Learning While Working Podcast

Sprout Labs, Robin Petterd

Listen to the Learning While Working podcast to hear how learning and development is transforming. The episodes are interviews with leading thinkers in learning. Common themes on the podcast include trends in eLearning and digital learning, performance driven instructional and learning design and learning data. Each podcast is packed with ideas, tips and insights about how to make learning at work succeed. read less
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Episodes

Transforming L&D teams with Gregg Eiler
2d ago
Transforming L&D teams with Gregg Eiler
In this episode of the Learning While Working Podcast, Gregg Eiler, Senior Manager for Learning and Development at Powin, unpacks how motivation, clarity, and leadership interact to boost employee performance. Gregg also dives into the art of coaching, sharing actionable insights from his own experiences that redefine how to build expertise within L&D teams. Find out why it’s about being more than just an instructional designer – it's about being a business problem solver with a curious mindset.About Gregg EilerGregg Eiler is the Senior Manager for Learning and Development at Powin, where he built the company’s L&D operations from the ground up. He is an experienced Instructional Designer and Performance Improvement Expert with over 15 years of expertise, collaborating with global industry leaders to create impactful learning solutions. Greg’s particular passion lies in optimising performance ecosystems, focusing on elements such as motivation, bandwidth expansion, deliberate practice, coaching, and feedback.Key takeaways:Embrace the problem-solver mindset: Learning and Development goes beyond training; it's about being a strategic problem solver who aligns with business objectives.The power of coaching: Gregg leverages coaching to unlock the potential of industry experts, building their capability to ask challenging questions and pivot their perspective.Curiosity as a capability: Encourage curiosity within your L&D teams – it's the driving force that fosters accountability and a sharp focus on solving core business problems.Segmented time stamps:(03:58) Accountability, progress, and curiosity in sports coaching.(07:40) Consider multiple factors before investing time.(13:00) Encouraging curiosity, coaching and using templates.(15:52) Question to envision future success and set expectations.(18:29) Advocates design thinking for a user-centred approach.(20:12) Prototyping and testing essential for effective solutions.(24:29) Improve business skills through coaching.(27:10) Respecting opinions and styles while offering feedback.Links from the podcast:Connect with Greg on LinkedInVisit Greg’s Website
Using AI for role plays with Andrea Laus
Feb 16 2024
Using AI for role plays with Andrea Laus
In this episode of the Learning While Working Podcast, Andrea Laus explores the importance of role plays for developing crucial human skills, the potential pitfalls in traditional role play designs, and the transformative impact of a digital approach to role plays guided by technology. Andrea als unpacks how AI can enhance role plays, improve the feedback process, and ultimately revolutionise the L&D landscape.About Andrea LausAndrea Laus has spent the last 20 years developing effective strategies for talent development. He is the CEO of SkillGym, which designs state-of-the-art digital role plays for rebalancing knowledge-based training approaches with actionable practice. He regularly shares his ideas about effective training methodologies and strategies through his blog, and speaks at several HR and L&D conferences around the world on these fascinating subjects. Key takeaways:The importance of role plays in learning experiences: Andrea shares how it's crucial for developing human skills such as communication, collaboration, and problem-solving. It also creates a safe environment for practising real-life scenariosOn the challenges and misconceptions about role plays: Learners often feel judged and uncomfortable during role plays. There is a common misconception too that soft skills are “soft” – in reality they require dedicated effort and practice. It helps to understand these barriers so you can create the best learning environment.The application of technology and AI: Andrea highlights that, when used thoughtfully, technology can have a very positive impact. AI can help generate dialogues and responses, standardised and effective feedback, and it can assist in tracking and analysing learner actions. However, it is vital to select the right technology for specific learning objectives. Segmented time stamps:(00:00) Introduction(04:05) Handling the feeling of judgement in role plays(07:06) Leveraging role plays for sense making in learning(12:15) Practice with digital standardised and accelerates improvement(17:50) Supervise generative AI for writing dialogues(23:39) Measure and improve with technology-driven feedback(26:37) Utilise strategies, trust the process, embrace technologyLinks from the podcastConnect with Andrea Laus on LinkedInCheck out SkillGymWatch the recording of the Upskilling Using Artificial Intelligence: AI Digital Role Play webinar
Computational thinking in the age of AI with Susan Stocker
Jan 26 2024
Computational thinking in the age of AI with Susan Stocker
