Learning While Working Podcast

In this episode of the Learning While Working Podcast, Eliza Cani, a learning designer at LearnWorlds, explores the topic of using ChatGPT for learning designers. Eliza shares valuable insights on how AI can be integrated into course design, the importance of prompting skills, and the future trends that can revolutionise the fieldAbout  Eliza CaniEliza Cani is an eLearning Designer at LearnWorlds, and an experienced public speaker with a background in IT. She started her career at LearnWorlds as a member of the support team where she demonstrated an in-depth knowledge of the platform and the ability to solve customer issues fast and efficiently. Over the years, Eliza has helped hundreds of trainers and course creators create engaging learning materials and deliver them effectively.Key takeaways:Prompt engineering and engaging with ChatGPT: there is a need for precise and specific prompts, e.g. specifying course duration, target audience, tone of voice, key takeaways, etc. Consider also the audience needs and preferences in prompts, as well as regularly reflecting on prompts over time to improve outcomes.Future trends in course design: expect more integrations of AI with platforms, including learning management systems and learning content systems. There will be less use of conversational interfaces, such as ChatGPT, and conversational AI will become more embedded in tools and platforms, to make AI more accessible to all users.Overall advice for Learning Designers working with AI: don’t be afraid to use AI tools. Start with simple tasks and gradually explore more capabilities so you can understand how AI complements and enhances the work of learning designers. Segmented time stamps:(00:00) Introduction(02:22) ChatGPT as an efficient and creative tool for content summarisation(04:22) Simplifying learning theories for all(09:59) How to talk to AI tools by being advanced and precise(13:26) Having a customised approach based on audience and goals(15:14) How AI tools enhance learning design and why you need to understand their impact(18:15) Tools that facilitate course design and integration seamlessly(21:32) How AI won't replace designersLinks from the podcast Connect with Eliza Cani on LinkedInFind out more about LearnWorldsDo the free Master ChatGPT: Supercharge Your Course Design With AI course   

In this episode of the Learning While Working Podcast, Pedram Parasmand shares his insights on using AI tools for workshop designs and emphasises the importance of not relying on AI to do the creative work for you, but rather using it as a thought partner and brainstorming tool. He shares his experience with Chat GPT and Copy AI, highlighting how he trains these AI generative tools on his own methodology to support workshop design. He also explores the potential of using AI-powered transcription tools like Otter AI for analysis and evaluation.About  Pedram ParasmandPedram Parasmand is The Co-Founder and CEO of Skills Lab and has over 11 years experience working with executive teams to new entrants in the corporate, public, third and education sectors. Pedram has partnered with clients such as Accenture, Barclays Bank, Mind, Ministry of Justice, Red Bull, The European Union Commission, and The British Council. Previously, Pedram worked in Leadership Development at the education charity Teach First and started his career as a high school Science teacher.Key takeaways:Don't rely on AI to do the creative work for you: Pedram emphasises the importance of trusting your own human instincts and using AI as a support system or brainstorming tool. AI can enhance your workshop design process, but it can never replace your skills as a facilitator.Align AI with your specific challenges: When incorporating AI into your workshops, consider your pain points and processes. Explore how AI can assist you in addressing those challenges and improving your facilitation techniques. AI should complement your objectives, not replace them.Train AI in your methodology: Pedram shares his experience with training AI tools like Copy AI in his own workshop design methodology. By giving detailed prompts and instructions, you can teach AI to analyse transcripts, identify pains and gains, and generate audience-friendly content.Segmented time stamps:(00:00) Introduction(01:53) AI aids in designing workshops for newbies(05:46) Using tools like Otter AI that summarise, analyse, and evaluate conversations(07:01) How evaluation is flexible with various data points(12:57) Generate ideas for workshop objectives and refine later(16:44) Workshop structured like a story for growth(19:22) Finding ways to removes manual tasksLinks from the podcast Connect with Pedram on LinkedInVisit the Skills Lab’s Website  Check out Copy AICheck out Otter AI 

