Mark Dangelo

The PAIR Framework: Cultivating Essential Skills for Responsible Generative AI Use (Adapted from #Harvard Business Publishing Education) The #PAIR framework provides a structured approach for developing essential skills when engaging with generative AI tools. Let’s dive into the five pillars of PAIR: #Problem Formulation: Clearly defining the problem is crucial. Students should translate their desired outcome into a well-structured problem that large language models (LLMs) can understand. This involves outlining the problem’s focus, scope, and boundaries before crafting prompts. A deep understanding of the problem ensures effective prompts, regardless of how they’re phrased for AI. #AI Exploration: Given the rapid emergence of new #AI tools, students must identify the most suitable one for specific tasks. Familiarizing themselves with prominent generative AI tools like ChatGPT and Stable Diffusion is essential. Proficiency in using generative AI-enhanced search engines (such as Microsoft Bing and Google Bard) is also valuable. Maintaining curiosity about upcoming advancements in generative AI tools is crucial. #Experimentation: AI tools are dynamic, so continuous experimentation is key. Students should engage in hands-on interaction, employ a trial-and-error approach, and analyze outcomes to stay proficient. #Critical Thinking: Generative AI tools have limitations, including potential inaccuracies or biases. Critical thinking empowers students to identify and address these limitations. They should rigorously evaluate information or arguments generated by AI, enhancing their learning experience. #Reflection: Engaging with generative AI can evoke emotional responses, especially when tasks relate to self-identity or self-worth. Cultivating a reflective practice helps students understand these reactions. Unlike critical thinking, reflection focuses on examining one’s own thoughts, feelings, beliefs, and actions in response to AI output. By embracing these skills through the #PAIR framework, students can responsibly use generative AI tools to enhance learning and problem-solving across disciplines. Remember that specific details about student interactions with AI were withheld to protect confidentiality. For a deeper exploration of problem formulation, check out the article “AI Prompt Engineering Isn’t the Future” on Harvard Business Review: (https://lnkd.in/dGg4bUHV).

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Thrilled that Accenture latest research is the featured cover story of the forthcoming Sept/Oct print edition of Harvard Business Review. In the article, Paul Daugherty and H. James Wilson argue that in this new era of collaboration between humans and machines, the ability to leverage #AI effectively will be critical to everyone’s professional success, and explain why most people will need one or more of what they call “fusion skills”: - intelligent interrogation involves prompting LLMs ie thinking with AI - judgment integration is about bringing in human discernment when a gen AI model lacks the necessary business or ethical context - reciprocal apprenticing includes training AI to be a co-creator Knowledge work is being transformed more quickly and powerfully than many of us can even imagine. It is critical to bring some rigor to the use of #GenerativeAI at work. Here is the link with the article: https://lnkd.in/eKKwAMBg

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AI is rapidly transforming economies, and a few countries are leading the charge. The United States is one of these AI pioneers—driving global innovation with a solid infrastructure, top-tier talent, and significant R&D investments.​ ​ BCG's AI Maturity Matrix places the US among the global frontrunners in AI readiness. We’re not only creating groundbreaking AI software, hardware, and cloud services but are also exporting these technologies worldwide, positioning AI as an ever-larger part of our economy. But as AI continues to scale, staying ahead means continually adapting our strategies to secure our competitive edge.​ ​ There’s also an ethical imperative. As one of the leading voices in AI, the US has a unique role in shaping responsible AI use. Collaborating with other countries to develop regulatory frameworks and address ethical questions will be essential as AI becomes more integrated into our lives and societies.​ ​ For leaders looking to navigate this fast-evolving landscape, understanding where each country stands—and what it takes to lead—has never been more important. Discover where your country stands in AI readiness and what steps can drive meaningful progress: https://lnkd.in/g6CJigCD

