ethical considerations. #ISO5339 and #ISO24368 provide practical tools for embedding ethics into the development and management of AI systems. ➡Connecting ISO5339 to Ethical Operations  ISO5339 offers detailed guidance for integrating ethical principles into AI workflows. It focuses on creating systems that are responsive to the people and communities they affect. 1. Engaging Stakeholders  Stakeholders impacted by AI systems often bring perspectives that developers may overlook. ISO5339 emphasizes working with users, affected communities, and industry partners to uncover potential risks and ensure systems are designed with real-world impact in mind. 2. Ensuring Transparency  AI systems must be explainable to maintain trust. ISO5339 recommends designing systems that can communicate how decisions are made in a way that non-technical users can understand. This is especially critical in areas where decisions directly affect lives, such as healthcare or hiring. 3. Evaluating Bias  Bias in AI systems often arises from incomplete data or unintended algorithmic behaviors. ISO5339 supports ongoing evaluations to identify and address these issues during development and deployment, reducing the likelihood of harm. ➡Expanding on Ethics with ISO24368  ISO24368 provides a broader view of the societal and ethical challenges of AI, offering additional guidance for long-term accountability and fairness. ✅Fairness: AI systems can unintentionally reinforce existing inequalities. ISO24368 emphasizes assessing decisions to prevent discriminatory impacts and to align outcomes with social expectations.  ✅Transparency: Systems that operate without clarity risk losing user trust. ISO24368 highlights the importance of creating processes where decision-making paths are fully traceable and understandable.  ✅Human Accountability: Decisions made by AI should remain subject to human review. ISO24368 stresses the need for mechanisms that allow organizations to take responsibility for outcomes and override decisions when necessary. ➡Applying These Standards in Practice  Ethical considerations cannot be separated from operational processes. ISO24368 encourages organizations to incorporate ethical reviews and risk assessments at each stage of the AI lifecycle. ISO5339 focuses on embedding these principles during system design, ensuring that ethics is part of both the foundation and the long-term management of AI systems. ➡Lessons from #EthicalMachines  In "Ethical Machines", Reid Blackman, Ph.D. highlights the importance of making ethics practical. He argues for actionable frameworks that ensure AI systems are designed to meet societal expectations and business goals. Blackman’s focus on stakeholder input, decision transparency, and accountability closely aligns with the goals of ISO5339 and ISO24368, providing a clear way forward for organizations.

According to a recent BBC article, half of all workers use personal generative AI tools (like ChatGPT) at work—often without their employer's knowledge or permission. So the question isn't whether your employees are using AI—it's how to ensure they use it responsibly. A well-crafted AI policy can help your business leverage AI's benefits while avoiding the legal, ethical, and operational risks that come with it. Here's a simple framework to help guide your workplace AI strategy: ✅ DO This When Using AI at Work 🔹 Set Clear Boundaries – Define what's acceptable and what's not. Specify which AI tools employees can use—and for what purposes. (Example: ChatGPT Acceptable; DeepSeek Not Acceptable.) 🔹 Require Human Oversight – AI is a tool, not a decision-maker. Employees should fact-check, edit, and verify all AI-generated content before using it. 🔹 Protect Confidential & Proprietary Data – Employees should never input sensitive customer, employee, or company information into public AI tools. (If you're not paying for a secure, enterprise-level AI, assume the data is public.) 🔹 Train Your Team – AI literacy is key. Educate employees on AI best practices, its limitations, and risks like bias, misinformation, and security threats. 🔹 Regularly Review & Update Your Policy – AI is evolving fast—your policy should too. Conduct periodic reviews to stay ahead of new AI capabilities and legal requirements. ❌ DON'T Do This With AI at Work 🚫 Don't Assume AI Is Always Right – AI can sound confident while being completely incorrect. Blindly copying and pasting AI-generated content is a recipe for disaster. 🚫 Don't Use AI Without Transparency – If AI is being used in external communications (e.g., customer service chatbots, marketing materials), be upfront about it. Misleading customers or employees can damage trust. 🚫 Don't Let AI Replace Human Creativity & Judgment – AI can assist with content creation, analysis, and automation, but it's no substitute for human expertise. Use it to enhance work—not replace critical thinking. 🚫 Don't Overlook Compliance & Legal Risks – AI introduces regulatory challenges, from intellectual property concerns to data privacy violations. Ensure AI use aligns with laws and industry standards. AI is neither an automatic win nor a ticking time bomb—it all depends on how you manage it. Put the right guardrails in place, educate your team, and treat AI as a tool (not a replacement for human judgment). Your employees are already using AI. It's time to embrace it strategically.

Can We Trust AI to Drive Fairness and Inclusion? AI is revolutionizing workplaces, but how do we ensure it aligns with DEI principles? I explored this pressing topic with Natasha Rainey, on All Inclusive, sharing insights on ethical AI use. What You'll Learn from This Episode: * Human Bias in AI: Understand how human biases can influence AI systems through flawed data and design, leading to discriminatory outcomes, and learn why addressing these issues is critical for fairness. * Ethical AI Development: Discover how diverse teams and transparent practices in AI design can reduce bias and ensure ethical, equitable outcomes. * AI Ethics Training: Learn the importance of equipping employees with knowledge to recognize and mitigate bias in AI, fostering inclusive and responsible innovation. * Global Collaboration: Explore how international cooperation on ethical standards can reduce global bias in AI and promote equitable benefits for all communities. Links in the comments section for how you can accesss via Spotify or YouTube. Also, be sure to check out my LinkedIn Learning course on Navigating AI with a DEI Intersectional Lens available now for FREE thru December 31st. Link in comments.

In some workplaces, especially in China, companies are turning to advanced AI and computer vision technologies to monitor employees. The aim? To ensure productivity and minimize downtime. While the potential for optimizing efficiency is clear, the approach raises critical questions about privacy, trust, and ethics. 𝐖𝐡𝐚𝐭 𝐈𝐬 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧? For those unfamiliar, computer vision is a field of artificial intelligence that enables computers to process and interpret visual data - essentially teaching machines to "see" like humans. In workplace settings, AI-powered cameras analyze behaviors and patterns to differentiate between work-related activities and distractions. 𝐎𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐢𝐧𝐠 𝐬𝐮𝐜𝐡 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐨𝐟𝐭𝐞𝐧 𝐡𝐨𝐩𝐞 𝐭𝐨: - Identify inefficiencies: Pinpoint areas where workflows can improve. - Increase focus: Minimize distractions and ensure tasks are completed on time. - Enhance performance tracking: Gain data-driven insights into employee habits. 𝐁𝐮𝐭 𝐈𝐭’𝐬 𝐍𝐨𝐭 𝐖𝐢𝐭𝐡𝐨𝐮𝐭 𝐂𝐨𝐧𝐜𝐞𝐫𝐧𝐬 While the tech has its advantages, here are a few critical considerations: Privacy and Stress: Being constantly monitored can make employees feel uneasy, potentially leading to stress or resentment. - Trust Issues: Over-surveillance may imply a lack of confidence in employees, impacting morale and workplace relationships. - Legal and Ethical Challenges: The acceptability of surveillance varies by country and culture, making this a gray area in many regions. What’s your take on this? Is AI surveillance in the workplace a necessary evolution or a step too far? #innovation #technology #future #management #startups