May Habib

🗞️🗞️ Exciting news from IBM and Meta! 🤝 Llama 3 models are now available on #WatsonX. Collaborating with Meta, we're driving open and responsible AI forward. This is the way to go! #OpenInnovation

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Thanks to #genai360 for the shoutout here for Consilience AI and our AlphaIQ product. Davit Buniatyan Joseph Byrum, Ph.D., MBA

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"Who's going to do the job?" A crucial question posed by VP, Senior Labor Economist Ron Hetrick at Lightcast on the TroopHR Podcast. With our structurally shifted US workforce, let's unpack some key insights on AI's impact: ☑ Adoption is Nuanced  An National Bureau of Economic Research study predicts only 20% of US labor tasks are exposed to AI, with just 5.4% likely impacted in the next decade. Interestingly, only 27% of that 5.4% can be profitably automated, suggesting a more nuanced adoption landscape than often portrayed in media headlines. I anticipate that the economics of LLMs will improve as more cost-effective, smaller LLMs become available ☑ Will AI Solve a Shortage of Human Talent?  Ron highlights a critical staffing shortage: "You just think about what is by far the biggest need in this country. It's not even close. If you look at job postings..The biggest job by far is registered nurses, and we're going all over the globe to try to find these people." Recent studies indicate that "easy-to-learn" tasks show potential for 27% labor cost savings, while "hard-to-learn" tasks may see only 7% gains. Nursing, with its complex, context-dependent decisions, likely falls into the latter category. While AI may alleviate some easy-to-learn tasks in nursing, it appears to be more of a complement than a substitute for human talent. ☑ Historical Perspective  SF Fed President Mary C. Daly reminds us, "Technology has never reduced net employment over time for the country." While current AI applications focus on productivity gains, the technology is evolving rapidly. Gartner's research predicts that "By 2027, foundation models will underpin 70% of natural language processing (NLP) use cases, up from less than 5% in 2022." This rapid advancement underscores the urgency for adaptation. 💡 Talent Leaders: Focus on developing skills in prompt engineering, identifying AI use cases, and implementing AI safely and ethically. These competencies will be crucial in navigating the AI-augmented workplace of the near future. #AI #Workforce #HumanResources #TaylorFromHR

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Today, Reuters reported on Russia’s election-related disinformation activities in the EU. This week, it was reported that Russia’s influence groups used OpenAI to spread false and harmful information. The US Election 2024 is coming. It will be the most important political event on Earth. And it is not only about competing spins, or narratives clashing. With flows of hyperinformation, with the intent of malign actors to deceive and manipulate attention, and with the need of public and private organizations to be prepared and react fast—it is about staying vigilant and tracking the pulse of digital discourse. This is where AI can help. Mantis Analytics is a risk management company. To help you navigate the election-related informational risks landscape, we created our US Election 2024 AI-driven monitoring solution. If you analyze election dynamics, research main trends, want to follow the debates, or detect emerging narratives and threats, feel free to contact us.

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Proposing a framework for #AIPolicy: The current technology-centered approach to AI policy is resulting in fragmented and piecemeal efforts -- often decoupled from the intended real-world results. We lack a comprehensive AI policy framework to support coherent and effective policy making anchored in meaningful outcomes aligned with our collective social priorities. I propose a Social Outcomes and Priorities centered (SOP) framework for AI policy, its core components, and recommendations on their implementation for #USA (the framework is applicable globally). The SOP framework provides a mechanism to build policy and regulatory structure encouraging outcomes that strengthen society’s core foundations and offer uniform and equitable benefits while minimizing the risks. Check out the paper for more details. I’ll soon publish an executive summary with a tldr version. #artificialintelligence #policy #aiforsociety #technologypolicy #machinelearning #datascience #genai #generativeai #llm #aisafety #aicognition #aiandhumans #aiforgood #aiautomation #AIEthics #AIBias #AISafety #AIGovernance #AIPolicy #AIRegulation #AIPrivacy #AIFairness #AIAccountability #AITransparency #AIHumanRights #AISocialImpact #AIWorkforceImpact #AIEducationImpact #AIEnvironmentalImpact #AIDigitalDivide #AIAlgorithmicJustice #AIDataSovereignty #AIInformedConsent #AITrustBuilding #AIHumanAICollaboration #AIEthicalDesign #AIResponsibleInnovation #AISustainableDevelopment #AIInclusivity https://lnkd.in/ggsfgE55

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In the rapidly evolving world of artificial intelligence, separating hype from reality can sometimes be a challenging task. Yet, as AI continues to reshape industries at a breakneck pace, understanding its real-world applications and future trajectory becomes crucial for businesses and professionals aiming to stay ahead. It was against this context that Sigma Computing recently hosted its fascinating "AI Leaders Spill Their Secrets, webinar" bringing together some of the brightest minds in the AI industry to share their experiences, strategies, and visions for the future. Throughout the webinar, the industry experts offered an in-depth understanding of the state of AI, its applications across sectors, and its implications for the future. The entire webinar is worth watching. However, in this article, we bring you a comprehensive summary of the event, highlighting key discussions and insights that emerged from this meeting of AI leaders.