In this episode of the Learning While Working Podcast, Susan Stocker uncovers the world of computational thinking and its relevance in the age of artificial intelligence. With the skills gap becoming a concern in the era of AI and data-driven decision making, Susan's research on computational thinking in the workplace is timely and informative. Listen, as we explore what computational thinking is, the importance of critical thinking, and how these skills can shape our approach to problem-solving in the age of AI.About Susan Stocker    Susan Stocker is a Digital Transformation L&D Consultant where she helps organisations quickly change and get ahead of the skills and capability curve. She is committed to hands-on learning that enables teams to accelerate their success and companies to retain their people. She is also a certified Lean Six Sigma Master Black Belt, Certified Product Owner, Certified Scrum Master, and Certified BADIR Citizen Analyst.Key takeaways:Computational Thinking and AI in the Workplace: Computational thinking is a key skill in the age of AI and data-driven decision-making, so reflect on how you can build the relationship between these skills.Reimagining Work and Learning with AI: it’s an exciting time to rethink work in strategic areas for impactful organisational change as we are incorporating AI in day-to-day work and collaborating with the business.The skills gap in computational thinking is a real concern. According to Susan's research, a significant percentage of people in the workplace lack critical and computational thinking skills. As professionals, we need to develop these skills to effectively work with AI and data.Segmented time stamps:(00:00) Introduction(04:46) The struggle with critical and computational thinking(10:01) Value drivers for AI transformation in business(11:33) Understanding AI's use cases and problem-solving approach(15:09) Moving beyond technical AI to include critical thinking and behavioural responses(20:29) Rethinking work Links from the podcastConnect with Susan Stocker on LinkedInVisit the Aryng WebsiteRead Boston Consulting report Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and QualityRead Ethan Mollich thoughts the Boston Consulting report Centaurs and Cyborgs on the Jagged Frontier
ChatGPT for learning designers with Eliza Cani
Jan 12 2024
ChatGPT for learning designers with Eliza Cani
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
AI-powered workshop design insights with Pedram Parasmand
Dec 8 2023
AI-powered workshop design insights with Pedram Parasmand
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
What is wrong with digital learning with Marco de Rossi
Nov 24 2023
What is wrong with digital learning with Marco de Rossi
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?
Embracing AI for learning design with Rustica Lamb
Nov 10 2023
Embracing AI for learning design with Rustica Lamb
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
Making sense of AI – Implementing AI in L&D with Markus Bernhardt
Oct 27 2023
Making sense of AI – Implementing AI in L&D with Markus Bernhardt
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
Use AI to increase the efficiency of instructional designers with Cara North
Oct 13 2023
Use AI to increase the efficiency of instructional designers with Cara North
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
Navigating future skills with Britt Andreatta
Sep 29 2023
Navigating future skills with Britt Andreatta
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
The role of Chat GPT in modern learning design with Megan Torrance
Sep 15 2023
The role of Chat GPT in modern learning design with Megan Torrance
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
Creating marketing content using AI with Lynne McNamee
Sep 4 2023
Creating marketing content using AI with Lynne McNamee
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
Moving L&D from focusing on knowing to thinking with Ray Jimenez
Aug 25 2023
Moving L&D from focusing on knowing to thinking with Ray Jimenez
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
Rethinking workplace learning in an AI-Driven World with Lars Hyland and Matt Linaker
Aug 18 2023
Rethinking workplace learning in an AI-Driven World with Lars Hyland and Matt Linaker
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
Danielle Wallace on the AI in learning community of practice
Aug 11 2023
Danielle Wallace on the AI in learning community of practice
In this episode Robin and Danielle discuss the influence of AI on learning design, its potential to standardise educational experiences, and the importance of maintaining human skills like critical thinking in AI applications. It’s a fascinating discussion which delves into the creative potential of AI and self-learning. The recent ‘hype’ surrounding AI calls for continual learning and community collaboration to understand and leverage this technology effectively.About  DanielleDanielle is a Learning & Development and business professional with Fortune 100 experience. As a passionate learner and critical thinker, She has dedicated herself to navigating through the hype and staying up-to-date in the world of learning development. She is currently Chief Learning Strategist at Beyond the Sky: Custom Learning Solutions.Key takeaways:Embrace neural networks for creativity: Danielle highlights how neural networks excel at making unexpected connections and providing creative ideas without bias. By leveraging AI as an assistant, we can tap into new perspectives and unlock innovative solutions.Human skills in the AI Age: Critical thinking is an invaluable human skill that AI lacks. It’s important to nurture our critical thinking abilities and leverage our unique human qualities to complement AI technologies.Staying ahead in Learning & Development: The learning and development field must keep pace with technological advancements. There is a need for continuous learning, networking, and embracing new knowledge to create effective solutions. By staying informed and sharing expertise, we can shape the future of learning and development.Segmented time stamps:(00:00) Looking beyond the hype (01:32) Running an AI and L&D community of practice: what does that look like? (02:45) Common trends and questions people are asking in the community(03:33) The risks of unregulated usage of AI within organisations(07:43) Some great examples of leveraging AI(15:58) Reassessing what it means to be human(17:03) Using AI in creative work(20:15) Danielle’s key piece of advice around using generative AI Links from the podcast Connect with Danielle on LinkedInListen Daniellele’s podcast You in 2042 ... The Future of WorkFind out more about the AI in learning community of practice
