The Art and Science of AI-Driven Foresight

The Art and Science of AI-Driven Foresight

AI promised to make sense of the world. But what if the real challenge is not the volume of data it is knowing what to trust, how to validate it, and how to turn it into actionable insights? In this episode of AI in Motion, hosts Michael Hanf and Arash Hajikhani use the 4Growth project [https://4growth-project.eu/] as a case study to explore how AI is being used for foresight and horizon scanning in agriculture and forestry. From curating knowledge basesto clustering insights and tracking trends over time, they ask: Are we using AI to simply speed up the process, or are we leveraging it to ask better questions and make more informed decisions? Key takeaways: - How the 4Growth project uses AI to build a rigorous, bounded knowledge base to avoid the pitfalls of inferenceand noise. - The balance between human judgment and AI tools in turning data into meaningful insights. - Why transparency, validation, and context are critical when using AI for foresight. Subscribe now and join the conversation AI in Motion is produced by iksait Media and funded by theEuropean Union (GA no 101134855, 4Growth). Views are those of the hosts andguests only.

AI for Intelligence

AI promised to make sense of the world. Instead, it’s drowning us in data. In this episode of AI in Motion, hosts Arash Hajikhani and Michael Hanf explore what “intelligence” really means in the age of AI. How are large language models and knowledge graphs helping us extract meaning from the noise and what are we trading for speed and convenience? From automated innovation tracking in Finland’s economy to the ethical dilemmas of competitive intelligence, they ask: Are we using AI to augment our thinking, or are we outsourcing the very context that makes information valuable? No hype, no buzzwords, just a raw look at the tools reshaping how we know what we know. Key takeaways: * How LLMs and knowledge graphs transform unstructured data into actionable intelligence. * The hidden costs of automation: What do we lose when we rely on AI to “understand” for us? * Why context is everything and how to avoid the trap ofincomplete or misleading insights. * The fine line between competitive advantage andethical compromise in AI-driven analysis. For further reading, you can find information here: * SFINNO 2.0 – Advancing the Database of Finnish Innovations [https://cris.vtt.fi/en/equipments/sfinno-20-advancing-the-database-of-finnish-innovations/] * Leveraging large language models and knowledge graphs to map AI innovations in Finland [https://trepo.tuni.fi/handle/10024/187949] * What Is the claude.md File? How to Write a Permanent Instruction Manual for Claude Code [https://www.mindstudio.ai/blog/what-is-claude-md-file-instruction-manual] AI in Motion is produced by iksait Media and funded by the European Union (GA no 101134855, 4Growth). Views are those of the hosts and guests only.

The Commercialization of AI

AI promised to make everything easier. But what if the real cost isn’t just money it’s our data, our expertise, and even our ability to decide for ourselves? In this episode of AI in Motion, hosts Arash Hajikhani and Michael Hanf cut through the hype to explore the hidden trade-offs of commercial AI. From biased search results to algorithms replacing human expertise, they ask: Are we using AI to amplify our capabilities, or are we outsourcing our thinking and our responsibility along the way? Key takeaways: * How commercial AI isn’t just a tool it’s reshaping power, ownership, and trust. * The risks of outsourcing expertise when AI knows more about your business than you do. * Why convenience comes at a cost are we trading control for efficiency? AI in Motion is produced by iksait Media and funded by theEuropean Union (GA no 101134855, 4Growth). Views are those of the hosts andguests only.

Future of Work

AI promised to make work easier. But what if the real cost isn’t just jobs—it’s our cognitive skills, our collective experience, and even our ability to think critically? In this episode of AI in Motion, hosts Arash Hajikhani and Michael Hanf cut through the hype to explore the real impact of AI on the way we work. From the hidden trade-offs of productivity tools to the blurring lines of accountability, they ask: Are we using AI to augment our capabilities, or are we outsourcing our thinking, and our responsibility, along the way? Key takeaways: > Why AI isn’t just a tool—it’s reshaping roles, culture, and even how we trust each other. > The cognitive skills we risk losing when we rely too much on algorithms. > How organizations and individuals can navigate this shift without getting left behind. AI in Motion is produced by iksait Media and funded by theEuropean Union (GA no 101134855, 4Growth). Views are those of the hosts andguests only.

Signal in the Noise

AI promised to make information easier to find. Instead, we’re drowning in noise. In this debut episode of AI in Motion, hosts Michael Hanf and Arash Hajikhani explore the paradox of AI driven information overload: How did we go from scarcity to overload and why does it feel harder than ever to find what matters?   From rabbit holes that steal our time to AI generated research polluting the scientific record, they ask: How do we stay critical, intentional, and human in a world where machines shape what we see, read, and believe? No buzzwords, no predictions just real talk about the challenges and choices ahead.   Key takeaways: > Why AI’s "help" often feels like a trap and how to use it intentionally.> The hidden cost of information overload: trust, clarity, and our own thinking.> Where to draw the line between leveraging AI and losing our critical edge. AI in Motion is produced by iksait Media and fundedby the European Union (GA no 101134855, 4Growth). Views are those of the hostsand guests only.