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One-third of Gen Z donors plan to increase their giving in the coming year. Are you ready to meet them? Download the latest report from the #BlackbaudInstitute for exclusive Gen Z giving insights.​

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Model Explainability means different outcomes for different users. We can't have one size fits all when explaining model prediction. At the same time, unless the explainability is true to the model, it has credibility issues! All regulators expect to have explainable ML models, which is not standardised! How do you scale ML explainability in high-risk and high-compliance use cases? Continuing the article in Forbes, I've written about various XAI outcomes and how to approach setting up such explainability. #AryaXAI #ExplainableAI #EnterpriseAI #AIRegulations https://lnkd.in/gp7YgzB3

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Is AI going to replace you? Is AI going to eat your industry? Are you positioned to take advantage of tectonic shifts occurring? Tues Aug 20 at 11AM ET Sign up here: https://lnkd.in/g3mvM_iB Please join David Berkowitz, Aleksandar Sasha Grujicic and myself, moderated Progress Partners' EIR director Jessica Geran Straw, as we share our insights on AI's transformative impact on the workplace. Discover diverse perspectives on how AI might redefine work and the technological landscape—from minor changes to complete transformation—followed by an engaging debate and audience Q&A. 💡

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GenAI - changing the world - not that as a human being, we do not do it but it has the intelligence (and data) of the population. This short post/ article highlights three such processes!

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Interesting discussion and episodes on the use of the AutoGen framework for Agentic Workflows at the Microsoft Research Forum. The #Agenticframework allows LLMs to allow to perform more complex and intelligent tasks autonomously through one of the key concepts of reflection and autonomy. It has significant impact on practical applications such as personalized medicine, automated travel concierge, autonomous navigation etc.. It was also very interesting to read blogs posted on deeplearning.ai by Andrew Ng. https://lnkd.in/daa28seD

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The relationship between the digital world and security has always been a fraught topic, and that is especially true in the new age of #GenerativeAI. Even just a few years ago, the standards for digital #verification were lower, but now, with the existence of deepfake technology and AI-generated documentation, #cybersecurity needs to evolve. According to Finance Magnates, companies like Socure are leading the way to prevent fraud and identity theft with DocV, their new AI-powered document verification program that detects AI-generated assets. That’s right, AI vs. AI. As fraudsters have become adept at using AI generation to forge entire identities (faces, documents, and personal information/data) that might go unnoticed by the human eye, Socure hopes to train their #DocV program to understand the subtle details and ‘uncanny valley’ nuances that are patterned by generative AI. Even if successful, this raises many questions. Will our attempts to neutralize AI-based fraud and other crimes stifle #innovation? Can we trust AI to combat AI? Can we trust certain companies to lead a good example and wield AI for the greater good?

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At a recent internal event, we had a great conversation about the balance between owned storytelling on our platforms, and earned media. The dialogue started with a simple question -- when should you consider one over the other, and why? Owned offers a controlled environment to craft and refine your narrative. Take our recent quantum partnership story as an example. This is a super complex topic with many difficult-to-grasp concepts. It involves work with a partner, who is equally invested in getting these complicated details right. It is the kind of story that benefits from a longer runway up front to get it right, and here it is presented concisely with supporting assets and a concrete example that allows audiences to learn as they read the story.   When it comes to earned media, the dynamics shift. Here, newsworthiness and external validation play pivotal roles. The credibility and often the reach garnered through earned media often surpasses what we can achieve through owned channels alone. So as we think about news moments and engagement with influencers, we pivot our owned assets to support these efforts, rather than lead them. As is so often the case :) we have to find the right balance, the right tool for the moment. Every organization needs to have the capacity to tell its own story, and to find the right time to lead there. This is what I think of as the "voice" of the company. And, the understanding that not every piece of news should lead with that voice.

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latest edition explores implications around: (1) making sense of the rapid displacement of startups and “the best model” rat race, (2) how “artifacts of humanity” and Content Credentials will become a human flex of sorts… https://lnkd.in/ecGZKMvr

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It all about networks and relationships!

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I'm excited to share how our innovative sociotechnical methods are revolutionising the way AI solutions are developed and deployed.    By embedding domain experts, legal specialists, ethicists, and human rights advocates alongside our talented data scientists and engineers, we ensure that every stage of the AI lifecycle is informed by diverse perspectives.    This collaborative approach is key to creating AI systems that are not only technically advanced but also transparent, accountable, and aligned with societal needs.    Our Sociotech team draws upon expertise at the intersection of social science and technology to help organisations use data more meaningfully.     We assist in defining objectives, identifying the right data, and delivering practical knowledge to address complex societal issues while saving precious time and resources.    I invite you to discover how our sociotechnical approach can help your organisation develop AI solutions that deliver meaningful impact and maintain public trust. Visit our website to learn more: https://lnkd.in/e6iKfvEW #Sociotech #RTAI #ResponsibleAI #RTAI

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In this week's recap of #AI doings, I encourage you to comment on rules for ChatGPT. Also, a LinkedIn survey that says 66% of employers won't hire people who don't have AI skills, TikTok's AI labeling system & Meta Ray-Ban review. https://lnkd.in/g5pKzDFs

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The Imagining Summit Preview: Steve Sloman and Knowledge & AI Steve Sloman, professor at Brown University and author of The Knowledge Illusion, will catalyze a conversation about how we perceive knowledge in ourselves, others, and now in machines. What happens when our collective knowledge includes a community of machines? Steve will challenge us to think about the dynamics of knowledge and understanding in an AI-driven world, about the evolving landscape of narratives, and ask the question can AI make us believe in ways that humans make us believe? What would it take for AI to construct a compelling ideology and belief system that humans would want to follow? #ai #artificialintelligence #generativeai #airesearch #complexity #intimacyeconomy #chatgpt #complexchange #changemanagement #futureofwork #artificiality #mindforourminds #intimacyeconomy #agenticweb https://buff.ly/3KO7G5m

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