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Summary

In this episode, Isabela Parisio, an AI policy and governance expert, discusses the complexities of AI regulation, the race between law and technology, and the future of AI in legal and other sectors. She shares insights from her experience at King's College and her research on responsible AI.

Key Topics

• AI policy and governance complexities
• The pace of regulation versus technological development
• Global and regional AI regulations
• The impact of AI on legal practice and law firms
• Market power and geopolitical considerations in AI regulation
• The role of regulators and dialogue in AI governance
• AI hallucinations and legal liability
• Future predictions for AI regulation in five years

Chapters

00:00 Introduction to AI policy and governance
02:01 Isabella's background and journey into AI regulation
03:48 The increasing importance of AI regulation and political debates
06:07 The scattered landscape of global AI regulations
06:57 Law versus technology: the race and pace problem
08:56 The impact of market power and geopolitical interests
10:54 The role of regulation in innovation and risk management
13:03 Case study: AI in the legal sector and liability issues
15:57 The importance of dialogue and regulatory engagement
17:57 Future predictions for AI regulation and potential crises

Links and Stuff

Isabella’s Linked In - https://www.linkedin.com/in/isabela-parisio-?utm_source=share_via&utm_content=profile&utm_medium=member_ios

Richard Susskind — The Future of the Professions

The Future of the Professions: How Technology Will Transform the Work of Human Experts (Richard Susskind & Daniel Susskind, updated edn 2022) — https://global.oup.com/academic/product/the-future-of-the-professions-9780198841890

AI policy and governance research at King's College London

• King's Institute for Artificial Intelligence — https://www.kcl.ac.uk/ai
• TELOS — Centre for Technology, Ethics, Law and Society (Dickson Poon School of Law) — https://www.kcl.ac.uk/research/centre-for-technology-ethics-law-and-society-telos — the one to cite for AI regulation and governance specifically
• Responsible AI UK at King's — https://www.kcl.ac.uk/research/rai-uk
• UKRI Centre for Doctoral Training in Safe and Trusted AI (KCL / Imperial) — https://safeandtrustedai.org/

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Summary

In this episode, Emile Kfouri from Autodesk shares insights on AI's evolving role in construction and design, the future of outcome-based modeling, and how humans and AI can collaborate effectively.

Key Topics

• AI's role in construction and design
• Outcome-based modeling and its implications
• The evolution of developer work with AI
• Heuristics and their role in AI development
• Multi-agent systems and scaffolding in AI
• Responsible AI and ethical considerations
• Future skills for developers and users
• The impact of AI on human roles and collaboration

Chapters

00:00 Introduction and episode overview
01:13 Guest introduction: Emil Kofori from Autodesk
02:09 Emil's background and team overview at Autodesk
04:03 Challenges in AI adoption and responsible use
05:22 Changes in developer advocacy and AI's influence
07:33 Shift towards outcome-based design in construction
09:41 Scrutinizing AI models and understanding their thought process
12:25 Multi-agent architectures and scaffolding in AI
17:45 Heuristics, AI, and open-ended problem solving
23:06 Indicators for when not to use AI
28:50 The future skills of developers and humans in AI era
39:31 Books that influenced Emil's thinking
41:34 Predictions for AI in AEC in five years
43:06 Closing remarks and where to find Emil

Links and Stuff

Emile Kfouris's Linkedin : https://www.linkedin.com/in/emile-kfouri/

Listen on: Apple Podcasts Spotify

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Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.

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Summary

In this week's episode, we are joined by João Dias, Co-Founder and CEO of Constructer.ai, and Dr Shirin Dora, Senior Lecturer in Neuromorphic Computing at Loughborough University, to discuss what trustworthy AI really requires in construction.

Key Topics

• AI's impact on construction project management
• Data quality and unstructured data in construction
• Use of live data versus historical data in AI models
• The importance of domain expertise in AI solutions
• Challenges of AI adoption in construction industry
• The concept of faithful but wrong in AI outputs
• Future prospects of AI and AGI in construction

Chapters

00:00 Introduction to the episode and guests
01:09 Joao Dias discusses his background and motivation for founding Constructor
02:34 The personal pain points in project delivery that AI aims to solve
03:11 Shirin Dora shares her transition from academic machine learning to industry impact
04:11 The collaboration between domain expertise and AI technology
06:02 Differentiating Constructor from other construction tech platforms
09:52 Constructor's approach: detect, quantify, and act with live data
11:01 Why focus on live data instead of historical data
12:21 Choosing appropriate AI techniques for construction problems
16:15 Understanding hallucination versus faithful but wrong in AI outputs
21:32 Liability and trust in AI-generated insights in construction
24:13 Current AI adoption levels in the construction industry
34:24 Preparing for the future: building AI capabilities for construction professionals
41:54 The long-term outlook for AI and the possibility of AGI in construction

Connect with the Guests:

• Joao Dias - LinkedIn
• Shirin Dora - Linkedin
• Constructer.ai

Listen on: Apple Podcasts Spotify

Support the show

Subscribe to the Project Flux Newsletter!

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Project Flux is independently owned, funded, and operated by its founder. Any external references or features are for community benefit only and do not imply endorsement, control, or ownership.