The impact of Generative AI on the evolution of workplace learning with David James
Aug 4 2023
The impact of Generative AI on the evolution of workplace learning with David James
In this episode of the Learning While Working Podcast, David James joins the show to share his expertise and insights in Generative AI. David sheds light on why Generative AI is not simply a shortcut to faster and cheaper courses, but rather a disruptive force. He also talks about reinventing the learning process, the role of reflection, and how to not make your job redundant. About  DavidJosh Cavalier has been creating learning solutions for corporations, government agencies, and secondary education institutions for nearly thirty years. He is an expert in the field of Learning & Development. He has applied his industry experience to the application of ChatGPT and other Generative AI frameworks for business and life skills.Key takeaways:The big risk of relying solely on AI for producing course content is that it might render learning and development redundant. Instead, David encourages professionals to embrace the unique value they bring to address specific skills gaps in their organisation.Administrative tasks, be gone! Generative AI streamlines the learning experience by taking care of the administrative aspects, allowing educators and learners to focus more on effectively addressing real organisational challenges. By using internal data sets, Generative AI can help tackle the root of my performance  problems.It's about the learning process. Instead of relying solely on delivering information, the emphasis should be on enhancing the learning journey through practice, reflection, and behaviour change. Segmented time stamps:(00:00) AI is the path to making courses faster and cheaper. Doing this will make you redundant.   (01:38) What does Generative AI mean for L&D in the future?(05:08) How Generative AI can help us improve the actual learning process(11:03]) Viewing AI as a co-pilot(13:27) Distinguishing what L&D is(17:18) What will be talking about AI in 10 years time?(21:38) David’s main piece of advice for leveraging Generative AILinks from the podcast Connect with David on LinkedInFind out more about Learning360Read David’s article on What Future Does Generative AI Signal For L&D?
AI augmentation of L&D with Josh Cavalier
Jul 28 2023
AI augmentation of L&D with Josh Cavalier
In this episode, we explore the concept of using AI to enhance our strengths and compensate for weaknesses, prompt engineering techniques for L&D. Today’s guest is Josh Cavalier, who is helping people in L&D utilise AI tools effectively.  About Josh Josh Cavalier has been creating learning solutions for corporations, government agencies, and secondary education institutions for nearly thirty years. He is an expert in the field of Learning & Development. He has applied his industry experience to the application of ChatGPT and other Generative AI frameworks for business and life skills.Key takeaways:AI is a tool, not a replacement: Josh highlights how AI, specifically large language models like GPT, can augment traditional processes within L&D. Its powers are not in replacing humans, but as an aid to boost productivity and creativity.L&D professionals need to have a baseline knowledge of AI: It's important for L&D practitioners to have an understanding of how large language models and AI tools work. This will be essential as these tools become increasingly integrated into L&D processes.Where to begin with learning to use AI tools: be prepared for the learning curve associated with using AI tools effectively. Josh suggested starting with an AI like GPT and learning how to prompt it effectively. Using prepared prompts (like his ‘150 prompts for L&D’) can be a helpful starting point.Segmented time stamps:(0:00) Everyone in L&D needs to understand AI(01:18) AI augmenting our superpowers(04:21) Shadow tech and security risks (09:14) Scale and graphics card limitations(12:33) Prompt stacking technique(17:23) Difficulties of evaluating AI tools(22:00) Workflow and AI prompts(26:42) AI tools in L&D Links from the podcast Download Josh Cavalier’s 150+ Prompts for EducationConnect with Josh Cavalier on LinkedInVisit Josh Cavalier Website
Rethinking the future of work and learning with JD Dillon
Jul 21 2023
Rethinking the future of work and learning with JD Dillon
In this episode, Robin speaks with JD Dillon about the impact of AI on the future of work, and the importance of not being short-sighted with this technology. There is an ever-increasing need for critical thinking, and trust, transparency, and collaboration are key factors in AI adoption. JD encourages L&D professionals to engage with stakeholders and align their strategies with the organisation's vision for AI. About JD DillonJD Dillon is the founder of LearnGeek, where he helps organisations rethink how they enable their employees. Over the past 20 years, he has worked with some of the world's most dynamic brands, including Disney, Kaplan, AMC and Axonify. Today, he is the world's foremost expert on frontline learning and engagement as well as a prolific author and speaker in the global HR and L&D communities.Key takeaways:AI represents a significant shift in our relationship with technology, comparable to the introduction of the internet and mobile devices. It’s not about the quick-win – organisations need to see things long-term and should consider how it can fundamentally transform work processes and tasks.Trust and transparency are crucial for successful AI adoption: organisations must address data quality and knowledge management practices to establish trust in AI systems. L&D professionals should actively engage with stakeholders and align their strategies with the organisation's vision for AI-enabled technology.It is the perfect time to discuss how we can shape the future of work. Organisations need to actively participate in defining how AI supports work and learning, ensuring that it enhances productivity, decision-making, and overall employee experiences. The integration of AI in the workplace requires a balance between automation and human decision-making, and critical thinking will remain crucial in assessing AI-generated contentSegmented time stamps:(00:00) We need the think about how AI shift what organisations do(02:43) What AI means for the future of work(07:47) What AI means to be human(10:39) What is L&D’s role in AI technology?