The Importance of Collaboration in AI Governance

I’m catching up with my podcasts from last week after being at the #Alliance2024. Everyday AI's episode last Wednesday about AI Governance (link in the comments) is an absolute must listen for companies starting to think about how to incorporate AI into their workflows. Gabriella Kusz shared lots of actionable steps including: Acknowledge the Challenge: Recognize the fast pace of AI advancement and how it outpaces traditional regulatory or standards development processes. Take Action Internally: Proactively form a dedicated task force or working group to focus on AI governance. Multi-Departmental Collaboration: This task force should include representatives from various departments (medical writing, continuing education, publications, marketing, etc.) to provide a range of perspectives on potential risks and benefits. Educate Your Team: Provide team members with resources on AI, generative AI models, and consider regular updates or "brown bag" sessions to stay up-to-date. Start Small, Define Boundaries: Select early use cases with low, acceptable risk levels. Define ethical boundaries for AI deployment even before starting pilot projects. Learn From Mistakes: Embrace an iterative process where pilot projects offer learning opportunities. Adjust approach as needed rather than seeing any initial setbacks as failures. We, as an industry, need to step up and start creating internal rules for ethical AI use, especially for sensitive medical/healthcare content. What resources are you using to stay updated on AI ethics and responsible use in medical communications? In what ways do you think AI could positively transform medical writing and communication? Let's share ideas! #healthcare #medicalwriting #AIethics

📄New Preprint! How does AI policy *actually* get made across sectors? I interviewed stakeholders & studied real cases of synthetic media policy to find out. Not theoretical frameworks - real collaboration between tech, civil society, media & policymakers! 📖 Read it here: https://lnkd.in/ek7r6kVM 📣 And some takeaways: 🔹 Synthetic media isn't just a tech problem. It's fundamentally about misrepresentation & impersonation. This reframing changes how we approach solutions 🔹 Time shapes everything. Stakeholders draw on past experiences, weigh present contexts, & consider future implications when crafting AI policies. History & foresight matter as much as current tech. 🔹Trust emerged as the foundation. Not just among policymakers, companies & civil society - but crucially, between these groups & the public they serve. Without trust, even good policies struggle. 🔹 AI labels & transparency measures? Important but not sufficient. They need to go beyond simple "AI or not" binaries to be truly useful. 🔹 Cross-sector collaboration works when it: Complements (not replaces) government regulation, Has adequate lead time, builds on trusted relationships, combines social & technical expertise Check out the important implications for how we approach AI governance broadly in the paper here: https://lnkd.in/ek7r6kVM #AIPolicy #AIGovernance #deepfakes #syntheticmedia #contentauthenticity #responsibleAI #responsibletech

An AI leader asked me how to improve the collaboration with business stakeholders: “I told them: This is what we do and this what we need from you. How can we get more buy-in?” I wasn’t too surprised that “the business” has been apprehensive if the tone has indeed been “us vs. them.” That’s why I suggested to reframe and rephrase it: “Our team understands the technology really well and we are looking to partner with you to uncover the most promising AI opportunities together, based on your domain expertise.” But that is just the first step. Next, we talked about governance. Creating a simple table of roles & responsibilities can already increase transparency and drive alignment (AI team | Business team). Add the technical and business roles you need to bring together to work on an AI idea, consider what each role brings to the project, and who meets with whom and how often. Building on that, we talked about the typical project phases from idea to operation to show the project flow. Add the deliverables and documents needed for each phase along with the outcomes and go/no-go criteria for the project. (Check out the chapter on building your idea funnel in the AI Leadership Handbook.) Lastly, we covered getting sign-off on this governance framework across your senior business stakeholders. This will set you up for an aligned approach with top-down support and help you shine in your AI leadership role. I’ll check in again in a few weeks and can’t wait to hear how things are going. What’s slowing your AI program down? (Drop me a DM for an unbiased perspective.) #ArtificialIntelligence #GenerativeAI #IntelligenceBriefing