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Navigating the Digital and AI Revolution Lessons from McKinsey's 'Rewired' In the rapidly evolving landscape of digital and AI transformation, staying competitive demands more than just technological upgrades; it requires a holistic strategy that integrates tech with business processes and leadership vision. McKinsey senior partners Eric Lamarre, Kate Smaje, and Rodney Zemmel, in their book *Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI*, present actionable insights for organizations striving to thrive in this dynamic environment. The key to successful digital transformation hinges on making it a CEO-driven agenda that mobilizes cross-functional teams and secures necessary investments. The transformation is not merely a technological upgrade but a continuous process of learning and adaptation. Leaders must foster a culture of perpetual learning and integration of tech into the business fabric, making every leader a tech leader. Moreover, talent remains at the heart of transformation. Upskilling existing teams and ensuring new hires contribute effectively is crucial. The choice of operating models—whether a digital factory, a product and platform approach, or enterprise-wide agility—should align with organizational goals and the continuous nature of digital evolution. For CEOs and CXOs, the journey of digital transformation is about orchestrating a dance where technology and business strategies are in sync, driving growth and innovation. Embrace the challenge, and lead your organization to the forefront of the digital age. Key Takeaways --- CEO Involvement Crucial for steering digital initiatives effectively. Continuous Learning Essential for integrating technology with business. Talent Management Focus on upskilling and effective integration of new hires. Adaptive Models Choose the right operational model to fit your organization's needs. For more insights and practical guidance on leading digital transformation, explore *Rewired* by McKinsey. I highly recommend this book for all executives. #DigitalTransformation #AI #Leadership #Innovation #DearCEO #CEO #CDO https://lnkd.in/gFRN47fg

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Your Daily AI Implementation Tip for Business Leaders 📌 Tip: Start Small with Pilot Projects ⚠️ Problem: Jumping into large-scale AI implementations without proper groundwork can lead to costly failures and unmet expectations. Many organizations underestimate the complexity and overestimate their readiness for a massive AI rollout. 💡 Solution: Start with small, manageable pilot projects to test the waters. By beginning with smaller AI projects, you can effectively gauge the potential impact, identify challenges, and fine-tune your approach before scaling up. This iterative process helps ensure that your team builds the necessary skills and knowledge to handle larger, more complex AI implementations successfully. #AIforLeaders #GetSkillsAI #AIBusinessStrategy #SmartAIExecution

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Is #AI Changing #Board Structure? Mark A. Pfister of the "Across the Board" column explores: "Some may argue, as I have in the past, that AI will be challenging for Boards to govern within the historical parameters we define as today's modern governance. The complicated intertwining of ethics, morals, profits vs. investments, shareholder pressures, and many other considerations (some possibly not fathomable as of yet) will surely make evolving Board governance very interesting in the upcoming years. Make no mistake, AI will have an accelerating and significant influence on the direction of Board and organizational governance evolution in a short period of time. Directors need to be quickly preparing..." Today's image is from this article - priceless! or #StepfordWivesish. #Governance #GlobalBusiness

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How will companies leverage GenAI for real business impact? I participated in a report with MIT Sloan Management Review Connections sponsored by ThoughtSpot about the business imperative for GenAI in data and analytics, and how early adopters are already seeing returns. You can learn more in the report including best practices and proven use cases, found here: https://bit.ly/3AZ3D4l