(15:32) Why trust in technology is crucial for future success(19:38) Skills in trust, critical thinking, and human decision-making(23:29) JD’s greatest gem of wisdom when it comes to AI and L&D Links from the podcast Connect with JD on LinkedInVisit JD’s WebsiteListen to JD’s interview about continuous learningListen to JD’s interview about modern learning ecosystems
Start of the series on AI and L&D
Jul 14 2023
Start of the series on AI and L&D
This is the start of a series on AI in L&D.  The series is exploring what people are doing now with AI, what people are thinking about, and what people are learning.In this episode, we kick off the series where Robin does an interview with ChatGPT on transforming learning at work. The voice is generated by ElevenLabs.If you are interested, it might be easier to read the blog post along with the podcast, than listening to the computer generated voice.Key takeaways:Promoting self-guided learning and automation in instructional design can contribute to a culture of continuous learning. Automation can be used in instructional design to automate routine tasks and increase efficiency, such as AI automating content curation, learner data analysis, and feedback collection and analysis.There are risks and considerations to be aware of when using AI. These include the dangers of dependency on AI, the digital divide in access to AI tools, ethical concerns regarding biassed information, and the importance of data privacy. To address these risks, organisations should comply with data privacy laws, implement quality control measures, balance AI with human-led learning experiences, and provide training and support for employees who are not comfortable with technology.Strategies for using AI in workplace learning include having human mentors or instructors for discussions and social learning opportunities, providing training and support for employees who are not comfortable with technology, and incorporating ethical considerations when choosing AI providers.Segmented time stamps:(00:00) The argumentation of human lead learning(01:58) AI in workplace learning(05:35) Adaptive learning experience pathways(08:15) On-demand learning for safety leadership(11:41) Content curation and updates(16:07) The risks of using AI in L&D(21:33) The role of humans and AI in the workplace(24:53) Balancing the use of AILinks from the podcast Check out ElevenLabsTranscript:Robin: Act as an expert on L&D and learning. You're going to be a guest on the Learning While Working podcast. The audience is workplace L&D professionals. The interview is going to talk about how you (chatGPT) can transform learning at work. I'm going to ask you questions.ChatGPT: Sure, I'd be happy to participate in this mock podcast interview. Feel free to start with your questions.Please remember that while I can provide useful and insightful information, I'm an AI model developed by OpenAI and my responses are based on patterns in the data I was trained on, up until September 2021. Any information or insights I provide should be validated and adapted to your specific context.Robin: Welcome to the Learning While Working podcastChatGPT: Thank you for having me on the Learning While Working podcast. It's an exciting opportunity to connect with the L&D community. As an AI developed by OpenAI, I aim to provide insights and information that can help transform learning at work. Let's get started!Robin: What are 3 ways you transform learning at work?ChatGPT: AI, such as myself, can help to transform learning at work in various ways. Here are three significant ways:Personalised Learning: One of the biggest challenges in workplace learning is meeting the diverse needs of learners. AI can analyse an individual's learning style, previous knowledge, and performance data to deliver personalised learning experiences. For instance, based on a learner's progress, AI can recommend next steps, additional resources, or even a change in learning strategy to improve outcomes.On-Demand Learning: The traditional model of set training times and classrooms isn't flexible or scalable, especially in a world where remote work is increasingly common. AI can provide on-demand learning, allowing employees to learn at their own pace, anytime and anywhere. This is especially useful for quickly updating employees on new tools, policies, or industry developments.Automation of Routine Tasks: A lot of L&D professionals spend considerable time on administrative tasks like scheduling training sessions, tracking progress, and generating reports. AI can automate these routine tasks, allowing L&D professionals to focus more on strategic tasks such as designing better learning experiences and interventions.These are just a few examples of how AI can help. The actual impact will depend on the organisation, its culture, and its readiness to leverage AI in learning and development.Robin: Give me three examples of Personalized Learning?ChatGPT: Certainly, personalised learning through AI can take many forms. Here are three specific examples:Adaptive Learning Paths: AI can create adaptive learning paths based on each learner's knowledge level, skills, and learning speed. For instance, if