Conversational AIs like ChatGPT, BARD, and others seem to be in every headline and LinkedIn post today. Yet implementing conversational AI in a large organization isn't as easy as just creating a free account and asking a few questions—important consideration must be given to intellectual property, ethics, regulation, governance, business models, digital fluency, and adoption. Read More >

Learning Outcomes: Read Less ^

• Identify conversational AI opportunities
• Explore enterprise-specific use cases
• Learn about the implications of 'who owns' an AI's Large Language Model (LLM)
• Consider organizational change and digital fluency needs for true conversational AI adoption

The journey to exponential growth requires minding the gaps between your new journey and the incremental “defaults” of your organization. First, we’ll explore what ‘exponential’ really means in practice. How do we create room for exponential innovation while still making progress on incremental innovation? How do we create room for exponential innovation while still making progress on incremental innovation? Learn how to transform communications around four key gaps—in vision, expectations, accountability and resources—to ensure your exponential projects aren’t blocked by incremental thinking. Read More >

Learning Outcomes:

• The difference between incremental and exponential thinking in large organizations
• The way network effects function
• How to close four key gaps between incremental and exponential thinking

-The vision gap: make an exponential possibility accessible

-The expectations gap: differentiate between incremental and exponential initiatives

-The metrics gap: make progress visible and accountability possible

-The resource gap: prepare for exponentially-increasing needs without over-investing Read Less ^

Generative AI tools go beyond Q&A with ChatGPT. Major brands like Adobe, Shutterstock and Canva are joining the ranks of labs like Midjourney, Stable Diffusion, and Deep Agency to revolutionize how everyday people can bring their ideas to life in illustration, 3D worlds, video and music. Education is also confronted by the possibilities and risks of generative AI tools for research assistance, writing support, and more. How do we think through the impact of entire creative and education domains suddenly undergoing an explosion of content? And what will our culture value most about education and art as these fields transform? Read More >

Learning Outcomes: Read Less ^

• Learn about key tools disrupting education and art fields
• Try on new mental models for thinking about generative AI
• Explore new interpretations of familiar concepts 'creativity,' 'art,' and 'learning'
• See tangible examples of generative AI tools and their outputs—including those you can explore now
• Prepare yourself and your colleagues with 'what' and 'now what' discussion prompts you can apply immediately

Generative AIs are like super-knowledgeable coworkers promising massive benefits. However, they have other red flags we wouldn't tolerate in a human, like confident BS about subjects they don't understand, plagiarism, and a lack of critical thinking. It's time we look carefully at this new class of tools and their implications for work, life, education, and more. Read More >

Learning Outcomes: Read Less ^

• Understand how LLMs (Large Language Models) 'learn'—or don't
• Explore early, disruptive applications of conversational AIs
• Understand the ethical implications of Generative AI for privacy, truth and law
• Discuss what's realistic to expect from machine learning tech now and in the near future

Queer people have created and transformed modern technology, from Turing to Apple CEO Tim Cook and former U.S. CTO Megan Smith, into the trailblazing future of Queer metaverses and cyborg gender. Learn Queer strategies to guide sound design & security based on deconstructing and recombining systems, challenging rules, transforming interfaces, and re/creating identity. Read More >

Learning Outcomes: Read Less ^

• Understand Queer as a school of thought beyond the demographics of sexual orientation or gender
• The idea of “Queering” something (to deconstruct, assess, and recombine its elements—often in new ways and with startling results, as we're seeing with generative/conversational AI like ChatGPT)
• The importance of digital fluency in Queer communities—and Queer fluency in tech communities
• What Queer people do with tech and what it can teach designers (about power, [secret] communication, avatars, counterpublics, hacktivism, and online worlds like the metaverse)
• Correlation between the density of LGBTQ+ people in geographical innovation hubs—and the hidden risks of relocation of tech to less LGBTQ welcoming geographies
• Queer X Quantum: how the common Queer experience of living beyond or outside of binaries relates to emerging ‘fuzzy’ technologies like machine learning, natural language processing, quantum computing, and ‘cyborg’ extensions of the body

Digital transformation is creating a world where businesses must test new, exponential strategies like generative AI/ChatGPT while maintaining incremental business functions to keep the lights on. Read More >

How can we manage this balance between old and new, and choose which path to modernization is right for us? To lead our companies in the era of AI, we need to increase our Digital Fluency. Five key areas are critical to focus on: thinking, skills, tools, data, and business models.

Learning Outcomes: Read Less ^

• See what an AI future might hold for your work
• Understand what it means to be digitally fluent through a simple "five pillars" model with easy-to-understand language
• Explore the Digital Fluency strategies of leading firms
• Learn how to quickly launch an AI Readiness & Digital Fluency program and cultivate a network of transformative thinkers inside your business