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Monday Tech Report Review: The AI Index 2024 report by Stanford University. An overview of the landscape of artificial intelligence from the emergence of responsible AI to the increasing integration of AI in business. Key Points: Surge in Generative AI Investments: Noteworthy escalation in private investments in generative AI from 2013 to 2023 underscores the escalating interest and confidence in this sector, signaling a promising trajectory for future developments. Evolution of Responsible AI Benchmarks: The mentions of responsible AI benchmarks in academic literature from 2020 to 2023, including BBQ, BOLD, ToxiGen, RealToxicityPrompts, and TruthfulQA, reflect a growing emphasis on evaluating AI models against ethical standards. Enhanced Worker Productivity through AI: Research across diverse domains demonstrates that AI contributes to heightened worker productivity by expediting task completion and enhancing work quality, particularly benefiting lower-skilled labor segments. AI's Technical Prowess: AI systems have showcased superior performance compared to humans in tasks such as image classification, mathematics, language understanding, reading comprehension, and reasoning, underscoring the advancements in AI capabilities. Financial Benefits of AI Integration: The incorporation of AI technologies in business operations has yielded cost reductions and revenue enhancements across strategic, financial, research and development, supply chain management, marketing, and human resources functions, highlighting the financial advantages of AI adoption. Global Legislative Dynamics: The report reveals the enactment of AI-related legislation in various countries, delineating between expansive laws aimed at augmenting AI capabilities and restrictive regulations curbing AI applications, indicative of the evolving regulatory landscape. Public Perception of AI Technologies: Public sentiments towards AI products and services encompass a spectrum of understanding, anticipation of transformative life changes, concerns regarding benefits versus drawbacks, and trust levels in companies leveraging AI innovations. Debates on Foundation Models: Ongoing discourse on the dichotomy between open and closed foundation models in AI underscores divergent viewpoints on fostering innovation and addressing safety considerations, reflecting the nuanced discussions within the AI community. Corporate Adoption of AI: A substantial proportion of enterprises have integrated AI into at least one business unit, as evidenced by a McKinsey survey, indicating the widespread adoption of AI solutions across diverse industry sectors. AI's Advancements in Task Performance: While humans retain superiority in intricate cognitive tasks, AI has made significant strides in surpassing human performance in specific benchmarks, signaling the evolving capabilities of artificial intelligence technologies. #ai #artificialgeneralintelligence #business #work #innovation #technology

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I was intrigued by this 'Framework for Ethical Integration' because of the description of the last level. I presume the framework by its descending form proposes an increase in the value of use?! Before elaborating on my position let me opine on the first four in preparation. The levels of use mentioned are by default contextualized by the form of assessment, meaning that the AI attribution is guaranteed through permissions and the internal and external control mechanism of the assessment platform, e.g., Turnitin used in many tertiary institutions to assess plagiarism. Level hour specifically states any work produced by the AI must be cited; generally, it is a good and ethical practice, especially in research (as is the norm). However, suppose the application or use down these levels is NOT controlled. In that case, it begs the question of whether the human user(s) will by her own volition act ethically responsible to append or cite their work and that of the AI. The second question is whether the AI itself by its own volition will declare its use of other's work by citing or enforcing the user to do the same. These questions exist in the common use of AI, but within the context of assessing the application of knowledge for a passing grade, surely it cannot be as simple as that? Level five, therefore, imposes a conundrum in the context of use as I stated. The level that should warrant the best results in ethical use has zero limitations; worse even the reference to a much weaker form of assessment: 'support'. What happened to 'cite' or 'append' which imposes an onus of proof or evidence? In conclusion, the context of use should impose or otherwise direct the constraints placed on each particular form of intelligence - assume nothing from either.

Only 15% of companies are using AI for organizational learning. Yet, these Augmented Learners are 1.6 times more effective at managing uncertainties compared to others. (Source: global survey by MIT Sloan Management Review, BCG Henderson Institute, and BCG X) The study reveals three ways AI supercharges learning: 1. Knowledge Capture: AI turns massive amounts of data into actionable insights. 2. Knowledge Synthesis: It integrates internal and external data, making it accessible across teams. 3. Knowledge Dissemination: AI delivers the right information to the right person at the right time. The impact? Companies adopting AI in their learning strategies are twice as prepared for talent challenges and up to 80% more capable of handling volatile environments. To embrace augmented learning, organizations should: • Build a culture of experimentation—embrace trials and learn from failure. • Conduct postmortems—extract insights from both successes and setbacks. • Codify lessons—document and share knowledge for future use. • Use AI for feedback—create continuous improvement loops. Incorporating these strategies is a game-changer for building adaptability and staying competitive in a fast-moving world. Curious to learn more? I’ll drop the link in the comments!