an employee is already proficient in certain areas, the AI can automatically adjust their learning pathway to focus on areas where they need improvement. This avoids wasting time on content they already know and focuses on developing areas where they need growth.Recommendation Systems: Similar to how Netflix or Amazon recommends movies or products based on past behaviour, an AI can recommend learning resources based on a user's past learning behaviour and performance. For example, if a user struggled with a particular concept, the AI might suggest additional resources, such as videos or articles, to reinforce their understanding.Learning Style Adaptation: AI can adapt the format of the content to match the learner's preferred style. For example, some people learn better through visual materials like infographics and videos, while others prefer text-based resources or interactive simulations. AI can track how users interact with different types of content and then prioritise delivering content in the formats that work best for them.In all these ways, AI can help create a personalised, more engaging, and effective learning experience for each individual.Robin: You're being a bit vague. Give me and example of using ChatGPT for Adaptive Learning Paths for cybersecurity skills.ChatGPT: Certainly, let's take a more detailed look at how ChatGPT could be utilised for creating an adaptive learning path in the field of cybersecurity.Suppose an employee, let's call her Jane, is tasked with improving her cybersecurity skills. After an initial assessment or quiz, it's clear that Jane has a strong understanding of basic concepts such as types of threats and fundamental security protocols, but she struggles more with advanced topics like incident response management and network security.Initial Assessment: In this scenario, ChatGPT could begin by providing an interactive assessment, where Jane answers questions or solves problems related to various aspects of cybersecurity. This could involve everything from basic concepts to more advanced ones.Custom Learning Pathway: Based on Jane's performance on the assessment, ChatGPT identifies her strengths and weaknesses. Since she already has a strong understanding of basic concepts, the AI doesn't include these topics in her learning pathway. Instead, it prioritises advanced topics like incident response management and network security.Learning Delivery and Continuous Assessment: As Jane moves through her personalised learning pathway, she interacts with ChatGPT in a conversational manner, discussing cybersecurity scenarios, answering quiz questions, and solving problems related to her learning topics. ChatGPT adjusts the complexity and depth of the content based on Jane's progress.Regular Feedback and Adjustments: Throughout this process, Jane receives instant feedback on her progress, which helps her understand where she stands and how she's improving. If Jane is struggling with a certain topic, ChatGPT might choose to slow down, provide additional learning resources, or approach the topic from a different angle.In this way, ChatGPT can provide a flexible, responsive learning experience that adapts to Jane's needs, ensuring she focuses on the areas where she needs to grow most.This approach not only saves time by avoiding unnecessary repetition of known topics but also promotes engagement and effective learning by focusing on areas of need and providing instant feedback.Robin: This is good. How about an example for On-Demand Learning for safety leadershipChatGPT: Absolutely. Here's how ChatGPT could provide on-demand learning for an area such as safety leadership:Let's consider a manager, we'll call him John, who has been tasked with improving his safety leadership skills to better lead his team in a manufacturing environment. John works on a tight schedule and he often can't participate in traditional training programs during usual business hours.24/7 Availability: Since ChatGPT is an AI, it is available 24/7. John can interact with the training program whenever he has time, be it early in the morning before his shift starts, or late in the evening after he finishes his work. He doesn't have to wait for a scheduled training session.Learning in Context: Suppose a specific situation arises at work that John is unsure how to handle from a safety leadership perspective, like responding to a safety incident. He could immediately consult with ChatGPT, asking specific questions to learn how to best handle the situation. ChatGPT could provide guidance based on best practices in safety leadership, and provide resources for deeper learning.Role-Playing Simulations: On-demand learning isn't just about reading material or answering quiz questions. For example, John could engage in a role-playing scenario with ChatGPT at any time, where he has to navigate a simulated safety incident, make decisions and respond to changes. This on-the-spot, interactive learning can be highly effective for building practical skills.Just-In-Time Learning: If a new safety regulation or procedure is implemented, John can immediately get the necessary training from ChatGPT. It can provide an overview of the new rule, explain its implications, and even quiz John to ensure he has understood the change.This kind of on-demand learning can be particularly effective because it is self-paced, flexible, and contextual. It allows learners to get the knowledge when they need it, apply it immediately, and therefore, they are more likely to retain it.Robin: Is this key to type experience making sure employees are self guided learners?ChatGPT:Yes, fostering a culture of self-guided learning is a key aspect of successful implementation of AI-driven personalised and on-demand learning. Here's why:Ownership of Learning: When employees are self-guided learners, they take ownership of their learning journey. This makes the learning process more effective because they