In this episode of the Learning While Working Podcast, Marco de Rossi discusses the current issues with digital learning in workplaces, such as the misalignment between how we naturally learn as lifelong learners and how organisations push out content-driven learning. Tune in as we delve into social learning, synchronous vs. asynchronous activities, and how Generative AI is proving to be a valuable tool for L&D experts.About  Marco de RossiMarco de Rossi is the CEO of WeSchool, a learning platform that helps teams launch effective training in a user-friendly environment no matter their technical skills.Key takeaways:The challenges in digital learning in workplaces: there is a misalignment between how people learn in workplaces and how they naturally learn as lifelong learners. Learning is often seen as a buzzword, but not integrated into daily behaviours, so there needs to be a shift where learning becomes the responsibility of every team, not just HR.The people-centric approach: learning should be woven into everyday tasks and the focus should be on building communities and fostering social learning. Balancing cost-effectiveness and effectiveness: on-demand, self-paced learning may be cheaper, but it is not always effective. Cohort-based models and synchronous structures are important for critical learning experiences, like onboarding. Think about how a mix of cost-effective and quality-focused solutions can coexist.The role of AI can be a valuable tool for supporting learning design skills. E.g. conversational generative AI makes it easier for everyone to design engaging  learning experiences. Segmented time stamps:(00:00) Introduction(01:50) What is wrong with digital learning?(03:21) Marco’s vision of what great digital learning looks like(06:27) Why self-paced learning is not always the best solution(08:19) Conversational generative AI(11:16) The importance of instructional design skills(15:13) Adaptive learning(18:00) AI make it easier for more people to access learning experiences(19:23) Overcoming the current problems of digital learningLinks from the podcast Connect with Marco de Rossi on LinkedInVisit WeSchool Learn more about WeShool by watching this video      Read Robin blog post on What would happen if digital learning were more expensive than face-to-face training? 

In this episode of the Learning While Working podcast Rustica Lamb and Robin explore how to leverage AI as a powerful tool to enhance your productivity and creativity, learn how to effectively prompt, and stay conscious of the ethical implications of AI in the learning and working sphere. She has recently run the Elab AI program, which aimed to introduce a series of AI tools to learning professionals. It tested and evaluated various AI tools and discovered their potential to save significant amounts of time for learning designers.About Rustica LambRustica Lamb is a hands-on learning professional who is passionate about experimenting with new technologies and exploring how they can transform learning.  She is the founder of Bloom Learning Technologies, an international award-winning learning technologies company that is bringing the cost of elearning way, way down. They help organisations create engaging learning experiences, whilst supporting the business and budget goals.Key takeaways:Learning Designers can save about 40-60 hours per month through AI tools. By using this saved time, L&D professionals can focus on improving quality and fostering creativity. It  is important to remember that AI does not replace the expertise and insights of learning designers, so there needs to be human involvement along the process.Embracing AI in workplace learning is crucial for staying relevant, and Rustica points out that it is similar to the transition from traditional to e-learning.There is a need for expert guidance and coaching when using AI, to ensure accurate and reliable results from AI systems and maximising their potential in learning design.Segmented time stamps:(00:00) The importance of spending time playing with the tools(01:19) What is the eLab.ai program?(02:23) Key takeaways and insights from eLab.ai(04:13) Why humans won’t be replaced by AI(06:41) Generating the ‘core skeleton’(11:25) Where creativity sits in the world of AI(15:25) The importance of coaching(18:23) Rustica’s greatest gem of wisdom about using AI tools for learning designLinks from the podcast Connect with Rustica on LinkedInVisit the Bloom Technologies websiteFind out more eLab.ai Read ‘Scary Smart’ by  Mo GawdatExplore FuturepediaListen to Moonshots & MindsetsListen to Augmented reality for learning with Rustica Lamb 