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Crafting a business strategy without considering AI now seems impossible. It's integral to our planning and success. - Chief AI Wiz Grab my free guides at www.chiefaiwiz.com 👉AI Readiness Guide For SMBs 👉 ChatGPT guide for newbies and non-techie people. 👉 Gemini AI guide for newbies and non-techie people. Found this useful? ♻️ Share it with your network! 👉 Follow me here, in TikTok and Instagram @ChiefAIWiz | @LaGurudeIA (Spanish channel) #AI #BusinessStrategy #Success #Planning #Future

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🚀 Aloha, executives! Ready to harness the power of AI in your organization? 🔓 I've just released a new video revealing "3 Unbelievable AI Secrets Every Exec Should Know!" These transformative tips could be your ticket to paradise in the world of AI adoption. 🌴 Frustrated with slow AI progress? These secrets will help you build momentum and drive success. 📈 Want more AI guidance tailored for business leaders? Click "Visit my website" in my profile above👆. Let's navigate the AI revolution together! 🤝 #AIforLeaders #BusinessInnovation #TechStrategy

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Free Lessons on ChatGPT 🗒Writing a Meeting Summary FILL-IN-THE-BLANK PROMPTS: Summarize the five main takeaways from these meeting notes: [copy and paste notes]. If you would like to learn more about IA getting income. Join my community at Innovators Academy: https://lnkd.in/e7iTyDse If you like to Scale from 10k a month to $100k using AI, Visit https://lnkd.in/eUNzqM9z If you like to know more about our AI Engine, visit https://lheo.cloud/ #ai #artificialintelligence #digitaltransformation

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🗼Transform Your Innovation Strategy with 4 Key Foundations 🗼 Innovation doesn’t happen by accident—it requires a structured approach. 🔑 By building on these four critical pillars, organizations can unlock its creative potential: 1️⃣ Identify Trends Early: Spot emerging trends before competitors. 2️⃣ Leverage Partnerships: Collaborate with external experts to enhance innovation. 3️⃣ Support Intrapreneurs: Empower internal leaders to champion new ideas. 4️⃣ Foster Innovation Communities: Create spaces for cross-team collaboration and creativity. These pillars help create a culture of innovation, connecting new ideas with actionable results. 🔸 What pillar are you focused on improving? Comment below! 👇 👇 👇 #Innovation #futureofwork #Leadership

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Step 3 of 7 for AI Enablement: Identify and Prioritize AI Use Cases See full 7-step breakdown here: https://lnkd.in/g3t7MiZb In setting up AI for success, we’ve covered the foundations: Step 1 defined clear business objectives. Step 2 assessed team readiness, revealing gaps to achieve outcomes. Now for Step 3: Identify and Prioritize AI Use Cases. This step isn’t just about knowing where AI could fit; it’s also about evaluating tools to ensure they meet essential requirements—and testing the top choices with trial runs. First: Explore What AI Tools Are Out There Before diving into specific use cases, it’s important to understand the types of AI tools available that could support your goals. If you’re unsure where to start, here are two valuable resources: • Theresanaiforthat.com – A searchable directory of AI tools across industries. • GTM AI Tools Demo Library – A curated list of go-to-market AI tools from the GTM AI Academy (l^nk in comments). Identify AI Opportunities with the PRIME Framework With a better understanding of AI options, use the PRIME Framework to identify use cases that directly address your most critical business gaps: • Predictive: Can AI help forecast outcomes? • Repetitive: Are there time-consuming, repeated tasks? • Interactive: Could AI enhance customer engagement? • Measurable: Can AI provide useful metrics? • Empowering: Can AI support creativity or productivity? Evaluate Tools with a Checklist Once you’ve outlined use cases, evaluate potential tools to ensure they meet critical requirements before trialing them: • Security & Compliance: Does the tool meet company standards? • Governance: Does it support data governance and accountability? • Cost & ROI: Is it cost-effective based on expected value? • Scalability: Can it grow with your team’s needs? • Integration: Will it fit with your current systems? Evaluate Tools: Make sure selected tools meet security, compliance, and integration needs before trial runs. Pilot Testing Once you’ve prioritized and evaluated, move into a pilot phase. Select top tools to trial with a small pilot team. This phase helps test effectiveness, build internal champions, and refine any processes before rolling out to the larger team in Step 4. Your Checklist for Step 3 1. Explore AI Options: Start with Theresanaiforthat.com and GTM AI Tools Demo Library. 2. Identify Use Cases with PRIME: Target high-impact areas. 3. Evaluate Tools with the Checklist: Confirm tools meet security, compliance, and integration needs. 4. Pilot Test: Trial top tools with a small team to validate effectiveness. By following this approach, you’ll set your team up for measurable, AI-driven success with tools that are tested and proven valuable. Ready to PRIME your AI Enablement? Check out free resources in the GTM AI Academy: • PRIME Use Case Guide • Impact-Feasibility Template • AI Critical Requirements Assessment Up next.. Step 4 of 7 for AI Enablement..