are actively seeking knowledge, rather than passively receiving it.Pace and Style: Self-guided learners can set their own pace and choose their preferred style of learning. This flexibility can lead to more engagement and better absorption of knowledge.Immediate Application: Self-guided learners can immediately apply what they've learned to their work, which can reinforce their learning and demonstrate its practical relevance.Continuous Learning Culture: Promoting self-guided learning can contribute to a culture of continuous learning. In today's rapidly changing work environment, continuous learning is crucial for businesses to stay competitive and for employees to keep their skills up-to-date.However, it's important to note that not everyone may be used to or comfortable with self-guided learning. In these cases, organisations can provide support and guidance to help employees become more self-directed learners. This could include training on how to use AI learning tools, creating clear learning paths for skills development, and providing mentors or coaches to guide learners.Robin: Getting those top 3 things. How could an instructional designer use Automation of Routine Tasks?ChatGPT: Absolutely. There are several routine tasks within instructional design that can be automated with AI, which can greatly increase efficiency and allow instructional designers to focus more on the creative and strategic aspects of their work. Here are three specific examples:Content Curation and Update: AI can automate the process of sourcing, organising, and updating learning content. For example, an AI could crawl the web or a specific database to find relevant articles, videos, or research papers for a particular course topic. It can also regularly check for updates or newer versions of the existing learning content and replace outdated materials.Learner Data Analysis: AI can automate the analysis of learner data to provide insights into learning behaviours and performance. For instance, AI could automatically generate reports on learner engagement, quiz performance, areas of struggle, and more. This allows instructional designers to quickly and efficiently evaluate the effectiveness of their courses and make data-driven improvements.Feedback Collection and Analysis: Collecting and analysing learner feedback is an important but time-consuming task. AI can automate this process by prompting learners for feedback at optimal times (like after a course completion), collating the feedback, and analysing it to provide actionable insights. It could categorise feedback into themes, identify common issues, and even suggest potential improvements.By automating these tasks, instructional designers can save significant time and focus more on designing effective, engaging learning experiences. Additionally, the insights provided by AI can inform their design decisions, leading to more effective learning outcomes.Robin: How about for content creation?ChatGPT: AI can indeed assist with content creation in a variety of ways, which can be particularly useful for instructional designers. Here are a few examples:AI-Powered Writing Assistants: Tools like ChatGPT can assist in drafting course content. Given an outline or a set of key points, AI can generate draft content, which can then be edited and refined by instructional designers. This can speed up the content creation process, especially for first drafts or when creating content in a specific area of expertise.Content Optimization: AI can analyse content and suggest improvements based on best practices. For example, it might suggest simplifying complex sentences, adding more visuals, or including quizzes and interactive elements at certain intervals to boost engagement and retention.Translation and Localization: If content needs to be provided in multiple languages, AI-powered translation tools can be used to translate the content. Additionally, AI can help localise content, i.e., adapt the content to fit the cultural, societal, and linguistic context of different learner groups.Creating Interactive Content: AI can help create interactive content such as quizzes, simulations, or even chatbots for role-playing scenarios. Instructional designers can input the learning objectives and key points, and the AI can generate appropriate interactive content.It's important to note that while AI can assist in content creation, the role of instructional designers remains crucial. They provide the human touch, the deep understanding of learner needs, and the creativity that AI cannot replicate. AI should be seen as a tool that can augment the capabilities of instructional designers, not replace them.Robin: What are some risks of using you for workplace learning?ChatGPT: Using AI like ChatGPT for workplace learning presents several opportunities but also comes with some risks. It's important to consider these potential challenges:Data Privacy: AI platforms often rely on data from users to provide personalised experiences. This can raise concerns about data privacy, particularly if sensitive information is involved. It's crucial to ensure that any AI used in the workplace complies with data privacy regulations and that users are informed about how their data is used.Quality Control: While AI can generate content and assist with learning, the quality of that content may not always meet the necessary standards. Misunderstandings or inaccuracies could lead to the dissemination of incorrect information, which could be particularly harmful in areas such as safety training or compliance.Dependency: There's a risk that organisations could become overly reliant on AI for learning and development, neglecting the importance of human interaction and guidance in the learning process. While AI can deliver information and even personalise learning to some extent, it can't replace the mentorship and social interaction that humans provide.Digital Divide: While AI can offer powerful tools for learning, not all employees may have equal access to these tools. For example, employees who are not comfortable with technology or who lack access to high-quality internet may not benefit as much from AI-based learning tools.Ethical Considerations: AI systems, including ChatGPT, are trained on vast amounts of data, which can include biassed or prejudiced information. Even though measures are taken to prevent it, these biases can sometimes influence the AI's output. This is a broader issue with AI and machine learning and something to be aware of when using AI tools.It's crucial for organisations to be aware of these risks and to implement strategies to mitigate them when using AI for workplace learning.Robin: Can we just drill into Data Privacy? What are your Data privacy features?ChatGPT: As an AI developed by OpenAI, I am designed with privacy in mind. Here are some key aspects to understand about how I handle data:No Personal Data Storage: As of my training cut-off in September 2021, I don't have the ability to access or retrieve personal data from users unless it's shared with me in the course of our conversation. I don't store personal conversations or use them to inform my responses.Temporary Data Retention: By default, OpenAI retains data passed to the ChatGPT API for 30 days, but doesn't use it to improve my models.Privacy by Design: From the outset, I've been designed to respect user privacy. For example, I don't ask for personal data unless it's strictly necessary for the conversation.However, it's important to note that the usage of AI tools should still comply with the organisation's data privacy policies and any local laws or regulations. You should always be clear with employees about how their data is being used, and make sure you have their consent before using AI tools in a learning context.As data privacy is a dynamic field with constantly evolving regulations and standards, it's crucial to regularly review and update your data privacy policies and practices.Robin: But doesn't mean you're losing opportunities for training data?ChatGPT: While it's true that retaining and using conversational data could potentially provide opportunities for refining and improving AI models, OpenAI has chosen not to use data from individual interactions with ChatGPT to improve the model in order to prioritise user privacy and confidentiality.This decision reflects an important balance in AI development between improving the system and ensuring user trust. Given that AI systems like me are often used in contexts where sensitive or private information might be discussed, ensuring that users feel safe and confident that their data won't be used without their explicit permission is a critical priority.It's worth noting, though, that overall improvements in the model, which are based on extensive and diverse datasets, will continue to enhance the effectiveness and accuracy of the AI, benefiting all users.Robin: Going back to the risks you talked about, how can we overcome those risks?ChatGPT: Addressing these risks requires thoughtful planning and implementation. Here are some suggestions:Data Privacy: Ensure any AI tool used complies with all relevant data privacy laws and regulations, such as GDPR in Europe. Implement robust data protection measures, and be transparent with users about what data you collect, why you collect it, and how you use and protect it.Quality Control: Don't rely solely on AI for creating and delivering content. Always have a human in the loop to review and validate the information. Regularly test the system and provide opportunities for users to give feedback or report errors.Dependency: Balance the use of AI with human-led learning experiences. AI is a tool to supplement and enhance learning, not replace human guidance and interaction. For example, you might use AI for delivering content and personalising learning paths, but still have human mentors or instructors for discussions, mentoring, and social learning opportunities.Digital Divide: Provide training and support for employees who are not comfortable with technology. This might include basic digital literacy training or one-on-one support. Make sure your learning experiences are accessible on different devices and internet speeds, and where necessary, provide alternative, non-digital learning options.Ethical Considerations: Choose AI providers who are transparent about their training data and methods and who actively work to minimise and address bias. Incorporate ethical considerations into your AI strategy and continuously monitor and evaluate the AI's output for potential bias or ethical issues.These strategies can help mitigate the risks of using AI in workplace learning. However, each organisation's situation is unique, so it's important to continually assess and address risks in your specific context.Robin: In the past I’ve talked about how AI means that humans need to focus on the 3 things that AI can't do, Create, Collaborate and Change. What are your thoughts on this?ChatGPT: You've highlighted a critical perspective on the interaction between humans and AI in the workplace, and particularly in learning and development. AI technology has made significant strides, but there remain areas where humans outperform any existing AI. Let's unpack the three Cs you've mentioned:Create: While AI can generate content, solve problems within a specified context, and even mimic some forms of creativity, it fundamentally lacks the ability to truly innovate or think outside of the box. Human creativity, which involves the generation of new ideas, unique insights, and novel solutions, remains unchallenged. In learning and development, this creativity plays a crucial role in designing engaging and effective learning experiences.Collaborate: AI can facilitate collaboration (for example, by coordinating schedules or organising tasks), but it cannot