In this episode of the Learning While Working Podcast, Markus Bernhardt explores AI discussions with learning technology vendors, and the important topics of understanding the different types of AI being deployed and the value they add. We also touch on the critical role of training data and its reliability in AI solutions, and the rush toward generative AI and its impact on long-term strategic thinking.About  Markus BernhardtAs a Fellow of the Learning Performance Institute (LPI) and member of both the Forbes Technology Council and HBR Advisory Council, Markus Bernhardt is recognised as a global authority for AI and Learning. Markus is an accomplished author, panellist, and speaker. His leadership experience as CEO spans the direction of a for-profit educational institution as well as the stewardship of a charitable educational institution in the UK, with significant contributions in both executive and non-executive board roles.Key takeaways:Discerning between generative and non-generative AI deployment is essential for understanding AI's contribution to learning. It is beneficial for instructional designers, expediting tasks like summarising content, crafting questions, and facilitating collaboration with subject matter experts.The ideal landscape has AI-powered tools that offer real-time support, drawing from an organisation's internal data to provide personalised performance assistance.Adaptive learning journeys emerge as an exciting application, using AI to tailor learning experiences to individual strengths and weaknesses, thus enhancing learning outcomes.Segmented time stamps:(00:00) Introduction(01:38) Navigating the marketplace for technologies and solutions for the learning space (05:22) The impact of the ‘sudden’ rush of AI(09:46) Internal training of data(15:23) The way we work with language models in organisations and workplaces(19:13) interesting AI applications in L&D at the momentLinks from the podcast Connect with Markus Bernhardt on LinkedInRead Markus article on 5 Key Questions to Ask AI Vendors & How to Understand the AnswersRead all of Markus Learning Guild articles   

In this episode of the Learning While Working Podcast, we explore how AI technologies can be used to increase the efficiency of instructional designers. We tackle the challenges and ethical concerns of using AI-generated tools, focusing on their limitations and potential misinterpretations. Get insights into the importance of maintaining the human element in instructional design, especially in areas like assessment design.About  Cara NorthCara North has worked in the instructional design field for more than a decade and has won multiple awards for her learning experiences. Cara has worked in both higher education and corporate, and runs her own consulting business, The Learning Camel. Some of the clients The Learning Camel has served include Universal Records, WesBanco, NASA, Daisy and the National Association for Talent and Development (ATD).Key takeaways:Generative AI can be used for brainstorming and translation. Tools like Chat GPT are valuable for creating first drafts, but they lack the ability to capture context-specific language and formality. As such, human input is required for this purpose.There are tools that are useful in the localization and translation of content. Cara gives examples of Microsoft PowerPoint's built-in translation tool and Sonix.ai, which help in rapidly reproducing content in different languages, improving efficiency in the learning design process.The use of AI avatars for role-playing exercises in instructional design helps avoid logistical challenges associated with producing videos. However, these AI avatars require human input for more nuanced performance.Segmented time stamps:(00:00) The importance of focusing on making the best learning experience possible and not the tools(01:13) How Cara uses AI in her learning design process(04:42) Some key AI tools to check out (06:25) What human input is needed from AI translation tools(10:19) AI-generated avatars(15:39) Authenticity in art and AI(20:16) Cara’s advice for instructional design and using genetic AI nowLinks from the podcast Connect with Cara on LinkedInCheck out The Learning Camel 

In this episode of the Learning While Working Podcast, Britt Andreatta is back to discuss the impact of AI on organisations and the skills needed to navigate this shifting landscape. As an expert on brain-driven approaches to learning and a leading voice in the field, she shares some truly valuable insights. Tune in to learn more about the need for a clear strategy in L&D, developing strong change management skills and why we need to hone in scientific literacy and verification skills.About  Brit AndreattaDr. Britt Andreatta is an internationally-recognised thought leader who creates brain science-based solutions for today's challenges. As CEO of Brain Aware Training, Inc., Britt Andreatta draws on her unique background in leadership, neuroscience, psychology, and learning to unlock the best in people and organisations.Key takeaways:AI's influence calls for robust change management skills, and the technology’s verification will need to be a key quality in job requirements – on par with communication and time management.The imperative of reskilling is gaining prominence, with the World Economic Forum identifying a substantial global workforce needing retraining.AI-driven misinformation highlights the need for critical thinking and science literacy skills. The role of learning professionals will become ‘verifiers’, ensuring that AI-generated content is reliable while embracing the adaptability in a dynamic environment.Segmented time stamps:(00:00) Introduction(01:57) How will AI change the types of skills that organisations need?(03:11) Change management skills(05:12) Why is change not always successful?(07:00) Science literacy skills(12:27) Become verifiers(20:12) What should L&D be doing now to prepare for the future? Links from the podcast Connect with Britt on LinkedInVisit Britt’s WebsiteRead Wired To Resist 