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When your performance during an event that requires coordinated response is critical, then just like accomplished athletes, you need more than a Hearts and Minds game to be ready to perform at your peak. In the world of TTXs there are those like IRGame which are a sound introduction to TTX that can serve as the start to your training to become proficient at dealing with crisis. But there are also EXPERT systems designed to push this learning to a whole new level. That's where Dotan Sagi and cinten should be your next stop. Spend just a little time with Dotan and you will understand the unbelievable value proposition his team and their system represent. While I personally love the role IRGame plays in this ecosystem to address the masses with our Hearts and Minds game, cinten is where scientists get involved in tuning your organization for peak performance. Be sure to check them out below.

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CHALLENGES OF REINVENTION Commitment, and Timeframe Matters When Remaking Your Organization The odds of missteps and even outright failure are significant. For instance, a Harvey Nash/KPMG CIO Survey pointed out that only 18 percent of companies rate their use of digital technology as “very effective.” Other research points to a similar conclusion—reinvention is a decidedly tough nut. Establish clear objectives. Fuzzy promises such as greater efficiency and flexibility are fine up to a point—they can become problematic if that’s all you’re talking about. Instead, make sure that your goals are straightforward and easy to grasp. As I cite in my book REINVENT (published in association with IMD, a #1 The Wall Street Journal bestseller, and was shortlisted for 2023 Thinkers50 Strategy award) try using the principle embodied by the acronym SMART: ▪︎ If you’re hoping to achieve savings goals, where? ▪︎ What yardsticks are in place to measure savings? ▪︎ Is the plan aggressive but reasonable? An insurance company that dreams of cutting its underwriting costs in half within a year’s time is experiencing just that—a fantasy. However, the goal of a 20 percent reduction achieved systematically over a five-year period is not only more reasonable, but also engenders greater overall confidence. ▪︎ Why do you want to save all this money? Will it be redirected back within the company to improve employees’ work lives? …read my full article from the link in the comment section. 👇 Thank you so much Misiek Piskorski, Delia Fischer [she/her], and others at IMD for your generous support. #digitaltransformation #management #cio #ceo

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🌟 Interesting Findings from the Scoping Review on Generative AI Ethics! 🌟 I recently delved into the insightful paper "Mapping the Ethics of Generative AI" by Thilo Hagendorff, and I wanted to share some of the most compelling findings that emerged from this comprehensive scoping review. 🔍 Emergence of New Ethical Topics: The review identified 19 categories of ethical issues, revealing that discussions around generative AI have evolved significantly. New concerns such as "hallucination," "jailbreaking," and the potential for "harmful content" have surfaced, reflecting the unique challenges posed by these technologies. ⚖️ Shifts in Importance: While traditional ethical principles like transparency and accountability remain relevant, the study found that concepts such as fairness and safety have gained prominence in the discourse. This shift underscores the need for a nuanced understanding of how generative AI impacts various stakeholders. 📊 Taxonomy of Normative Issues: The research presents a taxonomy of 378 distinct ethical issues, providing a structured overview that can guide future research and policy-making. This comprehensive framework is invaluable for scholars and practitioners aiming to navigate the complex ethical landscape of AI. 💡 Balanced Perspective Needed: One of the key critiques highlighted in the paper is the tendency to focus predominantly on the risks associated with generative AI, often overlooking its potential benefits in enhancing creativity, productivity, and education. A more balanced approach is essential for a holistic understanding of these technologies. As we continue to explore the implications of generative AI, these findings serve as a crucial reminder of the importance of ethical considerations in technology development. I encourage everyone to read this paper and engage in discussions about how we can responsibly harness the power of AI! #GenerativeAI #AIethics #ResearchFindings #ThiloHagendorff #Innovation #MachineLearning #EthicalAI #FutureOfTechnology #AIResearch

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