PigeonLine - Research-AI

ResearchAI co-founder and responsible AI advocate Cody Dodd. Ph.D. at last week's Alan Turing Institute, LSE event in London, England. https://lnkd.in/gPbeBBNs

https://lnkd.in/dR_CNByh Interesting findings of Dutch Government Audit of current AI systems - 50% unable to demonstrate compliance with policy standards.

https://lnkd.in/g78XvwQr

UK and now NZ are moving forward with efforts to simplify citizen government access and interactions. I'd love to see evaluation criteria and data, including the uncovered unintended consequences. The challenge, as always, will be the "jagged productivity frontier" (i.e. it is not always possible to know if the application of GenAI will be a net benefit or net cost to the transaction). If known error rates (up to 20%)and unintended consequences are taken into account, it is possible for outcomes for disadvantaged client segments and front-line staff to be worse. So I'm looking forward to seeing how this trial is measured and works out. Overall, I am optimistic that this will have a positive impact on citizens. https://lnkd.in/gqvgxRVQ

ResearchAI goes big! Check out this groundbreaking study by the Conference Board of Canada. The CBOC used our tool to analyze the state of green skills across Canadian education involving 100,000s of lines of text. They cited how they used the tool here https://lnkd.in/gmezqYch

Summer update -The summer has been very productive for us and for R&D, Since we last chatted we have added: *Smarter searching and more power (https://lnkd.in/gcqpMeqV) *GenAI tools (based on BERT), which we use to find similar sentences when tagging data https://lnkd.in/g5sCx-qY We're being used by over 30 universities, government departments and research firms, helping expand research productivity https://lnkd.in/gR2bVXUB

The author has captured the key questions the public sector service leaders we work with are starting to wrestle with as they contemplate what it will take to build an AI-enabled service delivery organization. 1. What are the skills and knowledge gaps that need to be addressed in order for our people to be successful in an AI-enabled environment? This includes both technical skills, such as data science and programming, as well as those soft skills where AI is less than fully capable. 2. How can we create a culture of continual learning and development so that our people can keep up with the pace of change in AI? This includes providing access to training and resources, as well as creating an environment where employees feel comfortable asking questions and taking risks. 3. How can we ensure that our people are ethical and responsible users of AI? This includes setting clear guidelines and expectations, as well as providing training on the ethical and moral implications of AI. How can we mitigate the risks of bias and discrimination in AI systems? This includes carefully designing and testing AI systems, as well as carefully monitoring them for bias. 4. How can we ensure that AI is used to augment human capabilities, rather than replace them? This means finding ways to use AI to automate tasks that are repetitive or dangerous and using it to do things that it actually can do better than humans (e.g., big data analytics) while freeing up humans to focus on more creative and strategic work. As we deepen our relationship with client organizations we find ourselves providing guidance, insight and guidance re 1) Technical skills development. 2) Creating a culture of learning based grounded in innovation and self paced learning. 3) Providing seamlessly integrated guard rails and tools to reinforce ethical AI practices. 4) Working with client teams from day 1 of each project to explore, test and document best practices in AI augmentation. https://lnkd.in/gazks3Tk

https://lnkd.in/gedvmaaT

Check out our latest article describing emerging best practice using AI to generate actionable insights. https://lnkd.in/gR2bVXUB

How to Become an AI Insights Hero. Transform Your Research with Actionable, Authoritative Insights Welcome to a new era where researchers amplify their impact and professional stature through advanced technology. The journey to becoming an "AI Insights Hero" is paved with challenges that many of us face in the pursuit of meaningful, scalable research insights. Recognizing these hurdles is the first step toward overcoming them. Insights are delivered with remarkable quickness, transforming weeks of work into hours. Researchers today encounter a series of obstacles that limit their ability to deliver impactful insights swiftly and at scale: These barriers often stand in the way of researchers achieving their full potential and impact. The Challenge for Researchers Limited time amidst a demanding schedule. The inability to efficiently manage large datasets for analysis. The need for insights that carry weight and authority. A reluctance or inability to engage with complex coding for data analysis. ResearchAI is your ally in this journey, designed to eliminate these obstacles with a cutting-edge, user-friendly platform. Here's how we change the game: Introducing ResearchAI Speed: Effortlessly work with extensive datasets, breaking the barriers of traditional research methods. Scale Our platform ensures your findings are not just influential but also robust, replicable, and defensible. Authority: All results are explainable and replicable. Complexity Say goodbye to the complexities of coding. ResearchAI is accessible to all, requiring minimal training to yield maximum results.