In this episode of the Learning While Working Podcast, Megan Torrance joins the show to share what she is learning about using Chat GPT.  We focus on using Chat GPT to enhance the learning experience itself, and just using AI to generate content.About  Megan TorranceMegan Torrance is CEO and founder of TorranceLearning, which helps organisations connect learning strategy to design, development, data, and ultimately performance. Megan has more than 25 years of experience in learning design, deployment, and consultingKey takeaways:Chat GPT can act as an assistant for learning designers. It aids in structuring content and generating examples, particularly when subject matter experts may tire of providing numerous case examples. As a result, it helps designers craft more thorough and comprehensive learning materials.In the context of medical education, AI is employed to provide detailed feedback on learners' responses to case scenarios. This feedback is compared against expert responses to provide meaningful insights to learners. However, it's crucial to ensure that the AI never gives direct medical advice – the final decision must always be left up to the learner.Inform learners if the feedback they're receiving is AI-driven. This transparency ensures that learners understand the nature and source of their feedback and approach it with a degree of scepticism, especially in sensitive areas like medical education.Segmented time stamps:(00:00) Start exploring AI but be careful(01:11) What are some of the ways that ChatGPT can be used by learning designers?(02:40) Taking a simple approach(07:39) Using AI in complicated areas in medical education and legal training(10:46) Other ways AI is being used to put in a learning experience(14:44) Using ChatGPT as an assistant(16:46) Mitigating bias in AI(18:37) Megan’s greatest general advice for learning designers in using ChatGPTLinks from the podcast Connect with Megan on LinkedInTorranceLearning’s WebsiteDownload Megan’s one-page practitioner's guide job aid to using ChatGPTWatch a recording of the ChatGPT Driven Instructional Design: Dreams, Results, and Horrors webinar  

AI tools like ChatGPT are being used in various industries, including marketing and learning. In this episode of the Learning While Working podcast, we are joined by Lynne McNamee to explore the fascinating and evolving world of AI tools for content creation. Robin and Lynne unpack how the quality of the generated content varies, applications of ChatGPT in L&D work, and why privacy and data sources are also limitations for generative AI tools.About  Lynne McNameeLynne is a creative and strategic thinker who leverages data and technology to lead innovative organisations to measurable results through inbound, social, content, video and traditional marketing. She is the president of Lone Armadillo Marketing Agency, where she has managed marketing campaigns for companies such as Avis, HP, and Bank of America. She was cited by The New York Times for innovations in marketing.Key takeaways:Ways to leverage ChatGPT for marketing: Lynne shares how she uses ChatGPT in her work, specifically in writing copy for blog posts and websites. It’s important to understand the search engine interface and user intent to generate effective content, to align with SEO strategies. Be aware of the language AI generates, as tools like ChatGPT tends to provide overly literal keywords, which can result in keyword stuffing and impact your SEO score negatively. Try out some other key AI tools, like Lumen5 and SonixAI. Lynne has been using these for tasks in video creation and transcription. She also reflects on why ChatGPT has gained the most attention compared to other tools, which is due to social proof and practical applications. Segmented time stamps:(00:00) The changing nature of marketing work (01:25) How Lynne is using ChatGPT on a daily basis(02:51) Lynne’s process of writing a blog post with the help of AI(03:42) Considering SEO when using AI generated content(06:25) The impact of quality from using ChatGPT(08:12) Training AI to write learning material(12:43) Some of the weaknesses of using a tool like ChatGPT (19:28) Why has ChatGPT gained so much attention and widespread adoption?(20:38) Lynne’s main bit of advice around using AI at the momentLinks from the podcast Connect with Lynne on LinkedInLone Armadillo Marketing Agency’s WebsiteListen to Using learning campaigns to effectively drive behaviour change with Lynne McNameeCheck out Lumen5Try out Sonix AI  

