The Knowledge Summit Dublin 2024: Generative AI Meets Human Experience - a Conference Review

Guest Post by Mairéad Mc Keown, Knowledge and Critical Capability Manager at Bord Bia - The Irish Food Board.

Using AI to generate business ideas by MangKangMangMee via Shutterstock

This blog post will give an overview of the Knowledge Summit Dublin 2024 conference. The main theme of the conference was generative artificial intelligence and human intelligence combined for knowledge creation and discovery. The tacit knowledge exchange sessions focused on past experiences and future synergies of KM (Knowledge Management), AI and human experience. It would be impossible to cover content from every presenter/speaker so I have distilled some of the most widely applicable insights I hope will be of use to those of us working in library, information or knowledge roles. For each insight I have created a resulting implication to inspire action. 

Radical KM – Art aids innovation

Stephanie Barnes, Leading Knowledge Management Author, Speaker and Educator, on Radical KM.

Insight: Art aids innovation, curiosity, resilience, trust, collaboration.

Implication: Pilot radical KM by piloting an art-based intervention, e.g. drawing, painting etc. in your workplace to create a culture of knowledge sharing where people are open to seeing the world through a different lens. 

Meta on how knowledge and AI combined feed opportunity

Praveena Cherukuri, Customer Experience and Transformation Leader, on KM and AI at Meta.

Insight: Knowledge and AI combined feed opportunity.

Implication: Pair the right knowledge with the right AI tool to create opportunity but start small and fail fast, don’t boil the ocean, seek and act on robust user feedback and use technology that’s scalable.

Lessons in KM - Knowledge delivers triple value

Bill Kaplan, KM Consultant and Rebecka Isaksson, Knowledge Strategist, on Lessons from KM.

Insight: Knowledge delivers triple value to the customer, workforce and organisation.

Implication: Devise KM strategies to express, capture and share all the organisations’ information and all the organisations’ experience to create actionable, meaningful, relevant knowledge that delivers triple value.

Being human - Stories aid understanding

Prof. David Snowdon, Chief Scientific Officer, The Cynefin Co., on being human.

Insight: Stories aid shared understanding.

Implication: Build a community of real storytellers who are willing to share failures and successes to aid understanding, build trust and create valuable learning experiences.

KM challenges - KM challenges don’t change

Scott Leeb, Chief Knowledge Officer, Fragomen and Dr Liam Fahey, Leadership Forum, on Lessons learned from a 25-year KM Journey. 

Insight: KM challenges don’t change overtime.

Implication: Build KM strategies that address these five key Km challenges: 

1. Converting tacit to explicit knowledge

2. Demonstrating the ROI and value of KM

3. Discovery of knowledge

4. Collaboration

5. Technology as an enabler, NOT the solution.

NASA on 5 ways to kill KM 

Ed Hoffman, Chief Knowledge Officer NASA, on five sure ways to kill KM.

Insight: There are 5 ways to kill KM

Implication: Avoid all 5 below!

1. Hold one person responsible

2. Use complex KM language

3. Don’t measure the value

4. Don’t do governance

5. Limit communication and keep the leadership team in the dark 

NASA on how stories facilitate learning

Michael Bell, Lessons Learned Program Manager NASA, on ideas for applying AI to Nasa’s Lessons Learned database

Insight: Lessons learned stories facilitate learning in multiple generations.

Implications: Use AI to push lessons learned stories (about successes and failures) in multi-media formats, to the multi-generational user at the point of need. 

AI methods impact use cases

Dr Etzard Stolte, Global Head of KM Roche, on AI and Generative AI for KM. 

Insight: AI methods impact the use cases and successful deployment requires structured knowledge. 

Implication: Add more structure to your data, (coding, taxonomies, knowledge graphs) and choose the right AI method for the right AI use case to deliver value.

Becoming AI-powered is a journey

Kieran McCorry, National Technology Officer, Microsoft, on Becoming AI-powered.

Insight: Becoming an AI-powered organisation requires a three-step journey.

Implication: Follow these three steps: 

1. Develop leadership capabilities

2. Manage human change

3. Build and iterate technical skills. 

Conclusion

Overall, the key theme from the conference was generative artificial intelligence and human intelligence combined for knowledge creation and discovery. The transformative power of where AI and KM intersect cannot be underestimated but we must carefully decide what role we want to play, to use or be used by this new technology.

KM challenges don’t change much overtime, but technology keeps changing at pace. It’s important to remember that successful KM initiatives are made up of culture, people, processes and technology. KM is about executing robust strategies that get the right intel, to the right person, at the right time, in the right format, to make the right decision, or provide the right advice.

AI and related technologies are enablers not solutions, they can only help us discover information once we have first created and shared it. Which brings us nicely back to the main theme of the conference, the careful combination of generative artificial intelligence and human intelligence has the power to transform knowledge creation and discovery.