truly collaborate the way humans can. Human collaboration involves complex social interactions, empathetic understanding, negotiation, and the ability to build on each other's ideas in dynamic, unpredictable ways. Especially in a learning context, this ability to collaborate and learn from each other is a deeply human skill that AI cannot replicate.Change: AI can adapt to new data within a predefined framework, but it doesn't have the capacity for the kind of flexible, broad-spectrum change and adaptability that humans possess. Humans can change their beliefs, assumptions, behaviors, and strategies based on new experiences or insights, and this ability is key to learning and development.In the context of learning while working, humans should leverage AI for what it does best - managing large amounts of data, providing personalised content, offering on-demand support, and automating routine tasks. Meanwhile, human efforts can focus on these irreplaceable areas of creativity, collaboration, and change, which are at the heart of effective learning and development. This combination of AI's capabilities and the unique human skills can lead to a powerful, holistic approach to workplace learning.Robin: Now as the wrap questions what your greatest piece of advice about using ChatGPT is for learning while working?ChatGPT: When it comes to using ChatGPT or any AI in the learning while working context, the most important piece of advice I'd give is this: View AI as a tool that augments and enhances human-led learning, not as a replacement for it.AI tools like ChatGPT can offer great advantages in terms of personalising learning, providing on-demand support, and automating routine tasks. But they are not a silver bullet. The effectiveness of AI in learning and development depends greatly on how it's integrated into your broader L&D strategy.Here are a few key points to consider:Learner-Centric Approach: Focus on the learner. AI offers exciting possibilities, but ultimately, the goal is to create a better, more effective, more engaging learning experience for your employees. So always consider how the use of AI will benefit the learner.Blend with Human Interaction: Balance the use of AI with opportunities for human interaction and guidance. While AI can deliver content and personalise learning, it can't replace the mentorship, social learning, and human touch that are also crucial for effective learning.Ongoing Evaluation: Continually evaluate and adjust your approach. AI is a rapidly evolving field, so it's important to stay updated with new developments and be ready to adapt your strategies. Regularly solicit feedback from learners and use it to improve your AI-enhanced learning experiences.Training & Support: Provide training and support to help employees use AI tools effectively. Not everyone may be comfortable with technology, so it's important to help them understand how to use AI tools and how they can benefit from them.By keeping these principles in mind, organisations can leverage the power of AI to transform workplace learning, while still maintaining a human-centric approach that values and nurtures the unique capabilities of each individual learner.
Modern learning ecosystems with JD Dillon
Jul 7 2023
Modern learning ecosystems with JD Dillon
In this episode, we are joined by guest JD Dillon to discuss his modern learning ecosystem framework and its importance in a constantly changing environment. Tune in as JD delves into tactics for influencing different departments, reinforcement and retention mechanisms, and why we need to eliminate the need for formal learning  About JD Dillon  JD Dillon strongly believes in the power of help. He is the founder of LearnGeek and helps organisations rethink how they enable their employees. Over the past 20 years, he has worked with some of the world's most dynamic brands, including Disney, Kaplan, AMC and Axonify. Today, he is the world's foremost expert on frontline learning and engagement as well as a prolific author and speaker in the global HR and L&D communities.Key takeaways:What ‘modern’ means in the Learning Ecosystem Framework: there is a vagueness of the term "modern”, and JD Dillon seeks to define it in his book. It’s about the importance of being prepared for change, and the need to establish flexible and agile systems and processes. It’s important to provide a stable foundation for a good experience despite the constantly changing environment.The importance of influence in building learning culture in organisations: There is a need for everyone in the organisation to prioritise learning. There are a number of tactics for influencing different departments and individuals to shift their mindset towards learning and development. Consider how to convince executives to adopt new ways of sharing information, and challenge outdated perspectives on learning and development.The integration of knowledge management, Learning & Development, and corporate communications: a curator in the organisation can help solve problems instead of prioritising departments. Explore how to incorporate information flow and solve systemic issues.Segmented time stamps:[01:46] Insights from his book ‘The Modern Learning Ecosystem’[04:44] A framework to help connect tools for learning solutions[09:19] The disconnect in organisations hinders problem-solving and learning[13:19] Differentiating shared knowledge vs. performance support[17:46] How to influence everyone in the organisation[24:00] Embracing learning as a constant, and why reinforcement is vital[30:56] Replacing the word ‘Learning’ with ‘Helping’ in our job titlesLinks from the podcast:Read the The Modern Learning Ecosystem - A New L&D Mindset for the Ever-Changing Workplace  Connect with JD Dillon on LinkedInVisit the JD’s website Learning GeeksAnother Learning While Working podcast interview with JD Dillon on continuous learning and how it links with personalised learning