In this episode of the Learning While Working Podcast, Ray Jimenez talks about how employees are using AI for learning. Ray will share practical examples of incorporating ChatGPT into the learning experience, such as learner familiarisation, troubleshooting, and coaching. About  Ray JimenezRay Jimenez Ph.D. is the Chief Learning Architect at Vignettes Learning, trainingmagnetwork.com and situationexpert.com. He has worked with the American Bankers Association, Neiman Marcus, the US Air Force, NASA, Blue Cross, Goodwill Industries, Pixar Studios, among others. Ray's expertise is in microlearning, story-based learning design, scenario-based learning design and creative problem solving.Key takeaways:There have been successful experiments using ChatGPT's integration in learning platforms, such as rapidly familiarising technicians with new subject matter, accelerating ISO certification processes, and enabling coaches to provide targeted prompts and expand learners' growth mindset.The potential for private data integration in ChatGPT offers exciting opportunities for companies, allowing learners to explore and interact with their own proprietary information, creating a closer connection between learning and real-life work situations.Working with AI involves recalibrating the way we think about learning, moving away from a reliance on content delivery and toward nurturing critical thinking, questioning, and debating skills, thus enabling learners to become more autonomous and better equipped to navigate the complexities of the modern workplace.Segmented time stamps:(00:00) We need to recalibrate our thinking in learning away from content(01:56) How ChatGPT can be used by learners(05:04) On workplaces having their own Generative AI tools(11:08) The idea of templates for learners(16:00) Using AI for more hands-on and physical work(19:34) Examples of using critical thinking alongside AI(27:14) ChatGPT being more generalised than specialised Links from the podcast Connect with Ray on LinkedIn5 Experiments in ChatGPT/Situation Expert  

In this episode, Robin is joined by Lars Hyland and Matt Linaker from Totara to discuss rethinking workplace learning in an AI-Driven World. The conversation focuses on the importance of shifting from content-driven strategies to more context-based and collaborative learning environments. About  Lars HylandLars Hyland is a seasoned expert in learning technology with over 27 years of experience. He has worked with various international organisations and educational institutions, including the University of Oxford and Deutsche Bank. Currently, he leads Totara's EMEA operations, focusing on talent development and productivity. About  Matt LinakerMatt has a multifaceted career in the field of learning and education, with a focus on technology-enhanced learning.  He is currently the Partner Onboarding and Enablement Lead at Totara Learning.Key takeaways:AI tools have gone mainstream. It is impacting creative arts and we can see how it has helped improve the way we work. There is potential for governments and organisations to have their own large learning models and AI to enhance learning while working.Content-driven models in the workplace have caused a disconnect between business goals and training outcomes. New technologies can assist in connecting people to the right people at the right time, and automated feedback can aid development.Easy access to the right content to the right people can help contextualise the learning process, and conversations and collaboration can help people come together quickly to solve problems and meet goals. Providing feedback and rewarding people in an intentional way, contextualised to the situation, can help motivate them to learn and to apply their knowledge effectively. Segmented time stamps:(00:00) One of keys to the future of AI is open source  (01:35) What does the future of work look like?(04:59) How AI has gone mainstream(10:13) Moving away from content-driven approaches (15:32) L&D in Totara(19:19) Building learning platforms for talent experience(24:04) How can we make this future of learning happen now? Links from the podcast Connect with Lars on LinkedInConnect with Matt on LinkedinTotara’s WebsiteRead more about Matt's thoughts on Rethinking workplace learning in an AI-Driven World